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Springer Texts in Business and Economics
Michelle Brandstrup · Léo-Paul Dana Daniella Ryding · Gianpaolo Vignali Myriam Caratù Editors
The Garment Economy Understanding History, Developing Business Models, and Leveraging Digital Technologies Foreword by Aldo Bensadoun
Springer Texts in Business and Economics
Springer Texts in Business and Economics (STBE) delivers high-quality instructional content for undergraduates and graduates in all areas of Business/Management Science and Economics. The series is comprised of self-contained books with a broad and comprehensive coverage that are suitable for class as well as for individual self-study. All texts are authored by established experts in their fields and offer a solid methodological background, often accompanied by problems and exercises.
Michelle Brandstrup • Léo-Paul Dana • Daniella Ryding • Gianpaolo Vignali • Myriam Caratù Editors
The Garment Economy Understanding History, Developing Business Models, and Leveraging Digital Technologies
Foreword by Aldo Bensadoun
Editors Michelle Brandstrup Design School Kolding Kolding, Denmark
Léo-Paul Dana ICD Business School Paris, France
Daniella Ryding Department of Materials University of Manchester Manchester, UK
Gianpaolo Vignali Department of Materials University of Manchester Manchester, UK
Myriam Caratù Faculty of Economics Università degli Studi Internazionali di Roma - UNINT Rome, Italy
ISSN 2192-4341 (electronic) ISSN 2192-4333 Springer Texts in Business and Economics ISBN 978-3-031-33301-9 ISBN 978-3-031-33302-6 (eBook) https://doi.org/10.1007/978-3-031-33302-6 # The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023, corrected publication 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
This book is dedicated to Marie Dorthea Christiansen (1897–1973) early 20th century entrepreneur and seamstress.
Foreword
The Garment Economy is a fascinating compendium, which examines several aspects of one of the largest industries on earth. It is exactly the kind of book which didn’t exist when I attended university in the 1950s and 1960s. I realised early on that I was more interested in business than electrical engineering and when I made that change in my studies, I still found myself in a highly technical field focused on the rigours of accounting and finance. I gravitated towards marketing and economics which at least held some promise of trying to understand human behaviour! This book will serve as an excellent resource for anyone thinking critically about this exciting industry. In many ways, it is the most basic of industries: producing clothing which people will want to buy. But it is also one of the most complex. It is completely global and completely universal and yet it changes constantly as consumer demands change. Those demands now go way beyond style, quality, and price as enlightened consumers demand environmental and social responsibility from the brands they buy. When I founded the Aldo Group 51 years ago, I was determined to build a different kind of company—a company with a heart! I attended university at a time of tremendous social change and saw many of my classmates being very critical of business. This didn’t make sense to me as I had witnessed my parents running a 3-store business in a very socially responsible way—they were fair to their employees, their customers, and their suppliers. The small success they had allowed them to be philanthropic and to be a positive force in their community. I was proud of them and wanted to prove my classmates wrong. I wanted to build a company built around ethics, compassion, fairness, and a deep understanding of the customers, with a purpose to make the world gentler. Today the Aldo Group, with my son David as the CEO, has 1,600 stores around the world, operates in 110 countries, and sources products from 5 continents. Over the years, we have been at the forefront of our industry on several important movements, including ethical sourcing, the fight against AIDS, pay equity, worker safety, and the fight against climate change. I’m especially proud that in 2018 we became the first company in our industry to become carbon neutral. There is still much work to do and that is why our company’s purpose has some humility built
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into it—we speak of our purpose as a journey. It is: A Journey to Create a World of Love, Confidence, and Belonging. In order for a business to “do good”, it must first be successful! 50 years ago that could be achieved in relatively straightforward ways—carry beautiful product and sell it at a price which covers a bit more than all your costs... Although the basic formula is still the same, it is incredible to see how much innovation has come into the industry in the last 20 years. While Part 2 of this book can help drive positive social and environmental change in the industry, Parts 3 and 4 are the ones which will help businesses pay for that change. Part 3 and 4 cover exciting innovations and approaches, which will drive the next wave of success. While many equate success with more sales, that is a mistake. Success is equally found in efficiency—anything that allows a fashion company to better predict demand will reduce markdowns, and therefore reduce waste while also improving profits. Anything that allows a company to improve efficiency in supply chain or procurement will also have positive effects on profits as well as the environment. Far too often, social and business goals are presented as a sort of zero-sum game where for one side of the equation to gain, the other must lose. Anyone who has thought critically about the garment industry recognises the fallacy of that argument. My hope is that books such as The Garment Economy will elevate the discussion and equip the next generation of fashion industry leaders with new ideas and knowledge to find success in all its forms. I commend the editors and contributors for their efforts. They represent universities from around the world. These include, among others: Bar Ilan University (Israel), Ben Gurion University of the Negev (Israel), Dalhousie University (Canada), Dhofar University (Oman), Glasgow Caledonian University (UK), Metropolitan University (Bangladesh); Shri Ram Swaroop Memorial University (India); UNISA (South Africa); Università degli Studi Internazionali di Roma, Italy; University of Gloucestershire (UK); University of Manchester (UK); University of Technology (Australia); University of Tehran (Iran); University of the Arts (UK); and University of Turin (Italy). The contributors explain materials, conventional and unconventional. They provide international perspectives from Africa, Asia, Europe, and beyond. Various innovations are discussed and also circular initiatives that encourage recycling. The book includes discussions of business models for sustainable fashion. Worth more than the sum of its parts, the volume creates awareness of environmental sustainability in fashion. I commend the editors for this work, especially Michelle Brandstrup who is not an academic but actually a young designer in the process of launching her own brand in Lunenburg, Nova Scotia, after launching a brand in 2021 for a company in Europe. Her graduate degree focused on
Foreword
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sustainability in the fashion sector and now she puts her lessons to practice. Hopefully, this book shall encourage and inspire many other young people, to contribute with sustainable ideas, initiatives, and solutions for the future of the fashion industry. The Aldo Group Montreal, Canada
Aldo Bensadoun
The original version of this book has been revised. An correction to this book can be found at https://doi.org/10.1007/978-3-031-33302-6_29
Contents
Part I
Introductory Chapters
Introduction to the Garment Economy . . . . . . . . . . . . . . . . . . . . . . . . . Michelle Brandstrup and Léo-Paul Dana The History of Bedouin Clothing Made for Traditional Nomadic Lifestyle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Hafiz Wasim Akram and A. Allan Degen
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The Garments Economy: An African Perspective . . . . . . . . . . . . . . . . . L. B. Louw, S. van Antwerpen, and E. Esterhuyzen
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Indian Clothing: Its Evolution and Development . . . . . . . . . . . . . . . . . . Shweta Uttam, Vimal Srivastava, Rajni, Ila Sharma, and Rahul Dhiman
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A Migrant/Minority Economy? Jewish and Greek Migrant Entrepreneurial Patterns in the Greek Interwar Clothing Industry, 1923–1940 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Orly C. Meron Part II
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The Garment Business Today
Greenwashing in the Fashion Industry: Definitions, Consequences, and the Role of Digital Technologies in Enabling Consumers to Spot Greenwashing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Darya Badiei Khorsand, Xiaoxue Wang, Daniella Ryding, and Gianpaolo Vignali
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Modest Fashion and Sustainability: Research Trends by Bibliometric and Content Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Paolo Biancone, Valerio Brescia, and Michele Oppioli
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The Evolution of the Applications of Influencers for Fashion Brands on Social Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Liru Jiang, Gianpaolo Vignali, and Stephen Doyle
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Reuse of Pre-Loved Garments: Pain or Gain? . . . . . . . . . . . . . . . . . . . . Songyi Yan, Claudia E. Henninger, and Taylor Brydges
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Sharing Is Caring: The History of ‘Sharing’ New Interpreted . . . . . . . . Lucie Pocinkova, Claudia E. Henninger, and Aurelie Le Normand How to Promote and Communicate an Effective Green and Sustainable Communication: A Neuromarketing Study . . . . . . . . . . . . . . . . . . . . . . Ana C. Martinez-Levy, Daniele Sasso, Alessia Vozzi, Stefano Menicocci, Arianna Trettel, Fabio Babiloni, Giulia Cartocci, and Patrizia Cherubino The Influence of Sensory Marketing on Consumers with Different Characteristics Regarding Physical Store Shopping . . . . . . . . . . . . . . . . Enshang Shang, Gianpaolo Vignali, and Claudia Henninger Part III
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Business Models
Blue Ocean Strategy in the Fashion Textiles Business . . . . . . . . . . . . . . Léo-Paul Dana and Aidin Salamzadeh Sustainable Mass-Customisation Business Model by Incorporating Virtual Fitting Room Marketing Tools in Fashion E-Commerce: A Study of the Luxury Unstitched Market . . . . . . . . . . . . . . . . . . . . . . . Sadia Idrees, Gianpaolo Vignali, and Simeon Gill
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Digital Customer Relationship Management (e-CRM) in the Fashion Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Emanuela Sommella and Annarita Sorrentino
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The Use of Computer Information Systems (CIS) in the Ready-Made Garment (RMG) Industry in Bangladesh: Applications, Challenges, and Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Md. Mizanur Rahman, Pranto Barua, Md. Saidur Rahaman, and Iqbal Hossain Moral
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Part IV
Toward the Future
Enhancing Female Clothing Shopping Experience by the Use of the 3D Body Scanning Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . Daniela Campaniolo, Gianpaolo Vignali, and Daniella Ryding Simulating the Synergistic Experiences of Customers in Show-Rooming and Web-Rooming Retail Channels . . . . . . . . . . . . . . Louise F. Reid, Gianpaolo Vignali, Katharine Barker, Sadia Idrees, and Helen Hann Understanding the Application of AI-enabled Chatbots in Luxury Fashion Retailing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ni Zeng, Gianpaolo Vignali, and Daniella Ryding
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The Opportunities & Challenges of the Metaverse for Fashion Brands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Courtney Chrimes and Rosy Boardman
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Understanding Social Media & Future Experience . . . . . . . . . . . . . . . . Norliana Jailani and Gianpaolo Vignali
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The Impact of Virtual Interactivity on Shopper Behaviour . . . . . . . . . . Meera Dulabh, Delia Vazquez, Daniella Ryding, Alex Casson, and Myriam Caratù
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Exploring the Influence of Experiential Characteristics in Fashion Pop-Ups on the Retail Experience of UK Millennial Consumers . . . . . . Bethan Alexander and Hui Lai Ling
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Exploring the Perceptions of Climate-Aware Generation-Z Towards Fast-Fashion’s Greenwashing for the Climate-Crisis . . . . . . . . . . . . . . . Martha Paulina Bytof and Elaine L. Ritch
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Part V
Pedagogical Exercises
The Role of Islamic Culture on Product Designs and Use of Social Media Marketing in the Fashion Industry: Case Study in Saudi Arabia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reem Almesahri, Gianpaolo Vignali, and Daniella Ryding Paul Smith Meets Japanese WA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yao Yao, Léo-Paul Dana, and Claudio Vignali
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Vegan Fashion, Why Not? A Typology for Future Research, Classroom Discussion, and Informed Consumerism . . . . . . . . . . . . . . . . Jack Coffin
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Cotton Textile Industry in Ancient India (Tools, Techniques, and Organization) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shalini Wadhwa
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Correction to: The Garment Economy . . . . . . . . . . . . . . . . . . . . . . . . . . Michelle Brandstrup, Léo-Paul Dana, Daniella Ryding, Gianpaolo Vignali, and Myriam Caratù
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About the Editors
Michelle Brandstrup studied at Kingston University and obtained her postgraduate degree at the Designskolen Kolding. With a diploma in tailoring, and another in fashion design, she has been employed in Berlin, Paris and at Christianshavn, in Copenhagen. She is currently a fashion designer at Kabooki, where she has been heading the launch of a new brand. She was nominated for the Scandinavian Designers Nest award. Myriam Caratù is Assistant Professor of Marketing at UNINT—Università degli Studi Internazionali di Roma, Faculty of Economics (Rome). She is teacher of the courses "Green Marketing" (undergraduate), “Digital Marketing and E-Commerce” (undergraduate), and "Marketing for Made in Italy" (graduate). She holds an M.A. in “Italian Studies” and an M.A. in “Marketing and Communication” (both achieved at Sapienza University) as well as an M.F.A. in Creative Writing, achieved at LUISS Guido Carli University. She is Ph.D. in Sociology of Communication (Department of Communication and Social Research of Sapienza University). She has been a Visiting Scholar at CUNY—City University of New York and a Research Fellow both at the University of Rome Sapienza (2016) and at the University of Perugia (2018). She is member of SIMrktg (Società Italiana Marketing), SIMA (Società Italiana di Management), and AIDEA (Accademia Italiana di Economia Aziendale). Léo-Paul Dana is Visiting Professor at LUT School of Business and Management, Lappeenranta University of Technology, Finland and Professor at ICD Business School, Paris, France. He holds the title of Professor at Dalhousie University and is also associated with the Chaire ETI at Sorbonne Business School. A graduate of McGill University and HEC-Montreal, he has served as Marie Curie Fellow at Princeton University and Visiting Professor at INSEAD and at Kingston University. Daniella Ryding is a Senior Lecturer in Fashion Marketing, in the Department of Materials, Faculty of Science and Engineering, at the University of Manchester. She is the Academic Lead for the flagship teacher training programme, accredited by Advance HE, and is thus responsible for the training provided to all new academics in the faculty. The author is an active researcher for consumers in their locations and environments and specialises in research which examines contemporary trends and xv
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developments within changing environments and the ramifications for marketing strategy. Her specialism is centred on strategic marketing and complex cognition. She has published over 50 articles in academic peer-reviewed Journals and is the editor for several marketing and business textbooks, including Springer Nature and the Luxury Palgrave Series. Gianpaolo Vignali is a graduate from UMIST with his first degree in Mathematics. Later adding a Master’s in Strategic Management, his career started at Manchester Metropolitan University before moving to full-time employment in the Department of Retail at Leeds Metropolitan University. He then became the Programme Leader for Fashion Buying and Merchandising at Manchester Metropolitan University until he achieved his PhD and moved to Manchester University working in the School of Materials where he delivers on both undergraduate and post-graduate programmes.
Part I Introductory Chapters
Introduction to the Garment Economy Michelle Brandstrup and Léo-Paul Dana
Abstract
The garment economy is constantly evolving. During the early twentieth century, fashion ideas emerged in Paris, and this city became the world’s fashion capital; however, fashion capitals of the world today include London, New York and Milan. Since the turn of the millennium, clothing production has approximately doubled, and employing as many as 300 million people around the world. The garment economy of today currently exceeds US $1,000,000,000,000.00. Keywords
Fashion · Textile industry · Garments · Chanel · Dior · Singer · Sentier · Cotton
The garment economy is constantly evolving. As explained by Brandstrup (2021), until the nineteenth century fashion was largely dictated by the aristocracy. ‘In the late nineteenth century, the dressmaker evolved to become a fashion designer, similar to an artist, who then took the position of dictating fashion, instead of it being dictated by the aristocracy (Brandstrup, 2021, p. 165).’
M. Brandstrup Design School Kolding, Kolding, Denmark L.-P. Dana (✉) Dalhousie University, Halifax, NS, Canada LUT School of Business and Management, Lappeenranta University of Technology, Lappeenranta, Finland ICD Business School, Paris, France e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_1
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Exhibit 1 Metro station at Sentier neighbourhood; photo # Léo-Paul Dana
During the early twentieth century, fashion ideas emerged in Paris, and this city became the world’s fashion capital. Fashion designers experimented with new ideas here and the Sentier neighbourhood—see Exhibit 1 (in the second district of Paris)— is still a very important area for textile industries, including silk (Exhibit 2). It was 1910 when Gabrielle ‘Coco’ Chanel (1883–1971) opened her ‘Chanel Modes’ hat shop in Paris (at 21 rue Cambon 1—see Exhibit 3); in 1918 she expanded, purchasing the building at 31 rue Cambon (Exhibit 4) and created the concept of the modern boutique. It was here, in May 1921, that she launched her first perfume, Chanel No. 5 (see Exhibit 5). Also in Paris, in 1947, French designer Christian Ernest Dior (1905–1957) gained international fame for his revolutionary ‘New Look’, featuring a cinched waist, and a voluminous skirt—strikingly different than the style worn during World War II. In 1957, he died at 52, whilst on holiday in Montecatini Terme. His firm, Christian Dior SE, is now owned by Moët Hennessy Louis Vuitton, with world headquarters in Paris. Maison Louis Vuitton Vendôme is a prominent boutique at Place Vendôme 2 (Exhibit 6), in the first district of Paris. Also at Place Vendôme are boutiques of
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This street was named for a French revolutionary, the son of a fabric manufacturer. Gabrielle ‘Coco’ Chanel once resided at 15 Place Vendôme.
Introduction to the Garment Economy
Exhibit 2 Silk boutique; photo # Léo-Paul Dana
Exhibit 3 21 rue Cambon today; photo # Léo-Paul Dana
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Exhibit 4 Chanel at 31 rue Cambon; photo # Léo-Paul Dana
Exhibit 5 Chanel No. 5; photo # Léo-Paul Dana
other leading brands, including Chanel, Dior (Exhibit 7), and Gucci (Exhibit 8), amongst others.
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Exhibit 6 Place Vendôme; photo # Léo-Paul Dana
During the 1980s, France introduced incentives to entrepreneurs in the textile industry (Dana, 2006). Following Vietnamese liberalisation in 1986, private firms in (formerly French) Vietnam became increasingly involved in the garment economy (see Exhibit 9). Over time, regional clothing and indigenous patterns (see Exhibit 10) increasingly yielded to global trends. Nowadays, few peoples—such as the Kuna Indians (see Exhibit 11)—retain their traditional styles. Largely fuelled by a growing middle class in many countries, clothing production is approximately double that at the turn of the millennium. The garment economy today currently exceeds US $1,000,000,000,000.00. A trillion dollars is indeed significant and the sector employs 300 million people in countries as large as Canada (see Exhibit 12) and as small as Lesotho (see Exhibit 13). In the USA, the Cotton Belt was the name given to a region which grew cotton as its predominant cash crop (see Exhibit 14) from the late eighteenth century into the twentieth. An important link in the transportation of cotton was the St. Louis Southwestern Railway launched in 1891 and known as the Cotton Belt Route (see Exhibit 15). Exhibit 16 features a cotton cloth manufacturing facility in Egypt. Whilst Italy was the birthplace of several leading designers—including Giorgio Armani (1934–), Roberto Cavalli (1940–), Valentino Garavani (1932–), Guccio Gucci (1881–1953), and Gianni Versace (1946–1997)—according to IFDAQ, France is the world leader when it comes to fashion. Along with Paris, fashion
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Exhibit 7 Dior at Place Vendôme; photo # LéoPaul Dana
capitals of the world today include London, New York, and Milan. At a domestic level, Sydney is considered to be the fashion capital of Australia (see Exhibit 17). This book introduces the readers to the garment economy, with chapters discussing history of the sector and others developing business models and explaining digital technologies. Chapters ‘The History of Bedouin Clothing Made for Traditional Nomadic Lifestyle’, ‘The Garments Economy: An African Perspective’, ‘Indian Clothing: Its Evolution and Development,’ and ‘Migrant/Minority Economy? Jewish and Greek Migrant Entrepreneurial Patterns in the Greek Interwar Clothing Industry, 1923–1940’ provide a variety of perspectives about traditional clothing. Chapters ‘Greenwashing in the Fashion Industry: Definitions, Consequences, and The Role of Digital Technologies in Enabling Consumers to Spot Greenwashing’, ‘Modest Fashion and Sustainability: Research Trends by Bibliometric and Content Analysis’, ‘The Evolution of the Applications of Influencers for Fashion Brands on Social Media’, ‘Reuse of Pre-loved Garments: Pain or Gain?’, ‘Sharing Is Caring: The History of ‘Sharing’ New Interpreted’, ‘How to Promote and Communicate an Effective Green and Sustainable Communication: A Neuromarketing Study’, and ‘The Influence of Sensory Marketing on Consumers with Different Characteristics Regarding Physical Store Shopping’ analyse the
Introduction to the Garment Economy Exhibit 8 Gucci at Place Vendôme; photo # LéoPaul Dana
Exhibit 9 Barefoot and using old Singer machines; photo # Léo-Paul Dana
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Exhibit 10 Traditional Maori styles; photo # Léo-Paul Dana Exhibit 11 Kuna Indian in traditional style of San Blas; photo # Léo-Paul Dana
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Exhibit 12 Stanfield’s factory in Truro, Canada; photo # Léo-Paul Dana Exhibit 13 Youth in Lesotho; photo # LéoPaul Dana
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Exhibit 14 Cotton plant; photo # Léo-Paul Dana
Exhibit 15 Logo of the Cotton Belt Route; photo # Léo-Paul Dana
globalised garment sector today. Chapters ‘Blue Ocean Strategy in the Fashion Textiles Business’, ‘Sustainable Mass Customisation Business Model by Incorporating Virtual Fitting Room Marketing Tools in Fashion E-Commerce: A Study of the Luxury Unstitched Market’, ‘Digital Customer Relationship
Introduction to the Garment Economy
Exhibit 16 Manufacturing cotton cloth; photo # Léo-Paul Dana
Exhibit 17 Rex Simpson brought fine fashion to Sydney; photo # Léo-Paul Dana
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Management (e-CRM) in the Fashion Industry’, and ‘The Use of Computer Information Systems (CIS) in the Ready-Made Garment (RMG) Industry in Bangladesh: Applications, Challenges and Recommendations’ discuss how enterprises create and deliver value in the sector. Chapters ‘Enhancing Female Clothing Shopping Experience by the Use of the 3D Body Scanning Technology’, ‘Simulating the Synergistic Experiences of Customers in Show-Rooming and Web-Rooming Retail Channels’, ‘Understanding the Application of AI-Enabled Chatbots in Luxury Fashion Retailing’, ‘The Opportunities and Challenges of the Metaverse For Fashion Brands’, ‘Understanding Social Media and Future Experience’, ‘The Impact of Virtual Interactivity on Shopper Behaviour’, ‘Exploring the Influence of Experiential Characteristics in Fashion Pop-Ups on the Retail Experience of UK Millennial Consumers’, and ‘Exploring the Perceptions of Climate-Aware Generation-Z Towards Fast-Fashion’s Greenwashing for the Climate Crisis’ ponder the future of the garment economy. The book concludes with pedagogical exercises. Enjoy!
References Brandstrup, M. (2021). Entrepreneurs in the fashion industry. In L.-P. Dana (Ed.), World encyclopedia of entrepreneurship (2nd ed., pp. 165–176). Edward Elgar. Dana, L.-P. (2006). Entrepreneurship & SMEs in the Eurozone: Toward a theory of symbiotic enterprises. Imperial College Press.
The History of Bedouin Clothing Made for Traditional Nomadic Lifestyle Hafiz Wasim Akram and A. Allan Degen
Abstract
This chapter touches upon the historical aspects of Bedouin clothing made for the traditional nomadic lifestyle in the Arab World. It also emphasises the changes in taste and preferences of Bedouins in the Arab World that have occurred over time. The modus operandi adopted during the course of clothe manufacturing for nomads is described. The historical descriptive methodology is discussed following discussions with nomads and with experts working with and dealing with nomads. Apart from secondary sources of data, personal interviews and observations were also employed during the course of the chapter writing. Keywords
Bedouin clothing · Traditional clothing · Folk heritage · Arab world
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Introduction
According to the Merriam-Webster Dictionary, the term ‘Bedouin’ (plural: ‘Bedouin’ or ‘Bedouins’) refers to a nomadic person who hails from the Arabian, Syrian, or North African deserts. The etymology of the word ‘Bedouin’ is derived from the Arabic word ‘Baddu’ ()ﺏﺩﻭ, and the origin of the concept has its roots in the Arabian H. W. Akram (✉) Department of Marketing & Entrepreneurship, College of Commerce and Business Administration, Dhofar University, Salalah, Oman e-mail: [email protected] A. A. Degen Desert Animal Adaptations and Husbandry, Wyler Department of Dryland Agriculture, Institutes for Desert Research, Ben Gurion University of the Negev, Beer Sheva, Israel e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_2
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Exhibit 1 Bedouin in the Negev Desert, Israel, wearing traditional clothes; photos # A. Allan Degen
culture to refer to migratory, homeless people who move with the seasons. They have their distinct style of food and clothing (Exhibit 1). Nevertheless, with the passage of time and the societal development, many changes have taken place. Although many Bedouins have adopted a settled life, they have retained their culture even today. Their presence is found throughout the Arab world, from Morocco in the west (the Maghreb) through the deserts of Syria and Iraq, as well as the Arabian Peninsula (Exhibit 2). Herding sheep, goats, and dromedaries is how most Bedouins make a living, or, at least, they did in the past (Degen, 2021). Dromedaries were utilised for transportation as well as for production of meat, milk, and wool. It is worth noting that the Bedouin consider themselves as Arabs and not as Bedouin. According to Wright (1982), the term ‘Arab’ is a broad one, and cannot be defined precisely. Those who are identified with the conquest of Islam and the language and culture that accompanied it are considered to be Arab. The Bedouin are known for bravery, hospitality, family devotion, and ethnic pride. In the olden days, tribal chiefs exercised authority over Bedouin communities. The leaders ruled from stronghold areas, from which they oversaw trade and commerce throughout the territory under their jurisdiction. A sense of common lineage was of utmost importance, even until today, and it was the glue that held the different Bedouin clans together (Hourani, 2013).
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The Historical Aspect of Bedouin and Their Habitation
The weaving method of Bedouin is an indigenous technique that dates back to the prehistoric Arabian Peninsula (Balfour-Paul, 2012). The area was not identified in archaeological maps listing ancient places in the peninsula (Reinhold, 1981). Nonetheless, the peninsula witnessed serious explorations a few decades ago (Hogarth, 2011) to reveal evidence of a vibrant and rather complex history. As opposed to the lack of vegetation in contemporary times, the prehistoric Arabian Peninsula, similar to the Sahara Desert, was dotted with grasslands and lakes. Hunter-gatherers inhabited the area, but without an organised material culture (Wright, 1982). Around
The History of Bedouin Clothing Made for Traditional Nomadic Lifestyle
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Exhibit 2 Map of Arabian Peninsula: Nations Online Projects (with permission)
7000 BC, when water became scarce due to the drying up of lakes, the nomadic population moved, rather unwillingly, to the Persian Gulf in the north (Issar, 2013). By the turn of the Fifth Millennium, Neolithic farmers populated and settled the area (Headrick, 2009). They raised goats and sheep, fished in the Gulf, and had links with Mesopotamia, given the pottery art found in the region (Carter, 2010). The archaeological findings, in fact, suggested the widespread contact of the people of the Arabian Peninsula with other civilisations of the Fertile Crescent (Bailey, 2004). Various coastal places belonging to the Dilmum culture in Bahrain served as harbours for trade between the Indus Valley and Mesopotamia (Crawford, 1998). There is ample evidence found in the documented history of trade originating from the southern part of the Arabian Peninsula. One example is the trade of spices and incense with India (Boivin & Fuller, 2009). Later, the commerce expanded to include trade of cotton, yarn, and cloth. Contrary to the popular belief that nomadism was a remnant of some prehistoric phase in the cultural development of humans, it is, in fact, a recent phenomenon which preceded the emergence of sedentary pastoralism (Potts, 2014). A form of pastoralism, pastoral nomadism, is identified with the herding of livestock mainly for
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their products and by-products, such as milk, meat, hides, and fibres, in areas known for limited resources of water and forage. This warrants seasonal movements to provide grazing land and water for the livestock (Sadr, 2017). Both nomadism and shepherding can and do exist autonomously (Chatty, 1980). European gypsies can be termed as nomadic whilst not classified as pastoralists, whereas sedentary pastoralism formed the bedrock upon which African societies depended heavily (Marsch, 2008). It is imperative to understand that a clear demarcation between sedentary and nomadic people cannot be drawn, as these people alternate back and forth between lifestyles in their bid to adapt to the environmental exigencies, such as drought (Salzman, 1980). Since most of the Arabian Peninsula experiences dry seasons annually, nomadism was the only possible way of populating the region (Heard-Bey, 2001), and, by Biblical times, it was well established in the region. It is actually mentioned in the Old Testament, which describes the Patriarchs’ way of life. Because nomadic pastoralism vividly portrays the struggle to survive in harsh environments, it is not surprising that nomads were traditional folks—their environment did not permit experimentation or error (Hughes, 2003). In fact, several facets of nomadic life in the Arabian Peninsula were still palpable during much of the twentieth century. The emergence of Islam had a significant impact on the history of the Arabian Peninsula (Bell, 2012). The pilgrimage to Mecca, referred to as Hajj in Arabic, was well known even at the time of Muhammad, the last prophet of Islam (Timothy & Iverson, 2006). He eliminated the polytheistic elements in the Hajj pilgrimage and integrated monotheistic beliefs into his doctrine (Timothy & Iverson, 2006). The expansion of Islam beyond the contemporary Middle East led to the extension of the Hajj pilgrimage, which brought people from deep pockets of Asia and Africa into Arabia and, along with them, their diverse cultural influences and indigenous products (Amrith, 2011). Simultaneously, Islam is praised for bringing a unique distinctiveness to the culture, whereby it was a conscious policy not to harm non-believers from the region where this religion originated. The Saudi Arabian society, therefore, is very particular about the influences that have penetrated it.
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Inception and Evolution of Bedouin Clothing for the Traditional Nomadic Lifestyle in the Arab World
In understanding the techniques and technology of Bedouin weaving, it is imperative to acquaint oneself with the history of the Middle East, particularly textile fibres. Goats and sheep formed the original basis of nomadism in the region; camels were a later inclusion amongst the domesticated animals (Dyson-Hudson & DysonHudson, 1980). Originally, goats and sheep arrived from central Asia, from where these animals spread into Asia Minor, other parts of southwest Asia, Ethiopia in Africa, and the Arabian Peninsula in the earliest phase of nomadic pastoralism (Wright, 1971). The original sheep were of the hair-type, unlike the present breeds. Thus, their fleece could not be used for making comfortable cloths (Ryder, 2017). Initially, the sheep were not raised for wool, and to date, wool obtained from
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Bedouin sheep remains coarse (Wright, 1982) and of marginal quality. Shears were not invented before the onset of the Iron Age. Goat hair did not feature such defects, albeit rough and not comfortable, and, therefore, weavers generally used it before wool was mainstreamed for producing fabrics (Riley, 2008). This strongly supports the notion that the Neolithic pastoralists must have used goat hair for weaving (Sherratt, 1981). It is highly probable, however, that they utilised animal skins instead of woven fabric for clothes, containers, and shelters. It seems certain that felt was an intermediary material between animal skins and the onset of weaving because the process of felting happens naturally upon wearing the sheep skin (Wright, 1982). The development of textiles, therefore, may not have happened in a sequential manner. During the same period, the production of flax and the manufacturing of linen were already practised in Egypt (Sen & Reddy, 2011). To substantiate this claim, researchers cite the evidence found on a plethora of tomb paintings that indicate a date at least 2000 years BC (Seidlmayer, 2000). Land in the Nile Valley was rich and cultivated extensively; it was not used for nomadic pastoralism (Haug, 2002). No fibre was used other than that extracted from flax, and the trade of linen contributed substantially to the Egyptian economy. The first loom, a horizontal loom featuring a string heddle and shed stick, was invented by the Egyptians (Crowfoot, 1937). This was designed to be operated by two weavers. According to Wilson (2021), it was meant for weaving warp cloths because shedding was too complex for this loom. Technically, warp-faced cloth needs lesser sheds in comparison to other weaving methods (Mårtensson et al., 2009). The Egyptians invented the technique of weaving linen on drop spindles (Hochberg & Hochberg, 1980), effecting a left-handed or S-shaped twist because the fibre of flax naturally twists in that direction whilst undergoing the weaving process (Suhr, 1963).
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Bedouin Loom in Contemporary Time
In contemporary times, the Bedouin loom (Exhibit 3; Degen & El-Meccawi, 2022) appears very similar to the Egyptian loom, and seems to be inspired from the Egyptian model either directly or indirectly (Barber, 1991). It is quite apparent that there were cultural relations between the animal skin wearing nomadic population of the Arabian Peninsula and the Egyptian linen weavers owing to trade, and probably through nomadic exodus to the Nile Valley after crossing over the Sinai Peninsula (Liu, 2010; Moreno García, 2017). It is very likely that the loom might have arrived in Egypt indirectly through Mesopotamia or other civilisations of the Fertile Crescent as this region presents evidence of the use of wool much earlier (Broudy, 1993). The Bedouin loom, similar to the horizontal loom of Egyptian origin, features two beams affixed to the ground with the warp ensconced in the empty stretch (Wright, 1982). It features a shed stick and heddle rod to make openings in the warp (Crowfoot, 1937). Generally, the nomadic loom is thin, but can be operated by up to three weavers (Seyf, 1990). As opposed to its Egyptian counterpart, the heddle rod is supported by rocks (or empty cans or concrete blocks in recent times) at both ends
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Exhibit 3 Bedouin woman in the Negev Desert, Israel, weaving on a traditional ground loom; photo # A. Allan Degen
(Wright, 1982). The loom is well suited for the nomadic lifestyle as the design allows it to be folded easily, even with unfinished weaving, and transported on a camel’s back to a new site (Akou, 2011). It needs a minimal quantity of framing wood, which could be collected easily, even in deserts. Tents of Bedouin origin have seen fractional changes over the millennia (Katsap & Silverman, 2016), and hence the strips of cloth made of goat hair, which are stitched together, seem similar to Egyptian weaving, as they are long, narrow, and warp-faced (Broudy, 1993). Therefore, the notion that the tent cloth was amongst the first woven articles by the Bedouin seems quite plausible. The Bedouin continue to use the drop spindle for spinning yarns (WilleyAl’Sanah, 2013). This technique, too, was possibly derived from the Egyptians, although the technique might have evolved in one of the earliest known textile centres or could possibly have sprung up autonomously across multiple sites (Langgut et al., 2016). The direction of twisting yarns whilst spinning in the old textile centres lent a cascading effect up to contemporary times (Desai, 2012). Animal fibres and wool demonstrate no inherent disposition towards one direction or the other. As stated above, flax fibres twist in an ‘S’ pattern in processing (Corbin et al., 2020). The reason behind the pervasiveness of S-twisted yarn in eastern Africa is the dominance of Egyptian textile centres in developing flax (Frantz-Murphy, 1981). In Asia, Z-twisted pattern is intrinsic to the yarn used in rugs of the Orient (Ishtiaque et al., 2015), though spinning in either direction has been practised by Bedouin in Palestine and Syria, and by Baluchi in Afghanistan and Pakistan (Betts et al., 1994). It is not surprising, therefore, that the Arabian Peninsula, located between Africa and the Asian rug belt, spins in both directions (Wright, 1982). Not surprisingly, S-twist enjoys dominance in the southwest bordering Africa
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(Kriger, 2006), and Z-twist reigns in areas close to the rest of Asia (Gasparini, 2019). What is surprising, however, is the presence of different-twisted yarns juxtaposed with each other in numerous pieces of fabric, defying the established methods of weaving. Konieczny (1979) highlighted that the patterns of Baluchi-origin yarn spin are connected to the technique and standing or sitting position of the spinner. Crowfoot (1944) elaborated that Palestinian Bedouin women devised a complex method of spinning: although spinning in one direction was common, they would reverse it for the spinning of goat hair. From what she described about Palestinian Bedouin women’s technique of spinning, one cannot clearly determine the direction which was used for a particular type of fibre. However, from the way she recorded her findings, one can discern that the spinning is intimately associated with the direction of the twist employed. Additionally, the dissemination of yarns owing to crossregional trade may explain the blend of yarns discovered (Strand et al., 2022). Willey-Al’Sanah (2013), along with others, has recorded the selling of yarn by Bedouin women on many different occasions. People belonging to tribes fully engaged in the herding of camels would obtain goat hair and wool by trading (Losleben, 2003). These instances bring forth the rationale for using both twists in the fabrics weaved by one Bedouin family. The cotton’s history is pertinent, as it forms the basis for another type of loom discovered in the Peninsula (Bouchaud et al., 2011). Historians have found evidence of spinning cotton in the Indus Valley around 2000 BC. Weavers there needed distinct techniques for both weaving and spinning in comparison to wool (Wright et al., 2012). Whilst weaving on the loom, a cotton warp is required to be kept at uniform intervals to protect the delicate yarns from becoming entangled and ultimately broken (Lord, 1982). Therefore, weaving reed was invented for both creating space and ramming down. The weaver requires both hands to manoeuvre the weft smoothly through the warp (Campbell & Ainsworth, 2002); hence, the heddle rods were tied to foot treadles. Since Indians usually sat on the floor, it was a normal practice to carve a slot in the ground for fixing foot treadles instead of increasing loom height (Broudy, 1993). Roth (2019) named the weaving instrument obtained in this manner as the ‘Hindu loom’. It was also termed as the ‘pit treadle loom’ (Sigl, 2020). The design features two or four harnesses that are complex sort of heddles, a beater dangled above (by threads on some looms) clutching the reed (Hills, 2002), a cloth beam for rolling the finished cloth, and the warp tied tautly to an upright post or wall. Since there is hardly any ground for refutation that India exported cotton to the region accompanied by looms (Menon, 2017), it is quite plausible that the design of the loom remained the same in Eastern Arabia, Sudan, and Yemen for two millennia or more (Roth, 1918). As has been demonstrated over centuries, nomadism has always required the nomads to keep a symbiotic relationship with the villagers for meeting their supply of food and other materials which they did not produce (Kelly, 1992). In his book, Eickelman (1984) indicates that the textile for making clothes was almost always bought by villagers. Prior to the emergence of machine woven materials till contemporary times, the pit loom was used for weaving such fabric.
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The pit loom was employed for weaving several types of fibres in the Middle East and provided the Bedouin with clothes they were unable to manufacture themselves (Venice & Lamb, 1980). Contemporary manual Saudi Arabian weaving technology comprises these two looms with yarns either spun with the help of drop spindle or spun for commercial purposes (Hilden, 2010). People may find interesting comparisons between the two looms representing both a social and an economic division. Firstly, the horizontal loom, right from its inception in prehistoric Egypt, had been and is being operated by women (Kriger, 2006), whilst the pit treadle loom is operated wholly by men in most places across Africa and the Middle East. Secondly, the pit loom is employed for production of textiles on a commercial scale (Wilson, 2021), whilst the Bedouin loom is used mainly for manufacturing textiles for home use (Broudy, 1993). Finally, the pit loom is associated with cities and towns, whereas the Bedouin loom is linked to villages (Wright, 1982). Pit looms require stability, whilst for nomadic life, the portability and simple design of the Bedouin loom make it convenient for villages (Venice & Lamb, 1980). It is surprising that not a single variant of the vertical loom is discussed in the Peninsula despite its presence in neighbouring Egypt, Syria, Palestine, Israel, and Africa and the conventional rug belt of the Orient (Forelli & Harries, 1977; Homan, 2004). It is very portable, which makes it suitable for use by North Africa’s nomadic Bedouin (Condra, 2013; Forelli & Harries, 1977). This loom also appears to be the first to emerge in Egypt, and the history of cross-cultural exchange implies that it may have been present in some parts of the Peninsula (Jacoby, 2004; Moyer, 2011). Furthermore, some weft-faced textiles discovered in the inhabited parts of southwest Arabia might have been woven on a vertical loom, similar to the Bedouin loom (Wright, 1982). However, no mention of such a loom design has ever been made in any scholarly work.
5
Modus Operandi for Clothes Manufacturing for the Nomads
A couple of questions that warrant attention in analysing Bedouin textiles are: (1) why is there a predominance of warp-faced structures in Bedouin weaving? (2) Why has the design of the Bedouin loom remained virtually the same over the years (Wright, 1982)? The first question comes to the fore because a similar technology was used to manufacture primarily pile structure and weft-faced material in many parts of the Middle East. The loom does not guide the shape of specific structures. This, together with the Egyptian technique, inspired warp-faced structures and loom designs to be popular in Saudi Arabia. The prevalent conservatism explains the retention of both. Elsewhere in the Middle East, as the second question addresses, looms designed for easy portability are appropriate for nomadic use. One such loom is the vertical loom, which is used by Berbers in North Africa. Men’s narrow band looms are another design used by a number of groups in West Africa (Forelli & Harries, 1977). The response to the above two questions suggests that the warp-faced structure and the Bedouin loom belong to an ancient complex
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design (Eiland, 1998) encompassing an inclination towards geometric figures, overspinning of yarn, a requirement for acute strength, the use of coarse wool, embellishment with weft twining, a markedly Bedouin sense of space, and, of course, conservatism. All these factors combine to form a cohesive product, and to change any of them would be tantamount to altering the eventual outcome. The overspinning of yarn is possible, given the sturdy nature of the fabric. Further evidence suggesting overspinning of yarn is the usual back-twisted pairs of warp ends found at ends of an unfinished fabric piece. It is mandatory to overspin wool to obtain a warp-faced structure to preclude the possibility of a sticky warp, which is not possible to pick out for a shed. Overspinning and coarse wool result in great durability and warp-faced fabric featuring high tensile strength when compared to other fibres since it has a greater density of fibres running across the length (Redmore, 2012). The warp-faced simple weave is normally adorned with one of many variations. The most common and simplest is the omnipresent warp stripes, either developed to include alternating colours in the warp treadling, or simply in solid colours to create two-coloured transverse bars. Outside this boundary, simple substitution of warp is employed, generally in white and black, to make geometric shapes inside every single warp stripe. The fabric’s upper face remains a simple weave of similar density, the same as the remaining part of the fabric, with the black displaying the non-utilised colour outlining warp floats. Substitution of warp is ensured by threading additional warps by way of fixed heddles, the same as the ground warps in dyads. The weaver selects the colour to be displayed in particular sections (Bergh, 1999). Such a design incorporating geometric shapes within the precincts of a stripe is known as al-sharijah (the tree) and provides the weavers some scope for experimentation as per their liking. A substitution of warp design, namely, llwairijan, offers borders of such stripes or acts as the main embellishment on simple pieces of fabric (Wright, 1982). In Bedouin weaving, twining is the exception to structures that are explicitly warp-faced. The fabric features weft-faced string twisted to form a slit tapestry. The pattern of weaving begins when a single yarn is folded to form two ends, which, in turn, engender an area of solid colour. The featured triangles induce recurring geometric patterns. Twining, extrapolated to ornamentation woven onto small bags, costumes, and leather pieces, could be accomplished by using rayon, fine leather thongs, or cotton. The Bedouin technique of twining is used eternally for adornment, since it is not meant for serving a large area created by a single colour (Canavan & Alnajadah, 2013). Evidence suggests that such weaved structures may have originated from Africa to the Arabian Peninsula, where it is occasionally used for the fabric’s main parts. It is seen as narrow bands of woven piece ends in other textiles found in the Middle East. The twisted-string tapestry, when applied on woolen textiles, comes eternally coalesced with the customary warp-faced structures. In Bedouin textiles, it is a unique combination. Such a combination of techniques, though, poses challenges in the shape of irregular warp tension and alterations in the breadth of the weaving scheme across different areas (Gokarneshan & Alagirusamy, 2009). In Bedouin weaving, this problem is resolved by using an elastic, overspun warp. Whilst it resists some deviation across the width of weaving,
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it is overcome by twining 4, 6, or 8 ends to make it the sole working end (Wright, 1982). In principle, twined parts are arranged in solid bands in a systematic manner. These bands are formed by connecting selvedge to selvedge, although one block of fabric in Topham’s assortment features motifs with recurring small diamonds and triangles (Topham, 1986). Such motifs are adorned with cautiously arranged edges sidelined in a warp-faced section wherein the warps transform very clearly from a 1/1 interlacement to clusters of four. The intricacy of manufacturing a shed on a Bedouin loom may turn a warp-faced structure into an appealing piece, as the twining is more attractive because there is no shed. Furthermore, the twirling of the twisted string wefts renders it a substantially stronger structure than the plain weave. Only some cultures have manufactured textiles integrating weft- and warp-faced structures. In general, one weaving structure is preferred over the other, depending on the culture (Brownlow et al., 2015). Some Indonesian fabrics use weft twining towards the ends of ikat pieces having warp-faced weaving (Solyom & Solyom, 2021). The fabrics are either silk or cotton and, therefore, possess a look and technique distinct from the Saudi work. The border features Indonesian designs and is usually crafted in red, black, and white, appearing straight rather than geometric. In such designs, the twining is finished manually, with the warp strings drawn through the lightly tensioned twining wefts. The threads of the warp are employed in clusters of 2–6 threads in varying combinations inside a piece of fabric, and the clusters of warps are divided into overlapping patterns for each row. The twining is completed with a couple of threads of distinct colors. For Indonesian textiles, the twined sections are narrower than the remaining part of the cloth (Gittinger, 1975). The distinct aspects of working techniques and designs suggest only a fraction of the historical link between the two, despite the proven connections between the Arabian Peninsula and Indonesia. Historically, Kurdish tribes had connections with Bedouin tribes in the bordering areas of Saudi Arabia and Iraq (Strakes, 2011). The Kurdish textiles, therefore, provide the opportunity of comparing the Bedouin work with itself. However, none of these designs displays the Arabian blend of weft- and warp-faced structures. These formations, nonetheless, are manifested in different kinds of Kurdish weaving. The Iranian Kurds’ warp-faced strips, classified, at times, under the overarching term ‘Jajim’, are frequently stitched together to make blankets or covers. They are so similar in method and form that they can be considered as small variants of the warpfaced work of Saudi origin. However, they are normally very narrow and are woven using very fine yarns; therefore, the similarity in appearance is minor. With respect to substitution work in Kurdish warps, one can discern less variation in a single piece that is characterised by a single recurring motif or group of motifs. The Kurdish differ considerably from those of Saudi Arabian Bedouin. Weft-faced pieces of the Kurdish colours nomadic origin are normally weft brocade or slit tapestry. The clothes of West African men are possibly the most fascinating visually, consisting of an uncomplicated combination of weft- and warp-faced weaving. Here, it is quite perceptible that the weft-faced structures are plain weave and not
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twined. It features brocading, along with some other weaves of compound weft (Venice & Lamb, 1980). The cloths of Ashanti and Ewe men were made of thin fabric strips, with generally alternating design units of weft- and warp-faced weaves. These units are normally organised to make a pattern upon sewing the strips together. On some occasions, the arrangement resembles a plain checkerboard, whilst on others, it appears less formal. Several Bedouin pieces, where weft- and warp-faced are arranged alternatively, are similar to this pattern. This arrangement is done deliberately to create a pattern when they are stitched together. In northern Saudi Arabia, archaeologists found some large pieces of tent curtains, which were created on solid black or solid white warps and were distinguished for their notable similarity to African samples; the warps were arranged as alternating strips upon assemblage. These two were integrated by the parts having a dense pattern in the weft twining. The tent curtains and rugs characterised by their weave on the Tuareg for the Niger bend, manufactured in thin strips with wool and cotton, with weft inlay, were similar to these textile pieces. These pieces provide a patterned design throughout the fabric, perpendicularly in the warp thread’s direction, much like the Arabian textiles (Venice & Lamb, 1980). From the African pieces, it can be inferred that the local weavers’ purpose was to keep selvedges as straight as possible. Nevertheless, scalloping the minor selvedges enhances the overall effect. The Ewe and Ashanti textiles are of silk and cotton, lighter than the Bedouin pieces, and the strips are very thin, measuring 4–5 in. In African pieces, warp figure weaving, simple pick-up, and ikat predominate. However, there is also some similarity between African and Bedouin styles, as the border stripes in the narrow warps attract comparison. This type of weaving has been chronicled since 1000 AD, but not prior to this period. It is widely known that modesty in design was brought in by the emergence of Islam, and along with new materials and techniques, led to notable transformations in the variety and clothing in areas of West Africa (Venice & Lamb, 1980). According to Venice and Lamb (1980), it was very common in the Islamic world for cloth to be manufactured from a number of elements sewn together from their peripheral parts. They theorised that the narrow strips woven together with cotton originated in the Nile Valley, or, perhaps, somewhere else in the Middle East. It can be ascertained that there is a historical link, but it is unknown which textile preceded the other. To make the issue more confusing, the cloths of Africa are produced entirely by men working on a loom that closely resembles the modern foot treadle loom of European origin or the pit treadle loom, as opposed to the Bedouin loom. Lastly, the resemblance in feel and layout between Moroccan textiles made by Berber and Arab nomadic tribes and Saudi Bedouin textiles is worth noticing. Several of the later weaving styles appear to be the precise weft-faced Bedouin counterparts, turned perpendicularly, despite the absence of technical similarity. The Moroccan samples feature patterned horizontal bands against a horizontally striped background, with textiles using secondary patterned vertical stripes. The arrangement does not move towards a centre or climax, but, instead, is characterised by a uniformly sustained progression of equal parts. As Flint (1980) notes, this can possibly be linked to a society with no hierarchical organisation and the lifestyle
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of a nomad. Furthermore, in relation to the long-settled Moroccan groups, he highlights the rather confined and recognised sense of space in the weaving of textiles. His observations, undoubtedly, also apply to the Bedouin textiles. Bedouin preferred wool as a weaving material, although the reasons are not as clear as they might appear to be. Goats and sheep are not raised by all nomadic Bedouin; therefore, the Bedouin do not necessarily have an assured source of either goat hair or sheep wool. Goat hair was preferred for tents because of two main reasons: goat hair is very sturdy, providing good insulation, and once it becomes wet, it expands and prevents water from seeping through (Na’amneh et al., 2008). For such traits, most goat hair was preserved for making tents (prior to import of Syrian cloth). Moreover, goat hair is coarser with a grainier fibre than wool, which may be the reason for its demand. Most nomads have camel hair available, but it is rarely used in Bedouin weaving (Degen et al., 2019). Lastly, wool is generally lighter in colour than other animal fibres which makes it receptive to dyeing. Colour is essential in the dreariness of the desert, hence the inclination to dyeing. The symbolic aspect of Bedouin textiles is difficult to interpret because of the absence of substantial prima facie information. A few of the figures substituted for warp have names, but these appear to apply, in general, to the methods used in creating certain patterns rather than the particular motifs. Wasms—lineage and tribal markings—employed to identify camels are represented in some types of weaving, as noted by Topham (1986). It is questionable as to what extent they are symbols instead of simply identifiers or signs. In the Topham collection, three pieces include representational symbols, namely, camels, humans, scissors, and numerals. The two bags displaying human and camel figures belonged to Jordanian Bedouin and, thus, are less indicative of Saudi practice, whilst some figures were observed on a recently discovered rug. In this instance, the emblematic figures differ in attribute and finishing from the encircling motifs, suggesting a deviation from the established practice. Cole (1975) noted that the curtains of a tent signify the tribe and lineage of the Bedouin camp, but failed to point out the motifs or combination of motifs and colours. Pommerol and D’Anvers (1900) ascribed the symbolic connotation to woven motifs, terming them as ‘ancient writing’ and ‘hieroglyphics’, and inferred that the motifs’ names and meanings comprised an esoteric knowledge which was disclosed to elite weavers. It appears that there is much similarity in the weaving techniques of Saudi and Moroccan nomads. However, it is a matter of speculation as to how much credit should be given to Pommerol’s peculiar romanticisation of the nomadic arts. In stark contrast, Shelagh Weir (1978) observed that there was widespread Bedouin textiles trade. She also noted that Bedouin textiles were manufactured frequently by rural communities to align with Bedouin preferences. This occurred because the hamlet weavers were familiar with the tribal symbols of their Bedouin customers. Lastly, Denny (1973) presented alternative views on the symbolic aspect of motifs in the Asian origin weaving of clothing. Denny’s statement that ‘“simple geometric forms” derive ultimately from the weaver’s improvisation within the demands of the technique’ seems applicable to weaving of Bedouin origin, and
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also applies to rugs of the Anatolian origin. However, he allows that this ‘principle of least resistance’ does not explicate all geometries. Therefore, one should essentially deem this contention that if we fail to comprehend the symbolic meaning of Asian rugs, it is due to the fact that the original meanings were compromised because of the casual copying or radical cultural change necessitated by migration, foreign influence, or war.
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The Garments Economy: An African Perspective L. B. Louw, S. van Antwerpen, and E. Esterhuyzen
Abstract
With 11 official languages, South Africa (SA) is in the fortunate position to have a variety of local cultures and a strong influence from the rest of Africa that is evident in the traditional clothing businesses. In terms of economic contribution, the textile and clothing apparel (garment) industry contributes 14% of manufacturing employment and 9% of the national gross domestic product (GDP). This industry is also the second largest source of tax revenue for SA. The United Nations’ Sustainable Development Goals (SDGs) and 2030 Agenda for Sustainable Development are aimed at ending poverty and include specific strategies to reduce inequality and spur economic growth. Due to the nature of the garment industry, it can be used as a tool for upskilling local communities to contribute to poverty eradication in Africa. This is just one example of an African country and the vital role of the garment industry in its economy. This conceptual chapter utilises a semi-systematic literature review, investigating academic, governmental, and private sector publications in order to convey an informed picture of the current state of the garment industry. This chapter investigates the garment industry in Africa, upskill local community for poverty eradication (including SDGs 1 and 8, diversity, cultural differences, and female empowerment), opportunities and challenges of the garment industry, and related industries (including manufacturing, environmental issues, and foreign market access). Due to the economic impact of the COVID-19 pandemic, it is more important than ever to stimulate economic growth and empower communities to actively participate in strong economic sectors such as the garment industry. L. B. Louw (✉) · S. van Antwerpen · E. Esterhuyzen University of South Africa (UNISA), Pretoria, South Africa e-mail: [email protected]; [email protected]; [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_3
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Keywords
Sustainable development · Sustainable economic growth · African garment industry · poverty alleviation · SDGs · Entrepreneurship · Africa · Women’s entrepreneurship
1
Introduction
Africa is known for its vibrant, multicultural environment. The garment industry in Africa is not just an economic hub but provides Africans with an opportunity to showcase their different cultures on the world stage (Exhibit 1). Businesses of all sizes can contribute to poverty eradication and social upliftment through the garment industry, but it is in the microenterprises and entrepreneurial ventures that the true passion of the African people is showcased. In an industry characterised by a largely female-led workforce, women entrepreneurs have proven to be resilient whilst still bearing the responsibility of primary caregivers and community support networks (GEM, 2021). Africa is characterised by the highest rates of women’s entrepreneurial intention in the world, which provides an excellent forecast for the future of Exhibit 1 Bright Nigerian garments part of the Yoruba tribe made from Ankara fabric to celebrate special occasions. Source: # StyleMeDolapo, used with permission
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Africa when taking into account the fact that women entrepreneurs invest 90% of their income back into their households and communities (as opposed to 35% by male entrepreneurs) (Webber & Chandani, 2020). In a post-pandemic world, the garment industry is more important than ever for preserving and sharing African cultural heritage whilst simultaneously presenting opportunities for growth, development, and improved quality of life for people in Africa. Such a preservation of cultural heritage becomes more important in an information age where traditionally oral methods of communication were used to preserve values, beliefs, and principles across generations (Omeluzor et al., 2014). The potential of the African continent as the next hub of sustained industrial growth was already identified by the World Economic Forum. The continent’s potential has only increased since then with an expansion of the work-age population and GDP growth in need of expansion (Botti, 2019).
2
Overview of the Garment Industry in Africa
The advent of the global COVID-19 pandemic was characterised by a negative economic impact across all industries. However, African garment industry businesses were able to capitalise on the shift towards digital trends, creating greater opportunities to engage in e-commerce, artificial intelligence, and the advantages of digital printing tools (AfDB, 2021a). However, Africa is a continent of many contradictions, and despite the opportunities, some business owners were able to utilise; others seem to be stuck in the nascent entrepreneurial space, where poverty is a daily reality due to a lack of access to financial support and infrastructure, overregulation, or facing an administrative burden (Choto et al., 2014; Louw, 2018).
2.1
The Garment Industry in Africa
The fashion or garment industry in Africa is characterised by most women’s business ownership (Exhibits 2, 4, and 5). Women entrepreneurs are featuring more within the traditional, informal sectors, such as the garment industry (Webber & Chandani, 2020). On the one hand, their majority involvement in the garment industry can be seen as pursuing a less technical, lower profit business. However, the garment industry and its related industries are highly creative and flexible industries that allow women entrepreneurs to create and innovate whilst still being able to act as primary caregivers to their families (GEM, 2021; Webber & Chandani, 2020). This industry presents women entrepreneurs with a unique opportunity where they are not forced to choose between either earning a salary or taking care of their families. The top ten exporting countries within the garment industry are Mauritius, South Africa, Lesotho, Madagascar, Kenya, Botswana, Swaziland (Eswatini), Ethiopia, Tanzania, and Malawi. Their combined garment industry exports are totalling over US $2.5 billion. The governments of these African countries are involved in various initiatives to encourage creative industries, providing funding,
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Exhibit 2 Woman entrepreneur creating new garment design. Source: # StyleMeDolapo, used with permission
loans, skills programmes, and improved trade agreements (AfDB, 2020). This makes it an ideal hub for clothing production as it satisfies all the requirements regarding labour, institutions, and stability. Nevertheless, a common concern for international organisations is the fact that this improvement and growth is very uneven across the countries in the region when compared with global benchmarks (Botti, 2019). The challenges persisting this uneven distribution of growth are described in greater detail in Sect. 4.2 of this chapter. As with other industries, the small businesses in the garment industry face a number of challenges that make survival in the industry more difficult. The challenges faced by most garment industry businesses include a lack of financial support, and limited access to the market (ANDE, 2021). These businesses also face the issue of not having sufficient entrepreneurial or managerial skills, supported by earlier research in other South African industries (Louw, 2018). These include financial, agriculture, and e-commerce industries, which are garments and fashionrelated industries (Rabana, 2019). These businesses are also hampered by social issues and not having an entrepreneurial growth mindset (ANDE, 2021). The global supply chains in the garment industry rely heavily on the resources available in Africa. First, the raw material required by the garment industry that is produced by farming and ginning is sourced throughout the African continent. These labour-intensive activities rely on the availability of a sizable workforce and natural resources. Additionally, the components and final garments also have to be
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produced. Some of the largest garments factories in the world are located in the African country, Ethiopia (ILO, 2021). Exhibit 3 summarises the fashion, textile, and garment industry as percentage of value added in manufacturing of 38 of the 54 African countries (UNIDO, 2020). Despite the global reliance on the African continent for the supply of resources, very few African countries are identified as being part of the top distributors of textiles and textile products since these are mainly processed in China, the EU, and other eastern countries. Africa is also not the end market that textile manufacturers Algeria (1%)
Libya (10%)
Benin (14%)
Madagascar (30%)
Botswana (2%)
Malawi (2%)
Burkina Faso (19%)
Mauritius (32%)
Burundi (1%)
Morocco (11%)
Cabo Verde (4%)
Mozambique (16%)
Cameroon (6%)
Namibia (6%)
Congo (2%)
Niger (11%)
Cote d’Ivoire (10%)
Nigeria (11%)
Democratic Republic of Congo (2%)
Rwanda (9%)
Egypt (8%)
Senegal (1%)
Eritrea (10%)
Sierra Leone (1%)
Eswatini (6%)
Somalia (13%)
Ethiopia (10%)
South Africa (2%)
Gabon (1%)
Sudan (4%)
Gambia (22%)
Tanzania (7%)
Ghana (6%)
Uganda (4%)
Kenya (18%)
Zambia (1%)
Lesotho (14%)
Zimbabwe (3%)
Exhibit 3 Fashion, textile, and garment industry as percentage of value added in manufacturing per African country. Source: # Authors
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are focused on, despite representing 16% of the world’s population. The largest end users within the garment industry are the EU and the USA (ILO, 2021). Despite the continued success and growth of the garment industry in Africa, exports from African countries only account for less than 1% of the global exports (AfDB, 2020). The most active of these exporting African countries are Morocco, Tunisia, Egypt, Mauritius, Kenya, South Africa, Lesotho, Madagascar, Botswana, Eswatini, Ethiopia, Tanzania, and Malawi (AfDB, 2020; Fibre2Fashion, 2021).
2.2
Small Businesses in the Garment Industry
Within an African context, many small businesses are started out of a necessity to survive and take care of family, extended family, and even a community (Ranyane, 2022). In these cases, it is commonplace for entrepreneurs to have a survivalist perspective, where they tend to be satisfied with their business size as long as it meets their immediate needs (Du Toit et al., 2020). This also creates a situation where the business model followed by African garment industry entrepreneurs is not scalable. The prevailing cultural challenge within the African context seems to focus on attaining formal employment rather than developing a growing entrepreneurial venture and providing that formal employment to others (ANDE, 2021). For small businesses in the garment industry in Africa to fulfil its potential as an economic hub, a cultural revolution must occur. This cultural revolution refers to a revolution in entrepreneurial culture in Africa. A post-colonial Africa finds itself in an economic environment where great emphasis has been placed on the value of vocation as opposed to entrepreneurial pursuits (Ochonu, 2020). The youth unemployment rate in Africa reached 60% in 2021. With 60% of people under 25 being unemployed, there is a serious need to bridge the gap between education and economic activity (AUDA-NEPAD, 2021). Entrepreneurial culture is informed by entrepreneurial intent, opportunity, skill, and the availability of resources (Jackson, 2016). Despite the challenges this causes for countries across the African continent, it presents a greater opportunity for unemployed youth to enter the informal and micro-economy. The lack of cultural support for participating in the informal and micro economy can be addressed through private and governmental skills programmes focusing on developing entrepreneurial skills in unemployed youth (AUDA-NEPAD, 2021).
2.3
Industries Related to the Garment Industry in Africa
During the production of garments for distribution across the world, a number of related industries provide products and services. In addition to producing and sourcing raw materials through farming, ginning, and manufacturing, components are required to manufacture the final products. Capital-intensive processes such as yarn spinning, weaving, and dyeing are key components to creating finished garments. The majority of female workers are employed in the manufacturing of
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finished garments, cutting, spreading, sewing, ironing, finishing, and packaging the products in large, formal factories or smaller home-based microenterprises (ILO, 2021). Up to 70% of the workers employed in the garment industry work in sewing, and the vast majority of the workforce is female (Exhibits 4 and 5). The reasons for this phenomenon were described earlier in this chapter. The end product distribution required additional services such as warehousing and logistics, branding, marketing, and product development. These additional services are sourced in the import countries such as the USA and EU countries, not in the originating countries where the raw materials were sourced. The major role players within these global garments supply chains include the various governments in which materials are sourced, manufactured, exported, and imported. Governmental role players are usually represented by the ministry of agriculture and the ministry of trade, depending on the role the country is fulfilling in the process. Additional role players are employers and workers in the garment and related industries, their service providers, private and governmental compliance ensuring agencies, and skills development agencies (ILO, 2021). In order to capitalise on the resources available in Africa for the garment supply chains, the African Development Bank Group (AfDB) negotiated an African Continental Free Trade Area between various stakeholders. The AfDB Fashionomics Africa initiative aims to develop connections and relationships between major and minor stakeholders within the African garment industry. With the establishment of the African Continental Free Trade Area, they aim to reduce the barriers faced within Exhibit 4 Creating a new garment design in South Africa. Source: # StyleMeDolapo, used with permission
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Exhibit 5 Setswana cloth called seshweshwe in South Africa used for lobola or Magadi celebrations. Source: # Juliet Mochuana, used with permission
the industry, including trade tariffs. There is also an increased focus on utilising local resources within the garment industry, to ensure that the industry can capitalise on an African network of suppliers (AfDB, 2021b). As previously mentioned, reducing trade barriers is a key method of facilitating increased entrepreneurial activity and entrepreneurial growth.
3
SDG and Poverty Eradication
Agenda 2063 and the African Development Bank (AfDB) aim for inclusive growth and sustainable development. Investing in the creative industries (such as the garment industry) allows for incorporating and building on the African cultural identity and common heritage whilst unleashing the potential of its women and youth to catapult the continent towards a strong and influential presence (AfDB, 2020). The member states of the United Nations adopted the 2030 Agenda for Sustainable Development in 2015 (Exhibit 6). This Agenda comprises a plan of action aimed at eradicating poverty by 2030. Poverty is regarded as the greatest global
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Exhibit 6 Sustainable development goals. Source: United Nations (https://www.un.org/ sustainabledevelopment/news/communications-material/)
challenge and a non-negotiable part of sustainable development (United Nations, 2015a). To affect the vision of the 2030 Agenda, various Sustainable Development Goals (SDGs) were formulated and accepted to encourage action by developed and developing countries to improve health and education, reduce inequality, and enhance economic growth (United Nations, 2015b). SDG 1 and SDG 8 are of particular importance for the garment industry and merit further discussion and application. In their SDGs for better fashion 2018–2019 progress report, Regenerate Fashion (2020) highlight the role of key stakeholders in the transformation of the garment industry and its associated value chain in order to achieve sustainability. The garment industry’s sustainability requires an understanding of cultural values and geographic contexts and setting future goals. This is achieved through the continued commitment of stakeholders to achieve the sustainable development goals, education and skills programmes for students, and the education of consumers towards the understanding of sustainability and the role they can play in achieving it. SDG 1 and SDG 8, as illustrated in Exhibit 6, are of particular importance for the garment industry and merit further discussion and application.
3.1
SDG 1: No Poverty
SDG 1 is aimed at ending poverty in all its forms everywhere, illustrated in Exhibit 7 (United Nations, 2015b). Economic growth on its own is not a viable solution for all people living in extreme poverty, with poverty reduction being uneven between
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Exhibit 7 SDG 1: No poverty. Source: United Nations (https://www.un.org/ sustainabledevelopment/ news/communicationsmaterial/)
regions and countries. Sub-Saharan Africa mainly comprises middle-income and low-income countries. These countries face common challenges, such as structural rigidities, low levels of global trade, remoteness, poor infrastructure development, low productivity, economic growth without job increases, and limited resilience to absorb market changes (UN, 2017). Entrepreneurial activities in Africa and through the garment industry in Africa have been embraced as a solution to curb the prevalence of poverty on the continent (AfDB, 2020). Decent work remains one of the best routes to follow to eradicate poverty. A sufficient number of decent jobs must be created to meet labour market demands (UN, 2017). The garment industry has the potential to create jobs for both skilled and unskilled people (AfDB, 2020). SDG 1 encompasses addressing the most prevalent and reoccurring constraints to the eradication of poverty. One of these efforts comprises the prevention and reduction of vulnerability to conflict, natural disasters, and economic downturns (UN, 2017). The global COVID-19 pandemic, effects of forced displacements due to conflict-affected areas, and increased economic pressure (such as the dramatic increase in fuel prices) have led to various challenges in almost all industries, including the garment industry. Therefore, it is important to ensure that innovative, holistic, gender-responsive, and conflict-sensitive solutions are effected to assist industries in progressing towards poverty reduction and sustainable livelihood opportunities. The following recommendations have been made to progress towards poverty eradication to get and keep people out of poverty (UN, 2017): – Grow economies in an inclusive way that allows all people the right to work and to work in favourable conditions of work – Invest in people, especially women and children, to ensure upward economic and social mobility within and across generations – Protect poor and vulnerable people against shock that can increase poverty (such as pandemics and food prices) The garment industry can provide employment, ensure workplaces that are not harmful to the health and well-being of employees, accommodate women (which in turn allows them to provide for their children), and provide for poor and vulnerable
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people by having preventative strategies in place to lessen the impact of possible shocks that can increase poverty.
3.2
SDG 8: Decent Work and Economic Growth
SDG 8 promotes sustained, inclusive, and sustainable economic growth, with full and productive employment and decent work for all, illustrated in Exhibit 8 (United Nations, 2015b). Unfortunately, global economic recovery is hampered by new waves of COVID-19, rising inflation, disruptions in supply chains, labour market challenges, and the current Ukraine crisis, which led to, amongst others, drastic increases in oil prices, which negatively impacted fuel prices (United Nations, 2022). It is important to increase income-generating employment opportunities (United Nations, 2015b). The garment industry is of particular interest in this regard as various employment opportunities can be created. The garments industry can be of particular importance in empowering vulnerable groups, specifically women, urban poor, and unemployed rural labour. However, it is important to ensure that proper policies and procedures are in place to provide decent work for employees. With a global annual turnover of over $3 trillion, the garment industry could significantly alleviate poverty if workers at the bottom end of the supply chain shared in these profits. Unfortunately, too many workers are subject to abhorrent working conditions and an unlivable wage (NTU, 2019). SDG is divided into 12 sub-categories, each of which can be addressed by the garment industry in Africa (United Nations, 2015a, 2015b): – Sustainable economic growth: Government and private sector programmes are already in place to work towards attaining a sustainable per capita economic growth of a minimum of 7%. Endeavours to address this continue despite the economic setbacks caused by the COVID-19 pandemic. – Increased economic productivity: Economic productivity can be achieved through diversification, technological upgrades, and innovation. These activities are key in the garment industry, which needs to continue innovation to remain profitable.
Exhibit 8 SDG 8: Decent work and economic growth. Source: United Nations (https://www.un.org/ sustainabledevelopment/ news/communicationsmaterial/)
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– Promotion of development-oriented policies: Development-oriented policies are aimed at supporting job creation, innovation, and the associated entrepreneurial activities that should be associated with economic development. Many African countries and garment industry stakeholders are committed to the support of entrepreneurial activities and innovation. – Improve global resource efficiency: The garment industry is a resource-intensive industry, and therefore, the sustainable consumption of resources is more important than ever. Part of improving resource intensity is also addressing the fast fashion culture that has taken root in the Western world, causing the garment industry to be labelled as the second most polluting industry in the world (NTU, 2019). – Full productive employment and decent work for all men and women: This sub-section of the sustainable development goals includes the creation of gainful employment for people with disabilities and youth. The pursuit of these goals encourages a move towards a more inclusive workforce. – Reduce youth unemployment: Within the garment industry in Africa, there are numerous programmes aimed specifically at promoting youth development through education and skills development. These programmes are funded by governments, banking institutions, academic institutions, and private social entrepreneurship programmes. – Eradicate force labour: Unfortunately, the garment industry involves the employment of a cohort of unskilled, uneducated labour. This increases the risk of modern slavery, human trafficking, and various forms of child labour. – Protect labour rights: Promoting a safe and secure working environment for all workers should be a priority across all industries. This includes more vulnerable populations such as migrant workers, who are usually not protected by national labour laws. – Promote sustainable tourism: The importance of the garment industry in preserving the heritage of the numerous tribes who live on the African continent cannot be overstated. The garment industry links directly with sustainable tourism, creating an opportunity to promote local culture and products, thereby creating additional job opportunities in both the garment and the tourism industries. – Strengthen domestic financial institutions: By strengthening the capacity of local financial institutions, employees and entrepreneurs have improved access to banking, financial services, and insurance products. This assists in securing the financial future of entrepreneurs and employees. – Increase trade support: The negotiation of trade agreements within the garment industry makes a significant contribution to addressing employment needs within Africa. Many of these trade agreements are subsidised by the government, supporting the industry even further. – Global strategy for youth employment: As indicated earlier in this chapter, youth unemployment within Africa is extremely high and needs to be addressed as a matter of urgency. The garment industry is taking great strides towards creating gainful employment opportunities but, most of all, creating the opportunity for youth to be trained and educated in the entrepreneurial skills that they can use to create their own businesses, contributing to the creation of additional jobs.
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Small Businesses and Poverty Eradication
Small businesses, especially in labour-intensive sectors (such as the garment industry), allow for a unique opportunity to diversify African economies and further regional integration, aimed at job creation and poverty eradication. Unemployment remains a problem in Africa, thus resulting in poverty. Small businesses in the garment industry can contribute to youth employment, job opportunities for skilled and unskilled labour, and employment for women (AfDB, 2020). Unfortunately, the impact of the COVID-19 pandemic resulted in unprecedented challenges, especially for small businesses and the poorest countries. In 2020, sharp declines were seen in output and employment. Small businesses were especially disadvantaged, and recovery has been slow. Women are amongst those who were disproportionally impacted since the onset of the pandemic. Youth training, education, and employment have suffered, with women facing the biggest challenges (United Nations, 2022). Women entrepreneurs can greatly contribute to economic development as their small businesses can stimulate economic activity, create jobs, alleviate poverty, uplift living standards, and promote sustainable livelihoods (Moreno-Gavara & Jimenez-Zarco, 2019). Small businesses in the garment industry should be supported regarding, amongst others, access to industrial production, retail setup, access to financing, governmental support, skills development, and proper infrastructure. Such measures can assist in developing small businesses in the sector. With proper guidance and training, small businesses can be assisted in terms of increased productivity, brand building, market information, access to markets and suppliers, and the promotion of entrepreneurial activities (AfDB, 2020). The empowerment of women through female entrepreneurship can make a tremendous difference in poverty alleviation. Small fashion businesses are a route taken by many women, thereby enabling them to provide for their families. Consumers increasingly want to know the origin of the clothes that they buy; therefore, it is important to involve the consumer in the process for the time the garment is designed until it is purchased. Small businesses could be used in this process by introducing craft products to support them (Moreno-Gavara & JimenezZarco, 2019).
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Opportunities and Challenges of the Garment Industry in Africa
North America and Europe historically dominated the garment industry up to 2018 where regions such as Latin America, Asia, the Middle East, and Africa leverage their new status to gain even greater impact and influence on the fashion industry globally (Khurana, 2018). McKinsey (2022) mentioned that emerging markets such as Africa do not receive enough attention or acknowledgement for their contributions to the garment industry, and their market value is not valued. ‘Africa is the future’ is a common phrase and reflects how this continent is growing by
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following their own terms and not necessarily the ‘new market potential’ for firstworld countries to tap into. The following section outlines possible opportunities as well as challenges that the African continent faces regarding the garment industry.
4.1
Opportunities
A fashion designer from Kenia launched a campaign where she visited several countries from the African continent and showcased 100 different locally designed outfits on social media. Several African countries went straight to the use of mobile phones due to the lack of telecommunications infrastructure, which opened the world of online shopping and marketing of garments. Taking a closer look at manufacturing, Ethiopia, for example, was flooded with investment from Asia, more specifically China, and was able to take advantage of the radical changes that happened in the fashion supply chain. Factories in Ethiopia and other countries are built with the Japanese ‘kaizen’ system to ensure production of a high standard. Globalisation continues to play an important part in the garment sector, mainly due to digital connectivity and the flow of data, and this will lead to much greater international connectedness. The local clothing, textile, footwear, and leather work (CTFL) came up with a master plan that was launched in 2020, and its primary aim focuses on increasing the proportion of garments manufactured locally in-store from 44% in 2018 to 65% by 2030 (Smith, 2021). Although the garment industry was under pressure due to the COVID-19 pandemic, garment imports were hit more than locally manufactured garment imports as retailers bought goods that were produced locally, and these manufacturers benefitted from this. Smith also stresses that governments are committed to ensuring enabling environments for the investment in CTFL through measurements such as strategic tariff support, appropriate manufacturing incentives, and limiting illegal imports. The focus of African countries in the garment industry is targeting the notion of limitation of imports and increasing exports. Except for South Africa, which exports 50% of its textiles and clothing to other African countries, the African textile and apparel industry primarily exports to markets globally, with only a small share of exports dedicated to local or regional markets (Ismail, 2022). More and more businesses are incorporating 3D printing mainly to develop comfortable, flexible, and resilient products. The materials and designs used might positively impact society by empowering countries to use environmentally friendly materials and reduce waste (Botti, 2019). Furthermore, through technology, companies have access to their customers worldwide, especially those from new segments or fast-growing markets. AfDB Fashionomics (2021b) pointed out several opportunities such as increased productivity through relevant training, access to cheaper labour in sub-Saharan Africa as opposed to increasing wages in China and South East Asia, the integration in international value chains by addressing aspects of competitiveness, attracting global buyers to increase exports by replicating successful models in sub-Saharan Africa, the building of brands with African designers as links in the African fashion
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hub ‘African fashion for African people’, and finally access to untapped local and regional markets for garments. Men and woman from Ethiopia are emotionally attached to the traditional outfit consisting of Ethiopian design and motifs (Khurana, 2018).
4.2
Challenges
Challenges that African countries face include poor infrastructure, political instability to trade barriers, prohibitive tax regimes, and bureaucracy. Although fashion will probably always be anchored in cities such as Paris, Milan, London, and New York, this industry is evolving at a rapid pace, but through digital connectivity, upwardly mobile consumers, and bold business innovation, emerging market leaders are contributing towards finding a new centre of importance for the garment industry worldwide. Cities such as Seoul, Lagos, and Bogotá are regarded as fixed to the African garments map and power is increasingly shared as well as decentralised. Despite the importance that certain regions are gaining in the garment sector, it is highly volatile and uncertain. During the COVID-19 pandemic, several plant closures and associated loss of jobs during 2020 had a negative effect on local capacities to produce garments. Retailers had to face operational challenges that were mostly notable during supply chain disruptions that resulted in shipping challenges, the congestion of ports, and the rising of additional logistical costs. According to Botti (Botti, 2019 in Moreno-Gavara & Jimenez-Zarco), the garment industry is characterised by the following characteristics, namely: • Short life-span—garments are often short-lived and designed to reflect the mood of the moment. Furthermore, the season in which it will be saleable is likely to be very short, either measured in weeks or several months, depending on the country and its location. • High volatility—the demand for garments is rarely stable. It is often influenced by weather, films, or influencers. • Low predictability—due to the volatility of demand, forecasting the total demand within a period-specific period accurately is complex considering a demand that ranges from week by week or item by item. • High impulse purchasing—consumers may purchase certain garments as decided upon the point of purchase. Thus, when confronted with the garment, the shopper is stimulated to buy it, hence the critical need for ‘availability’. Unfortunately, the African continent seems to lack the will to execute the necessary changes to combat these challenges. However, promoting entrepreneurship by governments in Africa can be regarded as a solution to curb the high unemployment rates and poor economic growth (GALI, 2020). Other challenges might include the availability of raw material and manufacturing that include the cotton value chain, availability of raw materials, working capital and
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exchange rates, logistics and infrastructure, exposure to foreign markets, lack of skilled labour, and sustainability as emphasised by Khurana (2018). Women entrepreneurs strive to develop a ‘perfect’ product before its launch, and this risk aversion can discourage them from applying for funding or explore options for growth and to develop their businesses (GALI, 2020). Findings from the global GALI database indicate that prior to acceleration, men-led businesses (21%) have secured equity funding compared to women-led ventures (9%). This discrepancy persists when exploring average amounts raised. The same trend was identified in a Boston Consulting Group study which concluded that women-founded teams raise, on average, 50% less than men-founded teams. Entrepreneurs and SMEs are considered two of the most vulnerable actors in an economy—it is anticipated that this hurdle can be even more concerning for women entrepreneurs (GALI, 2020). The African Development Bank Group (AfDB, 2021b) points to several challenges for the sub-Saharan Africa garment industry, namely skills shortages, a lack of training facilities, and limited access to financing opportunities for women entrepreneurs and SMEs; most of the African countries do not have textile production facilities due to a lack of funding; small-scale designers do not have access to industrial production, limited input suppliers, and companies to export products, dealing with changing end market requirements making skills and flexibility vital and limited access to information (such as trends, buyers, and market data). Finally, the lack of government and institutional support to the garment industry in many sub-Saharan African countries has an impact on the delivery of goods.
5
Upskill of the Local Community for Poverty Eradication
The AfDB Fashionomics Africa initiative (AfDB, 2021b) pledged to build an industry that invests in people’s skills and qualifications, ultimately improving the quality of life for African people. The garment industry aims to employ a workforce that has the necessary skills to contribute towards the achievement of high-quality production flexibility whilst raising productivity. The production of garments offers large-scale employment opportunities. This industry has the necessary potential for job creation, especially for youth and women (Barran et al., 2020). The garment industry has immense potential to empower and bring change to some of the most disadvantaged groups, such as women and youth. Designers and small-scale manufacturers benefit from loans in Kenya. In Madagascar, new jobs are created in the garment industry. From a job creation perspective, jobs will be created to provide employment opportunities to areas in the garment industry that remain underdeveloped to attract traditional commercial market players and thus dependent on volatile donation flows. People from underdeveloped countries in Africa can use a people-centred approach to poverty eradication through participation in different phases and sectors of the garment industry through the equitable distribution of wealth and income distribution. Poverty eradication can be avoided through education, and women can be involved in the garment industry and learn the different
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trades to empower them. It is well documented that cash and microfinance are two of the best solutions to poverty. The creation and improvement of access to jobs and income and the development of entrepreneurial talent can reduce poverty, and women should form the foundation in the garment industry to ensure that the products reach the global market regarding the exportation of goods. More emphasis should be given on educating the women to become entrepreneurs and skilled workers in the fashion and textile sector. A pool of African expats who live in other countries worldwide, and if garments from African countries are exported, they form part of the buyers. Thus, technology plays a major role in promoting the products made in Africa. It is furthermore vital to empower people living in poverty to be involved in developing and implementing plans and programmes to reduce and eradicate poverty, and the garment industry can play a role in this intervention. Their involvement ensures that programmes reflect those things that are of importance to them. It is also important to remove barriers to equal access to resources and services. People from the garment industry should be provided access to technology and innovation, including Internet access and affordable energy to produce textiles and garments and market their products locally and internationally. Young people and women should be educated and upskilled to improve their career prospects in the garment industry, which is a fairly young industry to tap into the local and international markets, with regard to market and brand of the goods to be accessible to buyers. Another way to eradicate poverty is to create and improve access to jobs and income and develop entrepreneurial talent and, in this case, the garment industry. Furthermore, to remove possible barriers to equal access to resources and services.
6
Conclusion
Sustainable development is aimed at ending poverty, reducing inequality, and enhancing economic growth. Due to the economic impact of the COVID-19 pandemic, it is more important than ever to stimulate economic growth and empower communities to actively participate in strong economic sectors such as the garment industry. The vibrant, multicultural environment of African countries is a valuable, marketable asset that should be utilised, especially in the garment industry. The garment industry in Africa can assist in eradicating poverty, creating economic growth opportunities and decent work, and reducing unemployment on this continent. The African garment industry is characterised by the large number of womenowned businesses, allowing women entrepreneurs the flexibility to be creative and innovative whilst still being able to take care of their families. The opportunities and challenges within the garment industry were highlighted in this chapter, along with the importance of Africa in terms of the global supply chains’ reliance on African resources. It is suggested that further research be conducted in the African garment industry to determine how access to technology and innovation (such as Internet access and
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affordable energy) can be made accessible to small businesses in this industry—the implication thereof being that governments of African countries be convinced of the importance of investing in the development of the garment industry and capitalising on this valuable industry. More research is needed regarding the training requirements of young people and women in the garment industry to ensure the relevance and availability of upskilling programmes. Such investments and programmes can assist in reducing barriers to entry into this industry and further enhance the contribution of the garment industry in realising SDGs.
References African Development Bank Group (AfDB). (2020). Investing in the creative industries: Fashionomics. https://www.afdb.org/fileadmin/uploads/afdb/Documents/Generic-Documents/ Fashionomics_creative_industries_executive_summary_brochure.pdf African Development Bank Group (AfDB). (2021a). How the COVID pandemic has spurred innovation in Africa’s fashion industry. https://www.afdb.org/en/news-and-events/how-covidpandemic-has-spurred-innovation-africas-fashion-industry-40712 African Development Bank Group (AfDB). (2021b). African continental free trade area: Opportunities for African fashion entrepreneurs. https://www.afdb.org/en/news-and-events/ african-continental-free-trade-area-opportunities-african-fashion-entrepreneurs-42764 African Union Development Agency-New Partnerships in Development Agency (AUDANEPAD). (2021). Moving the needle on youth unemployment in Africa: From learning to employment. https://www.nepad.org/news/moving-needle-youth-unemployment-africalearning-employment#:~:text=In%20most%20African%20countries%2C%20the,of%20 Africa's%20unemployed%20are%20youths ASPEN Network of Development Entrepreneurs (ANDE). (2021). Entrepreneurial ecosystem snapshot—Township economies in South Africa. Aspen Institute – South African Chapter. Barran, E., Laucke, A., Nima, L., Prasad, M., & Schwank, C. (2020). Social enterprises as job creators in Africa. Siemens Stiftung. Botti, R. (2019). Fashion sector outsourcing to African countries: Taking advantage of low-cost labor? In C. Moreno-Gavara & A. I. Jimenez-Zarco (Eds.), Sustainable fashion—Empowering African women entrepreneurs in the fashion industry. Palgrave. Choto, P., Tengeh, R. K., & Iwu, C. G. (2014). Daring to survive or to grow? The growth aspirations and challenges of survivalist entrepreneurs in South Africa. Environmental Economics, 5(4), 93–101. Du Toit, M., De Witte, H., Rothmann, S., & Van den Broeck, A. (2020). Positive deviant unemployed individuals: Survivalist entrepreneurs in marginalised communities. South African Journal of Business Management, 51(1), a1627. Fibre2Fashion. (2021). African apparel exports expected to rise: TexPro report. https://www.fibre2 fashion.com/news/apparel-news/african-apparel-exports-expected-to-rise-texpro-report-27292 9-newsdetails.htm#:~:text=Morocco%2C%20Tunisia%2C%20Egypt%2C%20Madagascar, apparel%20export%20from%20the%20region Global Accelerator Learning Initiative (GALI). (2020). Accelerating women-led start-ups a South African perspective a knowledge brief by the global accelerator learning initiative and catalyst for growth. https://www.galidata.org/assets/report/pdf/Accelerating%20Women-led% 20Startups%20A%20South%20African%20Perspective.pdf Global Entrepreneurship Monitor (GEM). (2021). Women’s entrepreneurship 2020/21—Thriving through crisis. Global Entrepreneurship Research Association, London Business School. https://www.gemconsortium.org/report/gem-202021-womens-entrepreneurship-reportthriving-through-crisis
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International Labour Organization (ILO). (2021). Occupational safety and health improvement in the garment industry: Drivers and constraints. https://vzf.ilo.org/insights/occupational-safetyand-health-improvement-in-the-garment-industry-drivers-and-constraints-a-synthesis-review/ Ismail, F. (2022). A developmental regionalism approach to the AfCFTA and rules of origin for the cotton, textiles and apparel regional value chain. Discussion paper. Jackson, T. (2016). Why a culture shift is needed in SA entrepreneurship. Disrupt-Africa. https:// disrupt-africa.com/2016/09/27/why-a-culture-shift-is-needed-in-sa-entrepreneurship/ Khurana, K. (2018). An overview of textile and apparel business advances in Ethiopia. Research Journal of Textile and Apparel, 22(3), 212–223. https://doi.org/10.1108/RJTA-01-2018-0003 Louw, L. B. (2018). Retrenchment in the insurance industry: The small business development dividend. Unpublished MCom thesis, University of South Africa. McKinsey. (2022). The state of fashion 2022. McKinsey. Available from https://www.mckinsey. com/~/media/mckinsey/industries/retail/our%20insights/state%20of%20fashion/2022/thestate-of-fashion-2022.pdf Moreno-Gavara, C., & Jimenez-Zarco, A. I. (2019). Sustainable fashion—Empowering African women entrepreneurs in the fashion industry. Palgrave. Nottingham Trent University (NTU). (2019). Fair trade and fast fashion. NTU & The Sustainable Development Goals. https://ntu-sdgs.blog/2019/04/24/fair-trade-and-fast-fashion/ Ochonu, M. E. (2020). African entrepreneurship: The fetish of personal responsibility. Review of African Economy. https://roape.net/2020/05/26/african-entrepreneurship-the-fetish-of-per sonal-responsibility/ Omeluzor, S. U., Imam, A., & Bamidele, I. A. (2014). Preservation of African culture in the information age. Information Impact: Journal of Information and Knowledge Management, 5(1), 82–90. Rabana, R. (2019). How Africa’s entrepreneurs are changing the direction of globalization. Available from https://www.weforum.org/agenda/2019/01/african-entrepreneurs-changingthe-direction-of-globalization/ Ranyane, K. A. (2022). Survivalist entrepreneurship: An income generating alternative for the unemployed populace. Mediterranean Journal of Social Sciences, 6(4), 301–306. Regenerate Fashion. (2020). SDGs for better fashion 2018-2019 progress report. https:// regeneratefashion.com/wp-content/uploads/2020/08/SDGs-for-Better-Fashion-ProgressReport-.pdf Smith, C. (2021, June 30). SA’s clothing industry trying to stitch itself together following worst decline to date accreditation. Fin24. https://www.news24.com/fin24/companies/sas-clothingindustry-trying-to-stitch-itself-together-following-worst-decline-to-date-20210630 UN. (2017). High-level Political Forum on Sustainable Development - 2017 HLPF Thematic Review of SDG 1: End Poverty in All its Forms Everywhere. Available from https:// sustainabledevelopment.un.org/content/documents/14379SDG1formatfinal_OD.pdf United Nations (UN). (2015a). Transforming our world: the 2030 Agenda for sustainable development. https://sustainabledevelopment.un.org/post2015/transformingourworld United Nations (UN). (2015b). Sustainable development goals. https://sdgs.un.org/goals United Nations (UN). (2022). The sustainable development goals report 2022. https://unstats.un. org/sdgs/report/2022/The-Sustainable-Development-Goals-Report-2022.pdf United Nations Industrial Development Organization (UNIDO). (2020). Textiles and clothing (% of value added in manufacturing), international yearbook of industrial statistics. https://data. worldbank.org/indicator/NV.MNF.TXTL.ZS.UN Webber, A., & Chandani, F. (2020). Summarising the key characteristics, enabling environment and needs of women-owned businesses. Mennonite Economic Development Associates.
Indian Clothing: Its Evolution and Development Shweta Uttam, Vimal Srivastava, Rajni, Ila Sharma, and Rahul Dhiman
Abstract
The objective of this chapter is to synthesise the available literature on the subject field to present how the Indian textile industry has evolved over the years, being one of the oldest industries that India ever had. This purpose is achieved by reviewing the available literature on the problem area across multiple factors, such as numerous clothing agreements, and combining data on the Indian clothing industry and its significance in economic development. We have also tried to demonstrate how the Indian clothing industry has been able to tap into several international markets. The analysis shows that India’s clothing industry is one of the country’s historic manufacturing businesses and that it has benefited from various reforms and agreements such as the Multi Fiber Agreement (MFA), Agreement on Textile and Clothing (ATC), and New Textile Policy (NTP). In highly competitive worldwide marketplaces, the clothing industry has managed to sustain itself. Further, to eliminate seasonal and demand swings, we recommend that the clothing industry should concentrate on increasing labour and
S. Uttam Dr. APJ Abdul Kalam University, Lucknow, Uttar Pradesh, India V. Srivastava Mahindra and Mahindra Ltd., Mohali, Punjab, India Rajni University College of Engineering and Technology, Bikaner Technical University, Bikaner, Rajasthan, India I. Sharma Indira Institute of Business Management, Pune, Maharashtra, India R. Dhiman (✉) Department of Business Management, Dr. Y S Parmar University of Horticulture and Forestry, Nauni-Solan, Himachal Pradesh, India # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_4
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capital productivity trends. This chapter offers comprehensive insights into the Indian garments economy and adds value to the existing body of knowledge. Keywords
Clothing business · Economic development · Direction of apparel exports
1
Introduction
Indian textile industry is often considered a leg of the economy because this industry’s contribution to India’s economic development is immense (Conlon, 2020; Goyal et al., 2018). This chapter intends to offer an Indian perspective on the garments economy. It aims to illustrate how the Indian clothing industry has evolved over the centuries and reached new levels over the years. Though scientific literature is abundant with empirical studies on the economy of the global garments industry, but conceptual studies on the garments economy are very limited, specifically from the perspective of the Indian garments economy. In many countries, industry entrepreneurs took clothing as an appropriate business endeavour (Dana et al., 2020). Entrepreneurship provides employment opportunities and helps stimulate the economy’s growth (Agarwal et al., 2021; Dana, 2000, 2014; Ramadani et al., 2022). Similarly, people in India ended up choosing textile and clothing as a business enterprise (Dana, Ramadani, et al., 2022; Dana, Salamzadeh, et al., 2022; Wahee et al., 2022). Indian clothing is considered one of the country’s oldest industries (Bhatt, 1992, 2008). It has been extensively stated that the roots of textiles in India can be traced back to the Indus Valley Civilisation, when people weaved their clothes out of homespun cotton (Banerjee et al., 2016; Srivastava & Dhiman, 2022). It is also the only self-sufficient industry in terms of raw materials and highest-value-added products. As the first industry of any kind, it sprung up in clusters in some states of India. C.N. Dewar, a local Parsi entrepreneur, founded the first successful modern cotton textile factory in Mumbai in 1854. Other milestones in developing the Indian cotton textile industry include the Shahpur mill in 1861 and the Calico factory in 1863 in Ahmedabad. The cotton textile business took off in the 1870s. By 1875–76, there were 47 mills in Mumbai alone, with over 60% of them located in the city. Bengal, Gujarat, and Tamil Nadu were home to the majority of the remaining mills. The business continued to grow until 1914, when the First World War broke out. A total of 271 mills were operational, employing around 2.6 lakh people. (Dhiman, 2018; Dhiman & Sharma, 2016.) Spinning mills, integrated spinning-weaving mills, power looms, handlooms, hosiery, makers of man-made fibres and fabric, textile machinery, and component manufacturers, to name a few, are all historical components of the industry (Banerjee et al., 2016). Given the enormous size and early advent of the textile industry, it was only appropriate for India to commence as a dominant exporter of textile goods
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(Ismail & Ahmed, 2022). On the other hand, clothing exports increased considerably in the 1970s from a minuscule base (Dhiman, 2021). With appropriate usage of British Technology, India shaped a modern textile industry, utilising low-wage labour and native cotton. This helped in the potential growth of the Indian textile industry in closely modelled on the British textile industry. The primary activities affiliated with the textile and clothing industries are detailed here: (i) The management of input materials, i.e. the manufacturing of a wide range of textile fibres, as well as the spinning of yarns. Cotton, flax, silk, wool, jute, and other natural fibres are examples. Cellulosic fibres, synthetic fibres, and fibres formed of inorganic elements such as carbon, glass, and metal are all examples of man-made fibres. (ii) Knitting and weaving-related pursuits. (iii) Bleaching, printing, dyeing, impregnating, and other finishing processes are used to provide fabrics with the aesthetic and physical attributes aimed at fulfilling customer requirements and needs. (iv) The final process transforms these ingredients into completed goods, including garments, carpets, and other textile floor coverings, as well as typical domestic textiles like kitchen linen, bed linen, toilet linen, and curtains. This chapter is an attempt to put forward the evolution and growth of Indian textile industry. This industry has witnessed a significant growth over the years because of many factors such as increase in labour and capital productivity. This chapter shall be able to seek attention of readers as we have included various important aspects of the Indian textile industry such as the classification and vital role of various agreements to promote textile industry. We have focused on the role of this sector in the economic development of the nation. We believe that this chapter will be able to put forward a comprehensive picture of the textile industry, which is unique in nature.
2
Classification of the Indian Textile Sector
The textile sector of India can be predominantly categorised as an (1) organised mill sector and (2) unorganised decentralised sector (Dhiman & Sharma, 2017a, 2017b). An efficient and highly mechanised mill industry makes up the organised mill sector. Spinning and composite mills are reflective of the organised mill industry. A composite mill is a structure that combines spinning, weaving, and processing within one facility. The decentralised mill industry lacks an adequate organisational setup in terms of current technology or machinery requirements, production pattern, workforce, and so on. The unorganised mill industry is mostly engaged in weaving activities (Guha et al., 2022; Shahi et al., 2020). As a result, it increasingly relies on the organised mill to supply its yarn needs. The weaving segment has been recognised as one of the segments in which there is a dearth of technology across the
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system (Dana & Dana, 2005). Power loom, handloom, and hosiery are the three main segments of the decentralised mill business. Ginning and spinning, weaving and knitting, processing, and apparel manufacture are the four primary steps of the Indian textile and clothing value chain. Spinning is the process of converting cotton or synthetic fibre into yarn (Balchin & Calabrese, 2019). Cotton is ginned before spinning to remove seeds and impurities before it is spun. The cotton or synthetic yarn is then weaved or knitted into textiles. Bleaching, dyeing, and printing are all part of the processing process, which results in finished fabric that may be used to make garments. Clothing manufacturing is the final step of the process, in which the tasks of cutting, sewing, designing, finishing, and packing are accomplished in preparation for market distribution.
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Role of Agreements to Promote Indian Clothing
Numerous measures and agreements were formulated and materialised for the growth and expansion of the clothing industry (Chand et al., 2020). These steps played a pivotal role in opening the textile industry in competitive international markets (Biçer et al., 2020; Dhiman & Sharma, 2019). The government of India, over the years, has given key stimulus to the textile industry through various incentives and schemes, which has resulted in the growth of this sector. Further, owing to the importance of the textile industry, a separate Policy Statement was announced in 1985, which was succeeded by policy statements of 1993, 1994–94, 2000, and so on. The removal of quotas has opened up new opportunities for developing nations, but it has also increased competition from other formerly constrained exporters (Dana & Dumez, 2015). As a result, the outcome of every given country is highly dependent on its policy response. Countries that take advantage of the chance to simplify their policies and enhance their competitiveness are more likely to benefit from the elimination of quotas (Dhiman et al., 2018; Hemrajani et al., 2021; Rajni et al., 2022). Certain agreements have also played a vital role in the textile industry’s growth and expansion. Some of the agreements are as follows:
3.1
Multi Fiber Agreement and Agreement on Textile and Clothing
The first MFA was signed in 1973 with American backing and went into effect on 1 January 1974. MFA-I was an instrument of agreement designed to deal with textile trade to help countries that had lost their competitiveness in global commerce. MFA-I was succeeded by MFA-II, which went into effect on 1 January 1978, as a result of a set of regulations approved on 14 December 1977, and was extended for 4 years. With GATT laws, MFA-II also focused on industrial liberalisation. In
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January 1982, the MFA was reintroduced as MFA-III. The third MFA (1982–86) was debated in the context of rising concerns amongst developing countries about the negative impact on their exports. The fourth MFA’s duration was stretched until 1991 because of the presence of several unwanted elements. The MFA was to be phased away in phases by the implementation of the ATC during the Uruguay Round of trade negotiations in 1994. As a result, the MFA was taken over by the ATC. On 1 January 2005, the MFA was completely phased out. The end of the quota system was viewed as both an opportunity and a threat (Alam et al., 2019): a chance since the market will no longer be limited, and a risk because markets will no longer be guaranteed by quotas, and even the domestic market will be open to competition (Kathuria & Bharadwaj, 1998; Verma, 2002).
3.2
Textile Policy, 1985, and The National Textile Policy, 2000
The Textile Policy of 1985 was created to assist the sector in producing high-quality clothes at reasonable prices for the country’s large population as well as for export. Textiles were governed by the Essential Commodities Act (ECA) at the time, which introduced new rivalry and market dynamics. The main goal of this strategy was to help the industry expand its production of high-quality garments at a reasonable price for the country’s enormous population and export. As market forces dictated, the government continued to make revisions to this programme. The embracing of the NTP in the year 2000 paved the way for initiating an aggressive policy for the Indian textile sector. The overarching goal was to improve foreign exchange profits, and it included reasonable forecasts for the growth of all divisions of the textile industry. The key goal outlined in the textile programme was to increase textile and garment exports from US $11 billion to US $50 billion by 2010, with clothes accounting for US $25 billion.
3.3
New National Textile Policy, 2013
The Indian government formed an expert committee to examine the NTP 2000 and design the NTP from 2013. The NTP, 2000, was created 13 years ago, and the industry has changed significantly both domestically and internationally since then (Prasad et al., 2020). In the preceding decade, India’s textile sector underwent modernisation and technical improvement. In the international trade context, export quotas were removed in 2004. With a framework of helpful guiding principles, new changes in the global textile sector provide tremendous prospects for the industry to contribute to global commerce. For this obvious afterthought, the government planned to develop a more robust textile policy to address concerns such as skilled labour, labour reforms, and capturing investments in the textile segment with a view of holistic development for the industry. The new NTP, 2013, was articulated for providing a clear guideline and road map for the textile industry. This road map included provisions for a 3% interest subsidy, the addition of new markets such as
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New Zealand, Latvia, Lithuania, and Bulgaria under the Focus market scheme, and an incremental export incentive plan. To reduce dependency on Western markets, exporters are encouraged to explore other markets such as Latin America, Australia, Japan, Africa, Israel, Southeast Asia, and the Middle East. In addition, the Indian government authorised several refunds and incentives for the textile and garment industries due to a significant increase in total production in this industry. The preceding discussion reveals that several efforts were made to boost the Indian apparel business. As a result, various advantages can be noticed in recent times. Today, the Indian textile industry is a serious competitor for several Asian and European nations. The next section focuses on the current role of the Indian clothing industry around the world.
4
Clothing Exports and Economic Development
Because of the vast size and initial progress of the Indian textile industry, it was envisaged that India would begin as an exporter of textile items in its early stages. It was also embarked upon as more than 120 countries import Indian clothing. The markets of the USA and the European Union account for 76% of total exports. India’s textile exports climbed dramatically from US $M 4865.3 in 1991 to US $M 45,162 in 2020. India’s contribution to global textile and garment exports was previously low, but it grew in size considerably after 1991, reaching 2.02% of global exports in 1991 and 4.99% in 2021 (Dhiman et al., 2020). Following the withdrawal of the MFA and the reduction in levies, Indian textile exports have expanded to new markets around the world. Indian textile exports are primarily directed to South Asian countries and the South Asian Association for Regional Cooperation (SAARC) nations (Sharma & Dhiman, 2014). The USA remained the largest export market in 2015, with a 19.08% share, but this share has decreased since 1995 and 2005, followed by the UAE (9.84% share), the UK (6.96%), Sri Lanka (5.36% share), and Germany (4.39%), indicating the addition of more export destinations for Indian textile exports (Sharma & Dhiman, 2016). This demonstrates and amplifies that Indian textile commodities have been effective in gaining new export markets in the international market. As a result, it can be argued that India’s textile exports to a variety of international markets have increased in the post-reform period.
5
Growth Parameters of Indian Clothing Business
The number of textile industries in India increased from 14,612 in 1991–92 to 19,439 in 1995–96. After peaking in 1995–96, the number steadily dropped until 2001–02 (except 1999–2000). Following that, the number of factories climbed to 35,699 in 2020–21. The number of employees increased from 1,442,000 in 1991–92 to 1,826,000 in 1995–96, which is an essential sign of an industry’s progress. Following that, minor
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changes may be seen, with the number of employees rising from 1877 thousand in 2005–06 to 4,526,000 in 2020–21 (Chandra, 1999; Verma, 2002). The capital stock climbed from Rs. 8831 crores in 1991–92 to Rs. 29,603 crores in 1999–2000, followed by a decline, and the industry’s capital stock was Rs. 22,595 crores in 2005–06. Following this era, the capital stock climbed to Rs. 75,793 crores in 2013–14 and Rs. 65,728 crores in 2020–21, with volatility noted in succeeding years.
6
Direction of India’s Clothing Exports
The trade direction is a crucial part of export performance (Goel et al., 2022). The direction of trade is determined by a country’s historical evolution and commodity mix. Changes in a country’s commodity mix may also represent a shift in the direction of the country’s exports. It is critical to define trade direction because it indicates export destinations and also highlights the addition of new export markets to the global market. In 1995, the USA received the greatest part of India’s textile exports, accounting for 23.29% of total exports, followed by Germany (11.12%) and the UK (11.12%). In 2005, the USA had the biggest share of 29.80%, followed by the UK (8.62%), Germany (7.19%), and the United Arab Emirates (7.19%). The share of the Former USSR fell from 2.30% in 1995 to 0.88% in 2005, most likely due to the collapse of the Former USSR in 1991, whereas other countries had relatively minor adjustments in percentages that remained nearly constant. The USA remained the largest export market in 2015, with a 19.08% share, but this share has decreased since 1995 and 2005, followed by the UAE (9.84%), the UK (6.96%), Sri Lanka (5.36%), and Germany (4.39%), indicating the addition of more export destinations for Indian textile exports. In terms of structural change in export direction, the USA saw an increase in its share of India’s textile exports in 2005 as compared to the share in 1995 (the share of the USA increased rapidly from 23.29% in 1995 to 29.80% in 2005), whereas Germany saw a rapid decrease in its share from 11.12% in 1995 to 7.19% in 2005, which further declined to 4.39% in 2015 due to the imposition of stringent environmental and labour standards. Aside from the UK, Germany, Japan, China HK SAR, the Netherlands, Switzerland, Mauritius, Austria, Switzerland, and Singapore, the UAE, Italy, Sri Lanka, Saudi Arabia, Turkey, China, and Egypt acquired importance in India’s textile exports. This demonstrates that Indian textile goods have gained access to new export markets. Unlike China, Mexico, Eastern Europe, and other South Asian countries, India’s recent surge in clothing exports occurred despite a lack of significant foreign direct investment in textile and apparel production, entry into preferential regional trade agreements with buyer countries, or a significant direct role of global buyers. However, the SAARC Preferential Trading Arrangement (SAPTA) was signed on 11 April 1993 and entered into force on 7 December 1995, with the intention of the SAARC Member States (India, Pakistan, Nepal, Sri Lanka, Bangladesh, Bhutan, and the Maldives) to promote and sustain mutual trade and economic cooperation within
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the SAARC region through the exchange of concessions. Trade occurs amongst SAARC countries as well, although the percentage share of big SAARC importers amongst all textile importers has not been especially significant in recent years (Paul & Dhiman, 2021; Pillania, 2007, 2008). The clear and obvious fact is that the percentage shares of India’s export of all textile items as well as both textile and clothing items to the major SAARC countries have increased gradually, whereas the reverse trend is detected for the USA, which has customarily been the chief importer of Indian textile products.
7
Role of Productivity Trends to Promote Clothing Exports
During this period, there was a marginal increase in the growth rate of labour productivity (LP) in the ‘textiles’ group, whereas the growth rate of labour productivity in the ‘textile products’ group was comparably lower (Goldar, 1986, 2004; Mittal et al. 2019). The LP in the case of the ‘textile products’ group was lowest during the study period. Capital productivity (CP) in the ‘textiles’ group declined marginally as compared to the textile industry, whilst the growth rate of CP in the ‘textile products’ group was lowest during the study period (Kathuria & Bharadwaj, 1998; Narayanan, 2008). On the whole, the CP in the Indian textile industry increased during this period vis-a-vis textiles and textile products group. Henceforth it can be easily concluded that capital productivity (CP) came out as an area of concern for the complete textile industry and its two groups. For the ‘textile’ and ‘textiles products’ group, CP in the sub-period-I is very low and has not improved significantly for the entire period also. So, this presents a murky picture and appropriate and relevant strategies and action plans need to be formulated. One of the key action plans for the textile industries would be to provide ready and economic availability of capital imports. It has also been significantly put forth in earlier studies such as Bedi and Cororaton (2008, p. 47). Furthermore, the US International Trade Commission has also signified the low level of technological inputs in the Indian textile industries.
8
Conclusion
The Indian textile industry resonates with its position and importance in the world economy, particularly in developing economies. The textile products of Indian conglomerates have been able to place their value in the market because of the basic strength of the raw material availability and cheap labour. It has also played a pivotal and important role in not only harnessing industrial output but also providing ample opportunity for employment and generating foreign reserves for the Indian economy.
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The reforms of 1991 helped the Indian textile industry in providing open trade opportunities through the contours of globalisation and liberalisation. It gave them the necessary impetus and stimulus for growth which was evident from the economic reforms leading to the removal of the quota regime from 1 January 2005 as per the WTO Agreement on Textile and Clothing (ATC). The removal of the quotas at one end culminated in engraving new prospects for the developing nations but, on the other hand, exposing them to new grafted challenges of Competition of Cheaper Imports. Apart from this, export competitiveness (EC) is another premier challenge that needs to be addressed profoundly for the sustenance of Indian products in the world market. Thus, it can be concluded that the Indian textile industry has to work hard in various aspects to sustain its stake and share globally. It is pertinent to say that economic reforms have eased the barriers to trade for the Indian textile industry, but they cannot guarantee a continuous increase in export shares. In this competitive world, only the fittest will survive in the long run. The Indian textile industry has performed well in the previous times, but to compete and sustain, labour and capital productivity should be as per the international standards (Panigrahi et al., 2020).
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A Migrant/Minority Economy? Jewish and Greek Migrant Entrepreneurial Patterns in the Greek Interwar Clothing Industry, 1923–1940 Orly C. Meron
Abstract
This chapter surveys the development of the clothing industry that enabled mass production to develop in interwar Greece. The influx of over 1,000,000 repatriated refugees in the wake of the Turkish-Greek transfer agreement (1923) led to cheap labour markets and broader consumer circles. Jewish and Greek Orthodox entrepreneurs, particularly around Thessalonica—the largest Jewish community in pre-1940 Greece—took advantage of both these factors. Drawing, inter alia, on archival document from the Jewish-owned Bank Amar, the chapter analyses: • • • •
The context—industrial growth in Greece following the transfer The knitting and ready-made underwear industries The ready-made ‘needle industry’—shirts and clothing accessories Self-employed seamstresses (gender and entrepreneurship)
Finally, it discusses the question of whether and to what extent the clothing industry’s reliance on migrant and minority entrepreneurship can be compared with the digitalisation the industry is currently experiencing. Keywords
Ethnic entrepreneurship · Ready-made garment industry · Needle industry · Sewing machine · Knitting machine · Female migrant labour
To Almog Meron, whose training work in the digitalised clothing industry inspired me O. C. Meron (✉) Department of Social & Health Sciences, Bar-Ilan University, Ramat-Gan, Israel e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_5
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Introduction
With the literature available to date focusing primarily on the development of the garment industry in advanced economies, this chapter explores the case of an interwar European periphery. As Charlotte Jirousek (2000), a historian of consumer culture, has noted, the transition from traditional forms of production to mass fashion (including the materials used) was a gradual process informed by a change in cultural values regarding modest dress. The globalisation on which it rested also reaching rural Macedonia and the increased social mobility that accompanied it led to the growth of a bourgeois class whose members began enjoying imported goods, shifting from self-sufficiency to income-generating production to make cash available to purchase status goods. Presuming that consumer circles had already emerged in interwar Greece, this chapter traces the evolution of the clothing industry within the Greek metropolis area, addressing questions such as: • To what extent did the mass ready-to-wear industry develop between the wars? • Did urban fashion consumers rely on imported garments or traditional seamstress products? • Was the nascent garment industry in interwar Greece an ‘immigrant industry’? Following the transfer, Greek Macedonia became home to 638,253 Greek repatriated refugees (Kayser & Thompson, 1964, p. 204), principally from Asia Minor. Forming approximately 45.2% of the population, this group constituted 52.2% of the 1,221,849 Greek Orthodox congregation identified in official registers as ‘refugees’—i.e. those who entered Greece in the wake of the country’s defeat by Turkey in September 1922. The Greeks metropolitan population comprised veteran, refugees, and internal migrants who arrived in Greater Athens and Greater Thessalonica from rural areas seeking new urban opportunities (Sandis, 1973). Greater Thessalonica was much more ethnically heterogeneous (see below) than Greater Athens (98% Greek Orthodox in 1928), however. The capital of Macedonia, Thessalonica, was home to the old Jewish populace— the descendants of the Sephardi exiles who arrived in the city following their expulsion from the Iberian Peninsula in 1492. Numbering 55,250 (of the total population of 244,680) in 1928, their mother tongue was Judeo-Spanish. The concentration of over 100,000 Greek refugees around the perimeters of the city and the departure of expert rag-trade Muslim Turkish entrepreneurs from in and around Greater Thessalonica created new openings for Greek and Jewish entrepreneurs alike in the clothing industry. The Greater Thessalonican metropolitan population serves as an ethnic laboratory. This chapter outlines entrepreneurial patterns in the growing garments economy across the various migrant communities—internal Greek Orthodox migrants, ethnic minorities, and veteran/ repatriated refugees. Suggesting that all three segments participated in the garments economy in Greek Macedonia, it discusses their entrepreneurial performance, labour, business and legal organisational patterns, and production practices
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(including industrial infrastructure and the efficiency and internalisation of modern production methods). With clothing falling under the category of textiles in the official Greek census of 1928 and the garment industry (excluding articles d’habillement covering ‘[felt] hats’) not appearing in tables presenting industrial production data relating to the 1930s (e.g. Annuaire Statistique de la Grèce, 1930; 1931, pp. 125–128), the readymade garment industry remained small scale and marginal within the national economy (Christodoulaki, 2001). The division of textiles into sub-branches thus reveals the scope of the entrepreneurial activity in the clothing-manufacturing industry during the interwar period, with microdata retrieved from archival resources shedding light on garment economy practices. The chapter explores four areas: 1. The context—the growth of the Greek clothing industry in the wake of the transfer 2. The knitting and ready-made underwear industries 3. The ready-made ‘needle industry’—shirts and clothing accessories 4. Self-employed seamstresses and milliners with respect to gender and entrepreneurship
2
The Context: Clothing—A Growing Industry Within Textile
The clothing industry formed part of the textile industry (27% of all industrial production)—the most dominant production industry in 1938 in value added terms (excluding public infrastructures). The volume of textile production—which included the clothing industry—grew from 18% in 1921 to 28% in 1930, reaching a peak of 32% of all industrial production in 1935 (Christodoulaki, 2001). Between 1923 and 1930, the textile industry became the largest industrial sector in Greece, with annual production exceeding 20% of the total industrial production. Government and repatriation agency resources sought to exploit the pre-migratory skills of female refugees (e.g. carpet weaving, silk/cotton spinning, and weaving), thereby stimulating the growth of a large-scale textile industry (DOT, 1925, pp. 27–29; Kritikos, 2000, pp. 196–201; Pentzopoulos, 1962, pp. 160–167). With clothing only comprising less than 2% of the textile industry (DOT, 1937, p. 17), it was still in its infancy during this period. Because supply did not meet demand, it constituted a golden opportunity for new entrepreneurs.
3
Official Policy: Tariffs and Industrial Growth
Government protection of Greek producers competing with imports and the passive encouragement of private entrepreneurs in the clothing rather than the (wellorganised) tobacco industry created favourable conditions for entrepreneurs as the former grew between the wars. Like other new nation-states in the Balkans, Greece
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adopted a tariff policy that safeguarded domestic production against competing imports. From 1923 onwards, tariff rates rose on average from 22–30% to 35–40% of the value of imported industrial products (Mazower, 1991, p. 96, Table 4.6). The collapse of international trade in 1929 accelerated the development of local industry, which was further supported by higher protective tariffs and import quotas. The fall in standard of living and devaluation of the drachma also kept salaries low. Seeking to monitor competition with foreign producers, the Federation of Greek Industries sponsored legislation in 1935 and 1937 to protect and encourage local industry through the imposition of an extensive list of tariffs on imported goods (from 1922) and the easing of restrictions on the import of machines and raw material. Hereby, it stimulated domestic production of cheaper substitutes (Dritsas, 2003, p. 304 n. 14). The protective tariff policy increased both production and profits, spurring commercial businesses to expand by adding further production lines (Meron, 2011/2013, Chapter 8).
4
The Labour Force: Official Policy
The mass arrival of refugees compensated for the delay in the development of a modern industrial infrastructure caused by the Greek government’s protection policy. The share of industrial output in gross domestic product (GDP) increased from five per cent in 1922 to eight per cent in 1938 (Christodoulaki, 2001) due to the expanding female urban work force—including many women who had lost their husbands in combat in Asia Minor or to forced labour in the Ottoman army. This available, cheap, and semi-skilled pool helped maintain local industry’s competitive edge—at least temporarily. The Refugee Settlement Committee (RSC), which worked in tandem with the government, channelled refugee workers to textile rather than tobacco plants, the organised labour force of the latter—one of the most important industries in Greece during the period—being suspected of communist activism and thus posing a threat to state security along the new northern borders, where approximately half the refugee population settled. This official, nationalist, anti-labour-biased policy encouraged small-to-medium-scale entrepreneurship amongst veteran and refugees alike, promoting the recruitment of cheap female refugee workers—frequently primary breadwinners—thus keeping costs down (Mazower, 1991, pp. 91–100, 2004).
5
Textiles and Clothing
Urban migrants and minorities were targeted by the clothing rather than textile (weaving, spinning) industries. (Herein, we regard the clothing industry as including the manufacture of knitted and sewn garments alike.) With this circumstance providing employment opportunities for the many female refugees in the metropolis, local and international organisations sponsored the training of refugee women and
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Table 1 Women gainfully employed in clothing branches Females Seamstresses (couturières) Underwear producers (lingers) Flannels and stocking makers Milliners Clothing accessories manufacturers Total in clothing Percentage in textile
Thessalonica RF IF 1465 904 83 67 91 274 199 128 39 32
Athens RF 4556 335 115 1285 85
IF 1893 176 143 343 61
Piraeus RF 1406 16 23 223 59
IF 758 40 43 103 33
1877 78.6
6376 86.2
2616 48.2
1727 56.5
977 22.1
1405 45.3
Source: See Appendix Notes: For the total textile sum, see Appendix
girls in textile plants, offsetting the Greek government’s tendency to ignore the poor environmental working conditions in textile factories, long working hours, and low wages (Kritikos, 2000, pp. 204–205). Female refugees constituted the majority in the textile industry (Appendix) in Piraeus. In light of the biased government policy that privileged large-scale investment in the capital over the new northern border, the city had become home to numerous large weaving and spinning textile mills dependent on the masses of newly arrived refugees. 58% of the joint ventures funded by RSC were in Athens and 14% in Piraeus (Lampe & Jackson, 1982, pp. 415–417). The garment manufacturing industry, in contrast, was dominated by indigenous females (IF), with local Greek Orthodox women and internal migrants accounting for 79 and 86% of the Thessalonican and Athenian metropolitan areas in the 1928 census. Falling under the category of Greek veteran females, Jewesses were ‘hidden’ in the census data relating to the clothing branches (Table 1). The following chapters outline the entrepreneurial practices in the garment industry, including knitting and sewing ventures, in the Thessalonican metropolitan area. The new mass clothing production developed within two main sub-branches: (1) hosiery (bonneterie)—and by extension socks, stockings, shawls, and woollen/ cotton undergarments (Sect. 6), and (2) confection for men and children (Sect. 7). The traditional production of made-to-measure clothing by tailors and seamstresses operated in parallel to the new ready-made mode of production (Sect. 8).
6
Knitting and Ready-Made Underwear
Greek entrepreneurs had begun establishing and rationalising the spinning and weaving industry in Thessalonica and its rural environs before the transfer, with Jews and Turks exploiting the existing infrastructure for the manufacture of clothing (Meron, 2011/2013, Chapter 5). In 1912, the undergarment branch in the city was run by 50–60 workers in six non-Greek-owned plants for flannels, with another six non-Greek-owned plants for knitting socks, stockings, and undergarments
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employing a further 70-odd workers (Austrian Report, 1915, p. 52). The departure of Turkish rag-trade entrepreneurs created additional vacancies filled by veteran Greeks, refugees, and Jews. The influx of refugees from Asia Minor drove up demand for cheap and standardised basic undergarments. This was met by small-to-medium-scale factories that increased production for domestic consumption. The high tariffs imposed on imported knitwear and the relief given for importing knitting machines (primarily from Germany) further encouraged local production. The relatively cheap technology also promoted enterprises of diverse sizes, with the large supply of female repatriated refugees further attracting entrepreneurs. Indigenous and newly arrived businessmen opened local hosiery factories, with the standard mechanised production of hosiery (both cotton and wool knitted socks) lowering the production costs of undergarments and accelerating the growth of ready-made knitwear. The finished products made available by the mechanised knitting industry were sold on the competitive open market—generally ‘blind’ to ethnic background. The burgeoning advertising industry further fostered demand for the new, relatively cheap, local goods. The rapid growth of the Greek bonnèterie industry ‘democratised’ the readymade underwear economy, with knitwear production becoming so prominent during the 1920s as to draw the attention of the British Consul, who reported that around six factories running on 160 horsepower machinery for the manufacture of tricotage (knitting/knitted goods) were established in 1928 (DOT, 1928, p. 24). The explosion of knitting and hosiery factories in the mid-1920s resembled the ‘epidemic’ the Thessalonican tobacco trade witnessed during the first half of the 1920s, with the knitting trade being considered so lucrative that it attracted investors beyond industrialist circles to include those in the liberal professions. Archival documents indicate that all the ethnic sectors in the city participated in this profitable, fast-growing industry. George J. Mavridis, for example—a refugee who arrived before the transfer and made his home in the Harilaos quarter, densely populated by refugees from Asia Minor—was able to expand from hosiery trading into production due to the heavy tariffs, accessibility of simple and cheap knitting machinery, small work area required, and availability of cheap refugee female labour. Refugee entrepreneurs preferred private family firms, enabling underfunding and low family labour costs. Many refugees also championed an individualistic approach to business (Hirschon, 1989, p. 81; Meron, 2016). Jewish entrepreneurs were heavily represented in the knitting and hosiery industry not only as owners but also as partners in Jewish-Christian ventures ranging from large-scale firms with more than 25 workers to middle- and small-sized enterprises. Indigenous Jews, Greeks, and refugees alike maintained close business ties with one another, with the majority expanding their activities from trade in imported goods to local production and hosiery marketing. Jewish knitwear entrepreneurs favoured small workshops attached to stores selling the finished goods. As the knitwear industry developed during the 1930s, however, Jewish manufacturers became involved in large and important sock and stocking mergers. Drawing on Jewish capital and female refugee labour, they set up factories in residential districts
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populated primarily by Greek refugees. In 1936, Fabriques Réunies de Bas et Chaussettes de Sal/Que SA, for example, incorporated three Greek-owned factories in order to control internal competition, the Sarfati workshop—attached to the owner’s hosiery shop in the city’s commercial quarter—forming part of the new venture. This merger—the factory in the Harilaos quarter + retail shop—represented a small portion of Sarfati’s investments, with the entrepreneur also holding interests in another hosiery manufacturing corporation—SA Vergopoulos—with an annual profit of GRD 250,000 (CAHJP Gr/Sa FO 346 Sam A. Sarfati BA/4569 17–18/2/ 1937; Fabriques Réunies de Bas et Chaussettes de Sal/Que SA, BA/426 15/06/1937; Meron, 2015). Jewish entrepreneurs integrated vertically into the knitting industry from the provision of the mechanical infrastructure upwards. The Jewish-owned firm Veritas, founded by Ino Benmayor prior to 1922 (Lévy, 1930, p. 922), replaced the Turkish firms whose owners had left, dominating the import and distribution of knitting (and sewing machines). Benmayor continued to import new technologies during the 1930s, primarily targeting hosiery and clothing manufacturers (CAHJP Gr/Sa FO 346 BA/93 Ino Benmayor, Maison ‘Veritas’ 7/8/1935). According to Jacky Benmayor (August 2022), the present owner, the firm imported German Diamant hand-knitting machines and English Harrison sock-knitting machines that, being hand powered, were easily operable by women. Making vocational knitting training available to its female workers, customers were trained on the third floor of the store on Ermou Street by two or three instructors. In more distant rural areas, such as Halkidiki, Daniel Barzilay—an early partner in Benmayor & Co.—employed a lady (who later became his wife) to train the women how to operate the machine, with the staff loading some six to eight machines on two donkeys and travelling through the villages close to Thessalonica to sell the machines and teaching workers how to use them. In order to overcome the traditional barriers of modesty, he went to the village priest and explained the purpose of his visit, with the father than ringing the church bells to call the ladies together. When sufficient numbers had gathered, he informed them: ‘This Mr. Jew has come to show us the “latest word in technology” and thus improve our economic prospects.’ This approach appears to have been fruitful, with the technology and training that enabled the entrance of female labour circumventing the traditional phase of male domination due to technical knowledge that was characteristic of late nineteenthcentury England (Bradley, 1995). The Alliance Israelite Universal introduced vocational knitting training into workshop curricula for Jewish girls even earlier, in 1924—much later than the sewing and embroidery classes, however (Dagkas, 2003, pp. 544–546; Molho, 2005), due to the late date when improved German knitting machines reached Greece. Correspondence between a German factory furnishing needles and spare parts for knitting machines and its customers in Thessalonica—both Jewish (R. Assael, Torres, & Anastassiadis, Sam Sarfati) and Greek (Kosmides & Co., E. Charalampides & Fils, Joseph Lascaridis, N. Demetriades & Chr. Economou) in the early 1930s (YIVO, RJCS, Greece, RG 207, FO. 156, Vereinigte Strick und
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Wirkmaschinennadel [sic]-Fabriken, [United Knitting Machines Needle Factories] GMBH, Chemnitz, to Banque Union, SA, Salonica, 14/7/1932; 21/7/1932; 28/7/ 1932; 8/8/1932) and the details of the Service for the Disposal of Jewish Wealth (Yperesia Diatheseos Israelitikon Periousion, YDIP) inventory of Sam Sarfati’s workshop in 1943/1945 (USHMMA, Records of Sam Sarfati, 12.1.1945, Reel 5B-11) reflect the spread of innovative technologies—including knitting, flannel, and special rubber-underwear machines—and the expectation that this branch of the local economy would continue to grow. The newly installed knitting machines introduced into the big factories in the Harilaos suburb of Thessalonica were easily operable by women. This part of the workforce thus became overwhelmingly female. The growing knitwear industry and integration of prominent Jewish entrepreneurs are illustrated by the development of the Jewish family firm G. S. Modiano fabrique de bas et chaussettes. Modiano belonged to the Jewish Italian elite. In 1926, G/J [di] S Modiano (established 1908) transferred from the maritime agency business to the ‘highly successful’ (knitted) stocking manufacturing branch and Jacques and Humbert S. Modiano of Modiano Frères left brick production to join their brother in the knitting industry within Modiano Frères in 1931. In 1935, the partners rationalised the family partnership into an anonymous company they named Makedoniki Kaltsopiia [sic] SA [Mακεδoνικη Kαλτσoπoιια][Macedonian Hosiery Ltd.]. A large-scale enterprise, its capital (GRD5,500,000) included a new two-storey building in the Harilaos suburb, raw materials, and goods in stock. The factory was equipped with modern, professional machinery and mechanical accessories for the production of luxury socks [bas grand luxe], employing a total of 85 female workers and clerical workers. The products were sold in a store in the city centre run by Humbert Modiano, one of the partners. According to contemporaneous reports, it was regarded as one of the most important in the industry in Macedonia, producing 150 dozen pairs of socks daily. Gaining a good reputation, the Modiano brothers were well known in the industry, meeting all their obligations (CAHJP Gr/Sa FO 346 Makedoniki Kaltsopiia [the former Modiano Frères] BA/161, 21 February 1936).
7
Sewing and the Ready-Made ‘Needle Industry’
Like the knitting machine, the sewing machine accelerated standardised mass production within the outwear industry. The growing demand for ready-made basic clothing increased the scope of mass production (enabled by intensive female labour), with the assembly-line mode of production only requiring minimal skills. Refugees also entered the developing needle industry that had sprung up with the mass production of men’s shirts and expanded into the mass production of clothing accessories. These enterprises ranged from small (1–5 workers) to mid-sized (6–25 workers). With sewing machines only demanding a small initial outlay, they lay within the grasp of migrants, expediting the standardised mass production of outer clothing (Green, 1977). The small working space necessary also helped cut production costs.
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Entrepreneurs integrated vertically from the production of shirts to their distribution in the local market directly to the end consumer. Prosromos Zahmanoglou, for example—a refugee who found accommodation in the crowded new quarter—had easy access to a cheap female refugee workforce. Starting out mass producing ties, he then expanded into men’s shirts, for which there was greater demand. The production practice resembled that of hosiery, the scale simply being smaller—a modest mid-sized workshop with six workers, sewing machine, iron, etc., adjoining the shop (Meron, 2016). Like the knitting industry, this industry also attracted investment from free professional refugees. In 1931, Aristide Anthomelides—a physician refugee from Asia Minor—invested in his brother’s perfume, rubber goods, lingerie, and hosiery shop and attached corset workshop, for example (Meron, 2016). The factory’s location close to Thessalonica’s free port enabled its owners to import semi-raw material at reduced tariffs and export their goods abroad directly, without paying local tax. Refugees also made their way into the clothing industry via the production of notions (e.g. buttons), this industry hereby replacing imported goods. The protective tariff policy not only increased profits but also encouraged commercial businesses to expand by adding further production lines. Caradimos [Karadimos] & Stamoulis (est. 1905) operated a large retail store selling novelties, hosiery, leather goods, perfumery, gloves, etc., for example, also manufacturing trousseaus and lingerie (CAHJP GR/Sa 165a, BA/66 Caradimos & Stamoulis, 22/3/ 1935). As evinced by a contemporary, Bona Sarfatty, its shop was regarded as the place for well-established middle-class Jewish mothers to shop for their daughters’ dowries (Levine Melammed, 2013, p. 65, copla 119b). Employing a staff of fifteen, including salespersons and seamstresses, the capital invested in it was estimated to be worth around GRD2,500,000. Organisation of the ready-made confection industry (sewing) as well as the hosiery industry (knitwear) continued to be led by department stores (Kupferschmidt, 2007, pp. 37–38). Employing the putting-out system (manufacture by subcontractors), the ads they placed declared their marketing policy of prix fixes—the Western marketing practice prevalent in European department stores (Vecris, 1922, p. 108). They thus targeted the upper class, a clientele attracted by the Parisian source of the merchandise. Galleries Trias (former Matarasso, Saragoussi & Rousso) sold imported stockings (bas de soie), hats, and shoes, for example, also mass-producing ready-made garments for men and children—including undergarments, flannels, men’s cotton shirts, and men’s accessories (Lévy, 1930, p. 892). Vertical integration from production to commercial distribution significantly reduced the firm’s financial risks. The mass production of hats conforming to Western fashion, which replaced the traditional Ottoman fez worn by men, resembled that of cloth and confections—a workshop/factory adjoining an outlet. Migrants formed a particularly prominent sector of this industry within the Greek Orthodox community. Constantin Zografakis, for example—‘originaire d’Athènes âgé de 67 ans environ, marie et père de famille’—owned a large millinery factory with over 25 workers that produced a sizable volume of men’s hats (Meron, 2016)
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Seamstresses/Tailors
Approximately 60% of the commercial enterprises within the clothing industry documented in the Bank Amar reseinsements deal with inputs for the production of custom-made (outer) clothing—cloth and notions for tailors and seamstresses (Meron, 2011/2013). As the large number of seamstresses and tailors listed in the 1928 census evinces (Table 1; Appendix), most outer clothing at the time was still fashioned in this traditional manner, with Jewish archival resources confirming this trend (Table 2). About two-thirds of Jews who applied to immigrate to Mandatory Palestine in 1933 declared themselves to be seamstresses. In one such handwritten document, Daisy Broudo (1932), whose family belonged to the petite bourgeoisie, explained why Thessalonican Jewish girls sought jobs in the needle trades during the 1920s: ‘I learned the sewing and embroidering craft at school ... my eldest sister is a dressmaker and I help her’ (CZA S6/2533 [January 1932]). Right from the start, the sewing machine was recognised as a ‘female machine’ that could be used at home (Bradley, 1995). Like embroidery, sewing was an occupation eminently suited to women (including veteran and refugee Greeks), allowing them maintaining their traditional social norms of modesty (Hirschon, 1989; Strumza, 1995, p. 10). The ‘family wage’ concept common in both societies prevented married women serving as principal breadwinners, confining them to the home whilst exploiting the availability of younger, unmarried females (de Groot & Schrover, 1995, p. 3). Purchasing sewing machines enabled them to work whilst at home and contribute to the family income without neglecting their maternal or household duties (Papastefanaki, 2022, p. 85). The Thessalonican Jewish women’s preference for employment as seamstresses also reflects their access to the intergenerational transfer of professional skills and training available to Jewish women in the city (Handeli, 1992, p. 16). Jewish women acquired skills in sewing, embroidering, and ironing in training workshops organised by the Alliance Israélite Universelle attached to primary schools and supervised by the directors (Malino, 1998, p. 258). The latter’s archival statistics point to the pervasiveness of ‘needlework’—including sewing and embroidery—amongst Table 2 Jewish female clothing industry workers, Thessalonica, 1933
Occupation Seamstress (couturière or modiste) Shirtmakers Embroiderers Footwear Socks Milliners Total in clothing industry workers
N 37 9 5 2 1 1 55
% 67 16 9 4 2 2 100
Source: Adapted from CZA S6/2535, 14 September 1933—a list of Jewish women who applied to immigrate to Mandatory Palestine from Thessalonica Note: Of the 64 out of 110 female applicants who declared their occupation, 55 worked in the clothing industry
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Jewish women (Anastassiadou, 1992/1994, p. 70). Expert Jewish seamstresses and milliners taught these skills in Jewish schools belonging to the Alliance network, in Alliance-organised workshops, and in the seamstresses’ homes. Jewish entrepreneurs continued using the putting-out system, employing homebased seamstresses, with the late Shlomo Calderon attesting this practice by the Jewish owner of a factory producing riding breeches and suits for export to Europe (3 February 2009). Although working from home, these women supplemented the factory workforce during periods of high demand. Significant over-representation of indigenous home-based seamstresses (Appendix) indicates that this occupation served as a ‘pull factor’ amongst middle-class veteran Greek and Jewish women. Affording an opportunity for self-employment, these groups also viewed it as offering an escape from the gender discrimination that plagued the poorly paid confection (sweat) workshops (Mazower, 2004, p. 389; Meron, 2011/2013, Chapter 5). Their status as independent seamstresses (and tailors) enabled them to circumvent the ‘family wage’ concept that allowed employers and trade unions to pay them lower wages than their male counterparts— amongst other discriminatory practices (de Groot & Schrover, 1995, p. 3). Believed to pay more than clerks in commercial enterprises, the occupation was considered more advantageous for women than clerical work in 1934. Fakima, a clerk at Abravanel and Benveniste, earned GRD1200 per month; Esther, a regular en kaza tailoress, earned between GRD 80 and 100 daily (= GRD1600–2000 per month) (Naar, 2006, p. 20). Greek veteran females—including Jews—nonetheless held a significant initial advantage over refugee females in this respect, controlling the sector by virtue of their extensive social network of affluent female clientele. The status of independent seamstress also enabled Jewish women to remain modest in a familiar, controlled space. Married seamstresses continued to adapt themselves to the traditional entrepreneurial space allotted to women—the home— seamstresses rarely entering the larger space governed by the Chamber of Commerce and Industry still dominated by men (Meron 2011/2013, Chapter 5). Jewish seamstresses enjoyed several advantages essential for easy access to haute couture opportunities: (a) the working space available in their homes—a resource urban female refugees lacked due to resettlement-programme delays (Meron, 2011/2013, Chapter 3), and (b) the fact that they formed part of solid social and information networks that facilitated access to an affluent female clientele. Although the spatial dispersion of the Jewish minority in the wake of the 1917 fire reduced employment opportunities within ethnic enclaves, it did not destroy client networks, with Jewish seamstresses thus retaining their Christian (Mazower, 2004, pp. 417–418) and Turkish clients who had remained in the city following the transfer (Refael, 1988, p. 378; Strumza, 1995, p. 10). Recently arrived refugee women had no such social networks, with their homes lying at a geographical distance from the indigenous well-to-do Greek neighbourhoods (Hastaoglou-Martinidis, 1997). Jewish seamstresses also had easier access to inputs—such as imported Italian cotton tissue from Italy and fine English woollens—provided by Jewish merchants (Meron, 2011/ 2013).
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Conclusion: The Garment Economy—Migrant/Minority Entrepreneurial Patterns?
As a labour-intensive industry, clothing was deemed suitable for migrants, refugees, and minorities with an interest in keeping labour costs low. Greeks (primarily repatriated refugees and internal migrants) and Jews both engaged therein, participating in the mass production of knitwear, underwear, hosiery, confections, notions, and hats. In contrast to the weaving and spinning industries which, largely monopolised by indigenous Greek entrepreneurs and wealthy refugees and supported by repatriation agency resources, typically required large immovable investment and intensive labour, the mass-produced clothing industry was generally characterised by small- to medium-scale family partnerships. The vertical integration of small production and the sale of the goods from adjacent ‘factory outlets’ cut the costs of enterprises owned by refugees in possession of limited resources. In general, the Greek nation-state’s autarchic orientation and population expansion via national population movements and repatriated refugees helped build and establish its national economy. Inter-ethnic collaboration not only met the growing basic needs of the local populace for cheap clothing but also created jobs for large numbers of workers in an era of increasing unemployment in European work markets. Despite the rapid development of the ready-made clothing industry, however, it remained confined to specific items (e.g. underwear) and tailors/ seamstresses, with traditional manufacturers continuing to control the lion’s share of the production of outer clothing. Alongside traditional and new manufacturers, some importers also distributed luxury goods to the expanding bourgeoisie in the Greek metropolises. Whilst it was characterised by new technological investment, small workspace, and a co-ethnic cheap female refugee workforce (e.g. Light & Gold, 2000; Waldinger & Lapp, 1992), entrepreneurial skills combined with the cheap labour encouraged by official government policy even enabled minority/migrant entrepreneurs to expand their plants into large-scale factories. In contrast to the handicraft national heritage preserved by governmental policy seeking to maintain the rural population in the countryside (Dana, 1999), the garment economy, which targeted urban minorities and migrants—both entrepreneurs and their co-ethnic workers—developed much later in interwar Greece than in more advanced parts of industrialised Europe. When the sewing machine (Godley, 2006) and then new work-floor arrangements became prevalent in the late nineteenth century, productivity was expected to skyrocket and large factories become garment production sites. The ‘smarter’ post-war machines capable of coping with diverse garment sizes, materials, styles, etc., further rationalised garment production. Although Benmayor & Co. continued selling Diamant handknitting machines in rural Greece (these becoming electric in the 1960s), new Italian, German, and Japanese producers of modern machinery entered the market, offering new possibilities and electronic automations. The later machines, known as ‘flat knitting’ machines, were used for knitting sweaters and outerwear in general, with circular knitting machines producing underwear, t-shirt, and sweatshirt fabric. As
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Jacky Benmayor (2022) attests, such machines were rare in Greece before the war: ‘I can tell you with confidence that the first machines of this kind were sold by my father in 1946–47, imported from England.’ Later, Benmayor & Co. sold most of the German, Italian, and Chinese circular knitting machines sold in Greece. Currently (2022), the firm sells sewing machines manufactured by leading companies in the field for domestic and professional use and knitting machines for craft and industrial usage to retail stores throughout Greece (https://www.benmayor.com.gr/en [retrieved 30 July, 2020]). Despite the adoption of advanced technologies such as CAD-CAM systems, manufacturers continued to rely on cheap labour for garment assembly, but many outsourcing this part of the production process offshore. Whilst garment manufacturing in cosmopolitan cities declined dramatically, contrary to the gloomy expectations small garment factories in advanced economies demonstrated considerable resilience—due at least in part to the salient role played by immigrants (Light et al. 1999; Rath, 2003). The use of CAD/CAM software to create 3D prototypes of new automotive body staples and design components for the mass production of fashion items ensures the most efficient cut of fabrics, adjusts the pattern scale to size, and even shows how the clothing will fit. The halting of supply chains following the COVID-19 pandemic has impeded globalisation and encouraged reliance on domestic production. Garment production may thus return to metropolises in more developed countries, with migrant workers complementing the local workforce faced with unemployment. Alternatively, the garment economy may deepen its dependence on long-distance labour guidance and sales distribution—both online by international companies and through social media by local retailers. If so, the garment economy appears set to remain dominated by migrant/minority entrepreneurs and their co-ethnic labour force.
Appendix: Gainful Employment in Textile Sub-branches by Ethnicity and Gender (Greek Metropolises, 1928) Male Spinners/weavers Embroiderers/lace makers Carpet manufacturers Rope/string manufacturers Dyers/clothing cleaners Launderer/ironers Tailors Underwear (lingers) Flannel/sock makers Milliners Mattress/upholstery producers
Thessalonica IM RM 9.7 12.9 1.5 1.0 1.1 6.0 1.3 0.6 5.9 3.8 4.1 1.1 61.7 60.8 0.8 2.2 2.0 3.0 8.2 2.8 1.2 5.3
Athens IM 9.0 1.2 1.6 0.7 4.8 2.8 59.6 1.9 1.0 13.7 2.7
RM 8.7 0.8 10.9 0.2 4.3 2.4 59.2 1.9 1.5 5.6 2.8
Piraeus IM 34.8 0.2 2.8 5.3 9.0 1.2 37.8 0.5 0.6 3.2 4.6
RM 17.7 0.3 16.5 1.2 4.8 1.2 53.0 0.3 0.6 1.2 2.7
(continued)
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Male Clothing accessories manufacturers Total per cent Total Percentage in textile industry
Female Spinners/weavers Embroiderers/lace makers Carpet manufacturers Rope/string manufacturers Dyers/clothing cleaners Launderers/ironers Seamstresses Underwear (lingers) Flannel/sock makers Milliners Mattress/upholstery producers Clothing accessories manufacturers Total percent Total sum Percentage in textile industry
O. C. Meron Thessalonica IM RM 2.5 0.4
Athens IM 1.0
RM 1.7
Piraeus IM 0.0
RM 0.5
100.0 1285.0 8.8
100.0 1448.0 12.0
100.0 3245.0 9.1
100.0 1809.0 13.4
100.0 1179.0 7.4
100.0 1294.0 11.7
IF
RF 21.7 9.2 17.5 0.3 0.1 5.7 29.1 2.2 8.8 4.1 0.1 1.0
IF 7.0 0.0 1.2 0.0 0.5 5.0 61.6 4.5 1.6 17.4 0.0 1.1
RF 15.6 9.1 22.3 0.0 0.4 4.4 34.8 3.2 2.6 6.3 0.1 1.1
IF
5.9 7.0 1.4 0.0 0.2 6.9 61.3 3.5 3.8 8.3 0.1 1.6
33.1 3.3 2.5 0.5 0.2 3.9 46.0 0.5 0.8 7.3 0.0 1.9
RF 25.9 4.8 44.9 0.3 0.2 1.8 17.1 0.9 1.0 2.3 0.0 0.7
100.0 2389.0 60.4
100.0 3104.0 75.0
100.0 7397.0 85.4
100.0 5433.0 86.6
100.0 3058.0 83.2
100.0 4426.0 75.6
Source: Greek Census 1928, 3.1 For the total employees, see Table Ie, p. 351 (Thessalonica), p. 314 (Athens), p. 315 (Piraeus). For refugees, see Table IIe, p. 741 (Thessalonica), p. 704 (Athens), p. 705 (Piraeus) Notes 1. IM, indigenous males; IF, indigenous females; RM, refugee males; RF, refugee females; TI, total indigenous; TR, total refugees; TM, total males; TF, total females 2. The number of ‘indigenous employees’ in any sector was calculated by deducting the total number of refugees employed in the sector from the total number of employees in the sector 3. ‘Industry’ includes food, construction, electricity/public utilities (water), metals, wood, leather/ hides, textiles, tobacco, paper, unspecified industries 4. Textiles include the capital-intensive production of inputs for the clothing (cotton, rope, string) and carpet industries, home textiles (for consumption, including mattress/upholstery producers). Clothing includes knitwear producers and most of the consumption ‘needle industry’—tailors, seamstresses, lingerie producers, milliners, clothing accessories manufacturers (including umbrellas and ties)
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References Anastassiadou, M. (1992/1994). Artisans juifs à Salonique au début des Tanzimat. Revue du Monde Musulman et de la Méditerranée, 66, 65–72. Austrian Report. (1915). (K. K. Österreichisches Handelsmuseum, Dezember, 1915) Salonik, Topographisch-Statistische Übersichten, Wien (II.41.821). Benmayor, J. (2022, August). Email correspondence. https://www.benmayor.com.gr/en. Retrieved 05.08.2022. Bradley, H. (1995). Frames of reference: The hosiery industry. In G. de Groot & M. Schrover (Eds.), Women workers and technological changes in Europe in the nineteenth and twentieth centuries (pp. 17–34). Taylor and Francis. Christodoulaki, O. (2001). Industrial growth in Greece between the wars: A new perspective. European Review of Economic History, 5(1), 61–89. Dagkas, A. (2003). Recherches sur l’histoire sociale de la Grèce du Nord: Le mouvement des ouvriers du tabac, 1918–1928. Association Pierre Belon. Daisy Broudo. (1932, January). (CZA S6/2533). Dana, L. P. (1999). Preserving culture through small business: Government support for artisans and craftsmen in Greece. Journal of Small Business Management, 37(1), 90–92. https://www. proquest.com/scholarly-journals/preserving-culture-through-small-business/docview/220 957420/se-2?accountid=14483 de Groot, G., & Schrover, M. (1995). General introduction. In G. de Groot & M. Schrover (Eds.), Women workers and technological changes in Europe in the nineteenth and twentieth centuries (pp. 1–16). Taylor and Francis. DOT. (1925). Report on the industrial & economic situation in Greece, for the years 1923 and 1924. His Majesty’s Stationery Office. DOT. (1928). Report on economic conditions in Greece, dated May 1928. His Majesty’s Stationery Office. DOT. (1937). Report on the economic and commercial conditions in Greece, April 1937. His Majesty’s Stationery Office. Dritsas, M. (2003). Business and politics: The state and the networks in Greece. In T. Gourvish (Ed.), Business and politics in Europe, 1900–1970 (pp. 289–306). Cambridge University Press. Godley, A. (2006). Selling the sewing machine around the world: Singer’s international marketing strategies, 1850–1920. Enterprise and Society, 7(2), 266–301. https://doi.org/10.1093/es/ khj037 Green, N. L. (1977). Ready-to-wear and ready-to-work: A century of industry and immigrants in Paris and New York. Duke University Press. Handeli, Y. (J.). (1992). A Greek Jew from Salonica remembers (M. Kett, Trans.). Herzl. Hastaoglou-Martinidis, V. (1997). A Mediterranean city in transition: Thessaloniki between the two world wars. Facta Universitatis: Architecture and Civil Engineering, 1(4), 493–507. Hirschon, R. (1989). Heirs of the Greek catastrophe: The social life of Asia Minor refugees in Piraeus. Clarendon. Jirousek, C. (2000). The transition to mass fashion system dress in the later Ottoman Empire. In D. Quataert (Ed.), Consumption studies and the history of the Ottoman Empire, 1550–1922: An introduction (pp. 201–241). SUNY Press. Kayser, B., & Thompson, K. (1964). Economic and social atlas of Greece. NCSR. Kritikos, G. (2000). State policy and urban employment of refugees: The Greek case (1923–30). European Review of History, 7(2), 189–206. Kupferschmidt, U. M. (2007). European department stores and Middle Eastern consumers: The Orosdi-Back saga. Ottoman Bank Archives and Research Centre. Lampe, J. R., & Jackson, M. R. (1982). Balkan economic history, 1550–1950: From imperial borderlands to developing nations. Indiana University Press. Levine Melammed, R. (2013). An ode to Salonika: The Ladino verses of Bouena Sarfatty. Indiana University Press.
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Lévy, S. (Ed.). (1930). Le guide Sam: Le livre d’Or de l’Orient. Garches (S. & O.). Light, I., Bernard, R. B., & Kim, R. (1999). Immigrant incorporation in the garment industry of Los Angeles. International Migration Review, 33(1), 5–25. Light, I., & Gold, S. (2000). Ethnic economies. Academic Press. Malino, F. (1998). The women teachers of the Alliance Israélite Universelle, 1872–1940. In F. Malino & J. R. Baskin (Eds.), Jewish women in historical perspective (pp. 248–269). Wayne State University Press. Mazower, M. (1991). Greece and the inter-war economic crisis. Clarendon. Mazower, M. (2004). Salonica, city of ghosts: Christians, Muslims, and Jews 1430–1950. Harper Collins. Meron, O. C. (2011/2013). Jewish entrepreneurship in Salonica, 1912–1940: An ethnic economy in transition. Sussex Academic Press. Meron, O. C. (2015). Connecting threads? Greeks, refugees, and Jews in Thessaloniki’s textile industries, 1923–1943. Zmanim, 129, 78–92. (Hebrew). Meron, O. C. (2016). Greek industrialists in Salonica during the industrial boom of 1930s: Evidence from Jewish archival resources. Arxeiaka Analekta, 1, 51–70. Molho, R. (2005). Salonica and Istanbul: Social, political and cultural aspects of Jewish life. Isis. Naar, D. E. (Ed.). (2006). In their own words: Glimpses of Jewish life in Thessaloniki before the Holocaust. Jewish Community of Thessaloniki. Papastefanaki, L. (2022). Sewing at home in Greece, 1870s to 1930s: A global history perspective. In M. Nilson, I. Mazumdar, & S. Neunsinger (Eds.), Home-based work and home-based workers (1800–2021) (pp. 74–95). Brill. Pentzopoulos, D. (1962). The Balkan exchange of minorities and its impact upon Greece. C. Hurst. Rath, J. (2003). Undressing the garment industry: Immigrant entrepreneurship in seven cities. In J. G. Reitz (Ed.), Host societies and the reception of immigrants (pp. 253–285). Center for Comparative Immigration Studies. Refael, S. (Interviewer/Ed.). (1988). Routes of hell: Greek Jewry in the Holocaust (testimonies). Institute for Research of Salonica Jewry and the Organization of Jewish Survivors of Greece in Israel (Hebrew). Sandis, E. E. (1973). Refugees and economic migrants in Greater Athens: A social survey. National Centre of Social Research. Strumza, J. (1995). And you choose life: From Salonica to Jerusalem via Auschwitz and Paris. Institute for the Research of Saloniki Jewry (Hebrew). USHMMA. United States Holocaust Memorial Museum Archives. Vecris, J. (1922). Annuaire Commercial, Thessaloniki: Chambre de Commerce et d’Industrie de Salonique. Waldinger, R., & Lapp, M. (1992). Why immigrants stay in fashion: Insights from New York’s garment industry. Policy Studies Review, 11(2), 97–105.
Part II The Garment Business Today
Greenwashing in the Fashion Industry: Definitions, Consequences, and the Role of Digital Technologies in Enabling Consumers to Spot Greenwashing Darya Badiei Khorsand, Xiaoxue Wang, Daniella Ryding, and Gianpaolo Vignali
Abstract
With consumers’ growing awareness of sustainability issues in the fashion industry, many fashion companies have started developing green products and green marketing strategies to deliver on consumers’ demands (Zhang et al. The influence of greenwashing perception on green purchasing intentions: The mediating role of green word-of-mouth and moderating role of green concern. Journal of Cleaner Production, 187, 740–750 [online]. Available at: https:// www.sciencedirect.com/science/article/pii/S0959652618308722. Accessed 26 June 2022; 2018). However, as many fashion companies lack transparency of their supply chains (Kent. In search of transparency: Fashion’s data problem [online]. Available at: https://www.businessoffashion.com/podcasts/ sustainability/in-search-of-transparency-fashions-data-problem/. Accessed 29 June 2022; 2021), their green marketing efforts may be perceived as greenwashing as they lack the data needed to substantiate their claims (Zhang et al. The influence of greenwashing perception on green purchasing intentions: The mediating role of green word-of-mouth and moderating role of green concern. Journal of Cleaner Production, 187, 740–750 [online]. Available at: https:// www.sciencedirect.com/science/article/pii/S0959652618308722. Accessed 26 June 2022; 2018). With the emergence of digital technologies that can aid in providing transparency on supply chains (Amed et al. The state of fashion 2022. [online] Available at: https://www.mckinsey.com/~/media/mckinsey/industries/retail/our %20insights/state%20of%20fashion/2022/the-state-of-fashion-2022.pdf.
D. B. Khorsand (✉) · X. Wang · D. Ryding · G. Vignali Department of Materials, University of Manchester, Manchester, UK e-mail: [email protected]; [email protected]; [email protected]; [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_6
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Accessed 30 June 2022; 2021), rise in consumers’ demand for green products (Zhang et al. The influence of greenwashing perception on green purchasing intentions: The mediating role of green word-of-mouth and moderating role of green concern. Journal of Cleaner Production, 187, 740–750 [online]. Available at: https://www.sciencedirect.com/science/article/pii/S095965261830 8722. Accessed 26 June 2022; 2018), and the recent regulations set by the Competition and Markets Authority on greenwashing (Gov.UK. Greenwashing: CMA puts businesses on notice. [online] Available at: https://www.gov.uk/ government/news/greenwashing-cma-puts-businesses-on-notice. Accessed 31 Oct 2022; 2021), it has become more important than ever for companies to avoid engaging with greenwashing. Despite the fact that greenwashing has become prevalent in the fashion industry (Oliveira Duarte et al. From fashion to farm: Green marketing innovation strategies in the Brazilian organic cotton ecosystem. Journal of Cleaner Production, 360, 132196 [online]. Available at: https://www.sciencedirect.com/science/ article/pii/S0959652622018029#bib48. Accessed 13 July 2022; 2022), literature on it has remained limited. In this chapter, a critical literature review of greenwashing is provided which includes definitions, reasons why it occurs, and its impact on consumers’ purchase behaviour. To fill this in the literature, this chapter draws on key literature provided in academic books and journals, as well as industry reports and articles accompanied by recent examples in the fashion industry. Lastly, this chapter explores how digital technologies can be leveraged to enable consumers to spot greenwashing, and as a result, encourage companies to avoid engaging with it (Fernandes et al. When consumers learn to spot deception in advertising: testing a literacy intervention to combat greenwashing. International Journal of Advertising, 39(7), 1115–1149 [online]. Available at: https:// www.tandfonline.com/doi/full/10.1080/02650487.2020.1765656?needAccess= true. Accessed 10 June 2022; 2020). Keywords
Greenwashing · Green marketing · Consumer purchase behaviour · Digital technologies
1
Introduction
The consumption levels in the fashion industry have been growing steadily over the years, apart from the slight drop they experienced in 2020 and 2021 due to the coronavirus pandemic (Rausch & Kopplin, 2021). The worldwide revenue of the apparel market is forecasted to increase to almost US $2 trillion by 2026, a 29% increase from 2021 (Statista, 2022). To address the rise in consumers’ demand for apparel, fashion companies across the industry, from fast fashion to luxury, have developed mass production techniques, whilst disregarding the environmental and
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social impact of their actions (Rausch & Kopplin, 2021). Hence, the fashion industry has become one of the most polluting industries and is predicted to emit 2791 million tons of CO2 emissions, 118 billion cubic metres of consumed water, and 148 million tons of textile waste by 2030 (Rausch & Kopplin, 2021). Over the years, consumers’ awareness of the negative impact of the fashion industry has begun to rise, which has led to an increased demand for more sustainable/green products (Zhang et al., 2018). The terms ‘green’ and ‘sustainable’, which are commonly and interchangeably used along with ‘eco-’ and ‘ethical’ fashion (Carey & Cervellon, 2014; Ryding et al., 2022; Vignali et al., 2019), refer to a wide range of products that claim to cause ‘little or no environmental impact’ (Niinimäki, 2010, p. 152). They include products that are made with organically grown and recycled materials, fair-trade manufacturing, etc. (Henninger et al., 2016). In this chapter, the term ‘green’ will be used to refer to products with the aforementioned characteristics due to its relevance to the term ‘greenwashing’ which is the primary focus of this chapter. In a study conducted in 2021 Vogue magazine found that 38% of their readers purchase green fashion products as much as possible and 46% of them sometimes do (Cernansky, 2021). In a similar study, it was found that 31% of Generation Z consumers and 26% of Millennials are even willing to pay more for products that have a lower negative impact on the environment (Amed et al., 2019). Hence, many companies across all industries, including the fashion industry, have started developing green products in an attempt to minimise their negative and maximise their positive environmental impact, and deliver on their consumers’ demands (De Freitas Netto et al., 2020; Rausch & Kopplin, 2021). In addition, they have started making green claims, i.e. claims to communicate with their customers how their products and/or services provide a benefit or are less harmful to the environment (Zhang et al., 2018). Hence, green marketing, which is referred to as the processes and activities to promote green products (Groening et al., 2018), has become prevalent in the fashion industry (Oliveira Duarte et al., 2022). Whilst there are many benefits to green marketing such as increased customer interest and loyalty (Oliveira Duarte et al., 2022) as most fashion companies lack transparency in their supply chains (Kent, 2021) and the required data to substantiate their claims, their green marketing efforts may be perceived and counted as greenwashing (Zhang et al., 2018). As suggested by Sailer et al. (2022), the growing awareness of the negative environmental and social impact of the fashion industry has led to substantial growth in the green fashion market, and consequently, the birth of greenwashing in the fashion industry. Greenwashing refers to use of exaggerated, deceptive, and unsubstantiated claims of environmental benefits to improve corporate image (Sailer et al., 2022). However, with increased educational information regarding greenwashing and the negative impact of the fashion industry on social media platforms (Delmas & Burbano, 2011; Eng et al., 2021) and the emergence of digital technologies that can enable consumers to spot greenwashing, it has become more difficult for companies to mislead consumers with their green claims, and to get away with it.
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As a form of concealment and deception designed to mislead consumers, greenwashing is considered to have a range of negative consequences. It can be considered a fraud as consumers experience monetary loss by purchasing a product/service that is advertised as green, but actually is not (Kurpierz & Smith, 2020). Batista et al. (2020) pointed out the harm of greenwashing from the perspective of enterprises; that is, greenwashing may affect enterprises’ reputation after being discovered and, hence, negatively impact their financial performance (Walker & Wan, 2011) as well as the interest of the stakeholders including consumers and investors (Du, 2014). In addition, Speckemeier and Tsivrikos (2022) argue that misleading information can damage job attractiveness and perceived company image, making it difficult for companies to attract talent. Lastly, there are legal consequences to greenwashing. The Competition and Markets Authority (CMA) announced that they will start reviewing green claims made both online and offline from early 2022 and will take action against offending companies (Gov.UK, 2021a). In fact, in July 2022, the CMA opened investigations into three fashion brands to scrutinise their ‘green’ claims; these brands include Asos, Boohoo, and George as ASDA (Gov.UK, 2022). In addition, they have asked consumers to contact them if they come across any companies that may be engaging in greenwashing, making it more important than ever for companies to avoid greenwashing (Gov.UK, 2022).
1.1
Research Gap and Aim
As an issue that is prevalent in many industries such as the hospitality, automotive, and food industries, greenwashing has been studied by many academics and researchers in various fields over the years (Oliveira Duarte et al., 2022; Speckemeier and Tsivrikos, 2022; Turna, 2022; Zhang et al., 2018). However, research on greenwashing in the fashion industry has remained sparse, in particular how it affects consumers’ purchase behaviour. Additionally, there is currently limited research on digital technologies that can be leveraged to educate consumers and enable them to spot greenwashing. This is due to the fact that these tools such as blockchain technology are still relatively new, and hence under-researched. Therefore, this chapter aims to fill this gap in knowledge by providing a critical literature of greenwashing, including definitions, reasons why it occurs, its consequences and impact on consumers by building on literature on green scepticism and greenwashing concerns. To achieve that, it synthesises extant academic literature on greenwashing, industry reports, and articles as well as recent examples of relevant events in the fashion industry. Additionally, this chapter explores and critically analyses the digital technologies currently available in the market that can be useful in educating and enabling consumers to spot greenwashing.
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Literature Review
2.1
What Is Greenwashing
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The term greenwashing was first coined by environmentalist Jay Westerveld who wrote an essay in 1896 accusing the hospitality industry of greenwashing for asking visitors to reuse their towels as part of their water conservation strategy, whilst it was actually for cost-saving purposes (De Freitas Netto et al., 2020; Idowu et al., 2013). Since then, the literature on greenwashing and the definitions proposed for it have increased significantly and continue to grow (Yang et al., 2020). The term greenwashing refers to a range of communications that could mislead consumers into believing a company and/or their products are greener and have a lower environmental impact than they actually do (De Freitas Netto et al., 2020); it includes a range of phenomena from slight exaggeration to full fabrication (Lyon & Montgomery, 2015). The general use of this term and the academic debate on it has remained rather broad and vague as it has been defined slightly differently by various researchers (Yang et al., 2020). Several definitions of greenwashing proposed by various researchers over the years are presented in Table 1. Seele and Gatti (2015) argue that the definitions used and provided by academics have one key shortcoming which is ‘greenwashing is not understood as a Table 1 Definitions of greenwashing Definition ‘The practice of falsely promoting an organization’s environmental efforts or spending more resources to promote the organization as green than are spent to actually engage in environmentally sound practices. Thus, greenwashing is the dissemination of false or deceptive information regarding an organization’s environmental strategies, goals, motivations, and actions’ Putting ‘forward fewer substantive claims but more posturing claims in environmental advertising’ ‘Poor environmental performance and positive communication about environmental performance’ ‘Selective disclosure of positive information about a company’s environmental or social performance, while withholding negative information on these dimensions’ ‘Greenwashing is a PR tactic used to make a company or product appear environmentally friendly, without meaningfully reducing its environmental impact’ ‘Greenwashing, also known as eco-bleaching, whitewash, eco-washing, green washing, green makeup or green image washing, is a form of misleading advertisement to promote the product’s, goals, or policies of an organization and thus increase the aggregate benefits of the product’ ‘Symbolic information emanating from within an organization without substantive actions’
Reference Becker-Olsen and Potucek (2013, p. 1318)
Zhang et al. (2018, p. 742) Delmas and Burbano (2011, p. 65) Lyon and Maxwell (2011, p. 5) Das (2022)
Braga Junior et al. (2019, p. 228) Kahle and Gurel-Atay (2015) Walker and Wan (2012, p. 231)
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phenomenon in the eye of the beholder (likely, NGOs and the media)’ (p. 241). They argue that current literature does not address the key aspect of deliberation in the definitions as it tends to assume that greenwashing is a deliberate action engaged in by companies, and disregarding the fact that a company could engage with it unintentionally. Additionally, they argue that greenwashing only exists when a company is called out for it, hence it they conclude that ‘no accusation, no greenwashing’ (p. 241). Moreover, whilst all the definitions provided in Table 1 refer to some kind of deceptive practice, they differ in the way in which deception takes place. For instance, Becker-Olsen and Potucek (2013) define greenwashing as ‘the dissemination of false or deceptive information regarding an organization’s environmental strategies, goals, motivations, and actions’ (p. 1318), whereas in Lyon and Maxwell’s (2011) definition, no false information is presented as they define greenwashing as ‘selective disclosure of positive information about a company’s environmental or social performance, while withholding negative information on these dimensions’ (p. 9). Hence, it can be argued that there are different ways in which deception can take place and consumers can be misled, which is not reflected in the definitions provided. In 2007, TerraChoice, a marketing firm, conducted a study on green claims made on products carried on category-leading big box store shelves (De Freitas Netto et al., 2020; UL, n.d.). Using the results of the study, they identified ‘seven sins of greenwashing’ which provides different ways in which greenwashing may occur. Seven sins of greenwashing have been cited in many academic journals over the years across various disciplines (Baum, 2012; De Freitas Netto et al., 2020; Markham et al., 2014; Scanlan, 2017). It has become a popular tool amongst companies and consumers as it enables consumers to evaluate green claims, and can also be used as an effective tool for companies to ensure they do not engage with greenwashing (Baum, 2012; De Freitas Netto et al., 2020). The seven sins of greenwashing proposed by TerraChoice are presented in Table 2. In addition to the different ways in which greenwashing can occur, there are different types of greenwashing, which are not reflected in the definitions of greenwashing. De Freitas Netto et al. (2020) divided greenwashing into firm-level executional, firm-level claim, product-level executional, and product-level (see Fig. 1). Firm-level greenwashing refers to misleading consumers regarding the environmental practices of a company, whilst product/service-level greenwashing refers to misleading consumers regarding the environmental impacts of a product/service (De Freitas Netto et al., 2020; Delmas and Burbano, 2011). Many fashion companies, from fast fashion to luxury, have been found guilty of both firm-level and product/service-level greenwashing. Firm-level greenwashing could be found in companies’ sustainability report; for instance, H&M group in their sustainability report mention that they have tripled the share of recycled materials used in their garments from 5.8 to 17.9% (H&M Group, 2021). However, they do not provide much information on the details of the recycled materials used, which year has their use tripled from, and how much that actually helps to reduce their overall negative environmental impact. Hence, this could be viewed as greenwashing, sin of
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Table 2 Seven sins of greenwashing (UL, n.d.) Sin of greenwashing Sin of the hidden tradeoff
Sin of no proof
Sin of vagueness
Sin of worshipping false labels
Sin of irrelevance
Sin of lesser of two evils
Sin of fibbing
Definition A claim suggesting that a product is ‘green’ based on a narrow set of attributes without attention to other important environmental issues
A claim that is not and/or cannot be substantiated with supporting evidence or a reliable third-party certification A claim that is broad, poorly defined, and likely to be misunderstood by the consumer
Use of images and words to deceive consumers into believing that the green claims are endorsed by a third party, whilst that third party does not exist An environmental claim that is irrelevant, unimportant, and unhelpful to consumers and therefore distracts them from finding a truly green product
A claim that could be accurate within the product category but distracts consumers from holistically evaluating the product category’s environmental impacts A claim that is false
Example A fashion company claiming their packaging is green as it uses paper from sustainably harvested forest whilst ignoring the environmental impact of other stages of producing paper A fashion company claiming that they have reduced their carbon emissions but have no evidence to support their claim A fashion company claiming their products are made from recycled materials but fail to mention exactly what per cent of the products are made from recycled materials, and exactly what those recycled materials are A fashion company using a label that they have created themselves to substantiate their claim of being carbon neutral A fashion company claiming their products are ethically made as they pay their workers minimum wage, whilst that is a legal requirement in many countries; hence they are obliged to meet that requirement regardless A fast fashion company claiming their products are green due to use of recycled materials and ignore other unsustainable and unethical aspects of their business model A fashion company claiming they use recycled materials when they actually do not
vagueness, sin of lesser of two evils, and if the claim is false and they have no proof for it, sin of no proof and sin of fibbing. With regard to product/service-level greenwashing, in a study conducted by Changing Markets Foundation, it was found that out of 283 items reviewed from Gucci, a luxury fashion brand, all had green claims, and none of them had any certification to substantiate the claim (Changing Markets, 2021). Another company they studied was H&M. Out of the 499 products they reviewed, 212 of them had green claims, none of which had any certifications to prove the claims (Changing Markets, 2021) meaning they are potentially engaging with product/service-level
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Greenwashing
Firm-Level
Claim
Product/Service Level
Executional
Claim
Executional
Fig. 1 Classifications of greenwashing by De Freitas Netto et al. (2020)
Zara Zalando Walmart Marks & Spencer H&M Gucci George ASDA Asos 0
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300
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Total number of items with green claims with certification to support green claims Total number of items with green claims
Fig. 2 Number of items with green claims that are certified (Changing Markets, 2021)
greenwashing. Figure 2 illustrates a summary of Changing Markets Foundation’s study on various fashion companies, and their product/service-level greenwashing. Firm-level and product/service greenwashing can be further broken down to claim and executional greenwashing. Claim greenwashing refers to use of textual arguments to explicitly or implicitly make a misleading green claim about a product/ service or company (De Freitas Netto et al., 2020). On the other hand, in executional greenwashing, no green claim is made per se, but nature-evoking elements such as images of sea, greenery, and animals are used to create a perception that a product/ service or a company is green. Parguel et al. (2015) found that use of nature-evoking elements particularly impact consumers who are not knowledgeable in this area, as they were found to generate higher perception of a company’s greenness amongst
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them. This type of greenwashing is not reflected in many definitions of greenwashing as they all refer to the direct provision or lack thereof information, as opposed to indirect greenwashing using nature-evoking elements. Yu et al. (2020) provide another categorisation for greenwashing by dividing it into three categories: manipulating disclosure to boost company valuation, selective disclosure to mislead investors, and product-level greenwashing. In manipulating disclosure to boost company valuation, companies present a large amount of environmental data to their stakeholders in an attempt to distract attention from their poor environmental performance (Yu et al., 2020). In the second type of greenwashing, i.e. selective disclosure to mislead investors, companies only share their positive environmental information and withhold the information they deem negative (Yu et al., 2020). Hence, referring to greenwashing classification by De Freitas Netto et al. (2020), the first two types of greenwashing can be classed as firm-level greenwashing. The last type of greenwashing suggested by Yu et al. (2020) is product-level greenwashing that focuses on only the product, as opposed to the firm which is in line with De Freitas Netto et al.’s (2020) product/service-level greenwashing.
2.2
Why Greenwashing Occurs
Whilst greenwashing tends to be something companies intentionally engage with to portray a more positive image of themselves (refer to Sect. 2.1), it may be difficult to avoid it for several key reasons. First, the terms commonly used in green marketing such as ‘sustainability’, ‘green’, ‘eco-’, and ‘ethical’ are rather vague and have no coherent definition (Henninger et al., 2016). Although this issue was pointed out in older literature (Bañon Gomis et al., 2011; Becker-Olsen & Potucek, 2013; Dryzek, 2005; Henninger et al., 2016; Partridge, 2011), it is still present. For instance, in 2013, Becker-Olsen and Potucek pointed out that ‘there is no agreed-upon definition of a green product or even what the claim environmentally friendly manufacturing means’ (p. 1319), and 8 years later, at the time of writing this chapter, there still is no single widely known definition of those terms. Henninger et al. (2016) point out that sustainability is ‘context dependent and situational’ (p. 403) and is understood differently by different people. Hence, when using terms such as ‘green’ and ‘sustainable’ in marketing and advertising, the issue of greenwashing arises, as the claims made using these terms can be vague and misleading to consumers (BeckerOlsen & Potucek, 2013). To prevent this issue, the CMA, the Competition and Markets Authority in the UK, has provided guidance for companies who make green claims and use certain terms to ensure they comply with their obligations under consumer protection law (Gov.UK, 2021b). According to their guidance, companies are required to provide evidence to prove their reduced environmental impact, and all the information needed for consumers to make an informed decision, as opposed to being open for consumers’ own interpretation (Gov.UK, 2021b). In addition, they have developed the Green Claim Code checklist, a guide companies can use to ensure their green claims comply with consumer protection law and do not mislead
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Table 3 Green claim code checklist (Gov.UK, 2021c) Statement 1 2 3
4 5
6 7 8 9 10 11 12 13
Explanation The claim is accurate and clear for all to understand There is up-to-date, credible evidence to show that the green claim is true The claim clearly tells the whole story of a product or service; or relates to one part of the product or service without misleading people about the other parts or the overall impact on the environment The claim does not contain partially correct or incorrect aspects or conditions that apply Where general claims (eco-friendly, green, or sustainable for example) are being made, the claim reflects the whole life cycle of the brand, product, business, or service and is justified by the evidence If conditions (or caveats) apply to the claim, they are clearly set out and can be understood by all The claim will not mislead customers or other suppliers The claim does not exaggerate its positive environmental impact, or contain anything untrue—whether clearly stated or implied Durability or disposability information is clearly explained and labelled The claim does not miss out or hide information about the environmental impact that people need to make informed choices Information that really cannot fit into the claim can be easily accessed by customers in another way (QR code, website, etc.) Features or benefits that are necessary standard features or legal requirements of that product or service type are not claimed as environmental benefits If a comparison is being used, the basis of it is fair and accurate, and is clear for all to understand
consumers (Gov.UK, 2021c). They mention that to make a green claim, companies must comply with all the statements provided in Table 3. In line with this, in 2021, the ASA, the Advertising Standards Authority in the UK, started conducting research on consumers’ understanding of ‘Carbon Neutral’ and ‘Net Zero’ in the context of hybrid electric cars as they have been identified as an area with a great environmental impact (ASA, 2021). The aim of this study is to provide companies who use these words when making green claims with in-depth insights into how consumers interpret the claims using these terms, in an attempt to prevent misleading consumers when advertising (ASA, 2021). Similar research on terms commonly used in the fashion industry such as ‘sustainable’, ‘green’, and ‘ethical’ would be beneficial to ensure all companies and consumers have a mutual understanding of these terms and subsequently claims made using them to prevent greenwashing. The second reason why greenwashing may be difficult to avoid is that supply chains in the fashion industry are ‘fragmented, complicated, and global’ (Niinimäki, 2010, pp. 152) and as a result, quite opaque. In fact, in a recent study, it was found that less than 20% of companies in the apparel industry have a comprehensive overview and visibility of all stakeholders in their supply chain, and only 15% of
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companies can trace all the materials they use through each step from their origin to processing and manufacturing (KPMG, 2021). Hence, it can be difficult for fashion companies to provide the required evidence to substantiate their claims of reduced environmental impact. It is important to note here that blockchain technology is predicted to help solve supply chain transparency issues which is discussed in more depth in Sect. 4.1 (Amed et al., 2021; Park & Li, 2021). Hence, if in the future blockchain technology proves successful in providing full transparency of supply chains, this cause for greenwashing could potentially cease to exist. In addition to a lack of transparency, due to the complexity of fashion’s supply chain, if a company mentions their efforts to reduce their environmental impact in a specific part of their business, such as packaging, advocacy groups may regard that as greenwashing as the company is not mentioning the other areas of their business, and/or is believed to not be moving fast enough (Becker-Olsen & Potucek, 2013; Henninger et al., 2016). This will in return create a ‘boomerang effect’ (BeckerOlsen & Potucek, 2013, p. 1319) where companies become hesitant to mention the actions they are taking to reduce their environmental impact, which can lead to them moving at a slower pace (Becker-Olsen & Potucek, 2013) Lastly, the concept of sustainability in the fashion industry can be considered an oxymoron (Henninger et al., 2016). As an industry that is based on consumerism where trends go in and out of style in the matter of weeks, achieving true sustainability where purchases are made in moderation, based on real needs, and are used until they fall apart, may not be possible (Henninger et al., 2016; Kong et al., 2021). Regardless of the contradictory nature of sustainability and fashion, consumers believe that sustainable (green) fashion does currently exist (Henninger et al., 2016) and as mentioned in Sect. 1.1, the demand for green fashion products is growing. However, a key question that arises here is can green fashion products continue to be made sustainably with little to no environmental impact if the demand for them continues to rise? Currently, the greenest and most environmentally friendly products are from smaller companies that do not have nearly as many sales and customers as fast fashion companies (Cernansky, 2022; Remake, 2021). At the end of the day, the main reason why fast fashion companies produce in such large quantities is to meet the consumers’ growing demands. The strategic direction of the organsiation influences their overall approach (Ryding et al., 2022; Vignali et al. 2010; Vignali & Vignali, 2009). This is clear in Shein’s case, one of the world’s leading fast fashion companies, who produces over 300,000 new styles per year, almost 11 times more than H&M group, Zara, and Boohoo combined (see Fig. 3) (Kennedy, 2022). Even though they are highly criticised in the media for their poor environmental and social practices, and continuous greenwashing (Chan, 2022; Jones, 2021; Williams, 2022), they are estimated to be worth $100 billion, more than H&M and Inditex combined (Kennedy, 2022). For this reason, when fast fashion companies use materials with lower environmental impact such as recycled polyester or introduce a recycling scheme, they get accused of greenwashing. A prime example of this is H&M’s ‘conscious collection’ which includes products that are made with at least 50% sustainable materials such as organic cotton or recycled polyester (H&M, n.d.) but is heavily criticised for
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Number of new styles added in the US (Year to date) 350000 314877 300000 250000 200000 150000 100000 50000 4414
18343
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0 H&M Group
Zara
Boohoo
Shein
Fig. 3 Number of new styles added by four leading fast fashion companies in the USA from year to date (Kennedy, 2022)
greenwashing in the media with critics believing that a fast fashion company cannot produce green products due to their business model of mass-producing products at a low cost (Butler, 2022; Hitti, 2019; McCourt, 2022).
3
The Impact of Greenwashing on Consumers’ Purchase Behaviour
Despite the negative impacts of greenwashing highlighted in Sect. 1, recent research suggests that 40% of green claims made online could be misleading (Gov.UK, 2021a). Additionally, in 2020 it was found that only 20% of consumers trust companies’ green claims (Morris et al., 2020), 39% in 2013, and 48% in 2009 (Goh & Balaji, 2016). Whilst the percentage of consumers who do not trust companies’ green claims seem to have reduced, there is still a growing concern amongst consumers and advocacy groups regarding the accuracy of companies’ green claims and greenwashing (Rausch & Kopplin, 2021). Consumers’ lack of trust and doubt regarding the accuracy of companies’ green claims and whether they are engaging in greenwashing are referred to as ‘green scepticism’ or ‘greenwashing concerns’, two terms that are often used interchangeably (Rausch & Kopplin, 2021). Green scepticism is defined as a phenomenon ‘in which customers doubt or disbelieve environmental claims made by the firms’ (Goh & Balaji, 2016, p. 629) and greenwashing concerns is defined as ‘an individual’s extent of suspicion towards an organization’s intentional non-disclosure of negative environmental information or intentional disclosure of false positive environmental information about its products and practices’ (Rausch & Kopplin, 2021, p. 6). In this
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Fig. 4 Theoretical model proposed by Rausch and Kopplin (2021)
chapter, the term ‘greenwashing concerns’ is used due to its similarity to the term ‘greenwashing’. Greenwashing concerns have been studied by many academics over the years (Goh & Balaji, 2016; Pomering & Johnson, 2009; Rausch & Kopplin, 2021). It is present due to the increasing number of greenwashing incidents and irresponsible environmental behaviour from companies (Goh & Balaji, 2016). Greenwashing concerns have been found to negatively impact various aspects of consumers’ purchase behaviour such as purchase intention, attitude, and product judgement with literature from academics in various industries over many years supporting it (Elving, 2013; Goh & Balaji, 2016; Rausch & Kopplin, 2021; Zhang et al., 2018). However, it is key to note that consumers’ scepticism can be resolved if they are provided with sufficient evidence to substantiate the green claims (Goh and Balaji, 2016). Elving (2013) found that consumers’ greenwashing concerns can negatively impact their attitude towards the company and their green products. Zhang et al. (2018) found that greenwashing concerns have a direct and negative impact on consumers’ purchase intention, whereas Rausch and Kopplin (2021) found that they have an indirect impact on purchase intention as they moderate the relation between attitude, subjective norms, environmental concerns, and perceived environmental knowledge with purchase intention. To conclude their findings, they developed a theoretical model (see Fig. 4) by building on the theory of planned behaviour, a theory which seeks to explain consumers’ purchase behaviour (Ajzen, 1991). Rausch and Kopplin (2021) justify their contradictory finding with Zhang et al. (2018) by explaining that due to lack of transparency from companies and the imperfect information consumers have, they cannot test the validity of their greenwashing concerns. They cannot measure whether companies’ claims are true, and that their products do indeed have a lower environmental impact, nor can they be completely certain that companies are greenwashing. Hence, they argue that
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Percieved risk
Confusion
Perceived benefit Consumer behaviour
Attitude & belief
Consumption of green products Satisfaction & loyalty
Greenwashing perception
Subjective & control foreces
Controled behaviour
Fig. 5 Theoretical model proposed by Braga Junior et al. (2019)
greenwashing concerns are only antecedents rather than having a direct impact on purchase intention (Rausch and Kopplin, 2021). However, they found that due to consumers’ rising greenwashing concerns, their attitude towards purchasing green products to be significantly impacted. Their finding is in agreement with Goh and Balaji (2016) who argued that greenwashing concerns have an indirect impact on purchase intention. Building on the theory of planned behaviour as well, Braga Junior et al. (2019) developed a theoretical model to explore how greenwashing affects consumers’ purchase behaviour of green products. Their proposed theoretical model is illustrated in Fig. 5. In their study, they found that greenwashing perception negatively impacts consumers’ attitude and belief of green products, and consequently, their purchase decision. Munir and Mohan’s (2022) study is in line with Braga Junior et al.’s (2019) findings as they argue that ‘confusion’ (see Fig. 5) is negatively related to trust and can lead consumers to form a negative perception of a company and can negatively impact their purchase behaviour. ‘Confusion’ in this context refers to consumers’ difficulty to make a purchase decision with the ambiguous information they are presented, for which greenwashing can be a trigger (Braga Junior et al., 2019). Additionally, they argue that vague communication can lead to scepticism in addition to confusion, which leads to consumers mistrusting the company. Hence, as greenwashing can negatively impact various aspects of consumer behaviour, it is imperative that companies disclose accurate, clear, and explicit information when
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making green claims to not only gain their customers’ trust, prevent green scepticism, and encourage purchase intention but also to gain support from other stakeholders (Munir & Mohan, 2022; Nguyen et al., 2019).
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Leveraging Digital Technologies to Enable Consumers to Spot Greenwashing
Education is one of the key ways to educate and enable consumers to spot greenwashing, and as a result, create bottom-up pressure to encourage companies to stop engaging with it (Fernandes et al., 2020). Fernandes et al. (2020) argue that in the age of digital media where a breadth of information can be easily accessed by consumers via websites, social media, and blogs, consumer self-education is a ‘mouse-click away’ (p. 1442). They further add that the more consumers are aware and educated on topics surrounding green claims, the less like companies are to engage with greenwashing. In line with this, the CMA have developed ‘Green Claim Code for Shoppers’, a guide for consumers to follow to evaluate the accuracy of green claims and to spot greenwashing (Greenclaims.campaign.gov.uk, 2021). Furthermore, they have provided educational videos and quizzes for consumers to watch and complete in order to equip them with the correct information to identify genuine green claims (Greenclaims.campaign.gov.uk, 2021). In addition to the more traditional approaches to consumer (self)education, there are several digital technologies that can enable consumers to spot greenwashing such as third-party verification tools and blockchain which are explored and analysed in great depth below.
4.1
Third-Party Verification Tools
In 2013, Becker-Olsen and Potucek argued that it is next to impossible for consumers to determine the accuracy of companies’ green claims and environmental and social impact of a product. They suggested that consumers can use third-party tools to determine how environmentally friendly a product is. This issue is reflected in a more recent study as well. Compare Ethics, a sustainable product intelligence and compliance platform, has developed a verification technology which aims to enable companies to communicate their green claims with great transparency (Morris et al., 2020). In a study they conducted in 2020 on 1250 participants based in the UK, they found that 83% of consumers are more likely to trust green claims if they are verified by a third party (Morris et al., 2020). Additionally, they found that only 18% of consumers trust green claims provided by fashion companies alone. They add that verification tools can be extremely useful in translating the reported data from companies to data that are easily understood by consumers and, subsequently, build trust between consumers and companies.
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Fig. 6 Compare Ethics website (Compareethics.com, n.d.)
On their website, Compare Ethics have a list of companies and products that they have verified and are available to shop. As seen in Fig. 6, consumers can see exactly which claims of their chosen product are verified. Similarly, ‘Good On You’ is another website and application where consumers can check companies ‘sustainability rating’ (Good On You, 2020). Their ‘suitability rating’ is broken down to ‘Planet’, ‘People’, and ‘Animals’, along with a brief overview of companies’ sustainability initiatives (see Fig. 7). According to Good On You, they compile and analyse data from reliable indices (such as Fashion Transparency Index and CDP Climate Change), certifications/ accreditations (such as Fair Trade and the Global Organic Textile Standard), as well as companies’ own public reporting. They consider products’/companies’ entire supply chain by evaluating 500-plus data points to finalise companies’ sustainability rating and score (Good On You, 2020). As seen in Fig. 7, they translate the analysed data into easily understandable information and graphics for consumers to help them make more informed decisions when shopping, and to spot any companies that may be greenwashing. It is important to note that the tool recommended by Becker-Olsen and Potucek in 2013, Greenwashingindex.com, where consumers could rate and see the rating for companies’ green claims, is no longer available to use. However, as previously mentioned, new websites and tools such as ‘Good On You’ and ‘Compare Ethics’ have been introduced since. Hence, it could be argued that there is no guarantee that similar tools and websites that are currently available to use would be available in the future as well, meaning that whether these tools could offer consumers guidance in the long run remains unclear. In addition, to some extent, these third-party verification tools rely on companies’ own reports and information meaning they are
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Fig. 7 Good On You website (Good On You, n.d.)
potentially not entirely reliable. Lastly, the ratings given to companies are not regularly updated. For instance, on Good On You, some ratings have not been updated in over 2 years, which raises questions regarding the reliability of the ratings.
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Blockchain Technology and Product Passports
Blockchain technology is a new decentralised, peer-to-peer, open-access network for storing, sharing, and updating data (Upadhyay et al., 2021). Although it is currently in its nascent stages, it is a hot topic for research due to its potential to have a revolutionary impact on many industries (Upadhyay et al., 2021). One of its main impacts is predicted to be on supply chain management (Amed et al., 2021; Park & Li, 2021). In the context of sustainability in the fashion industry, blockchain can have a significant contribution as it can record, store, and update information along the supply chain, and make it accessible to all parties, including consumers (Choi & Luo, 2019; Park & Li, 2021; Upadhyay et al., 2021). It can enable companies to gather information regarding the entire supply chain which would be extremely valuable to them as mentioned in Sect. 2.2; the majority of companies currently do not have access to that information (KPMG, 2021). In addition, it can enable consumers to evaluate companies’ green claims (Park & Li, 2021) which could potentially resolve consumers’ greenwashing concerns and green scepticism. Currently, a limited number of fashion companies use blockchain technology to communicate their supply chain information with their consumers. For instance, Jyoti Fair Works, a German-based fashion company, has partnered with Retraced, a blockchain software to provide transparency of their supply chain for their customers (Banks-Louie, 2020). By scanning the QR codes on Jyoti Fair Works’s products via mobile phones, consumers can find information about the products’ entire journey throughout the supply chain. According to Retraced, consumers can ‘see instantly that the cotton was grown organically by a local farmer, processed without hazardous chemicals at a nearby textile factory, dyed using environmentally friendly plantbased extracts, and then woven into biodegradable fabrics, which are then cut, sewn, and embellished by a Fair-Trade artisan’ (Banks-Louie, 2020). Having data stored on products, for instance as QR codes as mentioned in the Jyoti Fair Works example, is referred to as ‘product passport’ and it is predicted to become mainstream in the coming years (Amed et al., 2021). According to The State of Fashion 2022 report by Amed et al. (2021), product passports ‘link information that is valuable to both consumers and partners to individual products by leveraging a combination of technologies centred around blockchain and supported by the likes of radio-frequency identification (RFID), QR codes and near-field communication (NFC)’ (p. 88). These technologies can not only help the fashion industry overcome issues regarding supply chain transparency but can also help tackle other issues such as counterfeiting in the luxury sector (Amed et al., 2021). However, in the report the authors argue that product passports are not a ‘silver-bullet solution’ (p. 88) as they rely on suppliers to provide accurate and sufficient data with companies, and companies with consumers. Additionally, their high cost has been a hindering factor in the technologies becoming mainstream; however, the authors argue that with the growing demand for transparency and adoption of sustainable practices in the industry, the high cost required for pilot studies and scaling these technologies is justified.
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Social Media Platforms
Word of mouth, i.e. verbal communication between consumers in a social setting, is a common way for consumers to exchange information about products’ environmental aspects (Zhang et al., 2018). Green word of mouth which refers to ‘the extent to which a consumer would inform others about positive environmental messages related to products and brands’ (Zhang et al., p. 741) has been found to be negatively impacted by greenwashing, which in return impacts purchase intention. Green word of mouth is becoming increasingly important, particularly after the emergence of social media; social media platforms, as forms of digital technologies, can help spread information widely and quickly (Jha & Verma, 2022; Zhang et al., 2018). In addition, they have become one of the main sources consumers obtain information about products/companies from (Chevalier, 2022), with 70% of users indicating that social media platforms help them decide what to buy (TikTok, 2021). Furthermore, it is argued that social media platforms are becoming increasingly effective in learning about sustainability issues (Eng et al., 2021), and as previously pointed out in Sect. 4, education is key in enabling consumers to spot greenwashing (Fernandes et al., 2020). Moreover, with the rise of influencers and social media accounts who create content centred around sustainability issues, companies who engage with greenwashing come under scrutiny and get publicly accused of it (Boulianne & Ohme, 2021; Delmas & Burbano, 2011). For instance, Fig. 8 shows a reel posted by ‘Remake our word’, a non-profit organisation which aims to help women who work in the fashion industry get paid fairly (Remakeourworld, 2022).
Fig. 8 Remake our world reel (Remakeourworld, 2021)
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Fig. 9 Fashion Roundtable post (Fashionroundtable, 2022b)
They have 135,000 followers on Instagram and use their platform to raise awareness regarding many issues in the fashion industry. As seen in Fig. 8, Remake our world have accused Boohoo, a fast fashion company, of greenwashing in their latest campaign, explained the reasons why they believe that to be the case, and have provided suggestions on what Boohoo can do to truly reduce their environmental impact (Remakeourworld, 2021). Another example is shown in Fig. 9 is an Instagram post by Fashion Roundtable, a non-profit organisation similar to Remake Our World, who have 10,100 followers on Instagram that create and share content about sustainability and ethical issues in the fashion industry (Fashionroundtable, 2022a). In a post shared in 2022, they not only call out Misguided, a fast fashion company, for not paying their suppliers but also encourage their followers to sign a petition to pressure the company into paying their suppliers (Fashionroundtable, 2022b).
5
Conclusion
Greenwashing has become extremely prevalent in the fashion industry as a result of consumers’ growing awareness of sustainability issues and demand for green products (Sailer et al., 2022). This is due to the fact that many fashion companies intentionally or unintentionally mislead their consumers into believing their company as a whole and/or products and services are greener than they actually are (Braga Junior et al., 2019; Rausch & Kopplin, 2021; Zhang et al., 2018).
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Although greenwashing should be strictly avoided as it has serious legal consequences, and negatively impacts all stakeholders, it is currently difficult for companies to completely avoid engaging with it (Munir & Mohan, 2022; Nguyen et al., 2019). This is due to the fact that certain terms that are commonly used in green marketing such as ‘sustainable’ and ‘green’ are understood differently by different people, and do not have a universally agreed on definition, meaning that green claims made using these terms are vague and misleading to consumers. Hence, it is imperative that further research is conducted on these terms, similar to the research currently being conducted on the term Net Zero as mentioned in Sect. 2.2, to understand how they are interpreted by consumers, and to provide a universally agreed on and accepted definition for them which will be valuable to both academia and the fashion industry. Another key reason why greenwashing could be difficult to avoid is that many companies lack transparency of their supply chains; hence, they cannot provide the evidence required to substantiate their green claims. Many industry experts believe that emerging digital technologies such as blockchain and product passports could potentially help resolve this issue and provide transparency of products’ supply chain to all stakeholders, including companies and consumers (Amed et al., 2021). However, these technologies are still not mainstream, and some are still in pilot stages (Amed et al., 2021); hence, it is imperative that research is conducted on them to understand how they are perceived by consumers and identify the optimum way of leveraging them to solve transparency issues across all industries, including fashion. Findings from this research would have significant contributions to academia as it could build on extant literature in marketing, psychology, and computer science realms such as technology acceptance model (Davis, 1989); it could offer valuable insights for various stakeholders in the industry such as fashion companies who currently do or wish to leverage these tools in the future, and technology companies who develop them. Lastly, education has been identified as an effective way of enabling consumers to spot greenwashing; hence, several guides and digital technologies have been developed to facilitate this. However, they all currently have limitations. One of their key drawbacks is that not all fashion companies are included on their platforms; for instance, only a small number of companies currently utilise blockchain technology to offer their consumers insight into their supply chain, and only a limited number of companies and products are included on third-party verification applications and websites. Hence, further research and development is required on these digital technologies to offer consumers more reliable resource. This gap identified in research could be used as a great starting point for the fashion industry to further develop existing or new tools and technologies.
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Modest Fashion and Sustainability: Research Trends by Bibliometric and Content Analysis Paolo Biancone, Valerio Brescia, and Michele Oppioli
Abstract
Modest fashion is a growing emerging market already developed in the leading Arab markets (the United Arab Emirates, Saudi Arabia, etc.) and growing in Europe (France, Germany, and UK) that will reach $484 billion in 2023. Modest fashion is one of the Islamic economy’s leading sectors, which is strongly influenced by the religious aspect. Despite this, there are few studies on the phenomenon and the trend. The study aims to identify the variables characterising modest fashion business models, highlighting the elements that support sustainability. The study is composed of two phases. In the first, the authors carry out a systematic analysis of the scientific literature; in the second step, the new variables and trends of the phenomenon are defined based on news articles and statements by professionals and companies in the sector identified through Nexis Uni. The study highlights a business model based on ethical principles that lead to an approach oriented more to the quality of the products than the quantity and use that the clothes should have. The business model recalls some typical elements of sustainability and fashion linked to messages of fairness and social justice, opportunities for female entrepreneurship and sustainable supply chain systems, environmental eco-fabrics, and zero-waste manufacturing techniques. The study is helpful for scholars and new entrepreneurs who can understand how to develop a new business model contaminating the world fashion markets.
P. Biancone · M. Oppioli Department of Management, University of Turin, Turin, Italy e-mail: [email protected]; [email protected] V. Brescia (✉) Department of Management, University of Turin, Turin, Italy Department of Finance, Wroclaw University of Economics, Wroclaw, Poland e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_7
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Keywords
Modest fashion · Business model · Sustainability · Islam · Fashion industry
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Introduction
Islamic law, called Šarī‘a (Shariah), covers all aspects of people’s lives through a Halal approach (Biancone et al., 2019). Halal is a Quranic word for everything that is allowed or permissible; in contrast, the Quran defines everything forbidden with the word Haram (Shah Alam & Mohamed Sayuti, 2011). These moral codes also have value from the perspective of clothes. Modest fashion (MF) refers to the clothing items allowed for Muslim people following the principles of the Quran (Radwan et al., 2019). MF clothing should be less tight-fitting and opaque than Western standards, particularly for women (AbdelAziz et al., 2021). MF covers different styles but solely conceals more of the contours of the human body (Rosenberg, 2019). The symbolic element of MF is the veil that covers the head, arms, body, and legs. The MF phenomenon is relevant because it meets the needs of Muslims, 24.1% of the world’s population, or 1.8 billion people (Bai, 2022). Thus, the business opportunities are extraordinary, and the Halal market has too high a profitability to be ignored by different stakeholders (Shah Alam & Mohamed Sayuti, 2011). The State of the Global Islamic Economy Report 2020/20211 attests that Muslim spending on clothing increased by 4.2% in 2019 to $277 billion. In 2020, it declined by 2.9% due to COVID-19. It is projected to grow by 2.4% between 2019 and 2024 to reach $311 billion. The growth of the Muslim population supports market expansion. According to Bai (2022), Muslims are growing rapidly worldwide, and in the coming decades, they will be the largest religious group on Earth. Moreover, the population group with the highest growth rate of Muslims is precisely amongst the under-30s, who are the ones most interested in MF (Hassan et al., 2019). Despite the high value of the MF market and a robust expansion of the Muslim population, few studies at the academic level address this research topic. The profitability, size, and growth of the MF market are relevant to such an extent that European fashion industry brands are also interested in this niche market. At the same time, it is also essential to investigate the MF phenomenon in connection with the sustainability of the business model. The fashion industry has been accused of taking limited responsibility for its behaviour concerning sustainability (Thorisdottir & Johannsdottir, 2019). Over the past two decades, numerous companies in the fashion industry have adopted a modus operandi called fast fashion. This approach is characterised by rapid acquisition of raw materials and fast disposal of homogeneous
1 https://www.salaamgateway.com/reports/state-of-the-global-islamic-economy-202021-reportenglish-executive-summary
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and standardised mass-produced items (Geissdoerfer et al., 2017). The downside of fast fashion is in terms of environmental, social, and economic sustainability. Numerous criticisms are inherent in the literature regarding the current business model of fashion industry companies. Current fashion industry business models— including that of fast fashion—are still linear, meaning it consists of “take, make, waste” (Thorisdottir & Johannsdottir, 2019). Instead, the fashion industry’s business model, like that of other sectors, should become a closed circular flow in which it is possible to regenerate the resources, inputs, waste, emissions, and energy losses used in the first production (Geissdoerfer et al., 2017; Massaro et al., 2021). New strategies require rethinking the product value chain by focusing more on product repair, recycling, and longevity; new materials; increased product flexibility; and supply chain innovations (Massaro et al., 2021). These new strategies involve changing and evolving the components of the business model in the fashion industry. Based on these premises, the study aims to identify the variables characterising MF business models, highlighting the elements that support sustainability. A bibliometric and content analysis (CA) was conducted to achieve the study’s aim. The authors identified the following research questions (RQs): RQ1: Does MF have elements of a business model oriented towards sustainability? RQ2: Does the vision of practitioners and professionals provide a sustainable business model in MF? The authors have divided the chapter into two phases. The first involves a systematic literature analysis following the steps identified by Zupic and Čater (2015) and a bibliometric analysis using R studio software with the biblioshiny package (Aria & Cuccurullo, 2017). The second phase of the chapter involves a CA (Krippendorff, 2018) using Leximancer software, which allows the definition of new trends and variables inherent in the evolution of the business model through the analysis of news articles and statements from companies and professionals identified through Nexis Uni (Massaro et al., 2021). Analysing scientific and professional articles can help reduce the gap between professionals and scholars on the same research topic. In particular, by analysing the research topic from different points of view, it is possible to contribute to the definition of the business model. Finally, the chapter is organised as follows. The next section covers an in-depth literature review on MF, sustainability, and the change in the business model of companies operating within the fashion industry. In the third section, the method used for the analysis is explored. In the fourth section, the research results are presented. Finally, the fifth section is the discussion and conclusion of the study, which also contains insights for future research.
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2
Theoretical Framework
2.1
Modest Fashion
The concept of modest fashion (MF) is derived from the Islamic religion, a monotheistic religion with one God, Allah, and one prophet, Muhammad (Radwan et al., 2019). Islamic law, called Shariah, consists of four primary sources: the Quran (Quran), Sunnah (Muhammad), Ijma’ (the consensus of the community of believers), and Qiyas (the legal analogy) (Ali & Ali, 1990). The purpose of Shariah is to cover the nudity of men and women whilst safeguarding the morality and protection of women. Shariah influences the actions and habits of Muslim people and thus also their manner of dress (Biancone & Radwan, 2015; Radwan et al., 2019). Qur’anic references are an integral part of the hijab and cover both sexes; however, there is a particular emphasis on female modesty (Ranathunga, 2018). Men are required to cover the area between the navel and the knee, whilst for women, the only exceptions are the face and hands (Radwan et al., 2019). The MF requires women to use looser, higher coverage, non-transparent garments (AbdelAziz et al., 2021). In agreement with Lewis (2017), this observance of clothing type can be seen as a social alibi for women who attend social settings where both genders are present. For women, dressing in clothes belonging to this niche allows them to reassure their family and those present there of their respectability. The term “modest” refers to various character traits such as loyalty, humility, timidity, and shyness (Ranathunga, 2018). Islamic law defines the hijab as a dress code that allows for women’s Awrah coverage (Radwan et al., 2019). Legitimate forms of dress for women vary by country primarily. Some examples of clothing allowed by the dress code in countries around the world are the Chador in Iran (Reece, 1996), the Burqua in Pakistan (Indarti & Peng, 2017), and the Jilbab in Egypt (Guindi, 1999). These listed types of clothing allowed by the hijab, combined with all the others, meet the needs of the Muslim population globally. These different types of dress have a common goal: respect for beliefs and customs, loyalty, purity, the superiority of men, group honour, and the legitimacy of children (Ranathunga, 2018). However, MF is not only influenced by religious aspects but also by sociocultural and political factors that have changed at present and in history (Lewis, 2007). Today, there is a growing academic and managerial interest in understanding the dynamics of the Halal, or Islamic economy. The “fashionable hijab” and MF have become an important research topic within fashion studies in Muslim-majority countries and countries with Muslim minorities, such as Europe and North America (Ranathunga, 2018). Believers in Islam are the second-largest religious group in the world, only after Christians (AbdelAziz et al., 2021). MF has been the largest and most visible segment of a current niche market in the past two decades (Lewis, 2019). The MF sector is one of the most promising in terms of expansion along with food and services (Radwan et al., 2019). According to Gateway (2022), the State of the Global Islamic Economy Report 2022 predicts that the MF market will grow by
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6.1% to reach US $375 billion in 2025. Like the rest of the fashion industry, MF has also been affected by the COVID-19 pandemic. However, even for MF, there has been a significant shift in sales towards e-commerce. Given the growth prospects of MF, several international firms such as Dolce & Gabbana, Tommy Hilfiger, and Zara are creating garment lines that follow MF principles (AbdelAziz et al., 2021; Radwan et al., 2019). In addition, due to its global relevance, the MF and fashion industry has recently heeded the call for sustainability and ethically sound production (McNeill & Moore, 2015). Indeed, in response to a global interest in sustainability and its related ethics, some companies in the fashion industry have begun to offer sustainable options in their product lines (Bray et al., 2011). Muslim consumer groups were once marginalised; instead, they are currently a group of young consumers with computer and digital skills, constantly connected globally, attentive to trends and fashions, and with a lifestyle that combines faith and modernity (Sandıkcı, 2018). Since 2013, numerous bloggers and modest brands have started to periodically cover the topic of MF on their communication channels, engaging more and more believers (Ranathunga, 2018). To follow this trend, the investments of companies operating in the MF have flowed into digitisation. In particular, some companies have launched their websites in other states, virtual versions of models, and use artificial intelligence to meet new consumer needs (Gateway, 2022). However, all these investments in the digital world should not suggest that physical shops have lost their importance. The physical channel should co-exist with the digital channel to enlarge the fashion spending of Muslim and non-Muslim people (Radwan et al., 2019). These two channels should follow consumer behaviour increasingly oriented towards ethical, sustainable, and inclusive procurement (Gateway, 2022).
2.2
Fashion Industry and Sustainability
The fashion industry market has a total estimated three trillion dollars, corresponding to 2% of the gross domestic product (GDP) globally (Thorisdottir & Johannsdottir, 2019). It is possible to divide the fashion industry into two macro-categories: slow and fast fashion. The former focuses on the quality of garments, textiles, and footwear (Thorisdottir & Johannsdottir, 2019). In contrast, the latter emphasises a modus operandi of rapid sourcing of raw materials and disposal of garments that have been mass-produced, standardised, and homogeneous at a low selling price (Todeschini et al., 2017). The main difference between slow and fast fashion is the time spent on the production process. In the former, it can take as long as 9 months from product conception until it is ready for consumption (Thorisdottir & Johannsdottir, 2019). In contrast, in fast fashion, new garment trends may be offered every 2 weeks inside clothing stores. In the past two decades, the fashion industry has been revolutionised by the fast fashion phenomenon. This revolution is due to a change in consumer needs, particularly amongst the younger generation, who increasingly demand low-cost clothing
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with a rapid change of styles in a short time (McNeill & Moore, 2015). Fast fashion encompasses the insatiable demand for novelty and an increase in the number of fashion seasons, as opposed to the traditional four (Barnes & Lea-Greenwood, 2006). Birtwistle and Moore (2007) state that consumers have low awareness of sustainable goods. At the same time, fast fashion, through its constant supply of new and more desirable goods, satisfies consumer needs (Bruce & Daly, 2006). Thus, consumers’ desire leads them to abandon the choice of more sustainable consumption (Morgan & Birtwistle, 2009). Accordingly, in this category of the fashion industry, sourcing, design, and production decisions are made with a focus on speed rather than sustainability (McNeill & Moore, 2015). These consumer demands result in a significant problem in the amount of clothing and fabrics thrown away each year. Because of these dynamics, the fashion industry, combined with the textile industry, is the world’s third most polluting industry (Gupta et al., 2019). However, to date, the phenomenon of the fashion paradox seems to be present. This phenomenon is defined by Black and Eckert (2010), who state that the importance of fast fashion on a global level has protected it from the criticism of pollution and spills. Other researchers add that the following fashion paradox has slowed down an industry movement towards ethical and sustainable practices (McNeill & Moore, 2015). The problem is not only environmental but also social. Most of these clothes’ production occurs in the world’s poorest countries, where workers’ rights are almost non-existent. In addition, consumer ethics in the fashion industry also play an important role. Ethical consumers can be defined as those who consider the wider impact of their consumption on other humans, animals, or the environment (McNeill & Moore, 2015). Consumer ethics has increased considerably recently (Connolly & Shaw, 2006). However, consumer beliefs about sustainable consumption often do not always translate into actions (Shaw & Riach, 2011). To date, several studies in the literature provide a better understanding of how the fashion industry integrates sustainability into its business models. There is a need to understand what drivers drive sustainability in fashion business models. The drivers identified by Thorisdottir and Johannsdottir (2019) are the company’s peer pressure, customer education, marketing strategies, process, product/service, raw material and waste, rewards, stakeholders, strategy, structure, and value creation. In particular, they can be divided into two categories of internal and external factors. Internal factors are financial pressure, ethical motivation, and ownership, whilst external factors are market pressure, social pressure, and peer pressure (Johannsdottir, 2015). In particular, sustainability drivers state that consumers’ purchasing behaviour changes when they know their responsibilities (Jung & Jin, 2016). To date, the entry of sustainability into the fashion industry is no longer a choice but a necessity (Gupta et al., 2019). It is increasingly required for designers to put the concept of a circular business model into practice, thus overcoming the current linear business model (Massaro et al., 2021).
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Evolution of Business Model
Given the relevance of the fashion industry market globally (Thorisdottir & Johannsdottir, 2019), the increase and interest of people towards MF (Gateway, 2022; Radwan et al., 2019), the importance of sustainability input given its environmental and social impact (Gupta et al., 2019), and consumer ethics (Connolly & Shaw, 2006; McNeill & Moore, 2015) it is appropriate to explore the topic of the business model. A business model is the set of strategic decisions determining how a firm generates a sustainable and successful enterprise (Cachon, 2020). Many theorists in the literature are in accord that business models exist to explain the way companies are creating value (Gockeln, 2014; Sosna et al., 2010). Following Todeschini et al. (2017), it is increasingly relevant that there is a change in the business model of companies operating within the fashion industry. The business model canvas is made with various purposes, including explaining, visualising, assessing, and the possibility of changing the business model of the company, so that the performance of the company is more optimal in the end (Ratnapuri et al., 2021). In addition, the business model canvas allows for a visual representation of the business model’s elements, the interconnections between the different sections, and the impacts on value creation (Joyce & Paquin, 2016). The canvas describes an organisation’s business model that is assigned to the four main areas of any business, namely customers, offer, infrastructure, and financial viability (Gockeln, 2014). According to Osterwalder and Pigneur (2010), it is possible to identify nine building blocks of the business model: customer segments, value proposition, channel, customer relationships, revenue streams, key resources, key activities, key partnerships, and cost structure. Using the business model canvas is appropriate to understand which parts of the business model will undergo the most significant changes (Ojasalo & Ojasalo, 2020). The business model canvas is the correct tool for this evolutionary analysis because it allows the exploration of possible innovations of the business model itself (Bocken et al., 2013). New socio-economic and cultural trends such as the shift to the circular economy and sharing economy, fair trade, and low consumption are changing traditional business models to avoid activities that harm the environment (Todeschini et al., 2017). In particular, these new trends involve mass production and sustainability as critical product design elements (Achtenhagen et al., 2013). In addition, another aspect that brings changes to current business models is a technological innovation in materials and garment manufacturing processes (Gockeln, 2014). Despite all these opportunities and evolutions, there is still much uncertainty, particularly in the literature, about how innovative business models should be structured in the fashion industry. Even in this sector, companies should evolve their business model by adapting to new external trends in order to maintain their competitive position (Demil & Lecocq, 2010; Osterwalder, 2004). Todeschini et al. (2017) identify some trends and drivers leading to innovative business models in the fashion industry. The five macro trends identified are consumer awareness, circular economy, corporate social responsibility, sharing economy and collaborative consumption, and technological innovation. All these aspects mentioned in the previous
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study can be traced back to sustainability. Through an evolution of the business model of companies operating in the fashion industry, it will be possible to pursue greater sustainability (Achtenhagen et al., 2013).
3
Methodology
The methodology used for the analysis performed within this chapter is structured as follows. The methodologies used are thematic analysis and CA. Thematic analysis was conducted through a structured literature review (SLR) with different search steps (Massaro et al., 2016). Amongst the possible methodologies of SLRs are bibliometric approaches that allow the analysis of certain variables. The variables used for a bibliometric analysis include authors, keywords, citations, and bibliography (Campra et al., 2021; Secinaro, Calandra, et al., 2020). The bibliometric analysis consists of five steps: (1) study design, (2) data collection, (3) data analysis, (4) data visualisation, and (5) data interpretation (Zupic & Čater, 2015). The steps of study design, data collection, and data analysis will be addressed in this section of the chapter. Steps (4) and (5) will be addressed in the results section. CA allows valid and replicable inferences to be made using texts (Krippendorff, 2018). CA is one of the most widely used qualitative techniques in research when the purpose is to analyse and deepen specific research streams (Massaro et al., 2021). The elements highlighted on the MF under discussion are analysed through the lens of the business model adopted in the fashion industry, considering the characteristic elements of sustainability.
3.1
Data Collection
The Scopus database was used to perform bibliometric and CA in the academic field. Following Massaro et al. (2016) and Secinaro, Brescia, et al. (2020), the authors used keywords as the search variable. The keyword identified on the Scopus database is “modest fashion”. The results returned by this search were 50 research studies. The following research step was to limit the search to only peer-reviewed scientific articles, limiting the search to only articles with scientific language and good quality (Kelly et al., 2014). In addition, the authors opted not to include a publication time limit in the search. The final sample consisted of 33 results. The second step of the five steps identified by Zupic and Čater (2015) ends with creating the .bib file containing all the results selected from the search. The next step, step (3) of data analysis, used the file created in the previous step on the open-source software R to perform the analysis. Specifically, the biblioshiny application package was used during this step to create graphs and tables (Aria & Cuccurullo, 2017). On the other hand, the Nexis Uni database was used to collect professional source documents. This database allows authors to consider new news articles rather than statements from companies and professionals. Using the word “modest fashion”
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within the software made it possible to retrieve data for use in the analysis phase (Massaro et al., 2021).
3.2
Data Analysis
To perform Zupic and Čater (2015) step (4) data analysis of bibliometric analysis, the open-source software R was used with the biblioshiny application. Leximancer software was used for CA on studies from practitioners and academic articles. Leximancer software allows lexical co-occurrence information to be transformed from natural language into semantic patterns unsupervised (Smith & Humphreys, 2006). There are two stages of information extraction; the first is semantic, whilst the second is relational. Both phases use static algorithms but employ non-linear, machine-learning dynamics.
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Results
Bibliometric analysis of articles in the literature allows authors to identify the main research topics and critical concepts discussed within academic sources and to find answers to the research questions highlighted above (RQ1–RQ2) by employing both qualitative and quantitative variables (Biancone et al., 2022). This section will feature two illustrations that will allow the authors to answer and explore the research questions. The first illustration will cover the descriptive statistics of the sample taken for analysis. The second illustration will delve into and show the most frequently used keywords within the studies in the literature. Again, to map the academic context, in addition to the bibliometric analysis, this section will also feature a CA conducted with Leximancer software on the selected articles on Scopus (33 Papers). The CA will identify the key elements identified in the literature regarding the business model of companies operating in MF and what elements of the business model will need to evolve to achieve greater sustainability. Turning to the practitioner side of the analysis, this section of the chapter features an illustration showing the key themes and their relationships inherent in the business model of companies operating in MF, also deepening sustainable aspects. In particular, in the last section of the study, a table (Table 3) summarising the elements that characterise the business model of companies operating in the MF sector was created.
4.1
Descriptive Bibliometric Analysis
This section discusses stage (5) of data interpretation identified by Zupic and Čater (2015), beginning with the descriptive analysis of bibliometrics conducted with R software, specifically the biblioshiny application (Aria & Cuccurullo, 2017).
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Table 1 highlights key information about the selected sample of articles on the Scopus database. The publication horizon covers more than 50 years, from 1970 until 2022. The papers in this sample included 33 studies. The sources on which these studies were published are 28, showing how there is no concentration on a few sources. The sharp increase in publications has occurred from 2015 onwards, except for a slight decrease in 2018. The increase in publications has occurred in tandem with the interest and relevance of the field. In fact, since 2015, the size of this niche market belonging to the fashion industry reached such a size that it was no longer possible to ignore. From 2015 onwards, the publication increase is also motivated by the adoption by all 193 UN member states of the 2030 Agenda for Sustainable Development (Azam et al., 2019). The peak of publications was reached in 2021, and the prospects for developing the topic in 2022 are also very interesting. There are 126 author’s keywords (DE), almost half of the keyword plus that the biblioshiny application identifies through artificial intelligence. Seventy-one authors are participating in this scientific production over time, with an average of 2.21 authors per paper in the sample.
Table 1 Descriptive bibliometric analysis
Description Main information about data Timespan Sources (journals, books, etc.) Documents Annual growth rate % Document average age Average citations per doc References Document contents Keywords plus (ID) Author’s keywords (DE) Authors Authors Authors of single-authored docs Authors collaboration Single-authored docs Co-authors per doc International co-authorships % Document types Article Source: Authors’ elaboration
Results 1970–2022 28 33 1.34 10.4 14.3 1611 215 126 71 12 13 2.21 15.15 33
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Author’s Keywords
This document section allows authors to drill down on the author’s keywords (Fig. 1) identified within the selected scientific output in the sample under analysis (Secinaro, Brescia, et al., 2020). From Fig. 1, the keywords “hijab”, “purchase intention”, “Islam”, and “Islam marketing” can be seen in larger font sizes and thus of greater relevance. For proper representation inherent to the topic at hand, the following keywords have been removed: “afdc program characteristics”, “abida Parveen”, “autobiography”, “afdc maximum aid”, and “drawing as a basis for painting and graphics”. The hijab is an Islamic dress code regulating the types of clothing allowed, particularly women’s (Radwan et al., 2019; Zaki et al., 2021). In the MF topic, this regulation is central because it demarcates the product’s characteristics to be sold to customers. Brands such as Dolce & Gabbana, Tommy Hilfiger, and Zara will need to understand these rules in detail to produce and provide clothing that is consonant with the needs of Muslims and the Islamic religion (AbdelAziz et al., 2021). “Purchase intention”, according to the study by Sumarliah et al. (2021) related to online shopping, is influenced by the following factors: fashion innovativeness, electronic innovativeness, perceived value, trust, attitude, and religiosity. These aspects are the same as those highlighted by Todeschini et al. (2017), such as technological innovation and consumer awareness. In connection with fashion innovativeness, it is possible to link the corporate social responsibility of companies and the circular economy. In addition, this study shows how Muslim people’s purchasing is influenced by religion and factors that influence purchasing in the Western world, such as fashion trends, perceived value, and trust towards that brand (Ranathunga, 2018). Papers in the literature highlight that a critical element of the business model is the customer (Todeschini et al., 2017). Businesses in the fashion industry should follow and meet the needs of this target customer, who is increasingly interested in sustainability (Thorisdottir & Johannsdottir, 2019). In particular, they should be able to follow the increased sensitivity to sustainability emerging in recent years amongst Muslim customers interested in the MF niche (McNeill & Moore, 2015). Fig. 1 Author’s keywords in modest fashion. Source: Authors’ elaboration using the bibliometrix R-package
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The keyword “Islam” is connected to the MF topic because it is the religion that influences and regulates the characteristics of clothing for men and women, for example, defining the body parts that can be kept uncovered, what types of clothing can be worn, and those that are forbidden. The keyword “Islamic marketing” is associated with marketers and stylists of different brands in the fashion industry who will have to create ad hoc campaigns for their target customers (Zaki et al., 2021). In particular, paying attention to the different types of clothing allowed according to culture and country. Furthermore, Zaki et al. (2021) state that within their business model, brands need to focus on their positioning through targeted communication strategies. Good positioning is also critical in communicating the initiatives and strategies implemented by brands to evolve their business model towards technological development and the circular economy (Thorisdottir & Johannsdottir, 2019; Todeschini et al., 2017).
4.3
Content Analysis of Academic Papers
This section aims to examine and explore the key themes that emerge from academic papers published on Scopus on the topic of MF. Using Leximancer software, was created Fig. 2. This figure shows the key themes in these studies and their relationships related to the MF topic. Specifically, the most relevant ones inherent to the business model are “cultural”, “market”, “online”, “customers”, “brand”, “loyalty”, “advertisements”, and “value”. The three key themes central to the illustration of CA (Fig. 2) are “cultural”, “market”, and “online”. Starting with “cultural”, following Kalliny and Ghanem (2009), it is possible to state that Islamic cultural values conveyed by advertisements are forces that shape consumers’ motivations, lifestyles, and purchase choices. Cultural values are defined as a set of customs and rules imposed by the previous generations of that place and the Islamic religion. All the rules imposed by the religion on how Muslims dress are included in the hijab (Radwan et al., 2019). Consequently, brands should understand the cultural and religious values of different societies to promote effective and appropriate advertising messages and hijab-consistent clothing (Pemberton & Takhar, 2021). The rules and garments for Muslim men and women may vary depending on the country of origin. An example of Muslim women may be Chador in Iran, whilst Burqua in Pakistan or Jilbab in Egypt (Guindi, 1999; Indarti & Peng, 2017; Reece, 1996). Turning to the second key theme, “market”, the MF market has been identified as an emerging segment within the fashion industry that presents specific opportunities and challenges for brands that want to become part of it (Slater & Demangeot, 2021). Indeed, the MF niche market, particularly that of Muslim women, is a target audience that cannot be ignored, given the substantial evolution in how Muslims dress (Shaari et al., 2021). Given the relevance of MF, in connection with the elements of the business model, it is crucial to analyse the relationship that is present in Fig. 2 between “market” and “online” and between “market” and “brand”
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Fig. 2 Key themes and their relationship in academic’s sources. Source: Authors’ elaboration using Leximancer
“Online” is a sales channel that enables brands to sell their apparel in the market. In particular, the online channel is the most used by brands operating in this niche market (AbdelAziz et al., 2021). Online channel refers to social media as an online sales platform and for customer-facing marketing communications. The most commonly used online channels are brand websites, social media such as Facebook and Instagram, and various third-party marketplaces. From the brands’ perspective, it is crucial to recognise the factors influencing customers’ intention to purchase modest clothing in the online channel. According to Sumarliah et al. (2021), the significant factors that influence customers’ purchase intention are buyer satisfaction, brand image, and trust. This will enable the brand to create appropriate sales strategies in the online channel. Advertising campaigns should be consistent with the cultural and religious values of Muslim customers interested in MF. The customer’s online experience affects their behaviour and engagement (AbdelAziz et al., 2021).
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“Customers” are the fourth key theme and relevant element of the business model of MF firms. In particular, customers are a central element of the business model because all brand actions aim to create a brand–customer relationship through their involvement and shared values (Zaki et al., 2021). In addition, customers’ needs and interests are evolving towards greater sustainability. Customers are increasingly sensitive to a change within the fashion industry to achieve greater environmental sustainability (Gupta et al., 2019). Consequently, brands will also need to be able to intercept and meet these new needs and values. Specifically, customers are looking for resource-conserving consumption, more efficient production with less impact on the environment, and careful management of the waste produced (Thorisdottir & Johannsdottir, 2019). The fifth key theme of this CA is “brand”. Following Zaki et al. (2021), it is possible to define a brand as a name, term, symbol, or sign that allows the goods or services of one seller to be identified from those of another seller. As is the case in the Western world of the fashion industry, in MF, it will be necessary for different companies to create excellent brand positioning and a relationship between the brand and customers. Particularly within MF, brands need to respect the concept of halal brand personality. Brands should convey purity, excitement, safety, sophistication, and righteousness to their customers (Zainudin et al., 2020). At the same time, brands must respect and communicate their sustainability actions, such as the development of a circular economy and the use of new technologies (Thorisdottir & Johannsdottir, 2019). All these elements are crucial for the brand to create a strong relationship with the customer and loyalty. “Loyalty”, in addition to being the sixth element of CA, is also a key element of the business model. In the case of MF, consumers will become loyal to a brand if it respects their religious values, culture, and their awareness of sustainability (Todeschini et al., 2017; Worthington et al., 2003). The benefits of brand loyalty are a reduction in price sensitivity on the part of the consumer, reduction in marketing costs, and attracting new consumers, and finally, consumers will be more likely to do word of mouth about the brand (Zainudin et al., 2020). One of the ways to create and maintain high customer engagement is “advertisement”, which is the seventh key theme of CA. Through advertising its products on different channels such as television, social media, and newspapers, the brand needs to be able to capture the attention of consumers (Aaker, 1997), and convey the quality of its products (Diamantopoulos et al., 2005), maintain a certain dynamism to trends, respect the religious aspects imposed by the hijab (Ahmad, 2015), and communicate the reduction of environmental impact (Todeschini et al., 2017). The eighth and final key element of CA is “value”. “Value” is the central element of the business model of all companies independent of the sector. Following Thorisdottir and Johannsdottir (2019), the business model canvas makes it possible to understand and visualise from which pillars the value created by the company is derived. The actions of marketing, advertising, loyalty, the online channel, and value sharing aim to bring value to the customer. The different building blocks will include different elements, whether the enterprise adopts a circular or linear business model (Thorisdottir & Johannsdottir, 2019). In particular, in the circular business model,
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there will be elements that allow for waste reduction to take care of the entire production process from conception to recycling or reuse.
4.4
Content Analysis of Practitioners’ Paper
This study section aims to analyse and explore the themes that emerge in practitioner journals. Specifically, through CA, it will be possible to identify the key concepts on the topic of MF and how they relate to each other (Massaro et al., 2021). Figure 3 shows the different concepts related to the MF topic. For example, the main concepts are “fashion”, “women”, “wear”, “brand”, “product”, “services”, “technology”, and “online”. These central concepts can be divided into four clusters: the first is fashion which includes “fashion” and “women”; the second is products which includes “wear” and “product”; the third is brands which includes “brand”; and finally, the fourth cluster technologies includes “technology”, “services”, and “online”. The first topic, “fashion”, is central to the relationships between the different topics in Fig. 3. For example, at flagship events in the fashion industry, increasingly, there are sections dedicated to the niche of MF. The goal is to bring MF to the attention of the fashion audience (Dhara, 2019; Shepherd, 2018). Another goal that can be pursued is to reach underserved consumers concerning hijab-consistent clothing (France-Presse, 2021). MF differs from other niches in the fashion industry because it has no seasonality and also follows religious rituals such as Ramadan, and consequently, the business model will have to be different from that of the fashion industry (Dewan, 2019). The second theme is “women”, a central topic within the MF because the rules of Islam and culture specifically define the clothes women can wear (Dewan, 2021). The first and second themes are well related in religious and cultural terms. Women who are most attractive to the aspects and expansion of MF are the younger and newer generations because they feel more involved in fashion trends (Ainley & Sinclair, 2017). In addition, another emerging theme concerning women is female entrepreneurship. More and more Muslim women under 40 are filling roles within the MF as designers, artists, and influencers (France-Presse, 2021; Ghana News Agency (GNA), 2019). The main focus of this category of women emerging from practitioners’ journals is entrepreneurship, inclusion, and ethical and sustainable practices (Dhiren, 2021). The entry of women in the MF will attract investment from the banking sector, given their sensitivity to social, economic, and environmental issues with particular reference to the pollution caused by the fashion industry (BR Research, 2018). Turning to the third theme, “wear”, as it could be understood, it is very much related to the two themes identified above because it is influenced by religion, the culture of that country, and the tastes of young Muslim women (Modanisa, 2017). “Wear” is very much connected to issues of sustainability. Since the end of the first decade, the fashion industry has increasingly started to approach sustainability aspects (Rehman, 2017). In particular, the main actions taken by brands concern an upcycling of products that have reached the end of their lives, the use of organic
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Fig. 3 Key themes and their relationship in practitioners’ sources. Source: Authors’ elaboration using Leximancer
fabrics and eco-friendly fibres for the production of clothes, the manufacture of eco-friendly furs, and a strong interest in slow fashion (Jennings, 2019). Increased efficiency is also brought about by new technologies that enable more efficient use of resources and the creation of new materials with lower environmental impact (Al-Sharif, 2018). All these aspects should allow brands to focus more on product
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quality at the expense of quantity (Textile articles, 2020). All these aspects can be traced back to those identified by Todeschini et al. (2017), who highlighted five macro trends in the business model of modest fashion companies. The fourth theme is “brand”, magazines talk about companies attracted to MF. Seeing the strong growth potential, different brands, even high fashion brands, are interested in providing products (Young, 2017). From the journals published in the practitioner world, some brands emerged that have entered the MF in the recent period, for example, Alberta Ferretti, Dolce & Gabbana, Nike, and Kayfi (Lewis, 2018). Brand positioning is relevant to differentiate from other competitors and should be consistent with the values the brand communicates and its products (Al-Sharif, 2018). In recent years, actions taken for sustainability have allowed brands to differentiate themselves from competitors (Malek, 2020). As customers are compassionate towards a sustainable lifestyle, actions of rethinking garment design use of natural, organic, and ethically sourced fabrics allow the brand to share sustainable values with customers (Mughal, 2021). Specifically, with regard to the aspects identified by Todeschini et al. (2017), these relate to technological development, the circular economy, and corporate social responsibility. The connection is direct with the fifth theme, “product”; that is, garments provided by companies should meet the needs of Muslim and non-Muslim customers (Shepherd, 2018). Specifically, products should both enjoy a brand that is well-positioned in the minds of consumers and have features that reflect design, sustainable, and ethical requirements demanded by Muslims (Dewan, 2019; Lewis, 2018). In particular, these aspects relate to those identified by Todeschini et al. (2017) for technological development, the circular economy, and corporate social responsibility. Apparel produced by companies can also be sold “online” through e-commerce platforms or on their company websites (May, 2019). E-commerce in all Middle Eastern countries, with a high concentration of Muslims, is growing tremendously. In particular, the Middle Eastern country with the highest e-commerce value is the United Arab Emirates, and its growth rate is also the highest (Mcarthur, 2018). This strong growth is also present in other countries, driven by the COVID-19 pandemic that has changed and is changing consumer buying habits (Modanisa, 2017). The theme of “product” is related to the “experience” that the brand should convey to the customer and the service that the brand provides at the purchase stage. The experience should be provided to customers through the physical, store, online, and marketplace (Ghana News Agency (GNA), 2019). “Services” offered by the brand may also not only be physical but through “technology” can be virtual or usable remotely. The technological development identified by Todeschini et al. (2017) refers not only to new production technologies but also to communication technologies (ICT). ICT has enabled innovations from the point of view of the functionality of apps designed to sell MF products, thus engaging customers more (The Times, 2021). At the same time, technologies have enabled a reduction in personnel costs, such as by automating e-commerce sites or a reduction in logistics costs through more efficient order management (Sherry, 2021). In addition,
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technologies have enabled the creation of virtual events organised by the brand for greater sharing of values with customers (The Times, 2021). As seen throughout the CA, each of the four clusters composed of different sub-elements seeks to evolve the current business model of companies in the fashion industry and MF towards a new paradigm of sustainability in this sector.
4.5
Characteristic Elements of the Business Model in Academia and Practitioners
In this section of the chapter, thanks to the bibliometric and CA conducted in the academic world and the CA carried out on the publications in the practitioner world, it is possible to note which elements of the business model emerged. Table 2 shows the connection between the emerging elements and the business model canvas sections. Table 2 includes amongst the building blocks the customer segment, channels, value propositions, key activities, key resources, and customer relationships. In contrast, revenue streams, key partnerships, and cost structure were not addressed.
Table 2 Key elements of the business model Building block of business model (Osterwalder & Pigneur, 2010) Customer segments Customer segments Customer segments Key activities Customer segments Customer segments Channels Customer segments Value propositions Customer relationship Key activities Customer relationship Customer segment Key Resources Value propositions Value propositions Key activities Key activities Source: Authors’ elaboration
Key elements Purchase intention Hijab Islam Islam marketing Cultural Market Online Customers Brand Loyalty Advertisement Value Fashion Women Wear Product Services Technology
Academic/practitioner Academic Academic Academic Academic Academic Academic Academic/Practitioner Academic Academic/Practitioner Academic Academic Academic Practitioner Practitioner Practitioner Practitioner Practitioner Practitioner
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Discussion and Conclusion
Using bibliometric analysis conducted on academic sources and CA conducted on both professional and academic sources, it is possible to define how the future business model of companies belonging to the MF should be structured. Taking up the framework of Osterwalder and Pigneur (2010), in this section, we will elaborate on the building blocks of a business model that have been addressed within the publications carried out in the literature and the world of academics (Table 2). From the building block of customer segments, academics show how focusing on hijab and cultures of different countries is crucial to proper segmentation within the MF (Radwan et al., 2019). In the literature, studies show how customers focus on low-consumption garment production and use a limited quantity of garments to adopt an approach favouring the conscious and moderate acquisition of goods (Todeschini et al., 2017). These characteristics push towards greater business model sustainability, moving away from the unsustainable dynamics of fast fashion and closer to those of slow fashion. In particular, it is possible to pursue these dynamics thanks to technological developments, the transition to a circular economy, and the focus on companies’ CSR (Todeschini et al., 2017) . On the practitioner side, the journals focus more on the subdivision of the fashion industry than on MF. In addition, it highlights some characteristics of this niche, such as the lack of seasonality (Shepherd, 2018). At the same time, these sources present how both sectors need to reduce their environmental, social, and economic impact (Sainul, 2018). These sustainability-related elements in this first building block of the business model canvas will be included in Table 3. This summary will also include the other building blocks discussed below. Turning to the value proposition, the opposite occurs to the previous building blocks. Practitioners focus considerably on this aspect of the business model by delving into wear, brand, and product issues (Alumona, 2020; Tenovici, 2017). In particular, these aspects are treated with a sustainability perspective, focusing on those actions that can make one’s clothing less environmentally impactful and how brands should make customers perceive and inform these activities. Publications from the academic world have branding in common with practitioners, whilst the other aspects are not present. In particular, the literature focuses on halal brand personality because brands should convey values such as purity, excitement, safety, sophistication, and righteousness to their customers (Zainudin et al., 2020). In addition to making clothing recognisable from competitors, the brand should be a conduit of communications regarding sustainability (McNeill & Moore, 2015). The third building block is the channels. In this case, practitioners and the world of literature deal with the topic following the same dynamics. Both worlds address the issue of online as a substantial opportunity for growth and expansion of sales in the Islamic world of MF’s products. The online channel consists of different possibilities such as the corporate website, social media such as Instagram and Facebook, or the different marketplaces of authorised retailers (Azuar, 2021; Sumarliah et al., 2021).
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Table 3 Variables characterising the business model of modest fashion companies Building block of business model (Osterwalder & Pigneur, 2010) Customer segments
Value proposition
Channels
Customer relationship
Revenue streams Key resources
Key activities
Key partners Cost structure
Variables characterising business model Muslims wearing hijab; people interested in sustainable aspects of MF; young Muslims interested in sustainability and technology Products that follow fashion respect sustainable aspects by reducing the environmental and social impact of the fashion industry. The transition from a linear to a circular economy Physical and online channels through websites, social media, virtual versions of models, and AI. The aim is to increase ethical, sustainable, and inclusive purchasing Respect religious aspects, share sustainable values, and use technology to improve environmental impact. Communicating trust and perceived value and brand positioning Variable not deepened, possible future research Muslim women, particularly female entrepreneurs, focus more on inclusive, ethical, and sustainable practices Production of sustainable clothes that follow slow fashion principles, with a focus on sourcing raw materials and production to reduce environmental, social, and economic impact. Transition to a circular business model. Advertising and marketing to share values in line with the target group. Customer engagement is both ex ante and ex post-purchase. Evolution of the supply chain Variable not deepened, possible future research Variable not deepened, possible future research
Source: Authors’ elaboration
Turning to the customer relationship block, as seen in Table 2, it is present only in the publications of academics. In the publications carried out in the literature, the topics mainly dealt with are those inherent in creating value for the customer and creating a loyalty relationship between the customer and the brand. Regarding sustainability, there should be a sharing of values on reducing the impact of the fashion industry and MF, perhaps even through awareness actions on the topic organised by the brand (Gupta et al., 2019). These actions aim to evolve their business model towards a greater focus on corporate social responsibility and the circular economy (Todeschini et al., 2017). In key resources, the topic is highlighted only in the practitioner world. The primary reference is women as a central element of entrepreneurship in MF. Women’s entrepreneurship will focus on the inclusion and application of ethical and sustainable practices (Alumona, 2020) compared to current practices carried out mainly by women.
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Finally, Osterwalder and Pigneur’s (2010) last building blocks addressed by the literature and practitioners are key activities. In the academic world, the key activities identified are advertising and Islam marketing that enable sharing of values consonant with religious, cultural aspects, and sustainability (Zaki et al., 2021). On the other hand, the aspects explored in depth by the journals concern: the services offered by companies to their customers, such as customer service and strong engagement throughout the product purchase phase; technologies used to engage customers more; technologies that enable the production of garments with a lower environmental impact (Fortune, 2018); the evolution of companies’ supply chains towards sustainability, including as a result of the threats and opportunities brought by the COVID-19 pandemic (Abubaker & WAM, 2020); and being a globalised market, the MF market, one should be careful not to implement the same marketing strategies or communication regarding sustainability in all the countries in which one operates (Daily Express, 2017). The elements highlighted in this last section are summarised in Table 3. Table 3 includes the variables of the business model canvas that emerge from the literature and the world of practitioners. The main focus of these elements in the different building blocks of the business model canvas is sustainability. In conclusion, the study made it possible to analyse the characteristic variables of MF’s business model and highlight the elements that support sustainability. Following Table 3, it is possible to subdivide the building blocks identified by Osterwalder and Pigneur (2010) into the categories of sustainability drivers identified in the literature by Thorisdottir and Johannsdottir (2019). The first building block, customer segments, can be linked to the diverse categories of “customer education”, “stakeholders”, “marketing strategies”, and “product/service”. Moving on to the value proposition is linkable to the driver “value creation”, “marketing strategies”, and “stakeholders”. Building blocks channel is in connection with “value creation”, “marketing strategies”, and “stakeholders”. Customer relationship is in connection with “customer education”, “company pressure”, “value creation”, “stakeholder”, “marketing strategies”, and “raw materials/waste”. The “key resources” building block is present in “process”, “value creation”, “structure”, and “product/service”. Finally, key activities are “customer education”, “marketing strategies”, “process”, “product/service”, “raw material/waste”, and “value creation”. The business model of companies operating in the MF niche is more relevant than the business models of other companies in the fashion industry because they have sustainability-oriented criteria. In particular, these recalled variables are consumer awareness, circular economy, corporate social responsibility, sharing economy and collaborative consumption, and technological innovation. The only variable of the above that has not been found in the literature and the world of practitioners is the sharing economy (Todeschini et al., 2017). Like other research in the literature, this study has some limitations. The first limitation is the sole use of the Scopus database, although it is recognised in the literature as one of the main databases in the field of interest. The second limitation of the search concerns using keywords to search for articles in the literature. Using
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specific keywords does not allow the study of holistic and all-inclusive subject matter. The same limitations also apply to CA. However, in academics, there is a gap in studies concerning the value proposition and key resources section. Whilst on the practitioner side, the gaps identified for Osterwalder and Pigneur (2010) business model canvas concern: customer segments and customer relationships. Consequently, the following gaps identified in the literature and practitioners’ side could also be used as future research questions. In addition, themes regarding the other building blocks such as revenue streams, cost structure, and key partnerships did not emerge from the content analysis. As a result, it might be interesting for future research questions to delve into the revenue and cost aspects of the MF.
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The Evolution of the Applications of Influencers for Fashion Brands on Social Media Liru Jiang, Gianpaolo Vignali, and Stephen Doyle
Abstract
The topic of social media influencers is widely discussed, especially in the fashion industry. Although many theoretical contributions in this area have been made in the past, new developments in influencer marketing are being studied based on new features in the recent world. This book chapter aims to clearly show the different academic understandings about ‘influencer’ and ‘social media influencer’ based on time order. In addition, by critically discussing social media influencers based on theoretical models (such as source models and market levels), academic contributions will be made to the understanding and use of those models based on the developing features of fashion social media influencers. The conceptual method (critical review) is employed in writing this book chapter. A conceptual method can contribute to a meaningful conclusion regarding the developments of social media influencer marketing; in addition, the critical literature review can link previous studies for getting a comprehensive understanding and figuring out the academic gaps. The literature of this chapter mainly includes four sections: definitions of social media influencer, theoretical models for measuring the effectiveness of social media influencers, the application of social media influencers for fashion brands, and opportunities/challenges for social media influencers. Keywords
Social media · Social media influencers · (Traditional) influencers · Fashion brands · Social media influencer marketing
L. Jiang (✉) · G. Vignali · S. Doyle Department of Materials, University of Manchester, Manchester, UK e-mail: [email protected]; [email protected]; [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_8
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Introduction
1.1
Context and Background
Social media marketing developed fast after the COVID pandemic (Dubbelink et al., 2021); in addition, the topic of social media influencer is popular in social media marketing studies (Brooks et al., 2021; Shan et al., 2020). Influencer marketing is changing over time, which is related to the application of influencers on new social media platforms, for example, TikTok (Mondalek, 2022). Furthermore, more than 4 billion dollars will be spent on influencer marketing in the USA, which is an explosive increase in the cost (Mondalek, 2022). However, from an international perspective, COVID-19 (Dubbelink et al., 2021) and some national policies such as ‘limiting the fan economy in China’ (BBC News, 2021) are leading to new challenges to fashion influencer marketing. Thus, it is obvious that although social media influencer marketing brings fashion brands great opportunities, challenges also need to be faced by brands to make themselves competitive in the rapidly changing global environment. Based on the research about influencer marketing for the fashion industry, in 2019, global fashion influencer marketing enjoyed a market size of 1.5 billion dollars, which will be increasing at 35.7% (compound annual growth rate) from 2020 to 2027 (Shin & Lee, 2021). This significant increase reveals the importance of social media influencer marketing for the fashion industry. All the analyses will be based on the definition and the background adapted from the relevant articles/books. The effectiveness of social media influencers can be understood based on different types of influencers, different social media platforms, and different brand market levels. Thus, a more comprehensive understanding of social media influencer marketing for fashion brands will be achieved. The detailed theoretical underpinnings and contribution will be introduced in next section.
1.2
Theoretical Underpinnings and Contribution
Social media influencer marketing for the fashion industry has been studied based on many theoretical aspects, such as social media fashion influencer and eWOM model (Shen, 2021), social media fashion influencers’ aesthetic labour and age (McFarlane & Samsioe, 2020), the motivations and consequent impacts for social media fashion influencers (Quelhas-Brito et al., 2020), and how social media fashion influencers impact consumers’ purchase intention (Chetioui et al., 2020). Although there is much recent research about social media influencer marketing for the fashion industry, different scholars used different typologies and definitions of influencer. In addition, the definitions of ‘social media influencer’, ‘celebrity’, ‘ambassador’, and ‘endorser’ vary in different studies (Wu, 2020), which leads to vagueness within this academic topic. Previous studies studied social media influencer based on different definitions and categories; their research results need to be reviewed for a more consistent understanding of influencers’ effectiveness. In addition, in different
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research, the social media platforms that are based on are different, some (Shen, 2021) are based on Microblog, and some (McFarlane & Samsioe, 2020) are based on Instagram. Those different social media platforms have different functions and features. A systematic and critical review of those functions mentioned in different research can contribute to the theory of purchase intention motivated by influencer marketing. A lack of this review may lead to vagueness in future citations about what makes an influencer marketing strategy effective. Therefore, the existing literature review is not consistent enough, lack of a comprehensive analysis may lead to vagueness in future research about social media fashion influencer marketing. This book chapter aims to create a social media influencer effectiveness model by reviewing the contributions to fashion brands promoted by those influencers. The objectives include introducing ‘social media influencer’ based on core time frames, introducing academic models for measuring the effectiveness of ‘social media influencers’ for brands, concluding applications of ‘social media influencers’ on different social media platforms, and identifying the opportunities/challenges for social media influencer marketing. In conclusion, the new model is based on different social media influencer definitions, types, platform functions, and fashion brand market levels. Thus, the model created in this chapter theoretically improves the previous influencer effectiveness models (introduced in Sect. 2.2) by including more factors (influencer definitions, types, platform functions, and market levels) rather than just the features of the influencer. In conclusion, this chapter will introduce the definitions and relevant theories, with the discussion pulling them all back to the theoretical underpinning and how the gap in knowledge is bridged.
1.3
Main Studies About Influencer and Social Media Influencer and Social Media Marketing from the 1990s
This section introduces the main studies about influencer and social media influencer marketing for fashion brands discussed in the literature review. Table 1 concludes the relevant research themes in time order. According to this table, before 2010, scholars talk about influencers from a broad perspective. In the following around 5 years after 2010, the studies about social media influencers are mainly at the exploring stage. With the development of social media and the Internet, after 2016, social media influencer became the main topic for ‘influencer’, and this topic became more popular after 2020. COVID-19 started influencing people’s lives by that time, offline activities became limited, and social media developed highly fast. In the following literature review section, more details about those researches are critically discussed.
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Table 1 Main research about influencer and social media influencer marketing for fashion brands discussed in the literature review section Author Schneider and Rodgers (1993) McGrath and Otnes (1995) Beaudoin et al. (1998) Engelland et al. (2001) Booth and Matic (2011) Ding et al. (2013) Langner et al. (2013) Lee and Watkins (2016) Abidin (2016) Khamis et al. (2017) Lou and Yuan (2019) Chetioui et al. (2020) Quelhas-Brito et al. (2020) Boerman (2020) McFarlane and Samsioe (2020) Shen (2021) Jin et al. (2021) Arsenyan and Mirowska (2021) Sun et al. (2021) Jansom and Pongsakornrungsilp (2021) Qian and Park (2021)
1.4
Research theme Influencers’ attitude to direct marketing Stranger influencers’ influence on retail The attitudes of fashion leaders and followers to domestic and external clothing How mavenship influences consumers’ evaluation of services How to identify social media influencers How to identify influencers on micro-blogging sites effectively Creating a conceptual model for social group influencers in the marketplace Vloggers’ influence on consumers’ impression of luxury fashion brand The labour of fashion influencers and followers on social media Self-branding for social media influencers Consumer trust caused by social media influencers Consumers’ attitudes to fashion influencers and purchase intention caused by fashion influencers Reasons for social media influencers’ posting information and relevant influences on those influencers The influence of social media disclosure on influencers with different quantities of followers 50+ (age) Instagram influencers’ posts creation eWOM for micro-influencers Comparison of the effectiveness of the posts made by brands and influencers on social media Social media users’ reactions to virtual influencers Classification of social media influencers and their influence on Generation Z Chinese luxury fashion consumers Millennial’s value perception and purchase intention to luxury sustainable fashion influenced by social media influencers The influence caused by a bad fit between influencers and luxury fashion brands
Research Method
The conceptual method (critical review) is employed in this book chapter. Relevant literature about influencer marketing is collected. The collected literature covers mainly who social media influencers are and what roles social media influencers play in the fashion industry. In terms of who social media influencers are, the definitions and typology made in the past are discussed first and then the theoretical models for measuring the effectiveness of social media influencers for brands are concluded.
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The theoretical models are introduced for understanding how social media influencers are defined and categorised. In terms of what roles social media influencers play in the fashion industry, the applications of social media influencers are discussed based on fashion brands of different market levels. This book chapter aims to create a model by reviewing the contributions (effectiveness) of fashion brands promoted by social media influencers. The articles about the effectiveness of social media influencers for fashion brands are critically concluded based on their different definitions and the different social media platforms. As a result, a relevant complete framework of the application of social media influencers in the fashion industry can be generated. In this framework, different social media influencers, the roles played by them, and how they adapt to fashion brands of different market levels are all included, which is original and meaningful.
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Literature Review
2.1
A Conclusion of the Development of ‘Influencer’ Based on Time Order and the Typology of Social Media Influencer
2.1.1 Definitions of Influencer and Social Media Influencer By reading this section, the readers will have a clear understanding of the difference amongst the definitions of ‘social media influencer’ stated by different scholars. These differences will be analysed based on time order, which is to clearly show the developing application of ‘influencer’ and ‘social media influencer’ for fashion brands. The differences between influencer, celebrity, and endorser are also mentioned in this section since some of their definitions are related according to scholars (Freberg et al., 2011). After the review of the definitions of influencer and social media influencer, a new definition of social media influencer is made in this section. Celebrity endorsement is a familiar and common marketing tool for communicating with the target audience (Schimmelpfennig, 2019). This has become an important strategic tool for fashion retailers to use (Vignali et al., 2010; Vignali & Vignali, 2009). Social media influencer marketing activities are slightly different from celebrity endorsement activities and have their features. According to Yesiloglu and Costello (2021), social media influencer marketing activities are based on the short term, whilst they are like celebrity endorsement in that the social media influencers are also paid for involving in those activities. However, social media influencer marketing is complicated in its forms because it is widely and freely used by different brands on social media (Yesiloglu & Costello, 2021). To clearly understand social media influencer marketing, the following form provides an introduction to the different definitions of influencer and social media influencer in time order. According to this table, before 2010, definitions of influencer tended to be based on broad society. The broad ‘influencer’ is also named as ‘prosumers’ in some research (McFarlane & Samsioe, 2020; Ritzer & Jurgenson, 2010); prosumer’s
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definition is ‘those consumers who actively do productive activities for getting or not getting paid’. According to those scholars, an influencer is a role between producer and consumer (ibid.). Additionally, an ‘influencer’ can be described as an ‘endorser’ (Lou & Yuan, 2019); endorser is an individual who makes use of being known by the public and shows consumer good in advertisement (ibid.). The different names of ‘influencer’ lead to further difficulty in studying influencer marketing. As a result, those different names should be also known by future researchers. From 2010 to 2015, much of the research related to ‘influencer’ was talking about social media influencers. After 2015, scholars are mainly talking about social media influencers; in addition, those scholars mention the difference between ‘celebrity’ and ‘influencer’, which is extremely different from the definitions in past research. However, some recent research is still using the definition of influencer made many years ago without explaining the reasons; for example, Shen (2021) adapted the definition made in 2013 by Brown and Fiorella. The differences amongst the definitions of ‘influencer’ over time ask scholars to pay attention to the definition used in specific research before citing the relevant research results; otherwise vagueness will be easily caused. Before the new definition of social media influencer is stated, the common and different features of the previous definitions are discussed in this paragraph. According to Table 2, the definitions of influencer are different even when they are stated in the same period. The main differences amongst the scholars are listed as follows. Some scholars believe that social media influencers need to have a great number of followers (Abidin, 2016; Jin et al., 2021; Lou & Yuan, 2019), but some scholars do not include followers as a requirement for being an influencer (Chetioui et al., 2020; Khamis et al., 2017; Levin, 2020; McFarlane & Samsioe, 2020); some scholars indicate that influencers are those who cooperate with brands or advertisers (Abidin, 2016; Khamis et al., 2017; Lou & Yuan, 2019; McFarlane & Samsioe, 2020; Uzunoğlu & Misci Kip, 2014), but some scholars do not consider this as a necessity in the definition (Chetioui et al., 2020; Jin et al., 2021; Langner et al., 2013; Levin, 2020; Uzunoğlu & Misci Kip, 2014). Some discuss the importance of how these relate to improving the online shopping experience (Chrimes et al., 2022; Idrees et al., 2020; Reid et al., 2016; Vignali et al., 2014; Vignali & Reid, 2014). Some scholars identify that an influencer needs to have expertise or attractiveness (Chetioui et al., 2020; Jin et al., 2021; Khamis et al., 2017; Lou & Yuan, 2019); however, some scholars state that individuals without expertise or attractiveness can still be an influencer (Abidin, 2016; Langner et al., 2013; Levin, 2020; Uzunoğlu & Misci Kip, 2014). Accordingly, different and common parts exist in the different definitions of social media influencers; to avoid being vague, this chapter identifies a new definition based on the critical review of the previous definitions. In this chapter, a new definition of social media influencer is created based on a combination of the one made by Chetioui et al. (2020) and the one made by Levin (2020); the new definition is social media influencers are innovators or early adopters, they do not have to be highly famous or have the expertise, and they consistently post their suggestions, ideas, advantages, and daily life based on their expertise or experience. This definition states the difference between social media
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Table 2 Definitions of ‘influencer’ (including social media influencer) in time order
Year Before 1995
Author Schneider and Rodgers (1993)
1995–2004
McGrath and Otnes (1995)
Beaudoin et al. (1998)
Martin and Bush (2000)
2005–2014
Engelland et al. (2001) Freberg et al. (2011) Booth and Matic (2011) Brown and Fiorella (2013) Langner et al. (2013)
Definition of influencer (including social media influencer) Influencer (market maven) is different from early adopter or opinion leader, since early adopter and opinion leader are focused on specific products, whilst influencers communicate general information (like shopping experience, shopping places, and different types of products) with other target audience Acquainted or unacquainted people who can provide 3 types of information: expertise, decision helper when one has no idea, and suggestions for making oneself have a better social image Fashion leaders who are more confident in their taste, early adopters, and more interested in fashion. They influence other consumers to know and buy new fashion products The consumption role model who can directly or indirectly influence the consumer’s purchasing attitude or behaviour. It can be family, friend, or celebrity Individuals who play the role of information sources for marketing A new independent third-party endorser that influences audiences’ attitudes on social media Those people who become continuously engaging with brands’ target audience on social media The third-party who influences the purchasing intentions of the consumers Individuals who have more influence on consumers within certain social groups
Key elements within the definition General information provider
Can be unacquainted; expertise; decision helper; suggestions for social image
Confident in taste; early adopter; interested in fashion; influence consumers’ fashion purchase
Family, friend, or celebrity who influences consumers’ purchase
Information sources for marketing Third-party; attitude; social media
Continuous engagement; social media
Third-party; purchase intention
More influence; social group
(continued)
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Table 2 (continued)
Year
2015–2022
Author Ding et al. (2013) Uzunoğlu and Misci Kip (2014) Abidin (2016)
Khamis et al. (2017)
Lou and Yuan (2019)
McFarlane and Samsioe (2020)
Chetioui et al. (2020)
Levin (2020)
Jin et al. (2021)
Definition of influencer (including social media influencer) Those who are interesting and have authority in a specific topic (s) on Microblog sites Opinion leaders who have many followers to communicate with Influencers are microcelebrities who attract lots of followers by posting their personal information (words and pictures) on social media, which are then used by advertisers Online micro-celebrity who gains attention on social networks, his/her trustworthiness is usually used in commercial activities Those people who have many followers, and design and post social media information which contributes to commercial brands based on their expertise in a certain area(s) A career of showing aesthetics through different skills on social media, and the items closely related to influencers conclude images, commercial sponsors, and hashtags on social media Social media influencers are opinion leaders who consistently post their suggestions, ideas, advantages, and daily life based on their expertise or experience Social media influencers are innovators or early adopters; they do not have to be extremely famous or have expertise Social media influencers are credible and attractive social media users who have a lot of followers; they are active and popular in one or more than one area (such as clothing and cosmetics)
Key elements within the definition Interesting; authority in specific topic(s) Followers
Followers; personal information; social media; advertisers
Attention; trustworthiness; commercial activities
Followers; expertise; design and post information; social media; commercial brands
Skills; social media; commercial sponsors
Personal information; expertise; experience
Innovator; early adopter; do not need to be famous or expert; social media Credible; attractive; social media; followers; active and popular in area(s)
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influencer and celebrity endorser; meanwhile, it admits that social media influencers are not necessarily always being controlled by brands/marketers. The reasons are as follows: Firstly, ‘influencer’ is a broad definition that appeared many years ago, whilst the ‘influencer’ mentioned nowadays is mainly about social media influencer. To avoid being vague, the previous definitions (Beaudoin et al., 1998; Engelland et al., 2001; Martin & Bush, 2000; McGrath & Otnes, 1995; Schneider & Rodgers, 1993) about the broad influencer are not used. Secondly, the consistent work nature of social media influencers is necessary to be shown in the definition; otherwise, anybody who posts product or brand information on social media even for only one time can be named as a social media influencer, which will lead to vagueness. Accordingly, the definitions made by Freberg et al. (2011), Brown and Fiorella (2013), Langner et al. (2013), Ding et al. (2013), Uzunoğlu and Misci Kip (2014), and Levin (2020) are not used; thirdly, social media influencers can be used by marketers; however, it is not a necessary factor for defining a social media influencer. Otherwise, those people who do not cooperate with brands but still influence social media users’ purchasing decisions consistently on social media will not be included. Accordingly, the definitions made by Abidin (2016) and Khamis et al. (2017) are not used. Fourthly, if people are possible to become social media influencers, they do not have to be experts and attractive; thus the definitions made by Jin et al. (2021) and McFarlane and Samsioe (2020) are not used. Fifthly, there is an ‘opinion leader’ shown in the definition made by Chetioui et al. (2020); this new item adds to the vagueness of the initial definition. In addition, the definitions made by Booth and Matic (2011) and Lou and Yuan (2019) are not complete enough. To conclude, the definition of social media influencer made by many scholars is not perfect; future studies need to be careful about defining ‘social media influencer’.
2.1.2 Typology of Social Media Influencer Like definitions of social media influencers, the classifications of social media influencers are different according to different scholars. To avoid being vague, traditional influencers and social media influencers are talked about in this section separately. When social media influencer is not the topic people are focusing on in the past, Engelland et al. (2001) stated that market mavens and opinion leaders were the two common types of ‘interpersonal influencers’. ‘Opinion leaders’ are those who influence others by their experience or expertise in a certain type of product, whilst ‘market mavens’ are those who influence others by general market information (ibid.). In addition, Wiedmann et al. (2010) state that fashion super spreaders, fashion experts, and friends who can offer helpful fashion information are the three main types of ‘social influencers’ in the fashion industry. Those classifications mentioned show that although scholars are similarly talking about ‘influencer’ in the fashion industry, those ‘influencers’ are studied from different perspectives, such as interpersonal influencer and social influencer, and those differences lead to different classifications of ‘fashion influencer’.
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As social media and technology develop, focuses are more on new types of fashion social media influencers. Boerman (2020) indicates that social media influencers can be divided into micro-influencers (less than 10,000 followers, maybe normal people who become famous online), meso-influencers (more than 10,000 but less than 1 million followers, maybe famous nationally, and full-time influencer), and macro-influencers (more than 1 million followers, maybe international celebrities). Social media influencers with more followers can be usually more effective in marketing activities (ibid.). Except for the typology of social media influencers based on followers’ number, there are other different types of classification based on the features of the social media influencer. Except for Engelland et al. (2001), Shen (2021) also mentions ‘market mavens’ in the typology of social media influencers. According to Shen (2021), social media influencers can be divided into ‘market mavens’, ‘brand adopters’, ‘product leaders’, and ‘occasion leaders’. ‘Market mavens’ are social media influencers who are so knowledgeable in fashion that they not only provide information to consumers but also provide information to other social media influencers; ‘brand adopters’ are social media influencers who tend to spread the latest brand and fashion news by using different branding strategies; ‘product leaders’ are social media influencers who provide suggestions and information about fashion and product rather than brands; ‘occasion leaders’ are social media influencers who give fashion suggestions related to occasions/situations (such as holiday, seasons, and places) (ibid.). This typology mentioned is based on the information posted by the social media influencer. The typology made by Shen (2021) is more detailed with the features brought by social media when compared to the typology made by Engelland et al. (2001). For example, opinion leaders are divided into product leaders and occasion leaders; additionally, brand adopters are included, since social media is closely related to timely news. However, Shen (2021) mentions that celebrities, micro-bloggers, industry consultants, and industry analysts are the typical ‘influencers’, whilst Lou and Yuan (2019) state that ‘celebrity’ is different from ‘social media influencer’, since ‘celebrity’ is famous on traditional media, whilst social media influencer used to be an ordinary human being who became famous online by posting information created by himself/herself. Similarly, Jin et al. (2021) indicate that celebrity endorsement is different from social media influencer marketing; the product or brand information posted by the social media influencers is more based on their views or daily life, rather than a highly formal endorsement. However, celebrity is included in social media influencers by Sun et al. (2021), who state that advertisers (specific product or service marketing communication), celebrities (traditional celebrities), opinion leaders (frequent and broad types of information), and friends/peers are the four main types of social media influencers. Accordingly, a ‘traditional celebrity’ is accepted as an ‘influencer’ by some scholars whilst there are different opinions. Recently, a new type of social media influencer starts being used by fashion brands: the virtual influencer. Arsenyan and Mirowska (2021) indicate that virtual influencer is a fictional character created through computers; they are designed similarly to or differently from real human beings. Virtual influencers are actively
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tried by many luxury fashion brands recently (Chitrakorn 2021b); however, they are still new and studied by few studies. To conclude, although the classifications of fashion social media influencers mentioned are different, having a comprehensive understanding of those different classifications can help scholars to make future research clearer by considering specific types of influencers. This helps scholars to avoid studying social media influencers without mentioning the differences amongst them.
2.2
Theoretical Models for Measuring the Effectiveness of Social Media Influencers for Brands
In this section, the theoretical models for measuring the effectiveness of social media influencers for brands are introduced and critically discussed. The chosen theoretical models are those that are used frequently in the social media influencer studies cited in this chapter. In addition, the models introduced in this section are commonly used in the fashion industry. According to Ohanian (1990), the source credibility model and source attractiveness model are the two main basic models for studying the effectiveness of celebrity endorsers and other different types of spokespersons. Accordingly, those two models are still applicable to social media influencers. Ohanian (1990) concludes that at the beginning, trustworthiness and expertise are two main elements of the source credibility model; trustworthiness means the degree of acceptance and confidence in the communicator and the message communicated, and expertise means being expert, experienced, skilled, knowledgeable, and qualified. On social media, source credibility refers to the source’s degree of being knowledgeable, trustworthy, and believable/credible (Zha et al., 2018). Although the source credibility scale made by Zha et al. (2018) is specifically designed for social media message creators, the difference between ‘trustworthy’ and ‘believable’ is not identified, which may lead to vagueness. In the new source credibility model created by Ohanian (1990), except for expertise and trustworthiness, attractiveness is also included. However, the research about travelling made by Yılmazdoğan et al. (2021) states that amongst the three factors within the source credibility model, the attractiveness of the social media influencer has no relation to the information receivers’ intention. As a result, the application of the source credibility model may differ when used for measuring celebrity endorsement effectiveness within different industries. The source attractiveness model indicates that the effectiveness of the communicator/message is closely related to the receivers’ perceived similarity (how the information receiver is similar to the source), familiarity (how the information receiver is familiar with the source), and likability (how the information receiver like the source based on the behaviour and physical attractiveness of the source) of the source (Ohanian, 1990). In the context of the source credibility scale made by Ohanian (1990), the scale for measuring attractiveness includes attractiveness, classiness, beauty, elegance, and sexiness. Frank and Mitsumoto (2021) mention that ‘likability’ can be divided into some more detailed scale items, for example, sex
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appeal, when studying a specific type of endorser (athlete endorser). Accordingly, the attractiveness of the endorser can drive positive effectiveness to the endorsement; however, the sub-dimensions within ‘attractiveness’ that may be important for specific types of endorsers need to be focused on. Although the source models (source credibility model and source attractiveness model) provide useful basic theories, they are not the only models for measuring source effectiveness. In addition, the source models still have their shortcomings. According to McCracken (1989), source models believe that when the credibility and attractiveness of the endorser are good, the effectiveness of the endorsement will be good; however, these two models ignore the product to be endorsed. ‘Product’ is the first basic item of the marketing mix; brands need to know what product their customers would like to choose, after which relevant marketing strategies can be made to satisfy customers’ needs (Berger-Grabner, 2021). Accordingly, making a celebrity endorsement strategy without considering the features of the product; instead, only thinking about the credibility and attractiveness of the endorser is risky. To solve this problem, the meaning transfer model was created by McCracken (1989) based on the source models. The meaning transfer model means that there are three stages where the meanings are transferred: the influence of culture on the celebrity (including the roles played by the celebrity) and then the meanings transferred from the celebrity to the product through the endorsement, after which the meanings are transferred from the product to the consumers in the consumption stage (ibid). The ‘meanings’ include both basic meanings and deeper meanings; basic meanings can be age, gender, weight, or height, and deeper meanings are lifestyle and personality (McCracken, 1989). Compared to famous traditional celebrities, many recent social media influencers may not be known to the broad target audience. As a result, the meanings of less-known social media influencers are not known to the broad audience, or these meanings may not be as clear as those of famous traditional celebrities. Another theoretical model is the match-up hypothesis concluded by Till and Busler (2000). According to this theory, the fit between the endorser and the product can increase the effectiveness of the endorser (ibid.). The research result by Till and Busler (2000) shows that the match in expertise is more effective than the match in physical attractiveness; however, that research is not based on the fashion industry. Bauer et al. (2022) indicate the limitation of the match-up hypothesis: the past applications of this model focus on the match between the endorser and the product/brand; however, the match between the endorser and the advertising message is ignored. For example, a celebrity endorser whose nature is warm is more suitable to show a symbolic advertising message whilst a celebrity whose nature is competitive is more suitable to show a utilitarian advertising message (ibid.). In addition to the ‘match’ between the endorser and the product, the endorser and the advertising message mentioned that there are other different types of ‘match’, such as the endorser and the consumers’ gender and the endorser and the consumers’ experience (Frank & Mitsumoto, 2021). To conclude, the ‘match’ can be various; it can be the match between the endorser and the product/brand/consumer/message, and it can also be the match of attractiveness/expertise; in addition, there can be many
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sub-dimensions within attractiveness/expertise, which depends on the specific industry type and the endorser type. Except for those typical models initially designed for measuring the effectiveness of celebrity endorsement, Lou and Yuan (2019) conclude a social media influencer value model. According to this model, informative value (product information that can satisfy consumers and make the product competitive), entertainment value (the ability of entertaining consumers), expertise, trustworthiness, attractiveness (physical attractiveness/likability), and similarity are the factors that influence trust in brand posts, brand awareness, and purchase intention (ibid.). Accordingly, the new social media influencer value model is like a combination of the source credibility model and source attractiveness model together with informative and entertainment value. From this perspective, the meaning transfer model and match-up hypothesis seem less important than source models for evaluating social media influencers. However, no scholar proves this; in addition, Voo Store cooperated with social media influencers to post the past-season product; this activity used the personality features of the social media influencers to build the brand rather than pushing the product shown in the post (Chitrakorn 2021a). As a result, the social media influencer value model should be used cautiously. In summary, the original theoretical models for measuring the effectiveness of social media influencers for the brands mentioned are being improved by the scholars as mentioned in this section. The examples include the application of those models that may differ in different industries, some new elements are added in some models, and the exceptions of the measurement of effectiveness are tested, and the match amongst different perspectives. With new types of social media influencers showing up, for example, virtual influencer, the previous models need to be improved to be more up-to-date. In the past, the influencers are mainly real human beings; thus, the credibility, trustworthiness, and attractiveness of the new virtual influencers may need to be studied further to be adaptable. In addition, those models are making up for each other’s shortcomings, and ignoring any of them may lead to limitations of the relevant research. Although social media influencer marketing is a relevant new academic area when compared to traditional celebrity endorsement, the theoretical models for measuring the effectiveness of celebrity endorsement models are still meaningful for studying social media influencers.
2.3
The Application of Social Media Influencers for Fashion Brands of Different Market Levels
2.3.1 Introduction to Market Levels in Fashion Industry Market levels are the factors to be considered during the applications of social media influencers in the fashion industry. In this section, the main market levels in the fashion industry are introduced. According to Waddell (2004), the fashion industry can be divided into different levels based on excellence, snobbery, and quality; those three levels can be named couture, ready-to-wear, and mass production. Couture is providing and making
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clothing to the individual customer; the product will be made according to the customer’s measurements and is handcrafted; different from couture, ready-towear is providing a lot of products to customers for selection with different sizes/ colours/styles directly in the shops (such as boutique, department store, or concession shop); compared to read-to-wear, mass production is less exclusively designed (ibid.). However, the difference between the definition of ready-to-wear and the definition of mass production stated by Waddell (2004) is vague to some degree since it is difficult to measure or define what ‘less exclusively designed’ is. Munasinghe et al. (2021) state a slightly different way of classification of market levels; they indicate that fashion brands can be divided into two big levels: haute couture and couture and ready-to-wear. Haute couture is more expensive than luxury ready-to-wear brands, and it provides made-to-order and made-to-measure products to individual customers; ready-to-wear includes high-end luxury market (accessible to much more customers compared to couture, the product is made in standard sizes rather than made-to-measure), middle market level (the price and design are located between high-end luxury market and mass market), and mass market (high street and value fashion). The classification of market levels made by Munasinghe et al. (2021) is based on design and price; in addition, this classification avoids the confusion of the difference between ready-to-wear and mass market when compared to that made by Waddell (2004). Aagerup (2011) concludes more ways for making classifications of market levels: classifying by company size or internationalisation degree; in addition, this scholar concludes a more detailed classification for fashion brands: budget market brands, off-price brands, moderate brands, brands of private label, contemporary brands, better brands, secondary line brands, bridge brands, designer brands, and couture. In this chapter, to avoid being vague amongst different market levels and to explain social media influencer marketing clearly and straightforwardly, the classification stated by Munasinghe et al. (2021) will be used. Additionally, since social media influencer marketing is mainly for influencing a broad target audience, haute couture and couture will not be focused on in this chapter. Thus, the application of social media influencers for fashion brands of different market levels will be discussed based on the three market levels (high-end luxury market, middle market, and mass market) within ready-to-wear.
2.3.2
The Application of Social Media Influencers for High-End Luxury Fashion Brands Social media influencer marketing is highly influential in the fashion industry; in China, luxury fashion consumers and young fashion consumers have a more obvious tendency to refer to social media influencers when they are making purchasing decisions (Qian & Park, 2021). Luxury fashion brands have their unique features in using social media influencers. According to Lee and Watkins (2016), the social media influencer posting luxury fashion product needs to be socially attractive (being socially similar to the target audience, and sharing similar social values), since this can motivate the target audience to buy the same luxury product to reach the same social status as the social media influencer. The effectiveness of social media influencer marketing is
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higher when the social media influencer is perceived as a friend of the target social media users (ibid.). Similarly, Jansom and Pongsakornrungsilp (2021) state that social media influencers’ social attractiveness is more important than physical attractiveness for luxury fashion brands in building customer relationships and motivating purchases. Except for similarities to target customers mentioned by Lee and Watkins (2016), social media influencers’ lifestyles and personalities are also included in social attractiveness by Jansom and Pongsakornrungsilp (2021). The studies by Lee and Watkins (2016) and Jansom and Pongsakornrungsilp (2021) both mention that customers’ purchase intention is one of the main aims for selecting socially attractive social media influencers. However, Sun et al. (2021) indicate that the main aim of social media marketing for luxury fashion brands is not selling a product; instead, it is building a luxurious brand feeling and image. In addition, luxury fashion brands need to differentiate themselves from non-luxury fashion brands (ibid.). This inconsistency is explained by Sun et al. (2021), who state that although the main aim of social media influencer marketing is not to sell products, the effects are related to increasing consumers’ purchasing intention. In addition to improving brand image, the application of social media influencers is also functional in providing important knowledge needed by the target consumers. According to Qian and Park (2021), when luxury fashion consumers are wondering what to buy, looking for fashion inspiration, or hoping to know more about unfamiliar luxury fashion brands, they are highly likely to find the information posted by social media influencers. Another important feature of luxury fashion social media influencer marketing is its potential risk: the poor fit between the social media influencer and the luxury fashion brand will lead to consumers’ bad impression of the brand and poor purchase intention (Qian & Park, 2021). Compared to non-luxury fashion brands, failure in choosing suitable key social media influencers for luxury fashion brands may lead to a higher risk of negative marketing results. To conclude, the main aim of social media influencer marketing for a luxury fashion brand is not for selling the product directly; instead, it is to build an attractive brand image for the target audience. In addition, social media influencers play the important role of introducing luxury fashion brands and luxury fashion products to the target audience; they provide interesting and abundant information and knowledge. As a result of those contributions, luxury fashion consumers’ brand awareness, purchase intention, and brand loyalty can be built gradually.
2.3.3
The Application of Social Media Influencers for Middle and Mass-Market Fashion Brands For middle and mass-market fashion brands, social media influencers are playing their unique and meaningful roles. According to Liu (2022), the credibility and attractiveness of social media influencers can increase fast fashion consumers’ purchase intention and impulse buying. The aims of social media influencer marketing for middle and mass-market fashion brands are different from luxury fashion brands. Luxury fashion product is usually bought less frequently; as a result, building a long-term relationship with
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consumers through social media influencers is less important for middle and mass fashion brands when compared to luxury fashion brands (Lee & Watkins, 2016). In addition, according to Sun et al. (2021), selling products is important for non-luxury fashion brands’ social media influencer marketing. As a result, the aim of social media influencer marketing for middle and mass-market fashion brands is more about selling products directly when compared with luxury fashion brands. The applications of social media influencers for middle and mass-market fashion brands have their features. Compared to luxury fashion brands, middle and mass market can relevantly show themselves more casually; thus, those brands of lower market levels are more active in using social media influencers through different channels from the early stage when luxury fashion brands were still exploring how to use social media properly (Sun et al., 2021). For example, live streaming is widely used by non-luxury fashion brands; social media influencers can communicate with the target audience and sell products directly through this channel. However, luxury fashion brands started to try this channel only 2 years ago in China (Wangyi Fashion, 2020). Like luxury fashion brands, middle and mass-market fashion brands are frequently using social media influencer marketing; the post is either motivated by brands or posted by social media influencers themselves in a voluntary way. However, little research studied the features and effectiveness of social media influencer marketing for the middle and mass markets. In addition, although the differences amongst fashion market levels are obvious and meaningful, many studies (Boerman, 2020; Lou & Yuan, 2019; McFarlane & Samsioe, 2020; Quelhas-Brito et al., 2020) have not mentioned this difference in their research about social media influencer marketing. Additionally, although some studies (Shen, 2021) mentioned luxury and affordable fashion brands, the scholar does not analyse the difference in the applications of social media influencers to those different market levels.
2.4
Advantages of Social Media Influencers and Future Challenges
The advantages and potential challenges caused by the influencers are necessary for understanding the effectiveness of social media influencer marketing for fashion brands. In this section, the advantages and future challenges of social media influencers are discussed. Many advantages can be brought by social media influencers for fashion brands; they are listed as follows. Firstly, social media influencer marketing is an economical marketing tool for fashion brands, since the social media influencers and even followers tend to actively express themselves with branding information whilst being little or even not paid for their labour (Abidin, 2016). This provides good opportunities for fashion brands to motivate and even guide relevant advertising activities economically and effectively. Secondly, social media influencers are likely to build close relationships with their followers, since their motivations include fashion interest and helping others with information (Lee & Watkins, 2016;
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Quelhas-Brito et al., 2020). Accordingly, the followers’ trust in social media influencers is a good opportunity for fashion brands to gain brand trust. Thirdly, social media influencer marketing can help to develop brands based on the various features of so many different individual influencers. For example, elder social media influencers (50 years old and over) have unique strengths in cooperating with brands on social media, their specific features, and target audiences are with great prospects (McFarlane & Samsioe, 2020). To conclude, social media influencers can bring the advantages of saving cost, broadly increasing brand awareness, effectively raising consumers’ purchase intention, providing the trustworthy information, gaining a positive brand image, transferring various meanings to brands/products, and targeting the correct audience. Challenges for social media influencer marketing are also very common in the marketing place. According to Shen (2021), cookie-cutter information and information with brand information posted by social media influencers can be much less effective, no matter how attractive or expert the social media influencer is. Accordingly, to attract and influence the target audience effectively, social media influencer marketing needs to be designed carefully, and the features of individual social media influencers need to be considered for making each post personalised. Except for individual differences of the social media influencers, the differences in social media platforms should also be considered and respected, since social media users tend to have different responses to those platforms based on their specific contents and forms (Lou & Yuan, 2019). Ignoring either the features of the individual social media influencer or the social media platform may be a waste of time and money. In addition, Boerman (2020) states that social media information tends to be gone through quickly by consumers; thus, low engagement tends to be an extremely common problem for social media influencer marketing. Except for the challenges that may be caused by the features of social media influencers and social media platforms themselves, the challenges that might be caused by policies should also be noticed. For example, new limitations or policy preferences regarding social media influencer marketing in China (BBC News, 2021) are changing the target audiences’ attitudes towards social media influencers, the product, and even the brand being endorsed. New advantages and challenges for social media influencer marketing for fashion brands will keep on showing up since the Internet and technology develop so quickly. Meanwhile, social media influencer marketing is still in the developing stage; some existing advantages might either be strengthened or disappear in the future.
3
Conclusion
A conclusion about the literature on social media influencers for fashion brands is made in this chapter. In this concluding section, the theoretical contribution and practical contribution are introduced separately; then the relevant academic gaps are identified in the final paragraph.
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Fig. 1 The new social media influencer effectiveness model for the fashion industry
This chapter academically contributes to social media influencer marketing. First, a new and clear definition of social media influencer is concluded based on previous definitions. Second, this book chapter creates a social media influencer effectiveness model, which is shown in Fig. 1. The new model theoretically contributes to the previous influencer effectiveness models by adding influencer definitions, types, platform functions, market levels, and relevant effectiveness. This model is created according to the literature reviewed in this chapter; it indicates that the positive effects and challenges can be caused by different social media influencers; Meanwhile, this connection can be influenced by the social media platform types and fashion brand market levels. In addition, fashion brands will have a clear map about how and why to use social media influencers by reading this chapter. By understanding the definitions and typologies of social media influencers, fashion brands can find the proper social media influencer that is more suitable for advertising their brands or product. In addition, the theoretical models for evaluating social media influencer marketing effectiveness and market levels help fashion brands use the correct social media influencers correctly and effectively. The advantages and challenges listed in this chapter can also help fashion brands to develop themselves wisely as social media develops. In the final part, relevant academic gaps are identified as follows: Firstly, social media influencer types, especially the new types of social media influencers, are not mentioned in some past research (e.g. Jin et al., 2021); however, according to models of measuring the effectiveness of social media influencer marketing, social media influencers are highly different based on their features. As a result, investigating different types of social media influencers may lead to different results from the past research, even though the research aim is the same. Secondly, fashion market levels are ignored in some research (e.g. McFarlane & Samsioe, 2020); different main marketing aims and product features of fashion brands of different market levels may ask for different social media influencer marketing strategies. Although some
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scholars (e.g. Jin et al., 2021) mention the difference in social media influencer marketing that may be caused by market levels, no comparison amongst the different levels is made. Thirdly, there is little research on social media influencer marketing for middle or mass-market-level fashion brands. Fourthly, except for being classified by market levels, fashion brands are quite different in styles and brand images; for example, some brands are elegant whilst some brands are wild; few studies have mentioned this difference, and as a result, the features of their different target audience are ignored. Fifthly, scholars (e.g. McFarlane & Samsioe, 2020; Shen, 2021) tend to study social media influencer marketing based on only one social media platform; however, the target audience features and platform features of different social media platforms are highly different; however, there is little research on those differences and their influences on the effectiveness of social media influencer marketing for the fashion industry. What is more, virtual influencers have been little studied by researchers; they are not real human beings. As a result, the previous theoretical models, for example, source models and meaning transfer models, might not be well applicable to the new types of social media influencers created based on new technology.
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Reuse of Pre-Loved Garments: Pain or Gain? Songyi Yan, Claudia E. Henninger, and Taylor Brydges
Abstract
This chapter provides insights into pre-loved garments and their reuse, by further evaluating whether this could be considered a pain or gain within the current economy. The chapter starts off by exploring why the pre-loved market is important, before exploring issues surrounding terminology of ‘pre-loved’, ‘pre-owned’, and ‘second-hand’. It finally moves on to outlining benefits and drawbacks of reuse and further highlighting examples of what is currently happening within the industry to actively encourage reuse and prevent landfilling of garments. Keywords
Pre-loved · Second-hand · Waste · EPR · Recycling · Waste hierarchy
1
Introduction
One of the key questions addressed and discussed within this chapter is: what happens to garments when they are no longer loved? Although it should be a very simple and straightforward task to answer this question, it is not as easy as it may look. A few decades ago, the solution may have been ‘make-do-and-mend’, as S. Yan (✉) · C. E. Henninger Department of Materials, The University of Manchester, Manchester, UK e-mail: [email protected]; [email protected] T. Brydges Institute for Sustainable Futures, University of Technology Sydney, Sydney, Australia Centre for Urban Environments, University of Toronto Mississauga, Mississauga, Canada e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_9
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resources, especially after World War II, were limited and garments were not readily available to buy (The National Archives, 2022). Thus, people had to make do with what they had and repair and reuse items and learn valuable skills to enable them to participate in this practice (Williams & Shaw, 2017). Fast forwarding to the twentyfirst century, digitalisation has enabled not only mass production of fashion garments, often referred to as fast fashion or throw-away culture (Blazquez Cano et al., 2020; Mukendi et al., 2020), but also people (or better consumers) no longer see the need to repair and/or reuse garments, as new ones can be acquired at a very low price. Although make-do-and-mend skills used to be commonplace in the past and something that has been practised as part of social events, in today’s society, in which, especially young people are increasingly time pressured, these skills (pre-COVID) are no longer practised as regularly as they once were (Ethical Gear, 2017; West et al., 2021). Yet, as alluded to, the COVID-19 pandemic has changed things again, in that there was a shift towards more consumers starting to join the doit-yourself movement and increasingly learn skills, such as knitting, sewing, and crocheting, allowing them to do increasingly more mending work themselves (Lewis-Hammond, 2014; Iran et al., 2022; Vladimirova et al., 2022). What becomes apparent is the fact that the question posed earlier is quite loaded, in that it highlights key issues that the fashion industry is facing. The fashion industry has been criticised for its unsustainable practices (Henninger et al., 2016; Mukendi et al., 2020; Dottle & Gu, 2022), with the fast fashion phenomenon having fostered a take-make-dispose paradigm, which has led to a waste problem (e.g. Beall, 2020; Brydges et al., 2022a, 2022b). This is also what is alluded to within the title, outlining that pre-loved fashion can be a gain, in that it extends the useful life of garments, but also a pain, when it is equated to waste. These aspects are further addressed in the remainder of the chapter. To provide more explicit examples, within the European Union 1 textile, including fashion consumption, has been recognised as the fourth most polluting lifestyle domain, after household energy use, mobility, and food (EEA, 2019; Vladimirova et al., 2022), with the UK leading the league table of not only clothing consumption but also as the fourth-largest contributor of textile waste (Labfresh, 2022). On the other side of the globe disturbing news headlines are emerging, such as ‘Chile’s Atacama Desert becomes a dumping ground for fast fashion leftovers’ (Glover, 2021) or news from Ghana outlining: ‘it’s the dirty secret behind the world’s fashion addiction. Many of the clothes we donate to charity end up dumped in landfill, creating an environmental catastrophe on the other side of the world’ (Besser, 2021). Could it be possible that the answer to the posed question is that garments are discarded in remote parts of the world, causing environmental hazards? This would be rather disturbing, and yet, it is clearly happening. But what can be done to avoid this from continuously happening in the future? And whose responsibility is it to ensure that not only countries are protected from being dumping grounds, but also
1
Here referred to as the EU 27, which includes the UK.
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the environment from these hazards? Is it consumers, businesses, manufacturers, suppliers, governments, or any of the other stakeholders? At this time, it is beneficial to pause here for a minute to digest this information and reflect on it, as the answers to these questions are not simple yes or no ones, but, similarly to fashion supply chains, are rather long and complex. Whilst within this book chapter not all questions can be addressed and/or answers provided to them, key issues are alluded to, and thus, spark debate as to how these may be challenged and/or looked at in the future. In a very simplistic manner, the answer as to what should happen to our pre-loved garments is: they should not even become pre-loved, but rather, this should be prevented in the first place. Yet, this may not always be possible, as humans are changing shape and sizes on a regular basis. As a second option, the focus for garments that are no longer wanted should be on reuse, and thus, allowing garments to gain a second, third, fourth, or even more life, prior to no longer being fit for purpose. The way to extend the useful life of garments is by, for example, donating them to charity shops, swapping them at swap events or amongst friends/family, or reselling these clothes on platforms, provided they are still in good condition. Engaging in this resume practice aligns with DEFRA’s (2011) Waste Hierarchy, which indicates that the top priority should be waste prevention, yet if this is not possible, it should ideally be reused, which also falls within the philosophy of the circular economy. The latter seeks to circulate raw materials for as long as possible prior to discarding it and ideally avoid waste altogether (EMF, 2017; Geissdoerfer et al., 2017; Brydges et al., 2022a). In returning to the Waste Hierarchy, if, here, garments can no longer be reused, they should be recycled—although out of scope of this book chapter, it needs to be highlighted that recycling is not always a possibility, as currently mixed fibres cannot be fully separated (e.g. Brydges et al., 2022a). In the case of garments neither being fit for reuse nor recycling, other recovery methods should be used, with the last option being disposal (DEFRA, 2011). The latter, disposal, should be the last resort and avoided at all costs, as disposing of garments can be very problematic, due to most garments being made from man-made fibres, often being synthetic ones (Bryce, 2021) that either take a very long time to biodegrade or never biodegrade at all (Yan et al., 2020). Looking at the different options available within the Waste Hierarchy (DEFRA, 2011: 1) (prevention, preparing for reuse, recycling, other recovery, disposal), consumers can not only play a key part in determining what will happen to our pre-loved garments but also foster a positive environmental impact, by keeping these in use for longer. To reiterate this point further, according to the EAC (2019) reusing and repairing of pre-owned and pre-loved clothing have been widely recognised as solutions to the fashion industry’s sustainability problem as extending the life of clothing by an extra nine months could reduce carbon, waste, and water footprints by around 20–30% each. What must be highlighted here, however, is that the responsibility should not be on the consumer alone—but rather there should be a balanced approach in which every stakeholder takes action and responsibilities of their own behaviour.
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Table 1 Selective statistics on annual garment disposal per person Country Australia USA EU UK Canada
Disposed kg of garments per year 12.1 37 11 30 37
References MRA (2021) Beall (2020) European Parliament (2022) WRAP (2020) Webb (2021)
Over the past decade, there has been an exponential growth of the pre-loved (second-hand) market globally. In 2021, the global worth of this market segment was $96 billion, and it is estimated to reach $218 billion in 2026 (Statista, 2022). (Within this chapter pre-loved as opposed to second-hand fashion is used, which will be further explored in Sect. 2.) The predicted increase in market value of this market segment highlights that consumers are embracing not necessarily having to purchase garments first-hand, but rather also look for alternative options, including pre-loved garments. Table 1 provides some insights into how many garments are discarded annually, which has seen a steep rise, especially since COVID-19, during which decluttering became a key activity (Vladimirova et al., 2022). Understanding how many garments are discarded is important, as this could provide an opportunity to ensure they are re-circulated, and thus, stopping them from ending up in landfill. Although the increase in pre-loved clothing consumption may initially be seen as a positive, as there is a potential to reduce the environmental impact garments can have, there are also some negative consequences. Not all pre-loved garments can be resold within the Western hemisphere. This aspect has received attention in recent years, in that unsold goods from Western, developed countries are increasingly flooding developing countries, which can have a negative impact on the local economy of developing countries, with fashion entrepreneurs and businesses unable to compete with the cheaper alternatives, as well as serious questions regarding local capacity to recycle these garments (Besser, 2021). Other negative consequences were also alluded to earlier, with fast fashion waste ending up in remote locations and polluting the environment (Glover, 2021). More impacts will be further discussed in Sect. 3. Linking to the original question posed in this book chapter on what happens to our garments when we no longer love them, we firstly focus on how ‘pre-loved’ garments have been discussed (terminology), before providing some examples of how different countries are addressing issues surrounding pre-loved garments.
2
Terminology
Within the literature different terms are used to describe the ‘second-hand phenomenon’. For example, terms that are often interchangeably used are second-hand, pre-loved, or pre-owned garments. A key commonality between the terms is that
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they all describe garments that have been used at least by one person, and this person has decided that the garment has reached their useful life for them. Within the context of the clothes swapping phenomenon, Henninger et al. (2019) have outlined what may happen to garments after purchase, and once they become ‘pre-loved’. Although their research specifically focused on clothes swapping rather than generally ‘second-hand consumption’, they provide an overview of different consumption cycle options, in that garments that are no longer wanted by one person could be sold, swapped, donated, given away to friends (hand-me-downs), up- or recycled, introduced into take-back schemes, or landfilled (Henninger et al., 2019: 337). What is apparent from here is that garments can not only go through multiple cycles, but also a variety of different ones (e.g. swapped and then resold, handed down before swapped, etc.), before being landfilled. Depending on the quality of the garment, they may become what is referred to as second-hand, pre-loved, or pre-owned. And although these three terms are interchangeable and similar in nature, there are differences in terms of the perceived meaning and subsequent associated connotation of the terms that are used. For example, the term ‘second-hand’ consumption is linked to different meanings across a variety of demographics and financial backgrounds, from positive connotations such as sustainable lifestyles, treasure hunting, or nostalgia seeking, to negative connotations that are mostly associated with the garments’ materials, which are seen as waste and, thus, being of inferior quality (Turunen & LeipämaaLeskinen, 2015; Sung et al., 2020; Alevizou et al., 2021). As alluded to earlier, within this chapter the term pre-loved was consciously chosen as opposed to secondhand fashion, for various reasons: Firstly, second-hand can be seen as misleading, as garments could change owners multiple times over their useful life, and as such they may be third-, fourth-, fifths-, or n-th hand (Henninger et al., 2019; Veerman, 2019). Secondly, culturally ‘second-hand’ garments can have negative connotations and, thus, may not be socially acceptable (Henninger et al., 2019). For example, in Germany second-hand items remain stigmatised in that they are associated with lower social class status. Unlike in countries such as the UK, in Germany secondhand stores are not part of the high street landscape, but rather in slightly more ‘remote’ locations and predominantly situated in the outskirts of big cities (e.g. Henninger et al., 2019). As fast fashion is making garments affordable, there is often no incentive for consumers to engage in second-hand consumption, which implies that breaking down stigma may be harder. Moreover, Steffen (2017) points out that the reason for German consumers to engage in second-hand consumption may vary from being a lifestyle choice, to being forced to engage due to limited financial capabilities, which implies that we may see a change in attitude in the future. A further example is China where the consumption of second-hand previously was a taboo, as wearing someone’s clothes who is no longer here is seen as a bad omen and bad luck (Lin, 2015; Bargeron, 2021), although, according to Minter (2021), this may no longer be an issue, as ‘China’s second-hand business is booming’, including second-hand garments. Thus, whilst stigmatisation and bad luck have in the past acted as key barriers to engaging with second-hand
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consumption, as the examples of Germany and China highlight, we may soon see a change in consumer behaviour, whereby these barriers are broken down and secondhand consumption becomes increasingly a ‘new normal’. To come back to an earlier point made in connection with fast fashion being more affordable and also coming at a cheap price point, one of the key criticisms is the low quality with which these garments are produced (WRAP, 2019; Blazquez Cano et al., 2020). As such, there may be a challenge when it comes to ‘reuse’ and ‘recycling’, as products that are described as low quality are subsequently of low value also. Currently, second-hand fashion that can be found in stores can be classified either as ‘second-hand’ or vintage. Second-hand as indicated previously encompasses any garment that has previously been owned, whether it has been actually worn or if it is brand new. Vintage on the other hand describes garments that were produced between the 1920s to the 1990s (Ryding et al., 2018b; Kane, 2019). Often vintage clothing is seen to be of higher quality (Shuck, 2019), which is also one of the reasons why some luxury brands now seek to buy-back their vintage clothing to create new collections (Henninger et al., 2022). Whilst newer secondhand garments could be of lower quality, depending on the brand and make, and therefore be described as inferior, this is not true for all second-hand items, and as such, second-hand could become a viable alternative to fast fashion consumption that is not only cheaper but also of higher quality (Cervellon et al., 2012; Carrigan et al., 2013; Joung & Park-Poaps, 2013; Ryding et al., 2019). To overcome some of the barriers mentioned with ‘second-hand’, we increasingly see the use of terms, such as ‘pre-owned’ or ‘pre-loved’. The former (pre-owned) encompasses all garments that were previously owned and/or worn by a consumer (Veerman, 2019), yet may also have a lightly tainted meaning, as not everyone is comfortable to wear items that have been owned previously (Turunen & LeipämaaLeskinen, 2015; Ryding et al., 2018; Veerman, 2019). The latter (pre-loved) may arguably have the most positive connotation, as it includes the word ‘love’ and is often connected to the feelings and experiences of authenticity and nostalgia, especially in the pre-loved luxury context (Turunen & Leipämaa-Leskinen, 2015; Battle et al., 2018). Describing an item as being ‘loved’ also indicates that it has been cared for and should be treasured.
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Positive and Negative Impacts of Pre-Loved Garments: The Pain or Gain of Reusing
As alluded to, stigma is slowly broken down in different country contexts, which coincides with seeing a change in consumer behaviour to more actively engage in the consumption of pre-loved garments, which can be evidenced by the economic worth of this market segment. According to Statista (2022) globally this market segment is worth $96 billion and estimated to reach $218 billion by 2026, thereby growing 11 times faster than first-hand or traditional retail (De Klerk, 2021). With the increased worth and interest in the pre-loved market, it may not be surprising that various opportunities have developed, including but not limited to new business
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Table 2 Snapshot of textile waste by country 2008–2018 (adapted from Morley et al., 2009; WRAP, 2020; CBI, 2021) Country Germany Poland France UK EU27
Textile Waste 2008 (tones) 212,632 83,578 391,050 523,000 2,140,000
Textile Waste 2018 (tons) 338,342 131,985 238,999 620,000 2,170,000
opportunities to collect and sort textiles and garments. New business opportunities also imply the creation of jobs. Authors (Hansen, 2000; Mhango & Niehm, 2005; Ryding et al., 2018) have highlighted that jobs in collecting, sorting, recycling, and reusing have seen an acceleration in recent years, especially within the developed countries. This may not come as a surprise, as textile waste has also increased over the past few decades. Table 2 provides some insights into textile waste generation over a 10 year period between 2008 and 2018.
3.1
Positive Impacts of Pre-Loved Garments: The Gains
During the COVID-19 pandemic, clothing and textile ‘waste’ have further increased, with consumers spending more time at home, and thus, having had more time to declutter their wardrobes (WRAP, 2020; Vladimirova et al., 2022). It could be assumed that with clothing donations accelerating there may also be a need for more people to handle these donations, whether this be checking them into charity shop shelves, or sorting them in facilities, which could lead to job opportunities. Keeping garments in the local economy and facilitating job opportunities are not the only ‘benefits’, we have also seen a growing export market, with over $4 billion worth of pre-loved garments and textiles being exported per year globally (WRAP, 2019). This may be seen to be a double-edged sword, as on the one hand imported garments can be a desirable and essential clothing source in developing economies, whilst on the other hand, developing countries who are importing these products may damage their own economy and decrease their local textile production (Norris, 2012; Wolff, 2021; Henninger et al., 2021). To ensure that (developing) countries are protected, there are also increasingly more regulations put in place. For example, the European Commission has indicated that they will provide ‘specific EU level criteria to make a distinction between waste and certain second-hand textile products’ (European Commission, 2022), in order to avoid that waste materials being ‘falsely labelled as second-hand goods when exported from the EU and in this way escape the waste regime’ (European Commission, 2022), which clearly states that countries outside of the OECD need to ensure they can manage these waste streams sustainably (WRAP, 2019; European Commission, 2022).
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Thus, it can be said that there are economic and environmental benefits that could be supported by the trade of pre-loved garments. Moreover, with the support of governments and the introduction of different rules and regulations, a positive change can be seen that may also address issues in developing countries, in that less garments can be exported and those that are exported are actually of use to the local community and, thus, may not end up in remote locations where they destroy the eco-system.
3.2
Negative Impacts of Pre-Loved Garments: The Pains
Yet, as alluded to in the previous sections, there are not only benefits associated with pre-loved garments and their import into especially developing countries. To provide a more explicit example, within the UK the average person discards 30 kg of garments per annum (see Table 1), of which a percentage goes to charity shops or is resold. Of all the garments that are donated to charity shops annually, only 10–30% are sold in the UK and the vast majority 70–90% are being exported overseas, predominantly to developing countries (Brooks, 2015). An interesting notion that needs to be mentioned here is that although we as consumers may donate our garments to charities, this does not necessarily imply that our garments are then also passed on free of charge to other countries, but rather ‘clothes will be sold to traders who will then retail them’ (Baden & Barber, 2005; Brooks, 2015). Although this may create some job opportunities, the opposite has also been observed in that ‘cheaper imported goods flooded African markets and workers in clothing factories lost their jobs’ (Brooks, 2015). Pre-loved garments that end up in overseas markets are often of low quality, with some further being damaged, which makes it hard to trade these on market stalls (ibid). With pre-loved garments further being exceptionally cheap, they also undercut prices of locally produced garments, and as such, have caused a detrimental impact on local economies (Baden & Barber, 2005; Fabric of the World, 2020). What may become apparent here is that the biggest issue is the quality of the garments, in that those that are broken and not fit for purpose can also not be resold in developing countries, and thus create issues, as they are discarded off, whether this be in landfills or nature. Neither is an ideal scenario. Moreover, the loss of jobs and cultural heritage often associated with creating textiles may be lost, as consumers are not willing to buy expensive clothes, but rather want to enjoy the cheap and cheerful garments sold pre-loved. As there are quite a few challenges with pre-loved garments, it may not be surprising that we see more and more policy makers, non-governmental organisations (NGOs), and other stakeholders getting involved in developing more transparent and less harmful approaches to tackling textile waste in a way that makes it more formal and also more even distributes responsibilities across the different stakeholder groupings. The following section will provide more detailed examples.
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Tackling the Pre-loved Textile and Garment Waste: The Pain of Reuse
One of the greatest risks to developing economies is the fact that pre-loved garments may neither be of high quality, nor actually usable when being exported to these countries. This implies that traders, who have specialised in dealing with pre-loved garments, are often buying into the unknown, as the quality of the bulked-up clothing bundles cannot necessarily be judged on their quality prior to purchasing them. This implies that these garments are often sold at a loss (Baraka, 2021). As alluded to previously within the EU, the European Commission has proposed new rules that carefully outline what can and cannot be shipped in order to avoid issues of dumping garment waste (European Commission, 2022). This also aligns with the East African Community’s push towards banning pre-loved garment imports, in an attempt to save their own textile and garment manufacturing industry (Krauß, 2018; Anami, 2019). Thus far it seems that although the intentions to ban the pre-loved clothing trade have been there since 2016, due to a variety of circumstances it has not materialised as of yet.
4.1
Case Examples of Tackling Pre-loved Textile and Garment Waste: Australia
Australia has been used as a case example, as the country, as of yet, has more local rather than fast fashion high street brands, which can be explained partially due to the fact that Australia is far away from other countries, and seasons are also different. The country furthermore has a strong stance on sustainability (e.g. Brydges et al., 2022a). To explain, Charitable Recycling Australia, for example, seeks to tackle transparency and sustainability in global trade in textile waste and used textiles. Their newly developed clothing reuse export accreditation scheme seeks to provide more transparency and a standardised approach that enables to highlight what the social, environmental, and economic benefits are and why this trade may have previously been perceived in a negative manner (Charitable Recycling Australia, 2022). Multiple stakeholders (e.g. local governments, industry stakeholders, consumers) are involved in developing the scheme, aiming to establish a reuse clothing export standard and a more transparent and efficient operation and management system for collecting, sorting, and downstream selling pre-loved clothing (Charitable Recycling Australia, 2022). In the section discussing barriers, it was indicated that one of the biggest issues, especially for pre-loved garment traders, is low-quality stock, as this is often sold at a loss (Baden & Barber, 2005; Fabric of the World, 2020). Thus, if it could be guaranteed that high-quality pre-loved stock is exported instead, this could be a valuable resource for low-income consumers overseas whilst providing clothing reuse jobs to help poverty reduction (Bukhari et al., 2018). To explain, it is estimated over two million people are employed in clothing reuse in Kenya. Whilst contributing to overseas resource and job markets, the 100,000 tonnes of pre-loved wearable clothing exported by Australian charities
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also generate $50 million for social welfare causes at home (Charitable Recycling Australia, 2022). Although this scheme would be valuable, it also implies that we need to see dramatic shifts in production and consumption in order to make it viable and future proof. To explain, if garments are produced in a manner that does not allow for multiple use times, it will be challenging to sell these to developing countries, and for traders in these developing countries to capitalise these garments. On the other hand, overconsumption implies that as consumers we may declutter more and more items and keep them for less time. There could be a risk in that the pre-loved market is not designed to deal with very increasing masses of decluttered clothes. Within the following sections Australia and France will be discussed in regard to some measures they have undertaken. Although there are other schemes globally that are addressing the issue of pre-loved textile waste, the case examples provided from Australia and France can be seen as success stories, as they have had stakeholder buy-in and are also almost acting as pilots to be introduced in other countries. For further examples on recycling schemes and textile waste prevention, Brydges et al. (2022a) have provided insights into different textile strategies that are seeking to foster a more circular economy, within their article entitled: For waste’s sake: A stakeholder mapping of circular economy approaches to address the growing issue of clothing textile waste.
4.2
Case Examples of Tackling Pre-loved Textile and Garment Waste: France
A further example of dealing with garment waste is shifting responsibilities to the manufacturer of garments through extended producer responsibility (EPR). Making producers responsible for post-consumer waste is essential to decouple textile waste generation from the growth of the sector (EEA, 2019; European Commission, 2022). EPR is defined by the OECD (2001) as an environmental policy approach in which producers are responsible for the collection, treatment, and disposal of their products at the post-consumer stage of a product’s life cycle. Similarly to the plastic bag tax, it was recommended that producers and/or retailers of garments should pay a penny per item, which would fund how garments are treated at their end-of-life (EAC, 2019). One of the goals of the EPR thus is to incentivise product design that not only promotes material durability but also encourages a more circular design process in that manufactures, producers, and/or retailers take the end-of-life into consideration (EC, 2015; WRAP, 2019). This would also go hand in hand with the EU’s proposed waste legislation, which aims to separate the collection of textile waste by January 1, 2025. This obligation will be introduced by several EU countries (e.g. UK, Netherlands, Sweden), who also already have or are considering the introduction of the EPR requirements for textiles (European Commission, 2022). Currently, the EU’s only mandatory EPR scheme is in France; its EPR policy was introduced in 2007 and passed into law to cover end-of-use clothing, linen, and
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shoes in January 2020 (Bukhari et al., 2018; Wilson, 2021; Brydges et al., 2022a). Thus far, there are some gains and some pains that can be observed. In terms of the former, in 2015, 65% of the overall collected textiles were sent to the ‘reuse’ stream. This in itself is a huge success, as garments are collected and entering one of the more desirable levels of the Waste Hierarchy (DEFRA, 2011), namely the reuse stream. Yet, of these collected garments, the majority are exported to the secondhand market in Africa and only very few quantities were sold in France. Around 35% of the materials were down-cycled and about 6% were either landfilled or incinerated (Bukhari et al., 2018). Again, this poses the question of whether this may necessarily be the best solution? On the one hand, it is a clear yes, as garments are diverted from landfill and producers are contributing to this phenomenon. Yet is exporting to developing countries the only solution to deal with our clothing waste problem? France has rather ambitious plans and is currently leading the field in the EU, in that France is targeting to collect 50% of all textiles on the French market in 2022. From within these 50% collected, they want to reach a 95% rate to reuse and recycle textiles, and a maximum of 2% waste. Although it is challenging to achieve such a high rate of reuse and recycle, the benefits associated with the implementation of EPR policy are evident. In France, under the EPR policy the collection and recovery rates of post-consumer textiles have been increasing since 2006—the amount textile collected now is three times as much as what was collected a decade ago (Bukhari et al., 2018). The increased collection rate also implies the consumer awareness and accessibility to collection bins/containers have not only been improved, but they are also made easily accessible, and thus there seems to be a lot of take-up from the consumer side. It is reported that in France the number of textile collection containers in 2016 was more than twice of what it was in 2011 (Eco TLC, 2016). Furthermore, it is also evidenced that the EPR policy can help textile reuse and recycle markets to overcome future challenges and create jobs. Sorting of textiles has provided 1400 full-time jobs in France in 2017, amongst which 49% have been reserved for workers facing employment difficulty (Eco TLC, 2016). Yet, as alluded to, the EPR scheme is not the end-all solution. To explain, whilst collecting post-consumer is commendable, the end solution cannot be sending the collected textile waste to developing countries. We have already seen a decrease in demand for reused textiles from potential markets within Africa and Asia. China has banned the import of used textiles in 2017, and some countries in the East African Community also agreed on a ban on used clothing import, with a hope to create a self-sustaining and reliable textile industry to provide jobs and improve local economy (WRAP, 2019; Wolff, 2021). On the other hand, expensive and labourintensive sorting procedures and the use of different fibre blends in the textiles make it difficult to sort and recycle these items (Bukhari et al., 2018).
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Conclusion
This chapter was set out to address one key question—as to what happens to garments when consumers no longer love them. As illustrated in this chapter, the answer is not easy. Whilst it was not the intention to give a one-size-fits-all answer, the chapter wanted to outline that every action has consequences; some are very positive and can be described as a gain, whilst others may be more associated with pains. In linking back to the Waste Hierarchy (DEFRA, 2011) prevention of waste is the top priority, followed by reuse. Although there are many benefits of reusing pre-loved clothing—political, commercial, social, environmental, and economic (Williams & Shaw, 2017; Bukhari et al., 2018), there are also a variety of challenges. Firstly, the idea and practice of reusing clothing is dependent on pre-loved clothing being collected and made available to the next user. What is important here is to collect high-quality and durable clothing to ensure they can be reused as long as possible. Yet, as aforementioned, fast fashion has been associated with low-quality material, with items often being designed to be worn 10 times or less. As a consequence, there is a lower potential for their eventual reuse. Secondly, collecting, sorting, preparing for reuse, and recycle of pre-loved garments remains a labourintensive activity, and as such very costly, which does not make it a highly economic endeavour. Although technologies are emerging that can help automate the sorting process, these technologies are either very expensive at the moment and/or not as effective as humans (Bukhari et al., 2018). Thirdly, societal preferences, peerpressure, and the desire to be seen to ‘wear something new everyday’ can, in practice, be a barrier to scale up the adoption of reused clothing. Lastly, economic barriers hinder collecting, sorting, preparing for reuse, and recycling of clothing which can be a costly operation, whereas new garments (fast fashion) can be produced with much lower price. In France, only 30–40% of the collected materials can cover the recycling cost in 2017 (Bukhari et al., 2018). Critics of reuse insist that it is just delaying time to disposal via landfill or incineration; however, by only extending the life of clothing by an extra nine months could reduce carbon, waste, and water footprints by around 20–30% each (EAC, 2019). Future research could focus on a case study perspective and investigate different initiatives, such as the EPR scheme in France or the Charitable Recycling Australia programme, and outline what the benefits and drawbacks are from a multistakeholder perspective.
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Sharing Is Caring: The History of ‘Sharing’ New Interpreted Lucie Pocinkova, Claudia E. Henninger, and Aurelie Le Normand
Abstract
This chapter will be conceptual in nature by drawing on secondary data (e.g. journals, websites) to provide an insight into sharing of garments and accessories. Thus, this conceptual chapter provides a historical overview of ‘sharing’ from the 1920s to the modern era—which currently lacks research. This chapter is based on a critical literature review and focuses on a European context. This topic is of significance, as focusing on how clothing is shared provides key insights into society, as well as provides opportunities to reflect on well-being and climate change. The latter two aspects are currently heavily debated and discussed, as the fashion industry in more general terms has been named the fourth most polluting sector within Europe (EEA, Textiles in Europe’s circular economy. EEA, 2019). With globalisation and more specifically the development of Web 2.0, garment and accessory sharing has become increasingly commonplace, which also led to the phenomenon of access-based consumption. Yet, it remains a niche not only in terms of uptake, but also in terms of being researched. The historical account (in the form of a critical literature review) will further be supported by European based case studies that outline the differences of sharing, as well as its significant role throughout the century.
L. Pocinkova (✉) School of Design, Clothworkers’ Central, University of Leeds, Leeds, UK e-mail: [email protected] C. E. Henninger · A. Le Normand Department of Materials, The University of Manchester, Manchester, UK e-mail: [email protected]; [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_10
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Keywords
Sharing · Access-based consumption · Fashion · Literature review · European perspective
1
Introduction
In 2014, The Guardian Newspaper posed an interesting question: ‘Would you share your wardrobe?’ (Brownie, 2014). The answer to this question may seem like a very simple yes or no type answer, but in actuality, it is more complex than that. An explanation, as to why this answer is complex could be emotional attachment (e.g. Henninger, 2020; Graul et al., 2022). If we think about our own wardrobe and all the items we have in it, would we really want to give someone our favourite band T-shirt to wear? Or the jumper we wore when we achieved something incredible? Perhaps yes, but perhaps the answer is also no, as the T-shirt or jumper is special to us, and we would do anything to keep it safe and preserve it for as long as possible (e.g. Graul et al., 2022). When we think about sharing wardrobes, we may have only more recently gotten more attached to our garments. Linding (2015) points out that throughout our lifetime we go through various phases of wardrobe sharing. As children for example, we may wear garments from older siblings, family friends, and/or other relatives. And why not? As kids grow very quickly, sharing implies that garments that may have only been worn a couple of times could be utilised more whilst saving money for parents/guardians. But hand-me-downs are not the only act of clothes sharing we participate in as children. (Un)consciously, we may also raid wardrobes to get dressed up and either be a famous movie star, princess for the day, or secret agent—all of which can often be found in the comfort of our home (Linding, 2015). Thinking about our teenage and university years, when we first go out, we may start looking at our friends and see whether they have anything that could fit us. If your bestie and you have the same shoe and dress size, why not purchase two outfits—one each—and you can both benefit from them (Linding, 2015; Alevizou et al., 2021). It may only become more apparent in our later years that we are less willing to share, as we have worked hard to earn that money and to reward ourselves. Why would we want to risk this by giving it up to someone else? From what we have mentioned here, you may have noticed that sharing is not a new phenomenon; rather it has a long-standing history within society (Belk, 2014), and can include a manifold of things, such as lending, borrowing, swapping, and gift giving, but also renting. In the past, we were often limited in terms of with whom we can share our wardrobe (e.g. Henninger et al., 2019, 2021), whilst with the development of Web 2.0 this obstacle, especially from teenage years onwards, is reduced. Thus, the sharing concept has reached new heights with the technological development of Web 2.0, enabling sharing to happen amongst local, national, and international communities of otherwise strangers (Hamari et al., 2016; Iran & Schrader, 2017; Iran et al., 2019).
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The aim of this chapter is to provide an overview of sharing and how this may have changed over the past few decades. In doing so, we will conceptualise the sharing concept within the literature, before coming back to the key question posed at the beginning of this chapter of ‘would you share your wardrobe?’ (Brownie, 2014). The chapter will conclude by providing suggestions for future research.
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Conceptualisation of Sharing
The word ‘sharing’ enjoys a multitude of definitions in the Cambridge Dictionary (2022), encompassing the tangible as well as the more abstract, communicative sphere. In a literal sense, the act of sharing possesses the meaning of distribution, having divisive implications (i.e. sharing a resource with another person). At the same time, sharing can mean having something in common with another person whether it is concrete such as a shared wardrobe or rather abstract, for instance culture, interests, or even style when it comes to fashion. Moreover, sharing can entail communication, sharing of an experience or feeling with someone (John, 2017). As already alluded to, sharing can take on a variety of shapes and forms, including, but not limited to lending, swapping, hand-me-downs, gift giving, or renting. Within the academic literature, sharing falls under the umbrella of collaborative consumption (Ertz, 2020; Henninger et al., 2021). Collaborative consumption is defined as the ‘set of resource circulation systems which enable consumers to both obtain and provide, temporarily or permanently, valuable resources or services through direct interaction with other consumers or through a mediator’ (Ertz et al., 2016, p. 6). This definition has various implications. To explain, collaborative consumption, and thus, sharing, is part of the circular economy, as the aim of collaborative consumption is to keep garments in use, for as long as possible, by, for example, passing a garment from one individual to another. Here is where the obtainer (individual who is taking a garment) and provider (individual who is offering the garment) become important, in that we, as consumers, play a dual role—we are not only the ones who want to have new garments, but by participating in sharing, we are also opening up our own wardrobe and give others an opportunity to access these (Philip et al., 2015, 2019; Henninger et al., 2019). Giving someone access to our wardrobe may take on the form of either temporary access, through, for example renting or borrowing items, or permanent access through hand-me-downs, swapping, or gifting. The complexity of (non-)ownership is further elaborated in a later part of this chapter. A last observation that is vital to highlight is the ‘with whom do we share?’ question—as collaborative consumption and ultimately sharing garments can be done with close friends/family, directly with strangers, or through a mediator or agency, aspects that will be further explored in the sharing-in versus sharing-out section of this chapter. Within the fashion context, Iran and Schrader (2017) coined the term collaborative fashion consumption (CFC), when talking about individual modes of sharing. This terminology will be used for the remainder of the chapter. What becomes
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apparent overall is that collaborative fashion consumption, irrespective of the mode, implies that individuals are automatically taking on a dual role and, thus, use or have access to existing garments and accessories instead of buying new products (BeckerLeifhold & Iran, 2018). With sharing being as old as humankind (Belk, 2014, p. 1595), it is necessary to understand its development to provide greater comprehension of the concept today. Whilst in the past collaborative consumption was defined predominantly in an offline setting (Ertz, 2020), this has since changed. The development of Web 2.0 has shifted what we understand as collaborative (fashion) consumption to predominantly focus on the online part, which broadens the reach of the sharing phenomenon (e.g. Hamari et al., 2016; Curtis & Mont, 2020). Within the fashion context, the former (offline sharing) is especially relevant when discussing its historical roots with concepts such as hand-me-downs, style-sharing, and fashion libraries. Sharing both old and new items forms an important part of human interaction; hence, it is important for further study (Alevizou et al., 2021). In addition, the chapter explores the shift in stigma surrounding sharing and related second-hand consumption (Henninger et al., 2019).
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The Level of Ownership in Sharing and Modes of Sharing
In line with Ertz et al.’s (2016) definition, the concept of ownership is key within collaborative fashion consumption as consumers can either acquire permanent individual ownership through gifting or second-hand shopping or gain temporary access to items that are owned by others through sharing, lending, or renting (Iran & Schrader, 2017). Swapping is thought to encompass the redistributed ownership concept as products can be owned again with access periods being undefined (Henninger et al., 2019). Table 1 provides an overview of different modes that have commonly been used within the sharing economy, as well as whether they are facilitated online/offline and the type of ownership. It has to be highlighted that this list is not exhaustive, but rather provides a snapshot of different modes of access. It is noteworthy to highlight that the modes of access in Table 1 can be facilitated both online and offline. This highlights that individuals can engage with ‘sharingout’ (between strangers) and not only share-in (with close friends or family), an aspect to which we will return later. Some modes, especially hand-me-downs and shopping in charity shops, are predominantly offline; this may be partially due to logistics and lack of staff (charity), and/or impossible to do online (hand-me-downs), as they are, by definition, only between close-knit communities. This chapter focuses on the evolution of the sharing concept of clothing and accessories, outlining the historical timeline.
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Table 1 Modes of access in sharing economy Term Borrowing
Online ✔
Offline ✔ ✔ ✔
Charity Hand-medown Second-hand market (resale) Swapping
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✔
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Renting
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✔
Gifting
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Ownership type Temporary access Permanent Temporary access, redistribution Permanent
References Iran and Schrader (2017), Iran et al. (2019), Henninger et al. (2022)
Temporary access/ redistributed Temporary access Permanent
Sharing-in Versus Sharing-out
We previously highlighted that sharing is not a new phenomenon per se, but rather has been practised throughout our history (Belk, 2014). Although the concept has not changed, the ‘how’ has. To explain, whilst in the past we may have only shared garments and/or accessories with close family members, friends, and/or neighbours in very close vicinity, the emergence of Web 2.0 has made the world a village whereby we can swap, rent, and borrow with anyone in the world at any point in time. We can clearly distinguish between two types of sharing: (1) sharing-in and (2) sharing-out (Belk, 2014). In addressing sharing-in first, this refers to the interaction of sharing between a close community (e.g. friends, family, neighbours). It could be described either as a geographical proximity, in which sharing garments can happen in a physical space, or in terms of ‘emotional proximity’ (e.g. Graul et al., 2022). With the latter we mean sharing garments with individuals we ‘know’. To explain, emotional proximity here is referred to as sharing with friends, family, and neighbours, or members of a community, with whom we have a connection, whether this is a really close connection, which we would see in friends, or a slightly more distant connection, such as with acquaintances. Prior to Web 2.0 sharing-in was the only option to either get rid of garments through hand-me-downs or gain new items, without having to necessarily pay for them (e.g. swapping, borrowing). In line with newer definitions of CFC and sharing, the online environment has brought forward sharing-out. As may be obvious from the term itself, it poses the opposite to sharing-in in that sharing is no longer between individuals who know one another, but rather can be facilitated between strangers, and ‘engage in simultaneous disposition and acquisition of everyday items with peers via an online network’ (Philip et al., 2019: 413). Yet, here we do have to make a distinction, as sharing-out can either be through direct contact between strangers or mediated by a third party.
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This may at first sound contradicting, as we always see a third party involved, who may facilitate the interactions between two strangers. Yet, there are differences on whether an individual is listing their own items and can be contacted by someone else, or if the items are centrally stored by a third party, who then will facilitate the exchange on behalf of the owner. What becomes apparent here is that with increased digitalisation the process of sharing has on one hand become easier, as the virtual wardrobe has increased (e.g. Henninger et al., 2022). At the same time however, sharing requires a lot of logistics in terms of logging who ‘shared’ which product when, how to get it from and to the individual, as well as cleaning processes. Since we already discussed a lot about what different modes of sharing exist and how these may take place, we now turn back to an initial debate in the introduction, as to what we may want to share, and if we do—what are the rules of sharing? A Vogue article written by Pike (2020) shares key rules and guidelines that were important to Eshita Kabra-Davies, the founder of ByRotation, which allows consumers to ‘rent, lend, and buy designer fashion’ (ByRotation, 2022). 1. What Is the Occasion? The first key question to address is the occasion to which the outfit will be worn. Thinking about our own garments, if we usually take very good care of one of our favourite white items in order to ensure it stays white, we probably would not want someone to wear it to a colour fun run, in which it could be permanently damaged. This may sound obvious, but we cannot assume that others have the same values as we do, which indicates that we either need to trust the person, which may be easier when we are sharing-in, or have very clear rules, especially when we are sharing-out (e.g. Pike, 2020; Graul et al., 2022). 2. The Cat in the Bag and How to Return it Trust is vital when sharing, and although we may trust the person who gives us the item, we should still inspect it carefully. We now see an interesting dilemma emerge. Whilst it may be very easy to inspect an item that comes from a stranger and point out any flaws, this may be harder when we have to do the same when the item belongs to a friend. However, it is vital to do this: ‘so that you can make sure they’re (friend) aware of any existing wear or tear—and won’t blame you for it when you give the item back’ (Pike, 2020). Whilst you may expect that things are in great condition, past research has highlighted that this may not always be the case (e.g. Henninger et al., 2019). This may also be the reason why hygiene and damaged items have emerged as key barriers to engaging with CFC and more broadly speaking sharing practices (Lang & Zhang, 2019; Park & Armstrong, 2019). At the same time, we also need to make it clear in which condition we want the item returned. Think of giving your friend a hoodie, would you expect it back worn, or would you want it to be washed and cleaned? Are minor damages acceptable to you? These are aspects that warrant careful consideration.
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3. Deadlines Deadlines are key, especially when you engage in modes that fall within the access-based consumption (see Table 1) (Battle et al., 2018; Hu et al., 2018). Accessbased consumption implies that an individual can make use of a garment for a limited amount of time. When sharing-in, especially with siblings or close friends, we may not necessarily set a deadline, which implies that we are either searching for our pieces or gain them back months if not years later, which can be problematic. This may also explain why CFC is complex, as especially online providers need to keep track of where items go and when to expect them back (including cleaning time), prior to being able to share it again. 4. Big NO Whilst shared wardrobes have their advantages, you need to understand which items you may never want to share. Here we return to emotional attachment (Brownie, 2014; Linding, 2015; Graul et al., 2022), as there may be items that have a special meaning to us personally and, thus, if anything happens to them, may be impossible to replace. Whether it cannot be replaced as the item no longer is on the market or whether it cannot be replaced due to a memory does not matter. If it has this connection with us, we should ensure that we can treat it in the manner we deem appropriate rather than relying on anyone else. 5. What if. . .? One barrier to engaging in sharing practices is the big ‘what if. . .?’ question, which implies: what if something goes wrong and we accidentally ruined a garment? What if we have been so careful, but the wooden bench we sat on had a splinter that rips a hole in our jeans? These aspects may not only act as barriers, but also need to be addressed. As the obtainers of garments, if we notice the item is damaged, it is our duty to make the sharer aware of it and see what can be done. But what if we do not notice that something ripped, or there may be the tiniest stains on the garment when someone walked past and spilled their drink behind us? Especially when sharing-in it is vital to address the issue, in order to avoid any longer lasting resentment. When we talk about sharing-out, these types of damages are often covered within the policy (Henninger et al., 2022). In summary, sharing-in and sharing-out (Belk, 2010) are very similar, yet there are also key differences. When sharing-in, we are aware of who the other person is and, thus, we need to ensure that we are enforcing clear rules in order to avoid any long-term resentment (Pike, 2020) should anything go wrong. Sharing-out is often regulated through the platform, especially when it comes to those that are third party facilitated (Henninger et al., 2022).
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Historical Overview of Sharing
After providing some information on what sharing entails, why it is important, and what rules there may be, we now turn to looking at how sharing has evolved. This part of the chapter is structured into two sections. Firstly, sharing will be considered prior to the development of the fast fashion phenomenon. Before ready-to-wear and fast fashion were available, apparel products were thought of as luxury which only the wealthy could afford. Hand-me-downs and forms of sharing-in were more prominent, which is further discussed. Secondly, the historical section explores the sharing concept as fast fashion emerged, paying attention to the development of Web 2.0 which enabled novel forms of sharing on a new, global scale. The second part of this overview will therefore contemplate sharing-out, renting, and swapping. It should be noted that the split is not definitive in that an era is purely defined by sharing-in or sharing-out. It is rather about the changing nature of what sharing itself meant and mapping the transformation of the concept and related stigma of secondhand clothing. The historical discussion is enriched with examples from across the European continent of sharing and its different forms that affected the concept today.
3.1
Pre-Fast Fashion/Pre-Internet
The sharing of clothing was a common practice prior to the birth of ready-to-wear fashion. For example, in France towards the end of the sixteenth century, ‘the Freppe’ (ancient French) or ‘Frappa’ (Latin) emerged, which in the Renaissance context meant rags or old clothes that were primarily used as trimmings to embellish shoes and cuffs of the aristocracy (de L’entrepot, n.d.). The term ‘Fripe’ is now more commonly known as ‘second-hand clothing’ (Larousse, n.d.); however the historical meaning of ‘fripe’ still conveys a pejorative image that some may have about wearing second-hand clothing (Lasalle, 2022). Early signs of a circular economy appeared as early as the nineteenth century in what is now Europe, with the market of the ‘Carreau du temple’ in Paris, the market ‘Mercato Vecchio’ in Florence, or ‘Petticoat Lane’ in London. Paris was the pivotal place in redistributing second-hand clothing across Europe and the world. The ‘Carreau du temple’ market was organised in four distinctive squares; each square was organised by a category of textiles and clothing and classified by the level of quality and/or level of wear, making second-hand clothing accessible to a variety of social classes (Le Carreau du Temple, 2022). ‘La fripe’ became a necessity due to the obsolescence of clothes as a result of low quality, as prior to the ‘take-make-dispose’ fashion phenomenon clothes were made to last and made to be adapted, mended, and adjusted (Charpy, 2017). The concept of buying ready-made garments started to grow only more recently in the consumer’s mind. The Industrial Revolution accelerated this transition, making new industrialised fabrics or buying readymade clothes affordable and made to be widely accessible to the detriment of second-hand clothing.
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What Happened to the Concept of Sharing-in or Sharing-out Post-1900? As aforementioned, sharing-in encompasses the idea of sharing with people we know (e.g. friends, family, community). Sharing-in is thought of as normative and, thus, does not require formal rituals, but rather happens organically. After our own personal needs, our family is the second most immediate layer of extended self (Belk, 1988). In the past, borrowing, hand-me-downs, charity, as well as secondhand were common forms of clothing consumption (Ginsburg, 1980). Within the familial sphere, sharing-in was not uncommon which is reviewed in the following. Historically, clothing represented a significant portion of one’s income and was expensive to acquire, especially up until the 1960s and 1970s (V&A, 2022). Interestingly, more income did not often mean obtaining greater amounts of clothing but rather spending more on individual pieces. Depending on the social and economic status, an average woman during the 1920s and 1930s would own approximately 10–15 clothing items which encompassed blouses, dresses, aprons, nightgowns, and undergarments as well as accessories (hats, gloves, and scarfs) (Vintage Dancer, n.d.). It is estimated that less than 40% of items in the average wardrobe were purchased in store. Instead a majority (especially corsets, aprons, and nightgowns) were homemade (ibid.). Although sewing machines became more available with the turn of the twentieth century and following the Industrial Revolution, garments were often altered, mended, and sewn by hand. It was common that people owned only one ‘best’ outfit which was sometimes referred to as ‘Sunday’ dress with the implication of wearing the best clothing to church and attend special occasions. Such garments would have been passed down in the family and were thus shared as hand-me-downs (ibid). Accessories were further shared amongst family members and women would borrow from each other to bring greater variety into the dressing practice. Jewellery was further passed down as family heirlooms, which, in recent years, has received increased attention (Shaw-Ellis, 2021). Nonetheless, in former times it was less likely that items of clothing, especially those that were made to fit the wearer, were shared amongst family members, and/or used by two or more members at the same time (with the exception of children’s’ clothing). Second-hand clothing trade and charity were other forms of consumption that were available; however, these were considered rather plebeian which is significantly different to second-hand consumption today. Ginsburg (1980) notes that with greater availability of ready-made clothing from the turn of the century, buying new clothing rather than wearing second-hand or borrowed items was a point of pride for young women (especially unmarried ones) as it signalled independence and wealth. During World War II, in Britain purchasing new clothing was rationed, resulting in a nation-wide government campaign to make, do, and mend. As such, existing clothing was reimagined into new pieces and greater emphasis was placed upon repair and care. With limited availability of new clothing, it can be inferred that clothing was shared more during these times, however not always in the sense of actual garments but more so through sharing of fabric to make new items (IMW, 2020). Even sentimental items such as wedding dresses were remade into undergarments, blouses, and formal dresses (ibid). Borrowing would have also
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been common. It is noted that the forms of sharing took place in the sharing-in circle rather than sharing-out which was only developed later in the twentieth century. Here we also need to discuss stigma. In some cultures, a stigma towards secondhand developed, based on the fact that it was seen to be for ‘the poor’. Interestingly stigma seems to be a cultural phenomenon; Henninger et al. (2019) pointed out that within their three-country comparison, participants from Germany were less likely to engage in swapping, as it was seen to be associated with low income class and, thus, stigmatised. Contrarily, within the UK it is increasingly seen as a patch of honour to wear second-hand, with efforts being made to break the stigma (Wightman-Stone, 2020; Scotter, 2022). The economic euphoria in Western countries following the war years was detrimental to second-hand markets. However, Ginsburg (1980) argues the war hangover still meant people retained certain habits of garment care and repair. The ready-to-wear market was in full bloom with the ‘New look’ and ‘out with the old, in with the new mentality’ (Reddy, 2019). Improvements in manufacturing and higher disposable incomes meant sharing of clothing was not a necessity nor as socially acceptable as it may have been during the war years. The 1950s were considered the inception time of consumer culture in Western Europe, an ideology, which, to an extent, continues through today. The 1950s was also the era when the youth started to challenge the status quo, using the excess of military supply to affirm their marginalisation seeking for the military jackets, the pair of US denim in flea markets. Wearing second-hand clothes became a form of singularisation, in an era of mass consumption and of conformist lifestyle (Pound, 2020). Though the fashion industry was booming in Western Europe, fashion behind the Iron Curtain in Eastern Europe developed significantly differently in comparison (Hlavackova, 2016). Communist rule in Eastern Europe influenced fashion consumption and practices of sharing, borrowing, renting, and hand-me-downs. Children’s clothing was passed down between families and extended family friends and was circulated time and time again. The new political direction in Eastern Europe meant clothing produced within the socialist block was not extravagant or trend-led but rather utilitarian (ibid). A lack of global influence meant that sharing of fashion styles was also limited, but women often shared foreign magazines (e.g. Vogue) for inspiration (Jerabkova, 2017). Mass-produced clothing was relatively affordable and available; however, items such as jeans were considered a luxury as they were imported. To provide a more specific example, Czechoslovakian citizens could only purchase jeans in ‘Tuzex’ shops with special currency called ‘bony’ and often waited in lines overnight to get them. During the 1970s and 1980s, owning a pair of jeans was a symbol of social status in Eastern Europe and garments like these were rarely shared (Hlavackova, 2016). Although renting is considered a new phenomenon today, renting initiatives were prominent in Eastern Europe pre-Internet, carrying garments for formal occasions such as weddings, ballgowns and suits (Jezdinska, 2019). The renting phenomenon has sustained until today in some parts of Eastern Europe such as the Czech Republic where clothing for formal occasions is rented rather than owned.
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Sharing-in has dominated prior to Web 2.0. Hand-me-downs and borrowing were normal practices in Europe, and sharing was common between family members and friends. Charity and second-hand clothing shops represent an established practice; however, the stigma around second-hand clothing grew after World War II (Ginsburg, 1980).
3.2
The Growth of Fast Fashion, Sharing-out in the Internet Era and New Business Models
In line with globalisation of the fashion industry, the fast fashion phenomenon grew from the 1960s in Western Europe. In the 1970s, fashion retailers such as H&M and later Zara sold mass-produced garments in London, sowing the seeds for expectations of low-cost, trendy fashion items and kick-starting what is now described as overconsumption practices or throw-away culture. It could be said that fast fashion has to a certain extent decreased the need for sharing because clothing was not only more available but also affordable. Nonetheless, in the mid-1970s, John (2017) contends sharing as caring has emerged which shifted the meaning of the word, giving it novel connotations and a warming glow encapsulating the practice. Although there is limited literature that explains the impact the new meaning had on clothes sharing, it is alluded that sharing ones’ garments would also be considered as caring and thus regarded as an altruistic and moral practice. Clothes swapping especially between friends would have been a common practice (Stanton, 2018). People were further likely to share-out through donations of old clothing to charities and continue in sharing-in. One aspect that also needs to be highlighted is the fact that donations can also have negative implications, even if the intentions are well. To explain, garments that are not sold may be sent to developing countries and/or may end up in landfill; neither of these are necessarily ideal outcomes. Norris (2012) reports on the rise of global textile trade from the Global North to international markets during the 1980s and 1990s which were motivated by both commercial and humanitarian principles. Through such activities, domestic consumption of second-hand clothing was to an extent aiding the stigmatisation of used garments as low-status goods (Laitala & Klepp, 2018; Rulikova, 2020). Nonetheless, waves of counterculture, anti-establishment and anti-consumption, especially during the 1980s, maintained the demand for second-hand clothing in the West (Cote, 2021). Through anti-capitalist movements, nowadays trendy clothes sharing practices such as swapping emerged (Stanton, 2018). What was then considered ‘alternative’ or ‘hippie’ (and not exactly in a good way) paved the way for a new era of sharing-out and CFC, which was later amplified by the rise of the Internet. At the turn of the millennium, the abundance of clothing as a result of fast fashion and technological developments have to a certain degree enabled the growth of redistribution markets and forging sharing practices between strangers (Botsman & Rogers, 2010). Consumption of pre-owned garments was not a necessity, but rather motivated by self-actualisation, fashion leadership, and seeking unique and
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alternative wardrobes (Battle et al., 2018). On the other hand, sharing-out made both economic and sustainable sense, whereas consuming pre-owned was cheaper (and potentially profitable) and more environmentally friendly (Botsman & Rogers, 2010). Sharing-out encompasses sharing with strangers either through a mediator or through peer-to-peer platforms as well as offline types of sharing such as swap events. The development of Web 2.0 allowed users to upload user-generated content, interact with other users, and form communities for a plethora of interests including clothing and fashion. For instance, Polyvore, which launched in 2007, was an online fashion community which allowed users to share styling tips, outfit inspirations, and fashion design advice (McMenamin, 2021). The Internet further enabled likeminded individuals to form groups and organise clothes swapping events which were open to everyone. Peer-to-peer resale sites such as ThredUp, the grandparent of Depop, also started in the first decade of the new millennium which aided the greater proliferation of second-hand consumption and expanded sharing-out. Renting can be considered another form of sharing-out, which reached new heights with technological advancements. As mentioned, renting of formal wear was and still is common in Eastern Europe. Wedding dresses were further commonly rented in the UK (e.g. Conroy, 2021). Rent the Runway and Bag, Borrow and Steal are other examples of rental success stories that began with renting formal and occasion wear and were considered prime leaders of the rental business model. Nonetheless, the common denominator of these initiatives is the mediator rather than a peer-to-peer renting scheme which has only started to boom in recent years (Henninger et al., 2022). Moreover, clothes rental platforms were often reserved for designer and luxury items as opposed to everyday clothes. ByRotation, the Hurr Collective, and Baukjen are changing this narrative by offering outfit rentals, sustainable clothing, and accessories and offering peer-to-peer rental options. Peerto-peer rental platforms such as ByRotation are trailblazing for sharing-out as users can rent out their own wardrobes to other strangers. Yet, as was highlighted in the introduction, it is unclear what we want to share and, thus, may need to consider ground rules on sharing. The Internet has further enabled swapping to transcend into the sphere of sharingout, meaning swapping now regularly happens outside of the immediate family. Swapping initiatives have formed on social network sites such as Facebook where users engage in peer-to-peer swapping and organise events to meet offline. Swap Society and Get Swishing are UK-based platforms where consumers can find and join local swapping groups. Nuw and Swopped are examples of peer-to-peer swapping apps where users swap clothing for points which are then used to ‘shop’ the wardrobe of others. Though Hamari et al. (2016) view the advent of CFC strictly through the technological lens, we deem it especially important to include offline modes such as swapping events which have been enabled through online communities.
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Conclusion
In summary, key observations that can be made are that sharing whether it be sharing-in or sharing-out has remained important throughout the century. With the emergence of the Internet, it has not only gained in popularity, but also broadened the scope and reach of different sharing practices. One of the most noticeable changes of sharing that we have highlighted is the fact that the ‘sharing concept’ has changed in terms of how it has been perceived. Prior to ready-to-wear fashion, it was seen as a necessity in order to access garments which would have otherwise been out of reach. After the war years, it got increasingly tainted and stigmatised as being for ‘lower’ social classes. Today, the sharing image is changing once more and progressively becoming a patch of honour, with the growth of second-hand platforms such as Depop, Ebay, and Vinted and normalisation of pre-owned goods consumption (Hur, 2020; Valor et al., 2022). Within this chapter we have only provided a brief historical overview, which is by all means not exhaustive. When reading the chapter, key questions may have arisen in your mind regarding the inclusivity of the sharing concept and questioning how the concept may develop in the future. As living costs and energy prices are accelerating, we may see a new wave of sharing emerge in the not-so-distant future.
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How to Promote and Communicate an Effective Green and Sustainable Communication: A Neuromarketing Study Ana C. Martinez-Levy, Daniele Sasso, Alessia Vozzi, Stefano Menicocci, Arianna Trettel, Fabio Babiloni, Giulia Cartocci, and Patrizia Cherubino
Abstract
Sustainability is a recent worldwide topic as there is a consensus that humans and companies are impacting the global environment. Companies can contribute to reducing the environmental impact associated with the product’s consumption by offering green and eco-sustainable products.
Ana C. Martinez-Levy and Daniele Sasso contributed equally with all other contributors. A. C. Martinez-Levy · S. Menicocci · G. Cartocci · P. Cherubino (✉) BrainSigns Srl, Rome, Italy Department of Molecular Medicine, Sapienza University, Rome, Italy e-mail: [email protected]; [email protected]; [email protected]; [email protected] D. Sasso Università Campus Bio-Medico di Roma, Rome, Italy e-mail: [email protected] A. Vozzi BrainSigns Srl, Rome, Italy Department of Anatomical, Histological, Forensic & Orthopedic Sciences, Sapienza University, Rome, Italy e-mail: [email protected] A. Trettel BrainSigns Srl, Rome, Italy e-mail: [email protected] F. Babiloni BrainSigns Srl, Rome, Italy Department of Molecular Medicine, Sapienza University, Rome, Italy Department of Computer Science, Hangzhou Dianzi University, Hangzhou, China e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_11
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In the last few years, the fashion industry, a major global polluter in the world, has been paying more attention to the environmental and ecological impacts of clothing production. Communicating correct information to consumers about the green consumption and recycling programmes raises their awareness, guides their purchasing choices, and helps responsible consumption. So, it becomes essential to adopt action to promote proper sustainability communication amongst people, especially in younger generations. This study aims to evaluate the marketing communication strategies to understand how specific advertisements and product elements can affect consumer behaviour and effectively promote the use of eco-sustainable products. By this research, the authors have evaluated the instinctive reactions like visual attention and emotion, using innovative tools like eye-tracker and facial coding in responses to two different sustainable commercials and eight social media posts (half with information related to sustainability). Research results show that social media posts that contain sustainable content are seen sooner, for longer, and with more attention than non-sustainable communication. Keywords
Eco-fashion · Green marketing · Advertising · Neuroscience · Emotion
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Introduction
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Fashion Industry
For decades, the fashion industry has become a multi-billion-dollar industry with an international presence worldwide (Han et al., 2017). In recent years, it has become increasingly pressing for companies in the clothing industry to pay attention to how the production of clothes can impact the environment. Between 1975 and 2018, global textile production per capita increased by 6 and 13 kg yearly (Peters et al., 2019), to the point of employing about 60 million people along its value chain (FashionUnited, 2016) and becoming after housing, food and beverages, and transport, the fourth most important European industry (European Environment Agency, 2020). On the other hand, fashion industries cause massive environmental damage and exploit many resources (The Boston Consulting Group and Global Fashion Agenda, 2017). One of the most severe fashion industry issues is that it is responsible for about 20% of industrial water pollution and the production of about 92 million textile wastes (Ellen MacArthur Foundation, 2013). According to the United Nations Climate Change (2018), the fashion industry can produce between 8 and 10% of the CO2 present on the planet each year. Furthermore, according to the Global Fashion
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Agenda (2017), this industry consumes almost 80 trillion litres of water annually. More specifically, the production of just one kilogram of textiles on average results in the use of 15 kg of carbon and about 10,000 litres of water, exploiting mainly cotton-producing countries, which paradoxically are amongst the most waterdeficient. Moreover, waste from textile materials has increased more and more because of their production and consumption (Dahlbo et al., 2017). According to the latest EPA studies (2019), textiles account for about 8% of landfill use, and of used clothing and footwear, only slightly less than 14% has been recycled. In particular, the fast fashion business model, which aims to produce new, inexpensive collections that are renewed in a brief time frame to accommodate consumers’ desire to change their style (Cao et al., 2014), has exacerbated the impact of garment production (Long & Nasiry, 2022). Further, this has enhanced the pressure on the environment, making a change in business models more complex (Niinimäki, 2017).
1.2
Eco-Fashion and Green Marketing
Over the years, the excessive consumption of resources based on marketing strategies and the lack of corporate responsibility in fashion for safeguarding environmental sustainability has opened an increasingly vibrant debate (De Brito et al., 2008). For this reason, one of the goals of fashion companies is to move towards fashion that is not only ecological but also ethical and characterised by good working conditions and sustainable business (Joergens, 2006). Schneider (2014), however, points out that the communication strategies to be used for sustainability communications need not necessarily be the same as those employed for ethical fashion. “Sustainability communication” is defined as the set of strategies and subsequent practices that have a relevant role in disseminating information about an organization’s environmental and social behaviours to influence, support and enhance the company’s corporate image in the eyes of its stakeholders and final customers and to indirectly promote its products (Morsing, 2006; Morsing & Schultz, 2006; Pomering & Dolnicar, 2009). Therefore, today it has become crucial for companies to learn how to combine in a precise way sustainability communication with the need to engage their consumers, who are often driven primarily by factors such as social status, simplicity, and the perception of potential success acquired through product acquisition (Schneider, 2014), and who are not very conscious of responsible consumption (Chan & Wong, 2012). Previous research found connections between eco-marking, green marking, and green estimating and the natural practices of purchasers (Kanade & Harwani, 2022). Moreover, even though brands and consumers have shown a growing interest in sustainability and respect for the environment is now one of the strategies to attract the public to their products, sales in this specific market sector are still not exceptionally high (D'Souza et al., 2015).
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In this context, emphasising how the product life cycle can be optimised and prolonged and incentivising new forms of consumption can lead to new communication strategies focusing on circular economy fashion (Han et al., 2017). The messages given to consumers can often be confusing at the media level and create natural scepticism towards communication (Zane et al., 2016). Consumers must be informed through direct and appealing strategies (Gam & Banning, 2011) to foster the development of circular economy fashion and promote more conscientious consumption patterns (Sharma & Hall, 2010). This is in order to elicit behaviours and attitudes that reduce environmental impact and focus not only on disposal but also on the use and handling of purchased products, as well as the search for sustainable alternatives (Eder-Hansen et al., 2012). Today, the web has become the predominant communication channel for sustainability initiatives (Delmas & Cuerel Burbano, 2011; Fulton & Lee, 2013) since corporate websites and social media allow companies to publicise a great amount of information in an economical and quick way and to release detailed information, which is constantly updated and customised, to different stakeholders groups, unlike traditional media (such as newspapers, magazines, television, and radio) (Esrock & Leichty, 2000). One of the main advantages of adopting web-based communication is that it enables a company to directly publish sustainability information on its website/social media and, consequently, to make that information directly available to the company’s customers (Da Giau et al., 2016). In particular, social media are the best tools for two-way communication with consumers, with the possibility of obtaining feedback and allowing one's audience to interact more directly, providing their opinions (Han et al., 2017). Consumer beliefs and purchase intentions are strongly associated with brand attachments and perceptions (Becker-Olsen et al., 2006). When green products evoke high trust and positive brand attitudes, consumers tend to form positive purchase intentions (Chen & Chai, 2010; Mandarić et al., 2022) because they feel that the products meet their environmental needs. The big challenge is to understand what kind of messages can have the most significant impact on consumers. Recent research studied the effect of social media marketing on purchase intention in fashion industry (Dewi et al., 2022) and the influence of social advertising on the buying behaviour towards fashion clothing brands (Rehman & Al-Ghazali, 2022). Exploiting the perks of environmental branding, some brands use exaggerated, deceptive, or unsubstantiated claims of environmental benefits to improve their corporate image. This marketing practice, known as ‘greenwashing’, has become an increasing issue. There has been an upsurge of misleading environmental appeals in advertising in the new millennium. The prevalence of greenwashing has led to ‘growing confusion’ and ‘alarming cynicism’ amongst consumers regarding green advertising in general (Sailer et al., 2022).
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Neuromarketing
Neuroscientific technologies are widely employed in marketing research (Briesemeister & Selmer, 2022). There is a growing interest in understanding how brain responses reflect consumers’ decision-making process. In this regard, the practical use of neuroimaging neuroscientific tools in real contexts and for real stimuli is named in the literature ‘neuromarketing’. The term explicitly describes a field of study as ‘the application of neuroscientific methods to analyse and understand human behaviour in relation to markets and marketing exchanges’ (Lee et al., 2007). Neuromarketing was born in the first years of 2000 and supported traditional marketing research. The traditional techniques allow us to measure the cognitive and emotional experiences only as verbally expressed at the conscious level during the interview. Instead, by using brain imaging techniques, it is possible to distinguish the unconscious states related to processes that have a crucial role in influencing behaviours, integrating what can be found by verbal or written declarations. The neuromarketing applications have grown significantly in the last few years in each marketing area, such as communication, product, packaging, brand, retail, and pricing (Cherubino et al., 2019). More particularly, the study of emotions and visual attention in environmental campaigns through social media can obtain valuable insights into consumer choices and preferences. Eye-tracking has been used to explore the effect of online consumers’ emotion on their visual behaviour between desktop screen and mobile screen (Hwang & Lee, 2022) Since the birth of the web, researchers and website developers have always kept in mind a focal question: what is a website’s optimum structure and content for attracting the web users’ interest and preferences? (Velásquez et al., 2005). The answer is not easy, and many efforts have been developed over the years. Traditionally, web user behaviour on the web has been studied by using web usage mining techniques (Facca & Lanzi, 2005; Velásquez et al., 2011), where the weblog files, which contain records of web user activities, are processed to extract information and knowledge about their navigation and content preferences. This information is used to improve the site structure and content to provide online navigation recommendations through an automatic recommendation system (Shinde & Kulkarni, 2008). The world of traditional retailing is changing to online retailing—the interest in attracting the consumer's attention with websites that create an impactful and satisfying shopping experience. The arrival of COVID-19 in our lives and social distancing has boosted online sales and the need to create competitive sales websites. The adoption of new technologies on consumer behaviour research aims to understand better what kind of people look at and pay attention to the website/app and the user experience characteristics.
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Methodology
The research involved 39 healthy volunteers (16 males, 22 females, 1 other; average age = 30.72 ± 7.04 years). The sample was recruited considering ‘Millennials’ people (Ryding et al., 2022). Six out of the 39 participants were not considered in the analysis due to technical problems in signal acquisition. Each participant’s eye movements and facial emotions were measured during the study. In particular, the experimental task procedure consisted of watching a series of social media posts (Instagram and Facebook) (Daema, 2022) with images of garments from four wellknown fashion companies (H&M, Tommy Hilfiger, Pull & Bear, Akala), and post and comments about the content of the garments. An advertising spot focused on sustainability (OVS company) was also watched by each participant. Specifically, after providing the consent to participate to the research, participants were asked about their age, gender, education level and income bracket. Then, participants had to look at eight posts, in particular two similar version of a post related to each of the 4 fashion companies aforementioned. One version of the posts contained references to sustainability, whilst the other contained a generic message without any reference to sustainability. The four posts were real, since they were taken from social media (Facebook or Instagram). If the original post did not contain any reference to sustainability, the corresponding version was created by manipulating only the text content (so the picture as well as the comments were taken as the original), and vice versa. Therefore, for each company, the social post was the same in both the versions apart from the text content (‘neutral’ vs. ‘sustainable’). Each image was presented for eight seconds to each subject in a randomised order (for more details, please see the appendix). After viewing these images, an online questionnaire with the following questions was administered to collect information about intention to buy, willingness to pay, quality, and sustainability, for each product: 1. Imagine that you want to buy an item of clothing for yourself or give it as a gift. How interested would you be in buying the dress you see in the post? 2. Imagine that you have (150 - 30 - 60 - 600) euros available. How much would you be willing to pay for this product? 3. How good do you think this product is? 4. How sustainable do you think this product is? After these questions, participants were administered the Lifestyle of Health and Sustainability (LOHAS) questionnaire (Choi & Feinberg, 2021). Finally, the participants were shown a commercial about one minute long focusing on environmental sustainability. It could be an ad with a kind communication style based on a T-shirt’s life cycle or a more blaming spot in which the earth’s narrative voice demanded more care and respect from human beings. At the end of the video, the subjects were asked some questions about what they had just seen:
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Fig. 1 Experimental protocol
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What are the parts of the video you just watched that you remember most? What are the parts you liked the most? What are the parts you liked the least? How much did you like the video from 1 to 10? In general, what topics do you feel best promote sustainability in the apparel industry?
In total, four groups were created: in the first group, posts with sustainable content were proposed first, then those with neutral content, and then the ‘kind’ video; in the second group, posts with neutral content were proposed first, then those with sustainable content, and then the ‘kind’ video; in the third, posts with sustainable content were proposed first, then those with neutral content, and then the ‘blame’ video; in the second, posts with neutral content were proposed first, then those with sustainable content, and then the ‘blame’ video (Fig. 1). The research was conducted using different methodologies such as quantitative, neurophysiological, and psychological metrics. Specifically, eye-movement and emotional reactions whilst viewing different images and videos will be measured using remote technologies. To perform this research, it will use two different platforms: • Qualtrics for the survey • Tobii Sticky Pro for eye-tracker and facial coding recognition For the eye-tracking measurements, a calibration session before the specific task was conducted, to precisely tune the participant’s video camera to participant’s specific eye movements. Participants was asked to look at specific points on the screen, also known as calibration dots, whilst the eye-tracking algorithm measures several characteristics of the participant’s eyes. This information is then used to calculate the eye gaze data. Specific conditions for lights and posture of the head were checked before the starting of the eye and emotion data collection, to remove any possible artefacts. In addition to these eye-tracker measurements, it was also possible to assess the emotional engagement of the respondents during the execution of the proposed task. The seven dimensions of emotion were explored: disgust, fear, joy, perplexity, sadness, surprise, and neutrality. These dimensions were divided into two groups:
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positive mood and negative mood. Mood describes the intensity of positive emotions and negative emotions, respectively. Positive emotion is referred to as the intensity of joy, whilst negative mode is the intensity of the negative emotion with the highest intensity. Anger/puzzlement, fear, sadness, and disgust are considered negative emotions. The acquisition of these emotions occurred through a facial recognition system of the participant’s face using the video camera of the PC. In this way, it was possible to describe the emotions felt by the participants through the proposed experimental task.
2.1
Eye-Tracker
For each image, it was possible to get information about the emotion and visual attention. For the eye-tracker metrics, each image in test was divided into several areas of interest (AoI), e.g. different sections of the image that have a specific meaning for the participant (for instance the product name, logo, image referred at the sustainable information, and product). Qualitative and quantitative eye metrics have been considered for the analysis as described below: • Heat maps based on fixations, related to each image to understand the visual attention distribution on the image. • Time to first fixation (TTFF): indicating the amount of time in seconds that it takes a participant to look at a specific AOI from stimulus onset. • Time viewed, seconds. The average amount of time that a respondent spends on an AOI. • Percentage of fixations (%F): indicating the percentage of fixations spent on a specific AOI.
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The Facial Coding Data
For the emotion, the automatic facial coding capability in Sticky by Tobii Pro, thanks to the webcam, helps to detect the participant’s facial expressions whilst they watch the stimuli and Sticky returns the probability distribution of each of the six universal emotions (puzzlement, disgust, fear, joy, sad, and surprise). Using emotion analysis in conjunction with eye-tracking uncovers not just what people are feeling towards the stimuli, but exactly what they are looking at on the screen when they feel that emotion. Specifically, they identified six core emotions, which Ekman termed universal emotions: these original universal emotions are: • Anger/puzzlement—symbolised by eyebrows lowering, lips pressing firmly, and eyes bulging
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• Fear—symbolised by the upper eyelids raising, eyes opening, and the lips stretching horizontally • Sadness—symbolised by lowering of the mouth corners, the eyebrows descending to inner corners, and the eyelids drooping • Disgust—symbolised by the upper lip raising, nose bridge wrinkling, and cheeks raising • Joy—symbolised by raising of the mouth corners (an obvious smile) and tightening of the eyelids • Surprise—symbolised by eyebrows arching, eyes opening wide, and the jaw dropping slightly These emotions were divided into two groups: positive mood and negative mood. Mood describes the intensity of positive emotions and negative emotions, respectively. Positive emotion is referred to as the intensity of joy whilst negative mode is the intensity of the negative emotion with the highest intensity. Anger/puzzlement, fear, sadness, and disgust are considered negative emotions.
2.3
Data Analysis
Three t-tests were performed for the eye-tracker results. Particularly, a t-test was performed for the TTFF to compare the neutral with the sustainability posts. A t-test was performed for the time viewed to compare the neutral with the sustainability posts. A t-test was performed for the % fixation to compare the neutral with the sustainability posts. Two t-tests were performed for the emotion results. Particularly, a t-test was performed for the positive mood to compare the neutral with the sustainability posts. A t-test was performed for the negative mood to compare the neutral with the sustainability posts. Four t-tests were performed for the declared statements. Particularly, a t-test was performed for the intention to buy to compare the neutral with the sustainability posts. A t-test was performed for the willingness to buy to compare the neutral with the sustainability posts. A t-test was performed for the perceived quality to compare the neutral with the sustainability posts. A t-test was performed for the perceived sustainability to compare the neutral with the sustainability posts. Two independent samples t-test with two tails was performed for the positive mood to compare two sustainability videos.
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Results
3.1
Eye-Tracker
3.1.1 Social Media Posts Regarding the measurements conducted by eye-tracking, the analyses showed a tendency for subjects to take less time to first fixation (TTFF) when placed in front of sustainable posts compared to neutral posts ( p = 0.07) (Fig. 2). As it is possible to observe in the following image, in addition to the distribution of visual attention (heat map) it is possible to observe that Tommy’s sustainable post (on the right) captures attention on average after 2 gazes, whilst the neutral one after 3 (Image 1). In addition, a significant effect was found in the time viewed and the % fixation. On average, subjects stared longer (seconds) ( p = 0.0001) and with a higher % fixation ( p = 0.0004) at sustainable posts than neutral posts (Fig. 3). Unfortunately, eye-tracker results for the videos could not be analysed due to technical problems. As the recordings were made online, there was no control by the experimenter.
Fig. 2 The graph shows the TTFF results by the experimental group in the two posts’ groups (neutral and sustainable)
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Image 1 The image shows the gaze plot of the two Tommy posts: on the left the neutral post and on the right the sustainable post
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Fig. 3 The graphs show the time viewed (on the left) and % fixations(on the right) results by the experimental group in the two posts’ groups (neutral and sustainable) Negative Mood 0.13
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Fig. 4 The graph shows the negative mood results by the experimental group in the two posts’ groups (neutral and sustainable)
0.125 0.12 0.115 0.11 0.105 0.1
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Face Reader
3.2.1 Social Media Posts Emotionally, on the other hand, there were no significant differences in experiencing a positive mood whilst viewing neutral and sustainable posts. However, there was a tendency for subjects to experience less negative emotions whilst viewing sustainable posts compared to neutral posts ( p = 0.12) (Fig. 4). Finally, regarding answers given through questionnaires, no significant differences were found in the answers provided by viewing neutral posts or those with content about sustainability. 3.2.2 Videos Regarding the measurements conducted by facial reading, the analyses showed a significant effect for a positive mood between the two different videos ( p < 0.001). The video with a ‘kind’ style was perceived with a higher positive mood then ‘blame’ style (Fig. 5).
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Positive Mood 0.2
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Fig. 5 The graph shows the positive mood results by the two different experimental groups in the two videos
0.15 0.1 0.05 0 -0.05 -0.1
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Fig. 6 The graph shows the liking results by the two different experimental groups in the two videos
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Considering the questionnaire, the two samples ranked the two videos in different ways: the ‘kind’ video obtained significant higher values ( p = 0.03) than the second one (Fig. 6).
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Discussion
4.1
Fashion Industry
Growing awareness of the fashion industry’s negative impact on people and the environment has led to considerable growth of the sustainable fashion market. Currently, fashion companies must not only face the challenges posed by high market unpredictability, but they must also adapt to a new business context that is increasingly focused on sustainability issues due to the consumers’ increased sensibility about and awareness of green and social concerns (De Brito et al., 2008; Gam, 2011; Hill & Lee, 2012). Therefore, many companies are undertaking a green and social transformation to respond to requests for more sustainable processes and products and to ensure that their partners, at every level of the supply chain, operate under responsible working conditions (De Brito et al., 2008; Turker & Altuntas, 2014). How companies communicate this responsibility could impact on the relationship with their clients.
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Green Marketing
Even though companies now have more opportunities to share data about their social and environmental practices with final customers than they had in the past, such information is still lacking. Only a few companies are in fact efficiently adopting web-based communication aimed at sensibly informing their stakeholders about their good sustainable behaviour, thereby achieving alignment between what they internally implement and what they externally communicate (Adams & Frost, 2006). In addition, it must be considered that the consumer is increasingly informed, demanding, and concerned about sustainability. Communicating this aspect by the company can create a competitive advantage over competitors. However, there is also a need for effective communication.
4.3
Eye-Tracking and Face Reader
This study has shown that social media posts that contain sustainable content are seen sooner and are read for longer and with more attention. They are also able to generate a less negative mood than neutral ones. Regarding the communication style of an advertisement, considering a gentler (soft) style versus a more aggressive style (in terms of music, tone of voice, and content), millennials (sample considered in this research) like a gentler style, with a softer tone of voice (female voice) with topics covered related to circularity and, specifically, recycling a new T-shirt. A more aggressive tone of voice in which they talk about what humans sometimes do to the earth (disrespect) is perceived as a threat.
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Conclusion
The results underline how, on the part of companies in the fashion industry, communication that considers concepts such as the circular economy and environmental sustainability can have a significant effect on consumers, leading to changes in how they interface with these kinds of products. Through tools capable of detecting the state of the consumer and based on technologies that exploit pupillary movement and automated facial expression analysis, it was, therefore, possible to learn about subjects’ attitudes towards sustainable communication even beyond the conscious awareness of such attitudes. From what emerged, taking eco-sustainability into account when advertising clothing favours visual attention towards the productrelated message and is able to act by tending to reduce the negative mood of the subjects. Despite this, the study leaves some limitations, especially in the numerosity of the sample (in particular for the videos stimuli) although neuromarketing studies consider a smaller sample size than traditional market research (Vozzi et al., 2021). This leaves the way open to the possibility of further deepening through (1) the use of a more significant number of subjects or (2) a comparison with different countries (cross-cultural study) with different sensitivity to the issue of sustainability and
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(3) the use of additional methodologies available to neuroscience, particularly neuromarketing ones (like EEG). The research, thus, allows us not only to increase the body of knowledge in the field of sustainable communication in the fashion sphere but also to highlight how, in a world in which social communication and environmental awareness are progressively more central, it is increasingly important to focus on their possible interactions and the effect these may have on the consumers.
Appendix Materials
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Link video_1 ‘Kind style’: https://www.facebook.com/OVS/videos/6738217405533 82 Link video_2 ‘blame style’: https://www.facebook.com/OVS/videos/714604989568814
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The Influence of Sensory Marketing on Consumers with Different Characteristics Regarding Physical Store Shopping Enshang Shang, Gianpaolo Vignali, and Claudia Henninger
Abstract
The retail industry is highly exposed to the revolutionary changes imposed by the acceleration of digitalisation; it is an inevitable challenge for traditional physical stores in light of online channels continuing to grow and increasing market competition (Biron, The last decade was devastating for the retail industry. Here’s how the retail apocalypse played out, https://www.businessinsider.com/ retail-apocalypse-last-decade-timeline-2019-12, 2022; Kumagai & Nagasawa, Asia Pacific Journal of Marketing and Logistics, 34:1809, 2021). In response to this situation, it is essential to provide both theoretical and practical research support to help retailers elevate the offline shopping experience and win the heart of customers (Gauri et al., Journal of Retailing, 97:42–61, 2021). An enjoyable shopping experience is identified as a significant factor for consumers to choose physical store shopping over online shopping (Duong et al., Journal of Consumer Marketing, 39:218–229, 2022). More importantly, consumers’ passion and need for the physical store experience are not eliminated in the last decade (Creswell, The incredible shrinking sears (Published 2017), Nytimes.com, 2017; Kumagai & Nagasawa, Asia Pacific Journal of Marketing and Logistics, 34:1809, 2021; Mintel, Beauty and personal care retailing—UK—2022: Consumer market research report | Mintel.com, 2022; PwC, Total retail survey: 10 retailer investments for an uncertain future, https://www.pwc.com/gx/en/industries/ assets/total-retail-2017.pdf, 2017). Even after COVID-19, when online shopping became compulsory during the period of lockdown, nearly half of the shoppers stated that they still prefer to shop cosmetics in the physical store, due to their ability to feel the product in real life (Eroglu et al., Journal of Retailing and E. Shang · G. Vignali (✉) · C. Henninger Department of Materials, University of Manchester, Manchester, UK e-mail: [email protected]; [email protected]; [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_12
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Consumer Services 64:102760, 2022; Mintel, Beauty and personal care retailing—UK—2022: Consumer market research report | Mintel.com, 2022; Wang et al., Frontiers in Psychology, 12:829696, 2022). Prior research on the physical store experience has concentrated on the influence of store atmosphere; sensory marketing; on the other hand, has been shown in recent studies to be important in providing a better consumer shopping experience (Duong et al., Journal of Consumer Marketing, 39:218–229, 2022; Shahid et al., Psychology & Marketing, 39:1398, 2022). Using sensory marketing to engage the customer through five sensations (visual, sound, smell, touch, and taste) is the unique advantage of physical store compared to online shopping; organisations could create an emotional bond between consumer, products, and services, rather than on a rational level only (Biswas, Journal of Retailing, 95:111–115, 2019; Hultén, Sensory Marketing, 1–23, 2015; Hultén et al., Sensory Marketing, 1–23, 2009; Hussain, International Journal of Management Studies, 2:32, 2018; Roy et al., Journal of Marketing Management, 36:299–333, 2020; Shahid et al., Psychology & Marketing, 39:1398, 2022; Yoganathan et al., Journal of Business Research, 96:386–396, 2019). The research aim of this study is to examine the impact of sensory marketing strategies on consumer in-store shopping experience, evaluate, and identify how consumers with different characteristics have different reactions and preferences on sensory marketing strategies. Retailers could provide better physical engagement to create customer value when selling deep products – that require ample inspection to make an informed decision (Zhang et al., Journal of Marketing, 86:166–185, 2021). Physical encounters are intimately linked to an individual’s five senses; using sensory marketing to engage them is the unique advantage of in-store experience compared to online shopping (Reid et al., International Journal of Business and Globalisation, 17:364–383, 2016; Vignali et al., International Journal of Business and Globalisation 13:387–418, 2014; Vignali & Reid, Technology driven sustainability: Innovation in the fashion supply chain, Springer, 2014); organisations could create an emotional bond between consumers, products, and services, rather than on a rational level only (Biswas, Journal of Marketing, 56:57, 2019; Hultén, Sensory marketing, Routledge, 2015; Krishna, Customer sense—how the 5 senses influence buying behavior, Palgrave Macmillan, 2013; Kumagai & Nagasawa, Asia Pacific Journal of Marketing and Logistics, 34:1809, 2021; Labrecque, Psychology & Marketing, 37:1013–1018, 2020). Especially for luxury stores, which promise a sensorial shopping experience (Joshi & Garg, International Journal of Consumer Studies, 45:259–272, 2021), the multisensory dimension serves as an integral feature of luxury brands and their related strategies (Shahid et al., Psychology & Marketing, 39:1398, 2022). Keywords
Sensory marketing · Physical store · In-store shopping · Cosmetics
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Introduction
The retail industry is highly exposed to the revolutionary changes imposed by the acceleration of digitalisation; it is an inevitable challenge for traditional physical stores in light of online channels continuing to grow and increasing market competition (Biron, 2022; Kumagai & Nagasawa, 2021). In response to this situation, it is essential to provide both theoretical and practical research support to help retailers elevate the offline shopping experience and win the heart of customers (Gauri et al., 2021). An enjoyable shopping experience is identified as a significant factor for consumers to choose physical store shopping over online shopping (Duong et al., 2022). More importantly, consumers’ passion and need for the physical store experience are not eliminated in the last decade (Creswell, 2017; Kumagai & Nagasawa, 2021; Mintel, 2022; PwC, 2017). Even after COVID-19, when online shopping became compulsory during the period of lockdown, nearly half of the shoppers stated that they still prefer to shop cosmetics in the physical store, due to their ability to feel the product in real life (Eroglu et al., 2022; Mintel, 2022; Wang et al., 2022). Prior research on the physical store experience has concentrated on the influence of store atmosphere; sensory marketing, on the other hand, has been shown in recent studies to be important in providing a better consumer shopping experience (Duong et al., 2022; Shahid et al., 2022). Using sensory marketing to engage the customer through five sensations (visual, sound, smell, touch, and taste) is the unique advantage of physical store compared to online shopping; organisations could create an emotional bond between consumer, products, and services, rather than on a rational level only (Biswas, 2019; Hultén, 2015; Hultén et al., 2009; Hussain, 2018; Roy et al., 2020; Shahid et al., 2022; Yoganathan et al., 2019). The research aim of this study is to examine the impact of sensory marketing strategies on consumer in-store shopping experience, evaluate, and identify how consumers with different characteristics have different reactions and preferences on sensory marketing strategies. Retailers could provide better physical engagement to create customer value when selling deep products—that require ample inspection to make an informed decision (Zhang et al., 2021). Physical encounters are intimately linked to an individual’s five senses; using sensory marketing to engage them is the unique advantage of in-store experience compared to online shopping (Reid et al., 2016; Vignali et al., 2014; Vignali & Reid, 2014); organisations could create an emotional bond between consumers, products, and services, rather than on a rational level only (Biswas, 2019; Hultén, 2015; Krishna, 2013; Kumagai & Nagasawa, 2021; Labrecque, 2020). Especially for luxury stores, which promise a sensorial shopping experience (Joshi & Garg, 2021), the multisensory dimension serves as an integral feature of luxury brands and their related strategies (Shahid et al., 2022). Sensory marketing is further classified into 10 variables in this study: stimulus from physical store design (visual store, smell store, sound store, touch store, and taste store) and stimulus from retailing staff service (visual staff, smell staff, sound staff, touch staff, and taste staff). This study investigated the consumer need by segmentations—comparison studies between consumers with different shopping orientation, shopping frequency, consumption level, and age group, to provide a
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deeper understanding of consumer preference. To achieve the research aim, this study conducted a survey with 600 female consumers who have shopping experiences in luxury department stores in the UK. A detailed insight of consumer comparison analyses will help companies understand their targeted consumer needs and then tailor their sensory marketing strategies to achieve desired outcomes.
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Literature Review
2.1
Sensory Marketing In-store
Marketers use sensory strategies to build a store atmosphere that differentiates products and services, approaching the mind and the consumer’s senses, both from a cognitive and emotional perspective (Evans et al., 2013; Joshi & Garg, 2021; Spence, 2022; Vignali & Vignali, 2009; Vignali et al., 2010). When increasing the number and level of sensory stimulation, more positive emotions and perceptions were recorded from individuals (Duong et al., 2022). Although the booming development of the online shopping context diminishes consumer interest and loyalty to brick-and-mortar stores, the physical store experience remains irreplaceable, because not all the senses can be completely engaged online (Nghiêm-Phú, 2017; Spence, 2022; Tyler, 2018). This allows marketers and retailers to concentrate on providing sensory opportunities that may attract customers to visit their physical stores through successful experiential marketing activities (Blazquez et al., 2019; Labrecque, 2020). For example, cosmetic brands hold the new product launch event in-store to invite consumers to try on the new products in person and had makeup artists teach consumers how to apply the products for different occasions (Head, 2017). Technology plays a key role in developing this experience (Vignali et al., 2019; however, in the real world, brands will create multisensory consumer interactions that cannot be reproduced digitally (Barros et al., 2019; Biswas, 2019; Duong et al., 2022; Labrecque, 2020). Sensory stimuli have an impact on retail environments, improve customers’ shopping experience, and change the nature of purchase behaviour in multi-way beyond our consciousness (Rodas-Areiza & Montoya-Restrepo, 2018; Soars, 2009; Spence, 2022); as the shopping context is not the consumption context, consumers learn about products not only through direct product experiences but also through mental simulations of consumption situations during prepurchase deliberation (Joshi & Garg, 2021; Kim et al., 2016). A retail environment consists of the external actors and forces that affect the retailers’ ability to develop and maintain successful transactions and relationships with its target customers; its typicality defines the degree to which kind of store atmospheric matches consumers’ expectations (Babin & Babin, 2001; Barros et al., 2019; Duong et al., 2022; Jackson et al., 2011; Kotler, 1973). In the face of rising competition, retail industry marketers have launched an innovative set of stimuli in the retail environment designed to have a positive effect on customers, increasing the shopping frequency and lengthening the duration of consumers’ shopping trips (Borges et al., 2015; Burke, 2002). Customers who stay
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longer are more likely to spend money, and the longer they dwell the more they spend; thus, an effective retail environment can influence the shopper’s propensity to spend (Barros et al., 2019; Borges et al., 2015; Soars, 2009).
2.1.1 Physical Store Design The effects of store atmospherics on consumer purchase decision-making, which is ‘using atmospherics as a marketing tool’, have long been recognised in the academic literature (Bitner, 1992; Kotler, 1973). It is almost half a century now since Kotler (1973) stated that atmosphere is a particular set of surroundings that is described in sensory terms, including sight, sound, scent, and touch. Later, studies have shown that retailers increasingly acknowledge the positive impact of retail atmospherics on shopping behaviour (Chebat & Michon, 2003; Hultén, 2015; Soars, 2009; Stoel et al., 2004). However, prior research was heavy on anecdote and illustrative example from the marketplace, but short on rigorous peer-reviewed empirical research (Spence, 2022). As retail experiences have become more important, the store environment has taken on a greater significance, providing spaces for interactivity, socialisation, and communication. An effective store environment may increase shopping value and induce consumers to exhibit increased purchase behaviours and stay longer in the store (Manzano et al., 2019; Stoel et al., 2004). An effective retail environment can command consumers’ attention and mediate their inferences about merchandise, service quality, and store image (Baker et al., 1994; Manzano et al., 2019). The design of the store atmosphere creates an environment that affects shoppers’ emotions and behaviour by emphasising the sensory qualities, to attract customer interest and response, as well as generate a positive shopping experience (Spence, 2022; Spence et al., 2014). With the development of modern retailing, taste sense has been introduced to the store as the fifth dimension of store atmosphere (Hultén, 2015; Lund, 2015; Perumal et al., 2021). The involvement of multiple senses can have a multiplier effect on consumer perceptions when each sensory stimulus reinforces the messages (Kim et al., 2016; Manzano et al., 2019). Previous research has shown that retail atmospherics may influence consumers’ current store behaviour, as well as their future shopping behaviour (Carter, 2013; Khan, 2016; Perumal et al., 2021; Spence, 2022; Turley & Milliman, 2000). Therefore, from the perspective of organisations, they want to use a retail environment to create an attractive and delightful store atmosphere. This research investigates how to deliver a positive shopping experience to satisfy the target consumer’s expectation in the luxury cosmetic context. 2.1.2 Retailing Staff Service Retailing staff work as social cues in the shopping environment have a significant positive effect on consumers’ emotion of pleasure and behavioural response (Satti et al., 2019). The degree of discrepancy between consumer general expectation for service and their perceptions of service performance is how the consumers evaluate service quality (Alhedhaif et al., 2016; Baker et al., 1994; Errajaa et al., 2022). In the context of the cosmetic industry, the retailing staff service quality relates to the
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professional skill and attitude of the sales personnel (Alhedhaif et al., 2016; Satti et al., 2019). For example, the retailing staff of the cosmetic industry is required with professional skills to help customers evaluate products, such as makeup, facial treatment, massage, hairstyling, and so on. Krishna (2013) discovered that when the senses are congruent in some way, they amplify each other. Such factors are subtle, which is why they are so effective. Consumers do not recognise them as marketing messages, so they do not respond the way they usually do to advertisements and other promotions. Therefore, the multisensory service provided by the retailing staff cannot be ignored, because consumers will not solely remember the sensory experience from the physical store design. Past studies in the sensory marketing area generally focus on sensory stimuli solely from objects like the physical design of store layout and decoration (e.g. Hultén et al., 2009; Parsons, 2011; Soars, 2009; Wade Clarke et al., 2012). The service of retailing staff has been considered as social characters in the retail environment that positively impacts satisfaction, relational variables, and satisfaction mediating effects (Chang et al., 2011; Errajaa et al., 2022), but has not been discussed as sensory stimulus in the sensory marketing domain. Social factors are less easily manageable for practitioners, which represent a growing interest for researchers (Eroglu et al., 2022) due to the social role that physical stores play compared to their virtual counterparts (Errajaa et al., 2022). People can play a major role in the whole shopping experience and have an impact on the decision-making process; this research gap is investigated in the following sections.
2.2
Consumer Characteristics
Understanding the consumer characteristics is the key to success in business: how to segment consumers and tailor specific strategies for them (Baptista, 2020; Gupta & Mukherjee, 2022; Kotler & Armstrong, 2012). According to Kotler and Armstrong (2012) consumer purchasing behaviour is influenced by several factors, as follows: • Cultural: variables related to the values, perceptions, religion, ethnic groups, and social class that the individual is inserted • Social: involving reference groups, family, social roles, and positions • Personal: they reflect the characteristics of people, such as age, occupation, economic condition, lifestyle, and personality • Psychological: the motivations, desires, and perceptions that lead the consumer to choose a certain product or service, combined with his needs at that moment and the position (positive or negative) of the consumer in relation to the consumption choices How to leverage the different factors that influence consumer purchasing behaviour to effectively market products and maximise sales is the goal of marketers (Durmaz, 2014). Consumers purchase different products and services according to their needs, preferences, and buying power (Lakshmi & Babu, 2019). For
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fashion-related products and cosmetics, personal factors like age and economic condition have a significant influence on consumer purchasing behaviour (Alhedhaif et al., 2016; Baptista, 2020; Eze & Bello, 2016). Moreover, the motivation amongst psychological factors is the activated internal need state leading to goal-oriented behaviour to satisfy that need (Durmaz, 2014). Consumers’ orientation towards shopping in general might have a significant influence on their behaviour (Gupta & Mukherjee, 2022; Scarpi, 2020). On the other hand, consumers with different perceptions on cosmetics will significantly affect their purchasing behaviour; for example, a consumer who is a cosmetic enthusiast and who just buys cosmetics for basic needs may have different emotional and behavioural responses to marketing activities (Lakshmi & Babu, 2019). Therefore, consumers’ individual characteristics need to be considered thoroughly as it will vary from one customer to another (Kondo & Okubo, 2022). This research targets female cosmetic consumers in the UK market and will further investigate their consumer characteristics from four aspects: consumer orientation, cosmetic consumption level, cosmetic shopping frequency, and age group.
2.2.1 Consumer Orientation: Utilitarian and Hedonic Consumer purchasing orientation and shopping motivation have been studied in the literature as a potential driver of consumers’ intention to visit a store and to distinguish consumer’s individual behaviour (Hidalgo-Baz et al., 2017; Ngoh & Groening, 2022; Scarpi, 2020). Therefore, consumers are typically classified by two shopping orientations: ‘utilitarian’ and ‘hedonic’ (Ferraro et al., 2016; Holbrook & Hirschman, 1982; Scarpi et al., 2014). In the physical store, the retailing staff would be able to identify the consumer’s motivation and assist them accordingly, but this is difficult for online shopping (Scarpi, 2020). • Utilitarian-Oriented Consumer Utilitarian consumers are, in terms of a functional, instrumental, rational type, who care more about practical purpose and efficiency (Adomaviciute, 2014; Scarpi, 2020; Scarpi, 2021). When a consumer is concentrated on achieving a functional need, this is known as utilitarian motivation (Chang et al., 2011). For consumers with task-oriented purposes, a good shopping experience entails the customer’s perception of comfort and usefulness as a result of achieving practical objectives (Adomaviciute, 2014; Ngoh & Groening, 2022). They prefer a simple, convenient, pleasant shopping experience and quick access to accurate product details (Celik, 2011; Scarpi, 2020). • Hedonic-Oriented Consumer Unlike task-oriented shopping, consumers tend to pursue utilitarian motives; hedonism is the festive and ludic side of shopping, which goes beyond solely desire of products; it is related to enjoyment and playfulness, to seek out experiences that help to reduce stress and anxiety (Sullivan & Heitmeyer, 2008; Wagner & Rudolph,
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2010; Adomaviciute, 2014; Scarpi, 2021). Hedonic consumption includes those behavioural aspects related to multisensory, fantasy, and emotional consumption, which are driven by benefits such as entertainment and fun in using the product and aesthetic appeal (Holbrook & Hirschman, 1982; Soars, 2009; Barbopoulos & Johansson, 2016), suggesting that the experience of the purchase may be more important than the acquisition of the product (Kim et al., 2016). Because hedonic consumption would seem to provide an opportunity not only for approaching fun and excitement but also for avoiding problems and stress in everyday life (Arnold & Reynolds, 2012; Barbopoulos & Johansson, 2016). The new focus on sensory and emotional experience according to psychological research finds that people prefer additional experiences to additional possessions as their incomes rise (Solomon et al., 2019). As such, since modern society is a more intensive and stressful context than the past, consumers’ needs of hedonic value from shopping experience may increase to even more variety (Scarpi, 2020). Nowadays, shopping is no longer only focused on purchasing goods; it becomes a decompression method in modern daily life (Krishna, 2013).
2.2.2 Consumption Level Personal economic condition determines its purchasing power, for example, the higher income level, the more will be the expenditure on various products, and vice versa (Eze & Bello, 2016; Lakshmi & Babu, 2019). However, a higher income cannot indicate a higher spending on a specific product type, such as people with a high income, but the need to pay for a mortgage may have a limited budget on other expenditures. Therefore, the discretionary personal income is the income left after meeting all the necessities of life basic needs, which is used for the purchase of luxury products and services (Lakshmi & Babu, 2019). As consumers may have different needs on allocating spending (Eze & Bello, 2016), this research will focus on the cosmetic consumption level of a consumer, which means how much they spent on cosmetics according to their needs and preferences. 2.2.3 Shopping Frequency Consumers who visit the physical store more, whether they make purchases there or not, are looking for the shopping experience that makes them enjoy the act of shopping itself (Krishna, 2013; Cachero-Martínez & Vázquez-Casielles, 2018; Ngoh & Groening, 2022). Moreover, shopping orientations generally increased with shopping frequency (Evans et al., 2022). Consumers with different shopping frequency suggest having different shopping orientation and preference; for example, more frequent shoppers tend to be more hedonic-oriented (Cachero-Martínez & Vázquez-Casielles, 2018). Consumers who have a hedonic orientation are pursuing an activity that they do not take as a task, and that they find personally gratifying. These consumers desire to derive richer and fuller experiences from the activity, which facilitates a greater engagement (Kaltcheva & Weitz, 2006; Vieira & Torres, 2014). A higher shopping frequency of cosmetics indicates consumption needs; for example, over 44% UK consumers shop skin care products once a month or shorter (Statista, 2020), and over 31% UK consumers buy makeup products at least once a
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month (Statista, 2020). Young women aged 16–24 are the most frequent beauty products buyers according to the latest Mintel report (Mintel, 2022).
2.2.4 Age Group People change their shopping habits in the course of time, as the needs will be different during different life-cycle stages (Kotler & Armstrong, 2012; Boardman & McCormick, 2019); therefore, design marketing strategies based on consumer segmentations are an effective approach (Kondo & Okubo, 2022). The age of a consumer significantly influences his/her behaviour, including the consumer purchase options, the motivation of purchase, and the decision to buy a product will change (Eze & Bello, 2016). For the cosmetics consumption, the consumers’ needs and preferences will change with their age growth. For example, they will have different skin concerns and conditions; their aesthetic standard on sensory experience will change over time as well. Consumers from different age groups may react differently to the sensory marketing stimulus (Xu & Cliquet, 2013; Jeong et al., 2017; Boardman & McCormick, 2019; Dash et al., 2021).
3
Methodology
Due to the dearth of primary quantitative data analysis of sensory marketing in the fashion sector, especially for the luxury physical store context, a questionnaire data collection approach is selected to test hypotheses and answer research questions. Regarding the influence of sensory marketing stimuli to consumer cosmetic shopping experience. According to the research context, the target female consumer will be those who have cosmetic shopping experience in physical department stores like Selfridges, Harvey Nichols, Harrods, etc. in the UK. The questionnaire was distributed by the professional data collection agency Qualtrics. The market research panel of Qualtrics is a group of people recruited to respond to a survey through online distribution. They are typically chosen from a pre-arranged pool of respondents who’ve agreed to be contacted by a market research service to respond to surveys. With many participants to choose from, Qualtrics provides a more comprehensive data collection for market research studies to specific demographics or audience groups. As the respondents have already agreed to be part of a panel, online samples tend to achieve higher response rates. As Qualtrics automatically disposed of incomplete surveys, this study received 672 complete responses in total. Furthermore, 72 responses were discarded as invalid data due to repetitive answers throughout the questionnaire. Therefore, the effective response rate is 89%; the valid sample size is N = 600 females in total with ages ranging from 18 to 50 years to provide a solid database.
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Data Analysis and Finding
This research conducted several quantitative analysis techniques through SPSS to analyse the data. First of all, a reliability test was run to determine the validity of the data. Tested variables are ten sensory marketing factors. The result reveals that there are 600 responses in total; 100% is valid. Secondly, a Cronbach’s alpha test was conducted to see if multiple question Likert-scale surveys are reliable. In general, a score of more than 0.7 is acceptable. According to the Reliability Statistics output, the Cronbach’s alpha is 0.804, which indicates the reliability of this data is good; there is a high level of internal consistency with this specific sample. After confirming the validity and reliability of data, this study executed comparison analysis amongst different age groups, shopping frequency groups, consumption level groups, and shopping orientation groups, to determine whether there is significant difference between or within groups. Specifically, this study uses independent samples T test to examine groups with two variables and use one-way ANOVA test to analyse groups with three variables. An overall outline of this section is summarised in Table 1:
4.1
Shopping Orientation
Participants are categorised by shopping orientation into two groups (Fig. 1): Hedonic consumer (care about the enjoyment and pleasure experiences)—298 participants, which takes 49.67% of 600 participants in total, and utilitarian Table 1 The outline of groups’ comparison analysis Testing variables • Visual store • Visual staff • Smell store • Smell staff • Sound store • Sound staff • Touch store • Touch staff • Taste store • Taste staff
Grouping variables Shopping Orientation Cosmetic Consumption Level
Cosmetic Shopping frequency (in-store)
Age group
Hedonic Utilitarian Spending more (£200+) Spending less (0– £199) Once every 3 months or longer Once a month Twice a month or shorter Young (18–30) Middle (31–40) Mature (41+)
Analysis • Independent Samples T test • Crosstabulation
• One-way ANOVA test • Crosstabulation
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Fig. 1 Consumers with different shopping orientation
Fig. 2 Hedonic consumers’ opinions on the rank of sensory marketing stimuli
consumer (care about efficiency and practical needs)—302 participants, which takes 50.33%. The mean result of consumer responses represents the average score of how important the influence of each sensory marketing stimuli is to consumer cosmetic shopping experience, from 1 – very unimportant to 5 – very important.
4.1.1 Hedonic Consumer Regarding hedonic consumers’ opinions, all ten sensory marketing stimuli are sorted by the importance level from high to low in Fig. 2. To hedonic consumers the most important sensory marketing factor is ‘touch store’, which is the touch setting in the
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physical store design (i.e. product testers and makeup tools). They care about the trying-on process of products and the tactical experience.
4.1.2 Utilitarian Consumer According to utilitarian consumers’ opinions, the ranking of sensory marketing stimuli by the importance level from high to low is presented in Fig. 3. To consumers with utilitarian shopping orientation, the most important sensory marketing stimulus is ‘visual store’, which is the visual setting (i.e. counter design, product display, and lighting) in the physical store. They care about the visual design and sight experience. 4.1.3 Comparison between Hedonic and Utilitarian Consumers To compare the result of hedonic consumer and utilitarian consumer, the figure of two groups’ opinions is summarised in Fig. 4: According to the figure, the hedonic consumer has a higher score than the utilitarian consumer in all ten sensory marketing stimuli, which indicates that sensory marketing has more influence on hedonic consumers for cosmetic in-store shopping overall. Multisensory experience and service is more important to hedonic consumers than utilitarian consumers. First of all, the null hypothesis is set as below: • H0: regarding the influence of each sensory marketing factor, there is no significant difference between two shopping orientation groups, hedonic consumer and utilitarian consumer.
Fig. 3 Utilitarian consumers’ opinions on the rank of sensory marketing stimuli
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Shopping Orientation
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Fig. 4 Comparison between hedonic and utilitarian consumers Table 2 The summary of shopping orientation comparison Sensory stimuli Sound staff Visual store Visual staff Smell store Touch store Taste store Touch staff Taste staff Smell staff Sound store
Comparison result No significant difference No significant difference No significant difference No significant difference Have a significant difference Have a significant difference Have a significant difference Have a significant difference Have a significant difference Have a significant difference
More important to
Hedonic consumer Hedonic consumer Hedonic consumer Hedonic consumer Hedonic consumer Hedonic consumer
The independent samples test to test the null hypothesis and determine whether there is a significant difference between two groups. Regarding the influence of sensory marketing to hedonic consumer and utilitarian consumer, there are four factors that do not have a significant difference between two groups: ‘sound staff’, ‘visual store’, ‘visual staff’, and ‘smell store’. Moreover, there are six sensory marketing factors that do have significant difference of influence between two groups: ‘touch store’, ‘taste store’, ‘touch staff’, ‘taste staff’, ‘smell staff’, and ‘sound store’. In conclusion, the comparison result between hedonic consumer and utilitarian consumer is summarised in Table 2; they have significant different opinions on sensory stimuli that are highlighted in bold: The result indicates that the multisensory shopping experience in-store for cosmetics is more important to hedonic consumers. Specifically, they care about the touch store (i.e. product testers), taste store (i.e. serve drinks), touch staff
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(i.e. makeup/facial/massage treatment), taste staff (i.e. have a bartender making fresh cocktails), smell staff (i.e. body odour and breath of sales assistants), and sound store (i.e. background music).
4.2
Cosmetic Consumption Level
Participants are categorised as two cosmetic consumption levels (Fig. 5), according to how much they spend on their daily beauty routine products. First group is consumers with lower cosmetic consumption levels that are willing to spend 0– £199 – 300 participants, which takes 50% of 600 participants in total. The second group is consumers with a higher cosmetic consumption level who are willing to spend over £200 – 300 participants, which takes 50%. The score of how important the influence of each sensory marketing factor is to consumer cosmetic shopping experience ranges from 1 very unimportant to 5 very important. The result is addressed as below:
4.2.1 Consumers with Higher Consumption Level on Cosmetics Regarding the opinion of consumers with higher cosmetic consumption level, all ten sensory marketing stimuli are sorted by the importance level from high to low in Fig. 6. To consumers who spend over £200 on cosmetics for their daily beauty routine, the most important sensory marketing factor is ‘touch store’, which is the touch setting in the physical store design (i.e. product testers, makeup tools). They care about the trying-on process of products and the tactical experience. 4.2.2 Consumers with Lower Consumption Level on Cosmetics Based on the opinion of consumers who are willing to spend less (0–£199) on cosmetic products, all ten sensory marketing factors are ranking by mean score from high to low in Fig. 7. To consumers who spend 0–£199 on cosmetics for their daily
Fig. 5 Consumers with different consumption level on cosmetics
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Fig. 6 The opinions of consumers with higher consumption level on the rank of sensory marketing stimuli
Fig. 7 The opinions of consumers with lower consumption level on the rank of sensory marketing stimuli
beauty routine, the most important sensory marketing stimulus is ‘visual store’, which is the visual setting (i.e. counter design, product display, lighting) in the physical store. They care about the visual design and sight experience.
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4.2.3
Comparison between Consumers with Different Consumption Level on Cosmetics The figure down below merged the result of two groups (Fig. 8), so as to make an initial comparison between different cosmetic consumption level consumers. As shown in the figure, the consumer with higher consumption level has a higher score than the consumer with lower consumption level on all ten sensory marketing stimuli, which implies that sensory marketing has more influence on consumers who are willing to spend more on cosmetic products overall. Meanwhile, multisensory experience and service is more important to higher consumption level consumers than lower consumption level consumers. Nevertheless, in order to determine whether this is a statistically significant difference between two groups, or one that could be caused by random chance, this study will conduct an independent samples test to examine the results as before. Initially, the null hypothesis is set as below: • H0: regarding the influence of each sensory marketing factor, there is no significant difference between two consumption levels groups: consumers that spend less (0–£199) for their daily beauty routine and consumers that spend more (£200+). Regarding the influence of sensory marketing on higher cosmetic consumption level consumer and lower cosmetic consumption level consumer, there are six factors that do not have significant difference between two groups: ‘taste staff’, ‘visual store’, ‘visual staff’, ‘sound store’, ‘smell store’, and ‘smell staff’. In addition, there are four sensory marketing factors that do have significant difference of influence between two groups: ‘taste store’, ‘touch staff’, ‘touch store’, and ‘sound staff’. In summary, the comparison result between consumers with different
Fig. 8 Comparison between consumers with different consumption level on cosmetics
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Table 3 The summary of consumption levels comparison Sensory stimuli Taste staff Visual store Visual staff Sound store Smell store Smell staff Touch staff Touch store Sound staff Taste store
Comparison result No significant difference No significant difference No significant difference No significant difference No significant difference No significant difference Have a significant difference Have a significant difference Have a significant difference Have a significant difference
More important to
Higher consumption level Higher consumption level Higher consumption level Higher consumption level
consumption levels on cosmetics is summarised in Table 3; they have significant different opinions on sensory stimuli that are highlighted in bold: The result indicates that the multisensory shopping experience in-store for cosmetics is more important to consumers with higher consumption level on cosmetics. Specifically, they care about the touch store (i.e. product testers), taste store (i.e. serve drinks), touch staff (i.e. makeup/facial/massage treatment), and sound staff (i.e. sales assistants’ greeting, communication, and recommendation).
4.2.4 Crosstabulation: Consumption Level—Shopping Orientation For consumers who spend £200 and more on their daily beauty routine, the most important sensory marketing factor is ‘touch store’, which is the touch experience setting in store. Moreover, the ranking result is similar to hedonic consumer; only the order of ‘sound staff’ and ‘smell staff’ has switched; the rest is the same. This indicates that consumer with hedonic shopping orientation and consumer with higher consumption level share a similar opinion on the importance ranking of sensory marketing factors. To determine whether there is a superposition between two groups, this research did a crosstabulation. For consumers with lower consumption levels on cosmetic products, the most important sensory marketing factor is ‘visual store’, which is the visual design setting in store. This mean score ranking has a similar result with utilitarian consumer; only the order of ‘smell store’ and ‘touch store’ has switched; the rest is the same. This indicates that consumers who care more about efficiency and practical needs share a similar opinion with lower consumption level consumers on the importance ranking of sensory marketing factors.
4.3
Shopping Frequency
Participants are categorised by cosmetic shopping frequency in-store into three groups (Fig. 9): Consumers shopping once every 3 months or longer (less often)— 158 participants, which takes 26.33% of 600 participants in total; consumers
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Fig. 9 Consumers with different shopping frequency
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Fig. 10 The opinion of consumers with less often shopping frequency
shopping once a month (standard)—245 participants, which takes 41.00%; consumers shopping twice a month or shorter (more often)—197 participants, which takes 32.67%.
4.3.1 Consumers with Less Often Shopping Frequency Regarding the opinion of consumers with less often cosmetics shopping frequency (Fig. 10), all ten sensory marketing stimuli are sorted by the importance level from high to low as the figure down below. For consumers who shop cosmetics once every 3 months or longer, the most important sensory marketing factor is ‘touch
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staff’, which is the touch service of retailing staff (i.e. makeup/facial/massage treatment). They care about the professional skills of sales assistants and the tactile service they provide.
4.3.2 Consumers with Standard Shopping Frequency Regarding the opinion of consumers with standard cosmetics shopping frequency (Fig. 11), all ten sensory marketing stimuli are sorted by the importance level from high to low as the figure down below. For consumers who shop cosmetics once a month, the most important sensory marketing factor is ‘visual store’, which is the visual setting (i.e. counter design, product display, lighting) in the physical store. They care about the visual design and sight experience. 4.3.3 Consumers with More Often Shopping Frequency Regarding the opinion of consumers with more often cosmetics shopping frequency (Fig. 12), all ten sensory marketing stimuli are sorted by the importance level from high to low as the figure down below. For consumers who shop cosmetics twice a month or shorter, the most important sensory marketing factor is ‘visual store’, which is the visual setting (i.e. counter design, product display, lighting) in the physical store. Similarly, they care about the visual design and sight experience like the consumers who shop once a month. 4.3.4
Comparison between Consumers with Different Shopping Frequency Fig. 13 merged the result of three groups, so as to make an initial comparison between consumers with different shopping frequencies.
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Taste Store
2.5 2 1.5 1 0.5 0
Visual Touch Store Store
Smell Store
Visual Touch Staff Staff
Smell Staff
Sound Sound Staff Store
Fig. 11 The opinion of consumers with standard shopping frequency
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Twice a month or shorter 4.5 3.98 4
3.95
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3.75
3.74 3.32
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Smell Store
Visual Touch Staff Staff
Smell Staff
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Taste Staff
Taste Store
Taste Store
Taste Staff
Fig. 12 The opinion of consumers with more often shopping frequency
Shopping Frequency 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 Smell Store
Visual Store
Visual Staff
Touch Store
Twice a month or shorter
Touch Staff
Smell Staff
Once a month
Sound Staff
Sound Store
Once every 3 months or longer
Fig. 13 Comparison between consumers with different shopping frequency
As shown in the column diagram, the most important sensory marketing factor for consumers is that shopping once a month and consumers shopping twice a month or shorter are the same, which is ‘visual store’. However, the consumers with less often shopping frequency think the ‘touch staff’ is the most important sensory experience to them. Besides, from the comparison column diagram, we could tell that sensory marketing stimuli are more important to consumers with higher shopping frequency, which is twice a month or shorter in general.
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Table 4 The comparison of cosmetics shopping frequency Sensory stimuli Visual store Smell store Smell staff Sound store Sound staff Touch store Taste staff Visual staff Touch staff Taste store
Comparison result No significant difference No significant difference No significant difference No significant difference No significant difference No significant difference No significant difference Have a significant difference Have a significant difference Have a significant difference
More important to
More often > Less often More often > Standard More often > Less often
To determine whether there is a statistically significant difference between three shopping frequency groups’ means, this study will conduct the ANOVA analysis for each dependent variable—sensory marketing stimuli. According to the one-way ANOVA test result, the comparison between consumers with different cosmetics shopping frequency in-store is summarised in Table 4: The result indicates that the multisensory shopping experience in-store for cosmetics is more important to consumers with more often shopping frequency who shop cosmetics twice a month or shorter. Specifically, they care about the visual staff (i.e. sales assistants’ makeup and uniform), touch staff (i.e. makeup/ facial/massage treatment), and taste store (i.e. serve drinks).
4.3.5
Crosstabulation: Shopping Frequency—Shopping Orientation/Consumption Level The crosstabulation analysis amongst shopping frequency, shopping orientation, and consumption level has been conducted. In conclusion, consumers with hedonic shopping orientation and higher consumption level have a more often shopping frequency, which is at least twice a month. Meanwhile, consumers with utilitarian shopping orientation and lower consumption level have a less often shopping frequency, which is once every 3 months or longer.
4.4
Age Groups
Participants are categorised by age, including three groups (Fig. 14): young consumer (18–30)—246 participants, which takes 41% of 600 participants in total; middle consumer (31–40)—201 participants, which takes 33.50%; mature consumer (41+)—153 participants, which takes 25.50%.
4.4.1 Young Consumer (18–30) Regarding the opinion of young consumers, all ten sensory marketing stimuli are sorted by the importance level from high to low in Fig. 15. For consumers who are
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Fig. 14 Consumers in different age groups
Fig. 15 The opinion of young consumers
18–30 years old, the most important sensory marketing factor is ‘touch store’, which is the touch setting of the physical store (i.e. product testers, makeup tools). They care about the process of trying on products and the tactile experience they feel.
4.4.2 Middle Consumer (31–40) According to the opinion of middle consumers, all ten sensory marketing stimuli are sorted by the importance level from high to low in Fig. 16. For consumers who are 31–40 years old, the most important sensory marketing factor is ‘smell store’, which is the scent of the store environment (i.e. spray perfume around the counter and product scent). They care about whether the aroma of the store atmosphere is
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Middle Consumer (31-40) 4.5
3.97
3.92
4
3.92
3.9
3.89
3.79
3.62 3.29
3.5
3.07
3.03
3 2.5 2 1.5 1 0.5
V
Sm
el
lS
to re is u al St or e To uc hS to re To uc hS ta ff V is u al St af f Sm el lS ta ff So un dS ta ff So un dS to re Ta ste St or e Ta ste St af f
0
Fig. 16 The opinion of middle consumers
Mature Consumer (41+) 4.5 3.85
4
3.85
3.8
3.8
3.76
3.59
3.43
3.5
3.04 2.77
3
2.69
2.5 2 1.5 1 0.5 af f So un dS to re Ta ste St or e Ta ste St af f
nd St
ta ff
So u
lS
e el Sm
uc hS to r
To
hS ta ff
e
uc To
el
lS to r
ta ff Sm
is u al S
V
V
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Fig. 17 The opinion of mature consumers
comfortable, the smell of products, and the overall olfactory experience they feel in store.
4.4.3 Mature Consumer (41+) As said by the opinion of mature consumers, all ten sensory marketing stimuli are sorted by the importance level from high to low in Fig. 17. For consumers who are above 41 years old, the most important sensory marketing factor is a joint first place,
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‘visual store’ and ‘visual staff’, which is the visual setting (i.e. counter design, product display, lighting) and the look of sales assistants (i.e. makeup and uniform). They care about the overall visual experience from both physical store design and retailing staff.
4.4.4 Comparison between Different Age Groups Fig. 18 merged the result of three groups, so as to make an initial comparison between consumers with different shopping frequencies. As shown in the column diagram, the most important sensory marketing factor is different between three different age groups: the young consumers care about ‘touch store’ the most, the middle consumers care about ‘smell store’ the most and the mature consumers care about the ‘visual store’ and ‘visual staff’ the most. Furthermore, from the comparison diagram, we could tell sensory marketing stimuli have a higher influence on the middle age group in general. To determine whether there is a statistically significant difference between three age group means, this study will conduct the ANOVA analysis for each dependent variable—sensory marketing factors. In conclusion, the comparison result between consumers in different age groups is summarised in Table 5; they have significant different opinions on sensory stimuli that are highlighted in bold: The result indicates that the multisensory shopping experience in-store for cosmetics is more important to middle-aged consumers who are 31–40 years old. Specifically, they care about the taste store (i.e. serve drinks) and taste staff (i.e. have a bartender make fresh cocktails in store) than consumers who are above 41 years old. Besides taste experience, consumers in different age groups do not have significant differences in the opinion of other sensory stimuli—visual, smell,
Age Groups
is u al St or e To uc hS to re To uc hS ta ff V is u al St af f Sm el lS ta ff So un dS ta ff So un dS to re Ta ste St or e Ta ste St af f
V
Sm
el lS
to re
4.5 4 3.5 3 2.5 2 1.5 1 0.5 0
Young (18-30)
Middle (31-40)
Fig. 18 Comparison between different age groups
Mature (41+)
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Table 5 The summary of comparison between different age groups Sensory stimuli Visual store Visual staff Smell store Smell staff Sound store Sound staff Touch store Touch staff Taste store Taste staff
Comparison result No significant difference No significant difference No significant difference No significant difference No significant difference No significant difference No significant difference No significant difference Have a significant difference Have a significant difference
More important to
Middle age > Mature age Middle age > Mature age
sound, and touch. This is not corresponded with the result from literature review chapter (Xu & Cliquet, 2013; Eze & Bello, 2016; Jeong et al., 2017; Baptista, 2020).
4.4.5
Crosstabulation: Age Group—Shopping Orientation/Consumption Level/Shopping Frequencies This study did a crosstab analysis amongst consumers with different ages, shopping orientations, consumption levels, and shopping frequencies. Combined with crosstabulation analysis results: young consumers have most of the hedonic orientation, spend relatively even on cosmetics, and shop more often for cosmetics in store. Middle consumers have most of the hedonic orientation as well, but they have a relatively higher consumption level, and standard shopping frequency for cosmetics, which is once a month. Mature consumers have most of the utilitarian orientation; they care more about efficient and practical experience and spend relatively lower on cosmetics; meanwhile, their shopping frequency is less often than middle and young consumers.
4.5
Conclusion of Compare Groups Analysis
In conclusion, the result of compare groups analysis revealed the significant difference between different grouping variables. Table 6 highlighted which sensory marketing factor has a significant influence on which specific group in bold.
4.6
Discussion
Previous studies (i.e. Evans et al., 2013; Hultén et al., 2009; Krishna, 2013; Parsons, 2011; Soars, 2009; Spence, 2022; Wade Clarke et al., 2012) have been solely focused on sensory cues of objects (physical design of store) and overlooked the people (retailing staff in store) as sensory cues in the shopping environment. However, the service of a sales assistant in the cosmetic industry plays an important
Visual store Visual staff Smell store Smell staff Sound store Sound staff Touch store Touch staff Taste store Taste staff
Shopping orientation Hedonic Utilitarian 3.90 3.86 3.84 3.77 3.91 3.79 3.77 3.58 3.33 3.08 3.67 3.51 3.94 3.80 3.92 3.70 3.21 2.69 3.21 2.62
Consumption level—Cosmetics 0-£199 £200+ 3.85 3.90 3.75 3.86 3.79 3.91 3.62 3.73 3.13 3.28 3.39 3.79 3.75 3.99 3.68 3.93 2.83 3.06 2.82 3.00
Table 6 The result of compare groups analysis Shopping frequency in-store—Cosmetics More often Once /month Less often 3.95 3.91 3.75 3.92 3.79 3.68 3.98 3.80 3.77 3.75 3.67 3.58 3.32 3.20 3.07 3.74 3.53 3.49 3.92 3.84 3.85 3.90 3.69 3.86 3.16 2.93 2.72 3.03 2.94 2.73
Age group Young Middle 3.87 3.92 3.71 3.89 3.79 3.97 3.63 3.79 3.24 3.29 3.66 3.62 3.9 3.92 3.73 3.90 2.96 3.07 2.96 3.03
Mature 3.85 3.85 3.8 3.59 3.04 3.43 3.76 3.8 2.77 2.69
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role in the consumer shopping experience (Satti et al., 2019; Eroglu et al., 2022), since the sales assistant provides multisensory services such as makeup, facial treatment, product recommendation, and so on (Errajaa et al., 2022; Jeong et al., 2017; Mintel, 2022). This research proved sensory stimuli from the retailing staff are important to consumer shopping experience, which fills the research gap as previous sensory marketing research did not consider retailing staff and their service as sensory marketing cues. With the booming development of modern society, marketing strategy must consider the fact that the consumer of today is more sophisticated and discerning than the consumer of the past (Kim et al., 2016; Spence, 2022). To achieve effective marketing strategy goals, design strategies based on consumer segmentation and characteristic are an essential consideration (Kondo & Okubo, 2022). This research investigated the up-to-date consumer need by segmentations—comparison studies between consumers with different shopping orientation, shopping frequency, consumption level, and age group, to provide a deeper understanding of consumer preference. Consumers categorised by different shopping orientation have the most difference between groups. Sensory marketing factors have a significantly higher influence on consumers with hedonic orientation than utilitarian consumers in general. Hedonic consumers care more about ‘the scent of retailing staff’, ‘the music in store’, ‘the touch experience setting in store’, ‘the touch service of retailing staff’, ‘serve food/drink in store’, and ‘the food/drink service of retailing staff’. Consumers who are willing to spend more on their daily beauty routine cosmetic products think ‘communication service of retailing staff’, ‘the touch experience setting in store’, ‘the touch service of retailing staff’, and ‘serve food/drink in store’ are more important to their shopping experience. For consumers who shop twice a month or shorter, they value ‘the appearance of retailing staff’, ‘the touch service of retailing staff’, and ‘serve food/drink in store’. There is no significant difference between different age groups besides the setting and service of taste experience. Overall, this detailed managerial insight of consumer needs in sensory marketing will help fashion and luxury organisations understand their targeted consumer needs and then tailor their sensory marketing strategies to achieve desired outcomes.
5
Limitations and Suggested Future Research
5.1
Limitations on Data Collection Method and Sample Size
This research chose a professional data collection agency Qualtrics to help with questionnaire distribution. The target participant is female consumers with luxury cosmetic physical store shopping experience in the UK. According to the IP address of responses, most questionnaires were mainly distributed in the UK to domestic consumers. However, there are a large number of tourist and international workers/ students in the UK who could be qualified as target consumers. Therefore, there is a limitation of implementation of data collection. Additionally, Qualtrics user base has
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a limitation, which may affect the proportion of consumer segmentation like consumption level and shopping frequency.
5.2
Suggested Future Research
• Male consumers—the market of fashion especially cosmetics for men is rising in the young generation such as Gen Z and Millennials; male consumers deserve more attention in both the industry and academic research. • Test the framework in different contexts and do a comparison analysis of sensory experience preference between consumers from different countries—consumers with different cultural backgrounds will have different taste in five senses.
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Part III Business Models
Blue Ocean Strategy in the Fashion Textiles Business Léo-Paul Dana
and Aidin Salamzadeh
Abstract
The notion of the Blue Ocean Strategy was first proposed and then promoted by Chan Kim and Renée Mauborgne. This approach is in contrast with the traditional competition-based strategies, as it provides firms with new insights on how to change the competition scene – a competition with non-zero-sum games that follows a reconstructionist view of the market. Kim, Mauborgne, and their followers have used this approach to investigate several case studies. Nevertheless, fashion textile businesses have rarely followed such an approach, and therefore, previous scholars have seldom studied such cases. Thus, this chapter uses the central tenets of the Blue Ocean Strategy and investigates three successful cases in an emerging economy in terms of market focus, competition type, demand type, value-cost trade-off, strategic focus, and type of the game. The authors have used a multiple case study research design to reveal how these selected companies have benefited from following blue ocean strategies. The findings revealed that following blue ocean strategies have increased their profitability and affected their brand reputation as creative firms in their market. Also, the imitation barriers, including alignment, cognitive and organisational, brand, and economic and legal barriers created by these companies, are explored
L.-P. Dana Dalhousie University, Halifax, NS, Canada LUT School of Business and Management, Lappeenranta University of Technology, Lappeenranta, Finland ICD Business School, Paris, France e-mail: [email protected] A. Salamzadeh (✉) Faculty of Management, University of Tehran, Tehran, Iran e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_13
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accordingly. Finally, the chapter concludes with some remarks for practitioners and policymakers and future research directions. Keywords
Blue Ocean Strategy · Fashion · Textiles · Emerging Economies · Case Study
1
Introduction
The growing needs of consumers and their increased choice mean that organisations must move in a new and creative direction. In the last decade, the world has seen significant changes (Dana et al., 2022b). The fact is that none of these evolutionary factors existed since the Paleolithic era. In addition to affecting our quality of life, these dramatic changes have also changed business strategies, and this is where the concept of the Blue Ocean Strategy becomes more critical. Whether one works in the private, public, or non-profit sector, a growing challenge for organisations is constantly reviewing strategies. The constant need of today’s organisations is to be able to differentiate and reduce costs at the same time. It is what is called value innovation and is the foundation of the Blue Ocean Strategy (Roth et al., 2018). In 2005, W. Chan Kim and Renée Mauborgne proposed the concept of the Blue Ocean Strategy and created a storm in the business space. The Blue Ocean Strategy book has been translated into more than forty languages (Muthuveloo & Teoh, 2020). The Blue Ocean Strategy is a systematic, iterative process that helps one identify opportunities by providing tools (how to create a blue ocean), frameworks (the mindset needed to move towards a blue ocean), and principles (generating and implementing strategies to get to a blue ocean) (Koay & Muthuveloo, 2021; Seng et al., 2015). It helps one understand the market’s uniqueness and operate in the traditional market segments and outside the conventional boundaries. The Blue Ocean Strategy does not look for ways to improve competition in the market or increase demand, but this strategy tries to lead people to a side of the market where there is no competition, and one has to create it instead of increasing demand. In fact, the concept of Darwinism or the struggle for existence in blue oceans is not in question (Irene et al., 2020; Priilaid et al., 2020); rather, one should look for opportunities that will quickly lead you to profitability. Although the blue ocean is almost a new term, if companies look at the industry’s evolution, they will realise that the creation of new industries has always happened in blue oceans. Notably, the simultaneous desire to create differentiation and reduce cost does not always happen easily (Agnihotri, 2016). Many companies misunderstand that the Blue Ocean Strategy is synonymous with differentiation. In such a situation, most of the company’s focus will be on improving the existing situation or creating diversity and innovation. This approach will focus on cost reduction by eliminating some unimportant and additional factors to zero (Kim, 2005). In general, the Blue Ocean Strategy is considered the most peaceful amongst strategic planning models (Kabukin, 2014). Because instead of sending one to an
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ocean full of predatory sharks, it leads them to a small, peaceful, and exclusive ocean. It is noteworthy that identifying the blue oceans from the red ones is not so easy either (Kittilaksanawong & Kandaswamy, 2018). It is more of a challenge for companies with fewer resources for trial and error and less experience in using them. It is best to start by identifying what the market needs, but it is not generally straightforward. Then one shall focus on those things that are not being done well by existing companies. Companies should have a proper understanding of where they are. To do this, they must, like a strategist, design their strategies to show their teams a big picture of the current state of the target industry. It allows them to clearly define new areas without losing sight of small operational details. The next step is to imagine what they can do very well. Asking this question will make them think beyond the industry’s demands and thus redefine their field of activity and the boundaries of the industry (Butler, 2008). If we define fashion as the art of creating and choosing unique wearables, we have to go back 200 years ago for its history. Although the concept of fashion has expanded over time to other items such as jewellery, bags, and shoes, the first origin of fashion design began in 1826 (Dana et al., 2022a; Salamzadeh et al., 2022). It is believed that Charles Frederick Worth (1825–1895) was the world’s first fashion designer. Charles was introduced as one of the first people who started the way of creating the House of Worth and told his customers what kind of clothes were suitable for them (João & Neto, 2018). At this time, many houses began to hire artists to prepare clothing patterns. Patterns were provided to customers, and orders were placed under the sewing machine based on the customer’s interest. During this time, the tradition of providing customers with patterns and tailoring began instead of the previous system of offering ready-to-wear or used garments (Gill, 2005). At the beginning of the twentieth century, the first new developments in fashion took place in Paris, and from there, it spread to other parts of the world. New clothing designs were born in Paris before they made their way to other parts of the world. In other words, Paris was known as the ‘fashion capital’ (Ruth, 2021). Fashion in this period was introduced under the name of ‘Haute Couture’ and was designed exclusively for special people (Bourdieu, 2020). In the middle of the twentieth century, the clothes of the fashion industry reached mass production. Production increased, and people had more options to choose. In the late twentieth century, fashion awareness increased amongst people, and they chose clothes based on comfort and style instead of trusting the prevailing trends in the market (Harmsen et al., 2021). Due to the importance of the topic, this chapter investigates three successful cases in the fashion textiles industries that have followed blue ocean strategies. It is noteworthy that only a few studies have earlier investigated the topic in other countries and not in Iran. Iranian cases are selected based on the history of this industry and new dynamics in its fashion textile markets (Fathi et al., 2021; Toghraee et al., 2022). Therefore, the main tenets of the Blue Ocean Strategy are used to investigate the cases (Dana & Salamzadeh, 2022). The chapter has multiple contributions as it investigates the topic in a less studied context. Besides, using blue ocean strategies in this sector is rarely investigated by previous authors (Nezam, 2019). The chapter is structured as follows. The literature is reviewed first, and then
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the fashion textiles industry is explored. Afterwards, the research method is explained, and finally, the chapter concludes with some findings and concluding remarks.
2
Literature Review
Over the last decade, extensive and profound changes have occurred in the global fashion textile industries and markets. For instance, China’s apparel exports increased from $184 billion in 2013 to more than $320 billion in 2020, accounting for nearly 40% of global trade in this sector (Zhang & Anadon, 2014). The growth of fashion textile exports from China and other leading countries such as India, Bangladesh, and Vietnam was accompanied by a decrease in fashion textile production in the countries of the target market in Europe and America (Kathuria, 2018; Piscopo, 2010). Meanwhile, the fashion textile distribution market in developed countries was also changing. New and powerful fashion textile retail groups have emerged and rapidly developed their markets. The retail fashion textile market in most countries has been freed from the dominance of small stores and has moved towards the rapid growth of chain networks of specialised branded retailers and online sales. According to many studies, the four largest clothing retailers in the world are the Spanish group Inditex (with the brands Zara, Massimo Dotti, Bershka, and five other brands), the Swedish group H&M, the American group Gap, and the Japanese group Fast Retailing (with Uniqlo brand) (Esbeih et al., 2021). It is noteworthy that these groups are suppliers of clothes with average price and quality for the general public and are not included in the category of luxury brands (such as Louis Vuitton, Giorgio Armani, Ralph Lauren, and the like) (Anwar, 2017). Inditex Group relies more on production in Spain and neighbouring countries, H&M in China and other Asian countries and somehow in European countries, Gap in various countries, especially China, and Uniqlo in China, which produce clothes. In addition to their international presence, the first market for Inditex and H&M is Europe, for Gap the USA, and for Uniqlo Japan. Uniqlo fiercely competes with other big retailers to capture the market in Asian countries, especially China and India. Gap and Uniqlo are considered retail clothing groups with a fast fashion approach, but Zara and, to some extent, H&M and smaller companies such as Mango are very active in this field (Aibar-Guzmán et al., 2022). For example, Zara’s strategies led to global dimensions. Also, Inditex Group became the world’s largest clothing group by relying on the supply and supply model of fast fashion (Picazo, 2021). Inditex achieved great success by adopting the fast fashion strategy and depending on the cluster of clothing manufacturers in Spain and Europe despite the high wages of labour in Europe compared to Asian countries (Stenton et al., 2021). Since traditional clothing production methods are slowly becoming obsolete, with the increasing awareness of consumers and with the change of direction of producers towards environmental responsibility, significant advances have been made in the technology of this industry. For this purpose, we will introduce ten
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extraordinary innovations that will revolutionise the clothing industry. In this chapter, we will review five of them: (i) Making fabric from milk, tea, and coffee beans: milk, tea, and coffee tend to stick to each other, but not in a way that can make clothes with it. As the complex technologies of the fashion industry have progressed, simple technologies have also stepped forward. In this regard, we can mention the food items that become wearable goods. A German student of microbiology, who is now engaged in design work, has used milk to make environmentally friendly fibres called OMilch. One of the companies producing high-tech sportswear uses recycled coffee beans to produce heaters. Also, several famous clothing designers worldwide use Kombuja or tea yeast to produce plant-based fabric and leather (Cardoso Filho et al., 2019). (ii) Painting with airflow and saving gallons of water: this method, which was developed in California, uses special dyes, which are transferred from the paper to the fabric in one step by applying heat. This method saves seventy to seventy-five gallons of water and energy in dyeing 500 grams of fabric, and no harmful by-products are produced. This technology consumes 85% less energy than traditional painting methods (Heiber et al., 2020). (iii) Digital printing: the printed photo is directly applied to the fabric using a printer in digital printing. This method can save up to 95% of water consumption and up to 75% of energy consumption, reducing the amount of textile waste. This method has been used by prominent designers such as Marie Katrantzou, Alexander McQueen, and Basso and Brooke (Köseoglu et al., 2019). (iv) Introducing plastic bags and malt jars: recycled synthetic materials, made from plastic bags to malted glass, have attracted much attention. Just as other materials and bamboo are turned into yarn, regenerated synthetic materials are broken down into fine particles, melted and turned into yarn. This combination is a soft yet durable fabric, and its performance is like denim (Chaudhary et al., 2021). (iv) Hand dyeing: sometimes, the latest innovations are some of the oldest. Some clothing design and sales companies are returning to using locally sourced materials and handcrafting clothing to create stunning colours and looks (Berradi et al., 2019). Factors affecting the strategic directions of fashion textile industries have always been the attention of researchers. In today’s world, due to the rapid global developments and the recent economic crisis, the issue of improving industry performance has become increasingly important. The results of empirical studies show that despite the influence of environmental restrictions and obstacles on the performance of industries, their senior managers have significant power to change the level of performance. Besides, strategic planning is a valuable tool for achieving desired goals. In reaching these goals, the design of strategic measures is decisive. Different strategy actions include cost reduction, differentiation, focus, and a combination. These measures appear at the product-market level, where differentiation is based on positioning. Therefore, determining the strategies and their content is one of the essential tasks that senior industry managers must do. In such a VUCA environment, companies look for solutions, strategies, and tools to improve their position in the market whilst maintaining their market share (Pereira et al., 2021; Radović-Marković et al., 2019). With such conditions and considering the active presence of prominent foreign fashion textiles manufacturers in the country’s
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market, will domestic manufacturers be able to compete? Thus, what path should domestic producers take to survive and grow their market share in such conditions? Before proceeding further, the next section discusses the fashion textile industries in Iran to shed more light on the context of this study.
3
Fashion Textiles Industries in Iran
The fashion textiles industry is one of the world’s largest industries. It has a vast, diverse, and attractive space for activity, and it is always changing due to the inherent human need for beauty and variety in addition to being worn. A good and up-to-date look is the desire of most people, who enjoy it a lot (Toghraee et al., 2022). Many women spend a significant part of their income on buying women’s clothes and fashion-related products, some are always looking for the latest trends in the world, and some spend a lot of time creating their own style. The fashion world has its complexities and beauty. In addition to creating jobs, this industry has the power to create significant added value; there is a lot of potential for it to succeed (Canepa et al., 2014). According to historical documents in the ancient civilisation of Iran, clothing and fashion were and still are very important. It can be claimed that the Iranian ancestors were pioneers of this industry. Cultural and ritual differences in Iranian peoples and their combination with beauty and colour are significant subjects for the inspiration of this industry (Rasuli et al., 2020). It is sometimes ignored that there are clues from our culture in the designs of international designers. Still, their audience may not have enough information about the origin of these designs. Whether domestic or foreign projects, they have been followed by the young Iranian generation and the neighbouring countries (Kashani-Sabet, 2014). Although the laws and regulations cover the diversity of culture in Iran, the design, production, and supply of clothing in this market differ from other countries. Still, looking at the changes in certain times and the behaviour of Iranian customers shows that they have never been far from global trends. However, scholars believe that this ability has always existed, and they have been pioneers and influencers in this field (Mohammadisaghand et al., 2020). Private and public events are held with limitations. These events are generally different from those in other parts of the world. The lack of catwalks and special and relevant events of clothing suppliers in the form that is common in the world has limited the space for brands to show off (Balasescu, 2013). However, in recent years, many efforts have been made to solve these problems, and private and public events are held with certain limitations, which are still far from the international world. Of course, these limitations and their combination with current world trends have sometimes led to creating new designs that fit society (Balasescu, 2007). These developments have attracted the international community’s attention to the fashion industry, but it still has a long way to go. The domestic garment industry has high capabilities. Nevertheless, the high cost of production and raw materials, international restrictions and international payment problems, the lack of recognition of
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these capabilities by the international community, and the lack of sufficient support for this industry have made the way a little difficult for the players. But the activists in this field are always trying to improve the situation (Fathi et al., 2021). In recent years, restrictions and international laws have affected Iranian businesses, and domestic clothing markets have suffered a lot of damage due to economic and trade sanctions in the past few years. These sanctions have closed the entry of foreign clothing. Thus, the Iranian audience of this clothing category is disappointed about accessing the clothes they want to look for ways to solve this problem. Access to international products is possible only by smuggling goods, the lack of assurance of the authenticity of the available goods and price fluctuations cause audience confusion, and the lack of direct communication between Iranian audiences and producers with the international market endangers the competitive conditions of the market (Ebrahimi et al., 2021). But some domestic manufacturers are looking for competition with the world’s famous brands to reduce the impacts of these damages by monitoring this market and increasing the quality of products and diversity in design. Informed customers are looking for quality that matches the price, receiving appropriate services and up-to-date and efficient products. Sometimes domestic brands do not respond to these needs. Of course, there is a little sense of mistrust amongst customers, branding problems, and a lack of awareness of good domestic brands amongst the audience. These are a few issues in this field. But in recent years, with the efforts of domestic producers and the remarkable progress of this industry, social media has created a good interaction between customers and high-quality Iranian brands (Hashemi & Ghaybi, 2021; Salamzadeh, 2021). With the increase in demand in society, a large number of retailers of custom and hand-stitched clothes with limited productions have started their work, and this activity in this field is increasing day by day. Thus, hopefully, women have become the pioneers. These retailers sometimes have a private maison, are grouped in a gallery, or are active only on social media (Dana & Salamzadeh, 2021). These activists have a significant impact on the style of their audience. Still, despite their advantages, they can hardly be present at the international level and respond to all the needs of society. Many believe that huge collections can help their products shine internationally with the ability to mass produce by employing the skills of these designers (Ghazali, 2016; Kateb & Mafitabar, 2019).
4
Research Method
This chapter follows a multiple case study approach, and a qualitative research design is used to conduct the study (Dana & Dumez, 2015; Groenland & Dana, 2020). Therefore, the central tenets of the Blue Ocean Strategy are being used as the framework, and three successful cases are investigated in terms of market focus, competition type, demand type, value-cost trade-off, strategic focus, and type of the game (Kim, 2005). The authors have conducted interviews with C-level managers and founders of the companies. Each interview took between 45 to 80 minutes, and the interviewees were interviewed in two stages. After the within-case analysis, the
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Table 1 Characteristics of the cases Case 1
No. of interviewees 4
Years of experience* 2
No. of staff 112
2
4
3
43
3
5
3
65
Major area Fashiontextiles Agrotextiles Textiles
Growth rate** (2020–2021) 32% 23% 35%
* Experience in applying the Blue Ocean Strategy; ** In terms of profitability indexes
between-case analysis was done, and the results were presented according to the preliminary structure (Dana & Dana, 2005; Salamzadeh, 2020; Salamzadeh et al., 2017). The authors have used a multiple case study research design to reveal how these selected companies have benefited from following blue ocean strategies and also revealed the major imitation barriers considered by them. Table 1 shows the main characteristics of the cases.
5
Findings
The Blue Ocean Strategy has many differences from the red ocean strategy. But the most important is the target market of these two strategies. A red ocean strategy is where all industries are located and use a specific and common way of conducting business. But the blue ocean is the niche market that has received less attention. Besides, in the blue ocean, the focus is on new customers, but in the red ocean, the company focuses on retaining the old ones. In order to create a basis to compare the cases, this chapter uses the central tenets of the Blue Ocean Strategy and investigates three successful cases in an emerging economy. The following sections cover the central tenets and reveal the major similarities and differences between the three studied cases.
5.1
Market Focus
A few companies adopt a Blue Ocean Strategy, whilst others continue to operate in red oceans. A blue ocean means an uncontested market. Then, if a company finds it, it will make a lot of money, at least for a while (Raith et al., 2008). These companies prefer to compete in uncontested markets rather than in existing ones. According to Table 2, the studied cases have followed the same strategy by respectively focusing on disabled children, recycled textiles, and people at the bottom of the pyramid (BoP). Focusing on these uncontested market spaces in the fashion textiles industries has created blue oceans for them.
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Table 2 Comparing cases based on their market focus Market Focus
Case #1 This case has entered specific markets related to disabled children and has followed a niche market approach
Case #2 This case has created an uncontested market which provides an opportunity for using recycled textiles in a safe manner
Case #3 This case has followed a BoP approach and has been mostly focused on specific low-income markets
Source: authors’ elaboration Table 3 Comparing cases based on their competition type Competition type
Case #1 Competition has become irrelevant as other rivals have marginally targeted disabled children
Case #2 Competitors have marginally followed the recycled approach towards fashion textiles
Case #3 Fashion textiles have been marginally considered at the BOP
Source: authors’ elaboration
5.2
Competition Type
Making the competition irrelevant is a key to creating a blue ocean. Competitive strategy, or the red ocean strategy, seems necessary for ensuring sustainable company performance, but it is insufficient. Companies must deal with issues beyond the competition – Issues that will bring them more growth, profitability, and survival, and this is the notion of the Blue Ocean Strategy (Chang, 2010; Yunus & Sijabat, 2021). The studied cases have made the competition irrelevant, as mentioned in the Table 3.
5.3
Demand Type
On the other hand, the Blue Ocean Strategy is based on the assumption that the boundaries and structure of the industry are not fully defined and determined and can be reconstructed or renewed by the industry players. Let us assume that the limits of the market and structure are only in managers’ minds (Chandrakala & Devaru, 2013). Then, different-minded and practical people try to abandon these boundaries and let their thoughts be free. From their point of view, there is a huge demand outside of this current market somewhere else that they need to tap into. The problem here is how to create it. It is a sudden change of direction from the supply to the demand side of the market (Kim, 2005). It is a change from a competitive environment to an innovation environment and to a market space where latent demands exist. It means using both cost leadership and differentiation strategies. The studied cases followed the same approach by lowering the costs and differentiation through using subsidised materials, taking advantage of recycled textiles, and low-cost materials at the BoP (Table 4).
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Table 4 Comparing cases based on their demand type Demand type
Case #1 They have captured new demand by offering a new set of products for specific unaddressed demands
Case #2 The environmentalists created an increased demand which did not exist earlier
Case #3 A new demand was captured by introducing fashion textiles at the BoP
Source: authors’ elaboration Table 5 Comparing cases based on their value-cost trade-offs Valuecost tradeoff
Case #1 The company has created a new fashion textile experience for disabled children and managed the costs by using subsidised materials
Case #2 By using recycled textiles, the company has lowered the costs and simultaneously created value for specific groups such as the environmentalists
Case #3 Low-cost materials were used, and the company has employed people at the BoP to further lower costs. Besides, it has created fashion textiles for people at the BoP
Source: authors’ elaboration Table 6 Comparing cases based on their strategic focus Strategic focus
Case #1 The company has followed a low-cost strategy with a differentiation strategy by simultaneously focusing on marginalised children with disability
Case #2 The company lowered the costs by using recycled textiles and simultaneously provided a fashion textile experience for environmentalists
Case #3 The company focused on low-cost materials and employees and offered a unique fashion textiles experience at the BoP
Source: authors’ elaboration
5.4
Value-cost Trade-off
In the red ocean, businesses try to create more value with less cost or make the product purchase more justified for the customer by removing costly features. In contrast, the blue ocean strategies are focused on breaking the value-cost trade-off through value innovation. Such companies try to effectively create a leap in value for both buyers and the company (Yardley, 2015). Table 5 highlights the value-cost trade-offs experienced by the studied cases.
5.5
Strategic Focus
In the red ocean approach, companies prefer to follow a differentiation or a low-cost strategy, whilst the Blue Ocean Strategy focuses on simultaneous differentiation and low-cost strategies, which is called value innovation. It deals with creating extra value for various stakeholders (Agnihotri, 2016). Table 6 highlights how the studied cases have followed this approach.
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Type of the Game
Competitive strategies assume that the structural conditions of different industries are certain, and these companies have no choice but to compete with each other. Companies try to overcome their rivals in this competitive environment by creating exclusive competitive advantages, sometimes even by imitating them and taking a larger market share. This is a zero-sum game, where one will win, and the other will lose. Companies that follow the Blue Ocean Strategy focus on non-zero-sum games as they approach new markets and do not seek their benefits in a market targeted by their rivals (Sindhu, 2018). Table 7 shows how the cases have done this.
5.7
Imitation Barriers
In today’s era, when the competition for the supply of goods and services in many industries has reached saturation point, organisations need solutions by which they can escape from this intensely competitive environment. For this purpose, companies must adopt strategies that lead them to niche markets. The Blue Ocean Strategy focuses on creating new markets and causing profitable and rapid growth (Iruthayasamy, 2021). Using this strategy and changing the trend from conventional strategies that only deal with the competitive environment, like any other organisational change, faces resistance and obstacles (Namboodiri et al., 2019). The studied cases devised a set of imitation barriers, including alignment, cognitive and organisational, brand, and economic and legal barriers created by these companies. For instance, all the cases created legal barriers for their potential rivals by negotiating with the State Welfare Organization of Iran, the Iranian Department of Environment, and the United Nations office in Iran. Besides, they have registered brands and protected their activities by following the copyright rules of the country. Their fashion textiles are used widely in the targeted groups and are well known amongst disabled children and their families, environmentalist groups, and lowerincome people at the BoP.
Table 7 Comparing cases based on their types of the game Type of the game
Case #1 The company offered its fashion textiles to disabled children whom companies have never targeted
Source: authors’ elaboration
Case #2 The tendency to use recycled textiles is very low as people do not generally like the material. Nevertheless, environmentalists have become interested in these fashion textiles, and there is no other competitor in the market space
Case #3 Whilst casual textiles are being used at the BoP, the company has proposed a new approach towards fashion textiles that the competitors do not consider
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Conclusions
The history of textiles industries, in general, and fashion textiles, more specifically, is of paramount importance, as it provides a better understanding of this industry’s evolutions and recent trends. This industry has become a complex phenomenon in an emerging economy with its complexities, such as sanctions. Therefore, this chapter provides a big picture of the fashion textile industry in Iran and explores three leading cases in this context. It is noteworthy that the selected cases were amongst those successful companies in implementing blue ocean strategies. The authors conducted multiple case study research to explore how managers have considered the critical tenets of the Blue Ocean Strategy in those businesses. The findings revealed that following blue ocean strategies has increased their profitability and affected their brand reputation as creative firms in their market. Although the generalisability of the results is limited as only three cases are studied in this chapter. Also, the imitation barriers, including alignment, cognitive and organisational, brand, and economic and legal barriers created by these companies, are explored accordingly (see Dana & Salamzadeh, 2022). In sum, it is suggested that the players in the fashion textile industry consider blue ocean strategies to increase their success rates. The three mentioned cases had reported significant changes in their profitability, and the C-level managers have mentioned that it was directly related to their pursuit of blue ocean strategies. Besides, they must consider some imitation barriers to keep the ocean blue. It is noteworthy that they shall focus on the central tenets, including market focus, competition type, demand type, value-cost trade-off, strategic focus, and type of the game. Finally, future researchers could investigate these tenets’ impact on the companies’ performance measures. They could also investigate more cases to increase the generalisability of the findings. Value innovation and defining nonzero-sum games were amongst the most repeated issues in the interviews. Then, future researchers might explore various possible non-zero-sum games as well as value innovation techniques.
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Sustainable Mass-Customisation Business Model by Incorporating Virtual Fitting Room Marketing Tools in Fashion E-Commerce: A Study of the Luxury Unstitched Market Sadia Idrees, Gianpaolo Vignali, and Simeon Gill
Abstract
This chapter is centred around the luxury unstitched apparel market of Pakistan and interactive virtual fitting room tools of fashion e-commerce such as 3D mobile app scanners, virtual reality, augmented reality, and mixed reality. Interactive virtual fitting room tools have been developed extensively for the advantage of both consumers and fashion retailers to improve online shopping experience (Idrees et al., International Journal of Economics and Management Engineering 14:318–333, 2020b). Thus, the chapter discusses the Pakistani luxury unstitched apparel market (Faust & Carrier, Textile Research Journal 79: 1446–1458, 2009), for the enhancement of Pakistani fashion e-commerce interfaces by utilising interactive virtual fitting room tools. The discussion of luxury unstitched apparel products demonstrates that the products are loved across the borders because of their garment customisation, talent, and craftsmanship, and this demand is flourishing and expanding rapidly due to exquisite quality and design uniqueness (Rehman, A cross-border fashion jaunt, 2014). Unstitched apparel products are sold in separate garment pieces normally declared as 2-piece and 3-piece suits. For instance, the upper garment includes separate fabric pieces or one full piece of fabric offering the front, back, and sleeves along with separate one piece of fabric for the lower garment, which is adorned with various options such as printed and embroidered fabric pieces. Nevertheless, Pakistani fashion e-commerce platforms lacks= the web 3.0 S. Idrees (✉) · G. Vignali Department of Materials, The University of Manchester, Manchester, UK e-mail: [email protected]; [email protected] S. Gill Faculty of Science and Engineering, Department of Materials, The University of Manchester, Manchester, UK e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_14
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technology virtual fitting room tools. Therefore, there is a need to incorporate virtual size and fit prediction, customisation, and virtual fashion viewing interactive tools. The virtual fitting room tools discussed in the chapter provide customisation approaches along with size recommendations and virtual trying on with 3D product visualisation (in 360-degree rotation), which generate beneficial competition amongst online retailers. The Lemon and Verhoef (Journal of Marketing 80:69, 2016) model is employed to present a sustainable masscustomisation e-commerce business model by combining virtual fitting room tools and luxury unstitched apparel products. The luxury unstitched apparel products are sustainable because they are customised according to personalised body dimensions which adds the benefit of reducing wastage of fabric due to mass production. Moreover, such demonstrations intersecting luxury unstitched apparel product with interactive virtual e-commerce tools would be beneficial for worldwide markets to employ in mass-customisation business approaches. Keywords
Unstitched Apparel · Pakistan · Fashion e-commerce · Sustainable · Masscustomisation · Luxury Fashion · Virtual Reality · Augmented Reality · 3D Body Scanning · Mobile app scanner
1
Introduction
This chapter presents an overview of Pakistan’s luxury unstitched apparel products and the innovative e-commerce virtual fashion viewing and size and fitting tools (virtual fitting room tools), which can be incorporated to enhance the fashion e-commerce of Pakistan. Therefore, the aim of the chapter is to explore the luxury unstitched fashion apparel meant for enhancing virtual bespoke garment construction with virtual fitting room tools. For instance, mobile body scanner apps are employed to acquire the contactless body dimensions in a minute. Whereas, to enhance interactivity, real in-store shopping experience in online atmosphere can be acquired through enhanced product information with 3D product visualisation; thus, these interactive tools such as virtual reality, augmented reality, and mixed reality will also been explored. Pakistan is well known for its luxury unstitched apparel which are bought worldwide (Latham, 2016). Unstitched apparel products are sold in separate garment pieces normally declared as 2-piece and 3-piece suits. For instance, the upper garment includes separate fabric pieces or one full piece of fabric offering the front, back, and sleeves along with separate one piece of fabric for the lower garment, which is adorned with various options such as printed and embroidered fabric pieces. Currently, in Pakistan, there are various luxury brands which are well known for establishing products and services that are lavish, highly desirable, distinctive, and highly crafted and offer personalised facilities (Roberts & Armitage, 2015). Unstitched luxury apparel goods are manufactured in Pakistan and marketed
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globally. The Pakistani global e-commerce players are Limelight, Gul Ahmed, Khaddi, Sana Safinaz, and Alkaram Studio. The requirement of unstitched apparel has risen because buyers are providing personalised services employing the unstitched product, which is specifically constructed as a made-to-measure garment (Latham, 2016). Manual tape measurement methods are used by Pakistani fashion retailers, which are not necessarily applicable to enhance sales through fashion e-commerce platforms in the international market. The main reason is that consumers are not capable of measuring their own body dimensions (Idrees et al., 2020b). Secondly, there is a requirement of a technical expert who can locate the exact body landmarks to acquire the body dimensions. Thus, the extraction of manual measurements such as self-measuring is prone to human error and is therefore challenging. However, having easy access to expert measuring is not easy geographically and time-consuming (Almalki et al., 2020). Similarly, the standard sizing systems (such as numerical (8, 10, 12) and alphanumerical (S, M, L)) are inadequate, due to the population of each country (US, UK, Pak, EU, etc.) having different body types and sizes (Jain et al., 2018). Thus, it is difficult to provide for consumers worldwide in an e-commerce environment where consumers cannot try on garments to find their right size (Reid et al., 2020). User-friendly mobile application scanners have been recently introduced by body scanning companies to be used by both retailers and consumers without any technical assistance (Idrees et al., 2020a). The body scanner apps for instance MeThreeSixty and 3Dlook can identify the body landmarks with artificial intelligence and machine learning technology. The body scanner apps have the potential to lessen the human error and deliver more than 100 body dimensions within 1–5 min (3DLook, 2022; Stream, 2022). The mobile scanner applications have a userfriendly mechanism, by taking 2D pictures, one front with an A pose and one profile view with the hand touching the thighs and feet joined together. The user can acquire the digital body dimensions and personalised avatar after the scanning process is done. This technology offers solution of mass customisation, size and fit recommendation, and visualisation and virtual trying-on, on personalised avatars with 360-degree rotation viewing in fashion e-commerce environments (3DLook, 2022; Idrees et al., 2020a). As stated by Idrees et al. (2020b) that in Pakistan fashion e-commerce platforms, buyers are not able to experience a real store environment, which comprises an online sales person, trying on the garments, mixing and matching of apparel, and accessories or physical stimulation (Escobar-Rodriguez & Bonson-Fernandez, 2017; Idrees et al., 2020b), all of which reduces their immersive experience and garment appeal. Interactivity, rich information presentation, and realism of products are vital aspects to accomplish the consumer’s social expectations in the online shopping platforms (Lee & Xu, 2019). The fashion viewing and presentation of products in online stores has been approached formerly in two-dimensional (2D) images, zoom in, or animation/video-footage/catwalk, virtual catalogues, and online blogs (Idrees et al., 2020b). This recent 2D approach is inadequate to provide interactivity as compared to a three-dimensional (3D) virtual model which can be utilised for virtual trying on and size and fitting evaluation (Altarteer & Charissis, 2019; Asizer, 2022).
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The 3D mobile app scanners are delivering better options through virtual try-on, size recommendation, and customisation (Asizer, 2022; Idrees et al., 2020b; Nettelo, 2022). Correspondingly, virtual fitting rooms (VFR) blended with augmented reality (AR) offer an advantage of virtual trying-on with mix and match accessories for garment customisation, as well as a choice of overlaying products on a personalised avatar (AR) during online shopping for a real-time experience (Feng et al., 2021; Qin et al., 2021).The virtual fitting rooms offer virtual models, virtual catwalks, 360-degree views, apparel heat maps, and size and style recommendation libraries in e-commerce platforms, for ease in selecting appropriate garments online (Lim & Jafari, 2021; triMirror, 2022). Thus, the virtual fitting room technology has a sustainable impact on the consumer experience during the pre-purchase phase of consumer shopping journey which can reduce the perceived risk of the size and fitting and online garment returns. Retailers have employed virtual fitting rooms to facilitate consumers in terms of providing right size and to resolve sustainability issue due to poor sizing system (Fernandes & Morais, 2021). Hwangbo et al. (2020) conducted a study which revealed the most essential outcome of reduced returns. The return rate was reduced by 27% by separating the inaccurate sizes and fits. Thus, the virtual try-on can substitute the physical garment try rooms. Furthermore, interactive 3D personalised avatar experience enhances the decision-making procedure which will lead to better gains for customers in physical stores as well as online stores (El-Seoud & Taj-Eddin, 2019). After reviewing the luxury unstitched apparel market and the virtual fitting room tools, this study will address the research gaps of fashion retailers in Pakistan that use manual tape measurement methods which is not applicable for fashion e-commerce because of 1) human error involved in extraction of manual measurements, 2) the time consumption of the tape measurement method, and 3) lack of technical knowledge of landmarking points of body part to get accurate measurements (Almalki et al., 2020). The traditional tape measurement technique used to collect body dimensions for customisation of garments is a notable impediment in the establishment of sustainable mass-customised e-commerce business worldwide (Idrees et al., 2020a). Moreover, even with standard size charts of mass-produced garments, consumers are dissatisfied, because worldwide consumers have various body types and sizes, and as well as the inability to try on garments during online shopping (McKinney et al., 2017; Reid et al., 2020). Therefore, the study addresses the following research question after highlighting the research gaps: how fashion e-commerce platforms of luxury unstitched Pakistani fashion apparel products enhance consumer satisfaction by employing virtual fitting room tools (such as 3D mobile app scanners, virtual reality and augmented reality and mixed reality)? To answer the research question, the luxury unstitched apparel products have been reviewed and analysed. The recent developments in application design, consumer behaviour research regarding intention to use, satisfaction and purchase with virtual fitting room tools and recent fashion industry examples of mobile 3D body scanner apps, virtual reality, augmented reality, and mixed reality have been explored. Findings from the analysis, subsequently, inform the sustainable
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e-commerce business model which is presented as an outcome using the model of consumer shopping journey and experience by Lemon and Verhoef (2016).
2
Methodology
The secondary data have been used for the conceptual chapter. The first section of the chapter presents an overview of luxury unstitched Pakistani fashion apparel products and market. The most recent and relevant literature was reviewed on the luxury unstitched apparel products from databases such as Google, Google Scholar, and academic journals using keywords ‘Pakistani unstitched lawn suits’, ‘Pakistani unstitched designer wear’, ‘Pakistani designer wear’, ‘Pakistani women luxury unstitched apparel’. The second section presents virtual fitting room tools such as 3D body scanning mobile apps, virtual reality, augmented reality, and mixed reality. The most recent and relevant literature has been reviewed by writing keywords such as 3D body scanning mobile application, augmented reality, virtual reality, and mixed reality using databases such as Google, Google Scholar, and academic journals. In the third section, the luxury unstitched fashion apparel products of Pakistan, virtual fitting room tools (virtual reality, augmented reality, mixed reality, and 3D body mobile app scanners), and process model of consumer shopping journey and experience by Lemon and Verhoef (2016) have been combined, to present another overarching theme or theory. Thus, a sustainable mass-customisation fashion e-commerce business model has been generated (Thomas, 2006). The sustainable mass-customisation fashion e-commerce model has been presented with a prospect to enhance the fashion e-commerce by incorporating virtual fitting rooms with unstitched apparel.
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Fashion e-commerce of Pakistan and Luxury Unstitched Apparel Products
This initial section of chapter offers an overview of the development of fashion e-commerce in Pakistan, focusing in particular on the Pakistan luxury unstitched apparel market and its global consumer demands.
3.1
Fashion e-Commerce of Pakistan
The fashion industry is an exceptionally vital segment of e-commerce businesses in Pakistan. The occurrence of fashion marketing and fashion show events of Pakistani unstitched products in the online and offline settings has facilitated e-commerce traffic (Arifeen, 2017).
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2022 2022
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E-Commerce growth statements The revenues and profits with e-commerce platforms have increased The Pakistani revenue in the e-commerce market is estimated to achieve The revenue is anticipated to deliver annual growth rate (CAGR 2022–2025) of 6.09%, which led to an expected market volume of US$9153.00 m by 2025 According to Statista revenue in Pakistani fashion segment estimated growth is The annual projected growth rate (CAGR 2022–2025) is noted to be 5,09%, resulting in an estimated market volume of US $1670.00 m by 2025 The Pakistan’s apparel segment revenue in 2022 is projected to achieve The revenue is anticipated to deliver an annual growth rate (CAGR 2022–2025) of 2.57%, resulting in an estimated market volume of US$644.80 m by 2025, with an anticipated market volume of In Pakistan apparel segment, the number of consumers is anticipated to reach to The expected operator penetration will be 8.0% in 2022 and is projected to reach 10.3% by 2025. The expected average revenue per user (ARPU) will reach to
Predicted market volume US$4094 m US$7666.00 m With anticipated market volume of US$1412.00bn in 2022 US$1439.00 m With a predicted market volume of US$312.20bn
US$597.50 m US$167,900.00 m
24.9 m US$32.71
References Statista (2021) Statista (2022b) Statista (2022b)
Statista (2022c) Statista (2022c)
Statista (2022a) Statista (2022a)
Statista (2022a) Statista (2022a)
Although Pakistan e-commerce is growing, and the use of mobile phones and Internet service worldwide is expanding. However, there are still numerous technological challenges that are limiting the development of e-commerce industry in Pakistan (Iqbal et al., 2018). Such challenges associated with the latest e-commerce technology such as mobile body scanners, virtual reality, augmented reality, and mixed reality will be discussed in the third section of this chapter to determine its functionality and its importance in fashion e-commerce. The following section will focus on delving into and discussing the technological tools used in luxury unstitched apparel products.
3.2
Luxury
There are two vital perspectives on identifying the luxury products. First, there is the consumption viewpoint, which entails the spiritual value of status a customer achieves from the product, generating unique customer engagement. Second is the product viewpoint, which focuses on the product’s superior quality, high price, and craftsmanship (Fionda & Moore, 2009). It was established by Mintel (2011) that
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60% of luxury buyers shop for luxury goods for pampering themselves and for their social gatherings. These approaches to luxury products have benefited the luxury entrepreneurs. Furthermore, innovation in technology, Internet, and globalisation has enhanced approach of global consumers to buy products. Consumers with disposable income are more satisfied with bespoke and customised services, particularly those who look for unique and distinctive products (Minkoff, 2022; Valich, 2017). Moreover, luxury retailers are completely modifying their business strategies to compete effectively by expanding their product lines and by incorporating the latest virtual fitting room features (Idrees et al., 2020b). The necessity for luxury goods and services has always been linked with the level of income of an individual; higher income levels lead to increased levels of dispensable wealth which facilitate purchases of expensive and exclusive product, which others might not be able to access (Ray & Vatan, 2013).
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Luxury Unstitched Apparel Product of Pakistan
Pakistan is well known for its luxury unstitched apparel which are bought worldwide (Latham, 2016). The demand of unstitched apparel product has been increasing worldwide since consumers receive the personalised experience, whereby the product is constructed according to consumers’ body dimensions (Sapphire, 2019). These products are considered luxurious due to their quality, exclusiveness, timeliness, elegance, and worth (Elan, 2021). In South Asian countries, particularly in Pakistan, the vogue of unstitched garment makes sense to consumers. Tailoring and personalised garments services are easily available for consumers (Sapphire, 2019). The designing of unstitched apparel products of Pakistan is exclusive, and thus offers personalised, bespoke garments to consumers worldwide (Latham, 2016; Rehman, 2014). The Pakistani e-commerce market has contributed to the global growth rate of 29% in the 2021. The designers’ shops have surpassed the fashion e-commerce ranking for Pakistan in 2021 (Bashir, 2022). In fact, the Limelight fashion brand has been remarked as the biggest player with a net sale of US $ 50 million; second position is held by Gul Ahmed shop with a net sale of US $ 48 million. Khaddi stood at third place with a net sale of US $ 29 million, followed by Sana Safinaz and Alkaram Studio, with net sales of US $ 23 million and US $ 22 million, respectively. It has been noted that there were over 61 million Internet users in Pakistan in January 2021, with an increase of 11 million users from the prior year (Bashir, 2022). Unstitched apparel products are defined by the components included in the garment; thus, they must be first taken into consideration. For unstitched apparel products, the upper garment includes separate fabric pieces or one full piece of fabric offering the front, back, and sleeves along with separate one-piece of fabric for the lower garment, which is adorned with various options such as printed and embroidered fabric pieces. The product is usually made available in specific lengths and widths determined by the size requirements of an individual’s body shape, size, and fitting style. There are several choices available when buying these products
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Fig. 1 Unstitched apparel product with demonstrated garment style model image
including 3-piece product (trouser/shalwar (2.25 meter/2.50 meter), shirt (3 meter (front 1.25, back 1.25 meter, sleeves 0.50 meter)), and dupatta (2.25)) and 2-piece product (trouser/shalwar, shirt) or (shirt, dupatta) and 1-piece product including any one of mentioned options. Adornment techniques to the fabric (such as printing, machine embroidery, and hand embellishments) are utilised with additional trims and accessories such as buttons, laces, and embroidered pieces for patch work according to the design requested. Moreover, for tailoring purpose and for style demonstration, a model image is offered by fashion retailers to consumers with each unstitched apparel product. The model image allows tailors to understand the style of garment to deliver exact style of garment with personalised size and fitting of consumers (view Figs. 1 and 2). Due to the personalisation of these garment, including their construction methods, it has been suggested as a sustainable manufacturing technique (Elan, 2021; Idrees et al., 2020a, 2020b; Sapphire, 2019).
3.3.1 Luxury Unstitched Collection The most famous and extensively used unstitched apparel products in summer and spring seasons include lawn, cambric, Swiss voile, jacquard, and cotton. For winter collection of unstitched apparel products, linen, cambric, wool, khaddar, and karandi fabrics are used. The products are available in online stores of Pakistani fashion brands. To design luxury unstitched collection, fabrics such as chiffon, silk, organza, cotton net, and velvet and expensive net fabrics are used in various shalwar/trouser, kameez, and dupatta styles (Sapphire, 2019). Moreover, bridal wear is one of the most expensive unstitched luxury product, which is incredibly famous and in demand internationally (view Fig. 3) (Elan, 2021; Utsav Fashion, 2016).
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Fig. 2 Unstitched garment after personalised tailoring
Fig. 3 Luxury bridal wear (unstitched) embellished and designed beautifully
3.3.2 Embellishment on Luxury Apparel (Unstitched) Luxury unstitched apparel are exclusively designed with hand and machine embroidery, digital textile printing, and manual embellishments. The embroidery and
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printing industry have faced serious competition due to the advancements in technology. However, it survived thanks to the development and adoption of new markets, which provided with new technologies and machinery that produced high-quality embroidered and digitally printed textiles (Rind et al., 2021; Zahid & Kamarudin, 2019). Manual hand embellishments which include embroidery with kora, dabka, cutdana or beadwork, Resham, zardozi, machli tanka, gotta work, beadwork, tarkashi, and stonework with exclusive motifs have been reigning the textile sectors for ages (Moghees, 2018). These embellishments are intricate and precise and they are mostly done on expensive fabrics (Elan, 2021). Therefore, consumers are willing to spend a substantial amount to buy such luxury products.
3.4
Limitations of Virtual Fashion Viewing Technology, Manual Measurement Method, and Standard Sizing System for Garment Construction
The traditional art of tailoring is generally constrained to developing countries; yet, the fashion industry globally appreciates the art of tailoring and has taken it as an indispensable element (Ahmed et al., 2016). For customisation of garments in Pakistan, traditional body measurement technique has been used to construct garments; however, it is a major obstacle to establish it as globalised masscustomised garments e-commerce business (Idrees et al., 2020a). The main obstacle is the consumers are not efficient in measuring their own body dimensions. Secondly, there is a requirement of technical expertise required for locating the exact body landmarks to acquire the body dimensions. Thus, human error involved in the extraction of manual measurements such as self-measuring is challenging, and expert measuring is not possible due to limitations in accessibility. Moreover, traditional measurement methods are also a time-consuming process (Almalki et al., 2020). Similarly, the standard sizing systems (such as numerical (8, 10, 12) and alphanumerical (S, M, L) are inadequate, due to population within specific countries (e.g. USA, UK, Pak, and EU) having different body types and sizes (Jain et al., 2018). Thus, it is difficult to accomplish the necessity of delivering customised garments to consumers worldwide in an e-commerce environment where consumers cannot try on garments to find their right size (Reid et al., 2020). Moreover, to acquire rich information of a product 2D images have been argued to be incapable of fulfilling the demand of worldwide consumers (Idrees et al., 2020b). Therefore, virtual fitting room tools such as 3D mobile app scanners, virtual, augmented, and mixed reality platforms have been introduced to enhance the fashion e-commerce.
3.5
Sustainability and Unstitched Apparel Product
The major problem with mass production is the heightened wastage of fabric from replicating single design for masses. The designing process includes standard size
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measurements for garment production. This process leads to increased fabric wastage, which is not well-fitted for diverse populations. This approach is extremely problematic and cuts down the window of sustainability (Nayak & Padhye, 2016). Unlike standard sizing system products, the unstitched apparel product is designed according to the specific size of wearer and cloth wastage is thus reduced. To develop an environment-friendly industry one of the best ways is to narrow down fabric waste during garment construction. Therefore, size specific cuts and fabric usage only as per requirement can lead to sustainable fashion construction environments (Noh et al., 2017; Saeidi & Wimberley, 2018). Therefore, the fashion e-commerce can be enhanced by the addition of virtual fitting rooms in the fashion e-commerce platforms of unstitched apparel products, to offer mass-customised garments in the international market with right size and the fitted garments (Idrees et al., 2020a). Thus, the next section will transition into discussing virtual fitting rooms in detail and their benefits to enhance the fashion e-commerce in terms of virtual fashion viewing and virtual size and fitting.
4
Virtual Fitting Room Tools
This section overviews virtual fitting room tools (virtual fashion viewing and size and fitting) of fashion e-commerce. The recent developments in application design, consumer behaviour research regarding intention to use, satisfaction and purchase with virtual reality, augmented reality, mixed reality, and mobile app scanners and the recent examples of virtual fitting rooms technology used in the international fashion industry are discussed.
4.1
3D Body Mobile Application Scanners
The mobile scanning apps have a capability to deliver body dimensions and personalised avatar by capturing 2D photo utilising the smart phone camera. These applications can be operated using a smartphone, tablet, and laptop. The applications offer benefits to both fashion retailers and buyers by offering full body scanning, scanning of various parts individually, virtual fitting room for size and fitting visualisation, recommendation, and customisation (3DLook, 2022; TechMed3D, 2020). The user can acquire more than 100 digital body dimensions in 1 to 5 min through a mobile scanner. The mobile app scanners can measure parameters such as distances, girths, heights, width, surface area, body fat percentage, and circumferences by detecting specific body landmarks through artificial intelligence. To acquire more than 100 body dimensions in a minute is not possible through the traditional manual measurement methods, which is on the contrary a timeconsuming process (3DLook, 2022; BS ISO 20685, 2010; Idrees et al., 2020a; Stream, 2022).
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4.1.1
Recent Developments and Consumer Behaviour Research of Mobile App Scanning The accuracy of measuring the dimensional traits of a human body utilising a 3D model has been assessed by iPhone 12 Pro LiDAR scanner. The study reported that the mobile scanner body dimensions can be used to construct personalised garments (Mikalai et al., 2022). Similarly, virtual fitting through virtual simulation and bespoke garments construction process has been studied with Styku (MyBodee) body scanner. The users reported that body scanning and simulation techniques are a better approach than traditional method for online garments buying (Sohn et al., 2020). The estimation algorithm, blended with the fuzzy logic model, has created an automated process of extracting the size and body shape possible. The outcomes of the study indicate a novel research method for rapidly notifying people about their body shape. The technology supports purchasing of ready-to-wear clothes and customised garments as well as facilitating garment purchase in both the online and offline setting (Thi Nguyen et al., 2022). Moreover, a comparative study has been conducted using MeThreeSixty mobile app and conventional anthropometry and size stream scanner SS20 which supports that smartphone app accuracy is comparable to conventional tape measurement procedure for garment construction (Smith et al., 2021). An integrated solution has been described for personalised made-to-measure (MTM) knitwear garments grounded on 3D body scanning by means of automatic data transfer from scanner to the flat knitting machine. Therefore, knitted garments can be personalised using the appropriately configured flat knitting machine (Surc et al., 2020). Therefore, the idea of integrated solution provides evidence that mass-customisation system can be incorporated using the virtual fitting room platforms. 4.1.2
Fashion Retailers’ Application of Mobile Body Scanning for Virtual Personalised Services Nettelo and Element Pure mobile app scanners has offered a fairly simple process by capturing two pictures: firstly, the front with an A pose and, secondly, the side with the pose adopting hands touching the thighs and feet joined together. These AI-based apps offer body dimensions and creates human model of the user. The Nettelo app offers size recommendations of different countries such as the EU, UK, and USA, whereas the Element Pure mobile scanning app offers an additional solution of custom shirt fitting including slim, regular, or relaxed fit (Element Pure, 2019; Nettelo, 2022). Similarly, size stream has introduced the MeThreeSixty mobile app scanner and Formcut 3D measurement technology. The user can scan himself or herself in selfie mode by capturing two images of the front and side pose by wearing a tight fitted upper and lower garment which displays their body contours clearly. This allows for the extraction of exact body dimensions and deliver the output in the form of body dimensions and a personalised avatar (Stream, 2022). The 3D Look mobile app scanner has a similar process as detailed in the abovementioned apps of capturing a 2D image using a smartphone. The app offers a virtual trying-on option (3DLook, 2022). More than 100 retailers are partnered with 3D look body scanning company; an example includes companies from the uniform
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industry (Safariland and Fechheimer Brothers, a Berkshire Hathaway company) (Edelson, 2021). Moreover, stylist Julia Pelipas founded the fashion brand Bettter, which is connected with 3Dlook to offer virtual made-to-measure solutions for the end user. The production of apparel products falls into sustainability line, which represents no overproduction of products. She declares ‘We really don’t want anyone to buy suits that won’t fit first’ to Vogue (3Dlook, 2021).
4.2
Virtual Reality
Virtual reality is an immersive and three-dimensional (3D) experience. The environment of virtual reality does not appear within physical surroundings; it is separated from the real environment by a VR head-mounted glasses or VR display screen (Belova, 2020).
4.2.1
Recent Developments and Consumer Behaviour Research of Virtual Reality Hwangbo et al. (2020) explore the basic meaning of virtual try-on as the user experience and evaluates the impacts of 3D virtual try-on on online sales. The study concluded that virtual try-on impacts the sales outcomes of women’s casual L brand: the average sales per consumer improved by 14,000 South Korean won (13USD). The most vital conclusion is that the return rate is reduced by 27% by sorting out inaccurate sizes and fits. Therefore, virtual try-on can replace the physical garment try rooms (Hwangbo et al., 2020). An in-home virtual dressing room has been studied by Li and Cohen (2021), which entails minimum contribution of consumers. The only requirement is that two images (frontal and profile views of themselves) are elicited from a smartphone camera and further specification made of the fitting of the garment (loose or fitted garment). The process is convenient, efficient, and an easy alternative to taking precise body dimensions as carried out by a tailor. The 3D reconstruction presents a high-level accuracy for online stores garment construction and virtual garment fitting (Li & Cohen, 2021). Comparably, Sarakatsanos et al. (2021) evaluated an interactive virtual reality application for fashion designers. VR application proposes to provide an immersive environment for garments visualising precisely whilst garment designing procedure. Thus, VR technology permits designers to have a close-up assessment of a personalised consumer avatar wearing a garment in numerous ways and how the final garment will look, fit, and behave (Sarakatsanos et al., 2021). Similarly, two virtual try-on apps have been evaluated in terms of its impact on the adoption intention. The study reported that affordance of customisation supported and motivated adoption intension. The consumers were satisfied with their avatar image and exhibited greater impact on perceived augmentation. The research revealed that perceived augmentation has been motivated by personalised body image for affective judgments developed during the pre-task of virtual try-on avatar creation phase (Tawira & Ivanov, 2022).
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4.2.2 Fashion Retailers’ Application of Virtual Reality Asizer a virtual try-on application has been providing a solution of apparel size recommendation and visualisation of variety of clothing brands by employing 3D body scanning technology. Buyers can virtually try on garments and can view a virtual catwalk video for customised experience in the virtual environment (Asizer, 2022). TriMirror, virtual size and fitting solution, has been introduced by a Canadian company. Along with virtual trying on the garments, buyers can benefit from using the heat maps which shows the tightness and looseness of a garment on a personalised avatar. Fabric performance can be analysed by moving around virtually in various styles prior to purchasing a garment (triMirror, 2022).
4.3
Augmented Reality
The interactive AR technology allows the users to view virtual objects in the real environment or to add or blend virtual objects with real atmosphere. Virtual products can be examined just as the physical products can be examined in the real environment. Furthermore, AR enhances the product visualisation and in-depth information in online setting, which is not possible with 2D images of e-commerce platforms (Udiono, 2021).
4.3.1
Recent Developments and Consumer Behaviour Research of Augmented Reality A clothing customisation full-featured system supported with augmented reality has been introduced by Feng et al. (2021). The augmented reality virtual try-on system offers the choice of style, styles, patterns, colours, and fabrics for custom designing of garment and virtual size and fitting simulation (Feng et al., 2021). An android augmented reality technology has been examined in terms of consumer behaviour, consumer experience, and the benefit of augmented reality to enhance the fashion retailing industry. Primarily, the outcomes of consumers behaviour revealed that the interface was acceptable and user-friendly. Moreover, the technology is effective to replace the traditional trying-on methods. Thus, the AR technology has a sustainable impact on the consumer experience during the pre-purchase phase of consumer shopping journey. The dynamic 3D objects experience enhances the decisionmaking procedure which will lead to the improved footfall of customers in store and online store (El-Seoud & Taj-Eddin, 2019). The AR virtual dressing room has been explored in which consumers can try on garments virtually and can share the product for reviews to choose the best fitting garment. The results revealed that the shopping experience is more realistic, fun-loving, interactive, accurate, and userfriendly. The technology has the potential to provide similar in-store experience whilst staying at home (Mehta et al., 2020). Moreover, Qin et al. (2021) research study discloses that consumers’ cognitive evaluation of MAR applications encourages their intuitive reactions, which ultimately develop conative behaviour. Therefore, this research permits a unified perception for examining continuous use
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and purchase intentions mutually in one research model and reported that MAR experiences enhance the consumer decision-making process (Qin et al., 2021).
4.3.2 Fashion Retailers’ Application of Augmented Reality AR mobile applications have been introduced by various fashion retailers; for instance, Sapphire a Pakistani fashion brand permits consumers to evaluate garments in a 360 degree view on augmented avatar (Idrees et al., 2020b; Sapphire, 2019). AR virtual mirrors have been launched by Ralph Lauren for their in-store fitting rooms which reveals 90 percent user involvement with improved hedonic value (Johnson, 2021). Moreover, Louis Vuitton introduced a filter concerning the League of Legends game; the outfits of characters were designed by the LV company. By employing the smart glasses and smartphone, Sack Fifth Ave established RPR’s virtual clothing configurator. Consumers can visit virtual clothing rack in-store and at home which offer size and style recommendations of clothing and accessories (Johnson, 2021). Burberry and Rebecca Minkoff have launched AR fitting rooms or magic mirrors in their brick-and-mortar stores and in their online platform (Minkoff, 2022; Valich, 2017).
4.4
Mixed Reality
A compelling concept for enhancing the user experience which combines the computer-generated knowledge into a real-world environment is (MR) mixed reality (Wang & Dunston, 2011). The interface of MR combines the AR and VR technology, for instance, using the real world in a natural style whereas at the same time the smart devices are used to examine associated information by networking with computer-generated virtual items. In face-to-face meetings, the users can see each other’s facial expressions, gestures, and body language, improving the interaction transmission capability (Billinghurst & Kato, 1999). VR transfers items into the artificial atmosphere and enables operators to participate in that situation; AR improves information of the object to the actual world. Additionally, the situation where both AR and VR communication opportunities are examined within the object relates to MR (Cabero-Almenara et al., 2021; Lee, 2021).
4.4.1
Recent Developments and Consumer Behaviour Research of Mixed Reality (AR and VR) Mass-customisation business model has been presented with the collaborated apparel new product development model supported with the virtual simulation technologies. Garments are customised according to the personalised body dimensions and consumers can view size and fitting simulations before making a purchase. In this virtual simulation technology, strength of both AR and VR has been used. For example, VR tools have been utilised in the product development stage such as virtual prototyping. However, AR tools have been used during the consumer integration, for instance, examining perceptions and fitting evaluations (De Silva et al., 2019). In 2021, Kim and Sung studied the virtual fitting with the avatar and
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self-image mode using the mixed reality technology. A direct impact on the intention to use the mixed reality technology has been confirmed with education and escapism constructs of experience economy. The mixed reality technology has been recommended in fashion retailing (Kim & Sung, 2021). Sustainability is the biggest issue in online garments’ purchase; poor sizing leads to the clothing returns. Thus, utilising current virtual size and fitting technologies to solve sustainability and sizing issue is essential in the fashion industry. Fernandes and Morais (2021) determined that employing single technology contributes to inadequate business model. Moreover, it is concluded that augmented reality (AR), virtual reality (VR), and mixed reality (MR) and interactive mirrors (IM) should be amalgamated with the latest smartphone evolution. The combination could introduce solutions like smart fitting rooms (SFR) to solve problems like poor fitting, online returns, realistic online fashion viewing, and sustainability (Fernandes & Morais, 2021). The next section will discuss the sustainable fashion e-commerce business model and shopping journey stages by using the virtual fitting room tools and unstitched apparel market.
5
The Shopping Journey and Sustainable Fashion e-commerce Business Model
Consumer shopping journeys are dependent on the consumer behaviour and experience through three stages: (1) pre-purchase, (2) purchase, and (3) post-purchase (Fig. 4). Pre-purchase stage regards the use of mobile app scanner, virtual reality, augmented reality, and mixed reality for size and fitting visualisation and garment style selection. Purchase stage includes paying for garment online after getting satisfied with the pre-purchase stage during garment selection by virtual garment visualisation and personal digital body dimensions. Post-purchase stage focuses on the bespoke garment, including virtual try-ons and then real try-ons of the garments when they are received. The Lemon and Verhoef (2016) model has been employed to present how consumers would react in the pre-purchase, purchase, and postpurchase stages, whilst using the virtual fitting room tools and unstitched apparel for personalised virtual shopping for bespoke garments. In Lemon and Verhoef (2016), they emphasise the importance of the post-purchase stage as most consumer behaviour models have previously focused on the purchase intention in the shopping process (Rose et al., 2012). This signifies the importance of both the pre-purchase activities, which can lead to purchasing, and the post-purchase experiences during the garment assessment/try-ons. Furthermore, a comprehensive review has been conducted in the chapter on unstitched market and virtual fitting rooms tools such as mobile app body scanners, virtual reality, augmented reality, and mixed reality— which related to the pre-purchase stage. To understand how virtual fitting room tools can be incorporated with unstitched apparel for the benefit of both consumers and retailers, to enhance fashion e-commerce interfaces and online sales, Lemon and Verhoef (2016) applied this three-stage model of consumer shopping journey and experience. They found that consumers are encouraged to progress the shopping journey when they evaluated the service marketing, customer relationship
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Fig. 4 Process model of customer shopping journey and experience. Source: Lemon and Verhoef (2016)
management, and the multi-channel journey – which are all overarching processes that overlap and take place within the 3 stages discussed above, including how a product is presented/marketed in pre-purchase; relations during purchase, and the various interfaces utilised in these stages that consumer journeys on. The virtual fitting room tools and unstitched apparel products have been combined to present a sustainable e-commerce mass-customisation business model (Fig. 5).
5.1
Pre-Purchase
Consumers search for product information during online shopping, which is an important step in their decision-making process (Detlor et al., 2003). Saarijärvi et al. (2017) identify that consumer return product as an aspect of information that consumers may evaluate preceding to buy, to collect information about the product. This can be linked directly to a product that the consumer intends to buy; for instance if a garment is described as body fitted, the purchaser might buy a number of sizes for the assessment to buy right fit. The consumer may have an intention to buy only one product prior to purchasing a number of sizes of the same product (Saarijärvi et al., 2017). Consumers assess inspiring products at home with the benefit of free return option, to try only without any intention to keep that product. In addition, free shipping raise returns considerably by up to 18% (El Kihal & Shehu, 2022). Traditionally, consumers try on clothes during offline shopping, whereas during
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online shopping, consumers need to correlate their body size with size charts or images of products to make the size decisions. To correlate body dimensions to available standard size charts, consumers need to remember their body measurements or to measure themselves using tape measurements which is a timeconsuming process, and also requires one to have profound knowledge about body sizing to get accurate body dimensions (Hwangbo et al., 2020). Apparel buyers typically lack the prepared knowledge regarding the measurement of their body dimensions. Additionally, there are technical challenges involved in taking body dimensions manually by buyers themselves, such as exact body landmarking points to be considered whilst measuring the human body (8559-1, 2017; Almalki et al., 2020). Therefore, customising apparel products in an online setting is challenging using the traditional manual method of capturing body dimensions (Idrees et al., 2020a). Given that size selection is a highly tricky process in an online environment, this is apt to consider and employ alternative, innovative, and more user-friendly solutions. In the pre-purchase stage of shopping journey, consumers can use the mobile scanning apps to acquire the body dimensions. Mobile scanning apps have the capability to deliver body dimensions and personalised avatars by capturing 2D photos utilising the smartphone camera. The user can acquire more than 100 digital body dimensions in 1 to 5 min through mobile scanner (3DLook, 2022; Stream, 2022). Mobile scanner apps measurements and unstitched apparel products can be utilised to deliver bespoke garments in e-commerce platforms. Since the unstitched apparel products are designed in such a way that it can be constructed for any body type and shape of the wearer. Furthermore, the prior approaches for apparel product viewing in e-commerce have often been two-dimensional (2D) images: zoom in and out, animation/videofootage/catwalk, and no virtual trying-on option; these are deficient in providing the rich and interactive information of the products. Interactivity, rich data presentation, and realism are vital features that can fulfil the consumers’ online shopping requirements. Thus, in the pre-purchase stage, virtual reality, augmented reality, and mixed reality tools can be used to create functional interface by offering interactive three-dimensional (3D) virtual models, for garment virtual viewing with 360-degree rotation, virtual trying-on garments, mixing and matching of products, and virtual size and fitting evaluation (Escobar-Rodriguez & BonsonFernandez, 2017) (Altarteer & Charissis, 2019). These improved pre-purchase approaches via 3D mobile app scanners, virtual reality, augmented reality, and mixed reality interactive tools prove that they are more comprehensive and accessible tools that can be used to gain rich information during the pre-purchase stage. These interactive technologies have the potential to positively contribute to decisionmaking during online pre-purchase stage.
5.1.1
Involvement, Hedonism and Utilitarianism, Touch and Non-Touch Preference, and Perceived Risk For most buyers apparel products worked as experience goods (Song & Kim, 2012); and garments provide self-identity and expression (Loureiro et al., 2017). Consumers generally have less information in the online platforms. Thus, to
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facilitate the online purchase, one can enrich the experience by providing the rich and accurate information for the satisfaction of the consumer (Belk, 2009). High task atmospheric cues such as features of augmented, virtual, and mixed reality, 3D avatar with virtual size and fit visualisation, and recommendation interactive tools can upsurge the interactivity in the e-commerce platforms (Fernandes & Morais, 2021). Furthermore, the characteristics of pleasure in e-commerce are related to hedonism, especially since human nature often demands entertaining experiences (Mehta et al., 2020). Olsen and Skallerud (2011) determined that buyers usually retain loyalty for brands that enables hedonic rewards whilst retaining utilitarian functions or justifications. Moreover, touch and non-touch aspects are also vital in the online settings. For instance, Dholakia et al. (2010) acknowledged that it is essential to allow cognitive behavioural practices integrated in haptic garment interactions along with the functional and utilitarian features, which facilitates the establishment for virtual interactions in fashion e-commerce platforms (Dholakia et al., 2010). Taylor (1974) illustrates that uncertainty, anxiety, and self-esteem are chief risk considerations involved in the purchasing situations. Taylor (1974) indicates enhancement in information contributes to a decreased risk in consumer buying environments; these involve information gaining, modification, and processing. Taylor (1974), additionally, emphasised that marketing strategies that decrease risk need to be implemented to target consumers efficiently in the e-commerce environment, including those like Bauer’s (1960) establishment of perceived risk (as the level of unreliability a consumer perceived with a product or service), which ultimately resulted in poor decisions. Therefore, to address the issues of pre-purchase stage in online environments, processes associated with consumer involvement, hedonism and utilitarianism, touch and non-touch preference, and perceived risk, must be accounted for. The online retailers have adopted various techniques such as mobile app scanner, virtual reality, augmented reality, and mixed reality as tools within the above-mentioned process, to facilitate online buying. Mobile app body scanners have provided a solution for providing accurate body dimensions in the online environment (Stream, 2022). Virtual reality, such as Asizer (a virtual try-on application) along with body scanning facility, has helped tackle challenges with garment size recommendations and the visualisation of a variety of clothing brands. Buyers can virtually try on garments and can view virtual catwalk videos for customised experiences in the virtual environment (Asizer, 2022). Along with virtual trying on the garments, buyers can benefit from using heat maps, which show the tightness and looseness of a garment on a personalised avatar. Fabric performance can be analysed by moving around virtually in various styles prior to purchasing a garment (triMirror, 2022). Consumers can also try on garments by AR virtual fitting room via laying over a product on personalised avatars and can share the product for reviews, to choose the best fitting garments. These results both reveal and demonstrate that the shopping experience is more realistic, fun-loving, interactive, accurate, and userfriendly with interactive 3D tools like mobile app scanners, virtual reality, augmented reality, and mixed reality. These technologies have the potential to provide similar in-store experience whilst staying at home (Mehta et al., 2020). Similarly,
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fashion industry examples, such as Louis Vuitton, introduced a filter concerning the League of Legends game outfits of characters designed by the LV company (Johnson, 2021). Burberry and Rebecca Minkoff launched an AR fitting room or a magic mirror in their brick-and-mortar stores and in their online platform (Minkoff, 2022; Valich, 2017). Furthermore, the examples of unstitched apparel products can be utilised for the construction of mass-customised garments to provide right fitted and size-specific garments. The heightened of wastage of fabric with mass-produced garments can be reduced and greater population with various sizes, shapes, and heights can be easily accommodated worldwide. Additionally, technological developments of virtual fitting rooms have also been stimulated to facilitate and generate solutions for autotelic touch. Technological growth with augmented reality features has been developing to offer a solution for autotelic touch in the virtual world specifically with introduction of virtual fitting rooms (Gatter et al., 2022). Autotelic touch embodies excitement and sensual provocation in the process of garment consumption. Additionally, with the introduction of fashion metaverse and modification towards involvement of consumers with virtual avatar such as idea of gamification of the online purchase experience (Gibson, 2021), Foxall (2009) also confirms that choice of consumer is developed through information acquired and their behaviour in that environment; thus, by allowing the consumer to attain whole information about the garment fit (utilitarian) whilst benefiting from evaluating garment on their body shape will establish approach behaviour (Foxall, 2009). In addition, the consumer gets a better viewpoint with this behavioural practice before making a purchase (Foxall, 2009). Geissler and Zinkhan (1998) support these findings via their illustrations on how the consumer considers both aesthetic and functional properties of garment during online shopping, and how a garment fits on specific body types during try-on processes. These autotelicfocused approaches adopted to display products such as virtual fitting room tools have helped facilitate consumers to decrease perceived risk in the fashion e-commerce and encourage re-patronage (Simon & Peppas, 2004).
5.2
Purchase
In shopping journey, the purchase stage focuses on the choice of the consumer to pay for a product or not which is often specified as purchase intention. The intention to purchase is dependent on the pre-purchase stage satisfaction (Bai et al., 2008; Chen et al., 2010). After evaluating the interface quality, product information, and technology accuracy, consumers decide whether to pay for a product online (Chen et al., 2010; Hausman & Siekpe, 2009). Several research studies on the virtual fitting rooms, debated in the second section of chapter, have shown that when consumers are satisfied with technology mechanism (i.e. use and accuracy), this informs their intention to make a purchase in e-commerce platforms (Feng et al., 2021; Hwangbo et al., 2020; Mikalai et al., 2022; Thi Nguyen et al., 2022). Thus, the combination of unstitched apparel product and virtual fitting room tools could introduce very useful
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and practice solutions to problems associated with poor fitting, online returns, realistic online fashion viewing, and sustainability (Fernandes & Morais, 2021).
5.3
Post-Purchase
The gratification and the validation or invalidation of expectations regarding a product are associated with the post-purchase phase. After the required expectations with products are fulfilled, consumers are likely to be captivated or enticed by a product through positive word of mouth, re-patronage of a product or brand, and gratification. In post-purchase stage, garment fitness can highly promote postpurchase gratification; therefore, it is an essential part of post-purchase evaluations of clothing products (de Klerk & Tselepis, 2007). Therefore, unstitched apparel product and virtual fitting room tools present a justification of enhancing the virtual fashion viewing technology and virtual size and fitting selection and development. Additionally, personal reviews and other user reviews are also employed in the buying decisions of product (Etkin & Sela, 2016). In the post-purchase stage, consumers’ experience is evaluated and is an essential element in the consumer shopping journey as well as the consumer’s intention to buy more; it is also considered as a reasonable indicator of product gratification.
6
Conclusion
Prospects of instituting global mass-customisation sustainable e-commerce business have increased. However, the fashion e-commerce of Pakistan lacks the virtual fashion viewing and size and fitting tools to confidently buy right size and fitted garment (Idrees et al., 2020b). Luxury unstitched apparel product is mainly used for customisation of garments in Pakistan. Thus, the utilisation of virtual fitting room tools provides customisation facilities/tools along with size recommendation and virtual trying on with 3D product visualisation (in 360 degree rotation), which can provide beneficial in online consumer purchasing experience as well as increase competition amongst online retailers (Asizer, 2022; Lim & Jafari, 2021; Nettelo, 2022; triMirror, 2022). The virtual fitting room along with unstitched apparel product has the potential to sustainably impact on the consumer experience decreasing product, time, and resource waste. The phases of online consumer shopping journey such as pre-purchase, purchase, and post-purchase with regard to unstitched apparel product can be enhanced with virtual fitting rooms. This sustainable business model can help reduce size and fit challenges and online garment returns and promote sustainable garment manufacturing methods. The interactive 3D personalised avatar experiences enhance the decision-making procedures, which can improve the footfall of customers in store as well as online store (El-Seoud & Taj-Eddin, 2019). As previously stated, globally, businesses have been utilising this technology to lessen the ambiguity of selecting apparel products and right size to cut back on returns. The innovative
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virtual fitting rooms adopted by these international fashion retailers have emerged as unique way to reap customers’ interests, interactivity, and accuracy (Idrees et al., 2020b). These examples, of the utilisation of these approaches by international fashion retailers, provide both evidence and confidence about the potential incorporation of virtual fitting room tools in e-commerce shopping domains of Pakistani luxury fashion brands. Virtual fitting room technologies permit time, place, and purchasing advantages for fashion brands and provide entertainment that is associated with the real-time experience online. Technological innovations have transformed the e-commerce environment to interactive environments and have positively impacted the fashion industry. Thus, this chapter has offered a conceptual background for future research and the extension of knowledge on innovative approaches for application in fashion e-commerce environment. Furthermore, worldwide fashion retailers could enrich their online businesses via potential application of these examples of unstitched apparel products, which is a unique category in South Asian apparel market, to enhance sustainable mass customisation.
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Digital Customer Relationship Management (e-CRM) in the Fashion Industry Emanuela Sommella and Annarita Sorrentino
Abstract
Customer relationship management (CRM) aims to acquire customers and to establish profitable and lasting relationships with them. The use of a digital platform to implement CRM (e-CRM) allows the operational manifestations of the relationship between customer and company to be reported. Such digital platforms record data from every single customer and every single transaction and allow firms to obtain potentially vast amounts of data, which can be used to segment customers based on their digital purchase behaviour. Indeed, for companies it is essential to understand who their customers are and to know which customers contribute most to their revenue. One of the most widely used models to segment the customer base is RFM segmentation. This analysis defines homogeneous clusters of customers based on three variables: recency (R), that is, the time since the last purchase; frequency (F), that is, the number of purchases made by a customer in each period; and monetary (M), which is the average expenditure of the customer on the company website over a given period. The goal is to attribute to each customer a value or score that can place that customer in a specific segment (loyal customers, top customers, low-frequency customers, etc.) allowing the firm to plan different marketing and communication strategies based on the segments that emerge. The aim of this chapter is to analyse e-CRM strategies and actions in the context of the fashion industry based on RFM segmentation. We adopt the case study method to validate this framework. The case study concerns EM, a traditional Italian firm that operates in a specific niche of the fashion market, premium clothing for women.
E. Sommella · A. Sorrentino (✉) Department of Management and Quantitative Studies (DISAQ), Parthenope University of Naples, Naples, Italy e-mail: [email protected]; [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_15
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Keywords
Customer Relationship Management (CRM) · Recency (R) · Frequency (F) · Monetary (M) · RFM segmentation
1
Introduction
The function of customer relationship marketing (CRM) has evolved from a mere tool for monitoring customer satisfaction to a tool for analysis and interpretation of purchasing behaviour. The most obvious measure of satisfaction is the level of sales or market share. Similarly, the level of dissatisfaction is often taken to be the number of complaints. Both approaches may be overly simplistic. Moreover, there can be a significant difference between what the company thinks the customer wants and what the customer really wants. Hence, there is a need to measure the customer experience directly (Shokouhyar et al., 2020). The importance of CRM has increased with the emergence of technologies that have made it possible to map and manage one-to-one relationships with a huge number of customers in a digital and global context. The purpose of CRM is to increase the acquisition and retention of profitable customers effectively and efficiently by selectively initiating, building and maintaining relationships with them (Payne & Frow, 2006, p. 136). The digitisation of CRM processes has made it possible for companies to have selective relationships with specific customer targets, identified through dynamic segmentation based on purchasing behaviour. The digital CRM (e-CRM) allows firms to acquire, analyse, interpret and use vast amounts of customer data. In fact, e-CRM can be understood as a technology, often based on the cloud, that companies use to record, analyse and create reports on the interactions between the company and users (Wong & Wei, 2018). The goal of CRM is to allow companies to stay in on-going contact with their customers, through marketing strategies aimed at improving customer relationships, with the main objective of acquiring and retaining customers. The information collected through e-CRM is used to involve more customers, to consolidate customer relationships, to understand key metrics such as the customer abandonment rate, customer value and cross-selling, making sales forecasts more reliable. Moreover, that information can be rapidly transferred between sales staff and customer services, increasing their effectiveness, and similarly insights can be quickly transferred elsewhere in the organisation to support decisions. Automation of the CRM system makes it much more efficient (Kabasakal, 2020). In the fashion industry, CRM is a valuable tool for the integration of inventory management, customer communication, sales and marketing within the organisation. The process consists of acquiring, differentiating and analysing customer data for the purpose of optimising productivity and enhancing customer satisfaction. With CRM software, apparel retailers can design their sales plan, marketing and customer service to improve business standards, increase brand loyalty and find unique selling opportunities.
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The development of digital marketing and marketing automation made the management of the CRM concrete, thanks to the implementation of specific software (e.g. salesforce, salesmanago). This means that the process of acquiring and retaining customers in a profitable way is concretely manageable. From a theoretical point of view, our study offers an empirical analysis that demonstrates how customers can be dynamically segmented and how to act to reward different levels of loyalty. This chapter enriches the existing literature by offering a case study that proposes managerial ideas for companies in the fashion industry and beyond. Specifically, we investigate the case of EM, a premium brand (“Made in Italy”) that has implemented the dynamic segmentation of its market to achieve success in terms of brand loyalty, and increases in the recency, frequency and monetary variables analysed here. The study triangulates multiple sources of evidence, particularly online documentation and in-depth interviews with managers. Results highlight that the dynamic segmentation in digital CMM processes makes it possible to customise the relationship with the different customer segments through differentiated contact strategies and that this leads to improved performance both in the short term in terms of sales and in the long-term period in the businesscustomer relationship.
2
Theoretical Background
2.1
Customer Relationship Management
The main theme of CRM is knowing customers better (Winer, 2001). This enables firms to serve them better and keep them loyal. Building lasting relationships and knowing how to track potential and existing customers is key to customer acquisition and retention, which is the primary function of CRM. With e-CRM, all the relevant information is available in one place: a simple, customisable dashboard where a customer’s history related to the brand is registered. Moreover, on this dashboard, the status of their orders, any outstanding customer service issues, and more are documented. CRM refers to four things: a business philosophy, a business strategy, a business process, or a technological tool (Rababah et al., 2010) (Fig. 1). As a business philosophy, CRM is an orientation to customer relations, customer loyalty and superior customer value—putting the customer first and offering the best customer experience (Ryals & Knox, 2001). As a business strategy, CRM is a customer-focused business strategy that aims to increase customer satisfaction and customer loyalty by offering more responsive and customised services to each customer (Croteau & Li, 2003). It concerns how relationships with both existing and prospective customers should be managed. The objective is for companies to stay in touch with their customers on an on-going basis through strategies geared at improving customer relationships. CRM as a business process is a macro-level process that subsumes numerous sub-processes, such as the identification of prospective customers and customer
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Fig. 1 The four elements of CRM. Source: our elaboration
knowledge creation (Srivastava et al., 1999). CRM is then a system adopted by a company to consolidate and manage customer relationships. And finally, as a technology CRM is an enabling system that helps organisations to foster closer relationships with their customers (Hsieh, 2009). The definitions of CRM differ because it is still an emerging phenomenon and more time and more studies are need for a consensus to be reached on its essential nature. Such a consensus is perhaps made more difficult by the different academic backgrounds of the researchers and scholars and the multidisciplinary nature of CRM, given that it is a combination of management and marketing (Rababah et al., 2010). Nevertheless, CRM may be broadly defined as a very important tool that is used by firms to enhance customer loyalty and satisfaction and to manage long-term relationships between corporations and customers (Herman et al., 2020). Rababah et al. (2010, pg. 223) provided the following holistic definition: “CRM is the building of a customer-oriented culture by which a strategy is created for acquiring, enhancing the profitability of, and retaining customers, that is enabled by an IT application; for achieving mutual benefits for both the organisation and the customers”. For a better understanding (and definition) of CRM, there is a need for an extensive and critical investigation of the elements of a CRM initiative or programme. There are three such elements: people, processes and technology.
2.1.1 A New Era of CRM CRM is crucial for firms, and the databases supporting the new era of e-CRM (Fig. 2) record various aspects of customers’ behaviour, with tracking of their habits, tastes and preferences. This allows firms to have more personalised relationships with their customers, with the aim of building better and lasting relationships; indeed, maintaining stable and faithful relationships with existing customers can be more profitable for companies than acquiring new ones. Customer retention is the maintenance of continuous exchange relationships with customers over the long term. Companies need to focus on retaining customers who contribute to value creation (Chaffey et al., 2019). At the centre of the network of unique relationships
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Fig. 2 The new era of CRM. Source: our elaboration
between business and consumers is CRM, which manages the flow of information, responding to the need for consistent communication between the parties. While the importance of CRM has traditionally been as a sales and marketing tool, some of the major benefits may come from other areas, such as customer service, human resources, and supply chain and partner management (Salesforce, 2022). Digital transformation, fuelled by new digital technologies, suggests the creation of new business models. Indeed, a growing number of companies are transforming their value proposition by extending the traditional product offering to the provision of advanced services in which it is crucial to manage customer interactions. Customers have become more and more demanding: they expect to have a customer experience consistent with the brand, an experience that is simple, personalised and homogeneous at all “touchpoints” (Lemon & Verhoef, 2016). However, the customer experience is itself changing, with an increasing number of differentiating elements, such as the products or services offered by the company. From the point of view of the company, the challenge is to put in place all the measures necessary to ensure that the touchpoints are opportunities to improve customer knowledge, establish a lasting bond with the customer and increase revenues. In this context, we can say that we are in a “new era of CRM”, in which the customer remains the central point of CRM, but the number of touchpoints has multiplied in line with the global connectivity of modern technologies. At each touchpoint there is an exchange of information and a customer-company relationship is established. CRM is the central repository where a 360-degree vision of the customer is stored and in which the relevant data from each interaction are recorded. The amount of data that can be managed in an e-CRM system is enormous. The “customer journey” is the path followed by a potential or current customer, from the phase of awareness of a product/service to its purchase/repurchase, through
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one or more touchpoints provided by the company itself. If in the past the customer journey was short and linear, today (with the proliferation of digital touchpoints) it is more complex and articulated (Lemon & Verhoef, 2016). Modern, e-CRM, however, allows companies to track the customer journey along a path of one-to-one contact. The tracking of the customer journey permits companies to have an overview of their customer interactions and gives the opportunity to better understand what the different needs at the various stages. In this way, the efforts and investments of the company can be focused on what really is a priority for customer satisfaction. The most advanced e-CRM systems are equipped with services and development tools that both allow easy integration with external applications and permit them to flexibly model their business processes through the workflows. CRM is always inserted into an ecosystem within the company, where there are applications, data and processes with which it must “dialogue” and exchange information. Modern CRMs are increasingly established on platforms on it is possible to configure sales, marketing, and customer service functions, and also to develop customised features (Capalbo, 2020). The new-generation e-CRM is based primarily on the “software as a service” (SAAS) model, where the application is provided via the Internet. The amount of data produced by CRM applications to be exploited requires business analytics tools that can perform not only descriptive and diagnostic analyses (what happened and why) but also predictive ones (what will happen). It should be noted that the most advanced e-CRM systems use artificial intelligence to analyse data and to provide predictive functions and recommendations for sales, customer service and marketing. Artificial intelligence can also help to reduce the rate of abandonment through churn prediction, based on which the company can undertake retention initiatives and offer more customised products and services. Digital transformation requires a “customer-centric” business philosophy, focused on customer needs with the aim of improving customer satisfaction and brand perception. A “customer-centric” approach involves the whole business organisation and requires the introduction of new technologies, the revision of existing processes and a new organisational culture (Capalbo, 2020).
2.1.2 CRM Technology Although the use of technology is not a sufficient condition for the success of CRM, it can nevertheless play an important role in CRM programmes, particularly when the customer base is large. Indeed, CRM technology constitutes the backbone of many operational aspects of CRM, such as call centre operations and sales force automation (Garrido-Moreno & Padilla-Meléndez, 2011). Accordingly, it is important from both academic and managerial standpoints to understand how organisations implement, use and benefit from these technologies (Ang & Buttle, 2006). CRM software can be used in a variety of ways in an organisation’s CRM programme. These range from account management applications through to business intelligence systems, sales force automation and marketing automation. From a relationship management standpoint, CRM technology can be used to support
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relationship initiation, maintenance and termination activities (Reinartz et al., 2004), as well as to perform the analytics necessary to generate information in support of these activities. From a broader business process perspective, the technologies can be used as operational, analytical or collaborative tools in managing customer relationships. As operational tools, CRM technologies support front-office customer-facing processes such as call centre management, customer service, sales force automation and marketing strategy automation (operational CRM). As an analytical tool, CRM software applies statistical and/or data-mining techniques to analyse customer data generated through operational CRM and provide insight for strategic decision-making (analytical CRM). Finally, as a collaboration and communications tool, CRM software is used to manage relationships with external stakeholders in a company’s supply chain, such as suppliers, distributors and valueadded resellers (collaborative CRM). Accordingly, Henneberg (2005) suggests two CRM implementation approaches—a hard approach that emphasises analytical CRM, and a soft approach in which customer experience management (through operational and collaborative CRM) is at the core. CRM technology can benefit an organisation in many ways. Studies that have examined the performance impact of CRM technologies have concluded that careful implementation can significantly enhance performance on various dimensions. For instance, CRM technology has been shown to moderate the impact of information processes on customer relationships. Deployment of CRM software has also been found to significantly improve organisational customer knowledge generation and customer satisfaction and to positively impact the development of durable customer relationships and customer-linking capabilities. CRM software also positively impacts company return on investment through its impact on customer retention, revenue growth, better customer information and insights, cost reduction and improved employee productivity.
2.1.3 The Role of CRM During the Pandemic During the Covid-19 pandemic, e-CRM has allowed companies to maintain relationships with their customers. In fact, it has forced some companies have had to digitalise their touchpoints. It has particularly affected the marketing processes because of the emerging difficulties in managing physical sales channels and interactions with customers, both in the business-to-consumer (B2C) and in the business-to-business (B2B) markets (Wang & Xu, 2012). CRM is used to be more focused on customer satisfaction and service provision, but with the development of e-commerce, e-CRM, while reinforcing this intimacy and connection with customers, it has tightly connected product sales and communication processes, through the development and management of digital content (Chaffey et al., 2019). The Covid-19 pandemic led many organisations to conduct their work through digital platforms, and e-CRM helped them to provide both information to customers and services. According to research by Bhattacharya (2011), organisations have used CRM to reduce their costs and increase their performance. The outcome is the loyalty of current customers and new customers. During the
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pandemic, e-CRM represented an asset for the organisation, as it enabled it to connect with its customers and fulfil their requirements, and also managed sales and other organisational activities. CRM is used in every field to maintain a healthy and long-term relationship between the customers and the organisation (Bull, 2003). During the pandemic, CRM has not only played a very important role in the management of customer relationships, also but it has also pushed the market in a new direction: the digital platform has been a way to explore the market in a new way during the pandemic, when nearly everyone has been working from home (Bettiol et. al, 2021). In this context, CRM helps organisations to maintain relationships with their employees and provide services to them. According to Spence (2020), during the Covid-19 pandemic, e-CRM has helped organisations to know about the tastes and preferences of their customers. Throughout the pandemic, customers’ and employees’ mental health has been a priority for every organisation.
2.2
RFM Analysis
According to the literature (Baran & Zerres, 2010), for effective CRM it is useful to analyse “customer lifetime value” (CLV), defined by Kotler et al. (2014) as the present value of the future profit stream expected over a given time horizon of transacting with the customer. CLV can predict the profits obtainable from customers and their purchasing behaviour. But how can a profitable customer, that is, one with a high CLV, be distinguished from a less profitable one? One means of doing so is RFM (recency, frequency and monetary) analysis. The goal of the RFM analysis is to create categories (clusters) to identify those buyers who are—with greater probability—more sensitive and responsive to promotions and/or personalised services. The technique has its roots in—good old—traditional direct marketing, where it was a practical solution to reduce the costs of printing and shipping catalogues and thereby increase the return on investment. In the academic field, it was introduced in 1995 by Bult and Wansbeek. With the natural evolution from paper to digital and the advent of “Big Data”, RFM analysis has increased in accuracy and effectiveness. Once customers have been divided into clusters with the RFM model, companies benefit from solid decision-making and forecasting support for promotion and/or loyalty strategies. For companies, it is of fundamental importance to understand who their customers are and above all to identify those customers who contribute most to their turnover. The company can then try to establish strong communications with a view to customer retention and satisfaction. One trend is for companies to make use of customer “brand ambassadors” and to plan differentiated marketing strategies with respect to homogeneous groups of customers. The identification of such groups is based on structural characteristics, purchasing behaviour and consumption. On the basis of CRM, and more especially e-CRM, a firm starts by identifying customers’ true value and loyalty, and the basic information required for more targeted and personalised marketing.
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the period since the last
number of purchases made
the money spent during a
purchase; a lower value
within a certain period;
certain period; a higher
corresponds to a higher
higher frequency indicates
value indicates that the
probability of the customer´s
greater loyalty
company should focus more
making a repeat purchase;
on that customer;
Source: our elaboration Fig. 3 Recency, Frequency, Monetary. Source: our elaboration
RFM analysis is a customer segmentation method based on three variables: Recency (R), Frequency (F) and Monetary (M). The advantages of using this RFM segmentation method all relate to the firm’s better understanding of the following: • • • • •
who the best customers are which ones are at risk of abandonment the categories most sensitive to promotions those who could become more profitable those whom it is important to retain.
The goal of RFM analysis is to attribute to each customer a set of scores that can be used to place that customer in a specific segment (e.g., loyal customers, top customers, customers with low frequency). Then the company will be able to plan different marketing and communication strategies for the segments that emerge (Fig. 3). Specifically, the variables are: R (Recency): the period since the last purchase, where a lower value corresponds to a higher probability of the customer’s making a repeat purchase. F (Frequency): the number of purchases made within a certain period, which a higher value indicates greater loyalty. M (Monetary): the money spent during a certain period, where a higher value indicates that the company should focus more on that customer. The RFM segmentation method assumes that the best customers are those who: have made a recent purchase, have bought more often in each period of time and have made large purchases. The individual variables comprise the RFM indicator,
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which can be used to create a segmentation, therefore, which considers all three customer behavioural variables. Examples of the segments produced for a particular company might be dormant or not very active customers, high-spending and highfrequency customers, or high-frequency and low- spending customers. Companies use this type of analysis to identify who their most loyal customers are, which is essential because they are the ones who contribute most to the company’s turnover. For these customers, excellent communication and good loyalty programmes are especially important.
3
Empirical Research: The EM Case Study
We use an exploratory case study approach (Yin, 2014) and examine the case of EM, an Italian premium women’s fashion brand. The case study method is useful for an exploratory study that “focuses on understanding the dynamics present within single settings” (Eisenhardt, 1989, p. 534). Through a qualitative research approach based on primary and secondary data, we used multiple sources of evidence for the triangulation of data (Yin, 2009) and organised a two-phase case study analysis. In the first phase, desk research was conducted to collect information from the company website and official documents, such as reports and statistical data. This preliminary phase was useful for an initial evaluation and a focus for ideas and objectives, to frame the customer profile and to map the whole CRM process. In the second phase, carried out in March 2022, five semi-structured interviews were conducted: with the area manager, data analytics manager and three members of the retail management team. Questions focused on the following issues: company profile, CRM management, RFM segmentation and loyalty programmes. The interviews were carried out face to face at EM’s headquarters, and each took around an hour. They started with a couple of explorative and engaging questions to make the interviewee feel comfortable and avoid cognitive bias (Babin & Zikmund, 2015). All interviews were audiorecorded, transcribed verbatim and anonymised. Transcripts were analysed using the coding process of dividing data into themes related to the theoretical categories (Braun & Clarke, 2006). Specifically, researchers manually identified some broad categories (themes) as an expression of the ideas or feelings given in the text.
3.1
The Brand Profile of EM
EM is a premium brand (“Made in Italy”) of clothing that the company says enhances the femininity of every woman on every occasion through garments with Italian style and contemporary design. The brand was created 35 years ago with the aim of bringing fashion to women without any form of stereotyping. Across Europe it has about 180 single-brand stores: 90 boutiques, 80 corners and 10 franchises. The purpose of the company is “Fashion in all its forms”. The brand is known for serving women with the curviest bodies; especially for larger women, the brand is a reference point for a good fit, always combined with a very elegant style.
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Nevertheless, EM has always been an inclusive brand. Today, the concept of feminine beauty has become more inclusive, and this has allowed the company to rejuvenate its customer base and attract new customers who are less attentive to size. The company’s new philosophy is to take a step forward in the world of ready-towear fashion that aims to include, enhance and welcome all women.
3.2
Results from the Desk Research: The Customer Profile
The official documents were evidence of the customer profile and the loyalty rate. Specifically, the company’s target consumers had an average age of 55, divided into Madame, aged from 45 to over 64 years, and Respectable, aged from 15 to 44 years. The rate of loyal customers was also broken down by age group, as follows: • • • • • •
15–24, 0.5% 25–34, 1.6% 35–44, 6.4% 45–54, 20.8% 55–64, 30.6% over 64, 40.01%
EM has recorded over the years largely constant loyal customer rates, but Italy has increased its proportion of total sales.
3.3
Results from the Interviews
This section presents the results of the interviews carried out with EM’s managers. The findings have been divided into three: managing the e-CRM, RFM segmentation and loyalty programme.
3.3.1 Managing the e-CRM According to one manager, in September 2020 in-store traffic was 25% lower than in September 2019. In October it collapsed by 55%. Fortunately, the measures taken during the first lockdown, that is, sending “smart boxes” to loyal customers containing a selection of samples, and the continuous dialogue between stores and customers via WhatsApp’s were welcomed and now account for 10% of total sales. The premium brand had in fact revolutionised the shopping experience even before the emergence of Covid-19, with new systems, services and modes. According to one manager, the omnichannel strategy implemented provided a unique customer experience for all customers, ranging from e-commerce to physical stores. The e-commerce is based on advanced apps that give an overview of the entire range, as well as other, connected tools. The same manager said, “Digital for the company means offering the customer real-time information and multi-channel, seamless and personalised experiences in order to reduce complexity to the utmost
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simplicity”. In 2014, the company offered digital innovation within physical stores, such as the ability for customers to view the complete collections on tablets and to order products directly from the store, creating a smooth connection between online and offline dynamics. Specifically, the services that have been introduced to improve the shopping experience are: • Shopping Smart Box: a revolutionary way of shopping, which consists of a personal stylist preparing a selection of clothes and a lot of “look proposals” based on the needs of their customers. The Box is sent directly to the client’s home and customers can try on the garments and decide what to keep, at their leisure. • Go In-store: an immersive shopping experience through a PC or smartphone, as if the customer were in the store. With this option, customers can view the clothes live, and receive style advice from store managers, carried over into online shopping. • SlowPAY: a service through which people can buy in-store and defer payments without any commission or interest. • WhatsApp Your Store: with this service, the customer has the opportunity to message a favourite store via WhatsApp; store managers are available via messages or video calls to answer questions and provide advice.
3.3.2 Customer Base Segmentation EM’s e-CRM is based on RFM segmentation. According to the one manager, the total number of clients registered with this company’s loyalty programme was approximately 24.200. Main KPIs (Key Performance Indicators) have been shown, which are an important part of the information needed to determine and explain how this loyalty programme progresses towards its goals. The KPIs measured in this analysis are: • average expenditure • unit per ticket (UPT), which is the number of units (items) sold per receipt (i.e., customer visit) • markdown (MD), which is the average discount on a receipt • frequency. Based on points earned during the six months, there are four loyalty levels. During the interview, one manager showed data on the loyalty programme, which had lasted only months at that time. It analysed the programme’s performance in the years 2019 and 2021. On average, although there had been a drop in customers by 8%, the frequency had remained unchanged, and customers spent more (+4%), discounting less, and the number of receipt units (UPT) had remained unchanged. The markdown, the discount percentage decreases as you level up. Customer retention in the years 2019 and 2021, then the set of activities and benefits generated by EM’s loyalty programme proved successful, even over the long term. In practice, if a
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Clients
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FREQUENCY
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Open
Once a semester
1.1
165€
Privilege
Twice a semester
1.8
480€
Premium
Three times a semester
2.9
858€
Élite
Five times a semester
4.9
1767 €
299
Source: our elaboration Fig. 4 RFM segmentation at EM (2019–2021). Source: our elaboration
customer confirms a purchase within six-month loyalty programme, then they become a confirmed customer rather than a lost customer. RFM analysis is applied here to EM’s loyalty programme (Fig. 4). As shown in Table 1, the RFM analysis segments EM’s client base into four groups. The open group totals about 12,300; on average, they make a half-year purchase with a frequency of 1,1 and spend €165. The benefits that this group of customers receives are: a newsletter, appointment in the store, shopping smart box, the ability to express opinions on the company’s products and services, and a “20% off” voucher on the client’s birthday. The privilege group totals are 7.300 customers. They make on average a purchase every three months at a frequency of 1.8 and on average spend about €480. This group gets free shipping for online purchases and is also sent newsletters with exclusive content. The premium group numbers only round 1500. They have a recency of about two months and the number of purchases made on average every six months is about 3, with an average spend of € 858. On top of the benefits offered to the above two groups, the premium group also receives invitations to exclusive events and also a gold card.
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Finally, the last category is Élite. This is a particularly important group for the company, with an average expenditure of € 1.767. They are also very loyal customers, who have established a strong bond in the sense of both brand loyalty and store loyalty. The number of customers is 3.100; on average, they make a purchase every 5 weeks and buy with a Frequency of 4.9. This group receives further services, such as previews of collections and a dedicated concierge.
3.3.3 Loyalty Programme The company uses its loyalty programme to make customers’ shopping moments even more enjoyable, with exclusive benefits from the first purchase both in-store and online. Joining the loyalty programme lasts six months. At the time of the case study, the programme spanned December 2021 to June 2022, by when the loyalty points had to be used (i.e. to benefit from the accrued discounts). The programme was offered only to the “premium” and “elite” groups of customers (see above, Table XX). The discount offered was 10%. According to one manager, “during the promotional period, points will be collected reserved for customers enrolled in the loyalty programme. Each customer for every purchase made in EM-branded stores or outlets, including the online shop, will receive one point for every full euro spent. The accumulated points will be usable from the following day”. The loyalty programme (Fig. 5) offers: Newsletter always updated and distributed every week via e-mail, news about collections, discounts or commercial initiatives. Appointment in-store provides the ability to make an appointment in the store. Shopping Smart Box is a service in which the customer can order their own box and try the experience of shopping from home. A personal stylist prepares a selection of garments and different “look proposals” and a box is sent to the client’s home. Customers can try on the garments and decide what to keep and what to return. Collaborate with us is a service where customers can express their views and opinions on relevant issues (such as trends, products, styles) through surveys. Birthday discount coupon offers a 20% discount coupon that can be used by everyone. Free shipping on online purchases. Gold card (only for premium and elite customers), which offers a 10% discount. Invitations to exclusive events, such as presentations of collections with a stylist, fashion shows with customers in the store, and photo-shoot activities in the store. Preview presentations of collections Dedicated concierge and special attention. There are four loyalty levels of the programme, reached by accumulating loyalty points: Open: up to 249 points. This level of the programme welcomes the client with a dedicated services section.
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OPEN
PRIVILEGE
PREMIUM
Newsletter service always updated
Appointment in store
Shopping Smart Box
Collaborate with us
Birthday discount coupon
Free shipping on online purchases
Dedicated newsletters
Gold Card
Invitations to exclusive events
Preview presentations of collections
Dedicated concierge
Fig. 5 EM’s loyalty programme, 2021. Source: our elaboration
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Privilege: 250 points to 699 points. The “privilege” level provides a 5% discount and a gift voucher worth €50. Premium: 700 points to 1199 points. Accumulated points can be converted into a 10% discount, and a gift voucher worth €50. Elite: 1200 points and more. At the elite level, points are redeemable for a 10% discount and customers have access to all the services of the programme.
4
Conclusion
This chapter has applied RFM analysis to EM’s loyalty programme in a case study. CRM guides firms towards a customer-centric approach. With e-CRM, digital tools allow real-time management and use of data on the customer base (i.e., sociodemographic and purchase behaviour). RFM analysis is a useful and practical technique to cluster customers in homogeneous segments with important implications for managers. First, it quantifies three key variables of purchase behaviour: time since the date of last purchase (recency), the total count of purchases (frequency) and the average monetary values of those purchases. Second, the data collected allows companies to compare clusters and adopt customised actions to improve their performance. Third, customers who receive personalised communications and marketing actions (i.e., ad hoc discounts, a preview of sales, invitations to events) should feel more loyal to the brand. This chapter’s case study in the fashion industry underlines how the RFM segmentation can be used to customise the loyalty programmes. Indeed, as postulated, rather than a mass marketing strategy, the RFM customer segmentation facilitates the running of targeted loyalty programmes. The RFM analysis examines recency, frequency and monetary value and produces a market segmentation. These parameters help firms understand how different clusters can be managed and how firm-customer relationships can be improved. Customer relationship management has become even more important during the pandemic, when the fashion industry has reconfigured the shopping experience by using online channels, such as e-commerce. EM had revolutionised its customers’ shopping experience even before the emergence of Covid-19, both for end-customers—with new systems, services and modes that “completely transformed the shopping experience for customers”—and for managers—by implementing the digital CRM platform and the RFM segmentation. Indeed, to maintain a good relationship with customers, EM has been using a loyalty programme which offers added value to its customers and exclusive benefits. Each level of loyalty is associated with several services and benefits: the higher the level, the more exclusive the services. RFM analysis can be used to assess the effectiveness of such a loyalty programme. EM had consistently achieved a loyalty rate of over 93%, although this declined slightly with the onset of the Covid-19 pandemic. Nevertheless, e-CRM maintained an extremely high rate anyway.
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In addition, the case study demonstrates how different customer segments can be identified—in EM’s case, Open, Privilege, Premium and Elite—and how to implement a loyalty programme for each cluster. Despite the potential benefits of e-CRM solutions, Harrigan et al. (2011) underlined several weaknesses of dedicated CRM software for small firms; in particular, they recommended the use of more simple solutions to maintain relations with customers and perform necessary analyses. From this point of view, designing and using digital solutions in CRM might be a strategic tool for competition. This process also helps companies to improve the customer experience, especially in the fashion industry, where the competition is intense. Loyalty programmes often represent an opportunity both for consumers (who take advantage of the benefits) and for companies (which can monitor users’ buying behaviours and use the data to establish close relations with customers). Loyalty is understood as the favourable attitude of a consumer, expressed through the intention to buy. To be successful, a loyalty programme should aim at the most profitable customer segment. This is likely to require database technologies to identify loyal, highspending customers. Under these conditions, it becomes a programme of selfselection and individual correction (O’Brien & Jones, 1995). Currently, the strategy that is used to acquire and retain customers is CRM, a system that helps companies stay in touch with customers, simplify processes and increase their profitability. Our study shows how the implementation of CRM concretely allows managing customer data along the journey. Particularly, it makes available to segment customers in terms of their recency, frequency and monetary, which are key dynamic data to increase their profitability. From a theoretical point of view, our explorative study suggests, through an empirical analysis, how customers can be dynamically segmented and how to act to reward different levels of loyalty. This chapter enriches the existing literature by offering a case study that proposes managerial ideas for companies in the fashion industry and beyond. Specifically, we investigate the case of EM, a premium brand (“Made in Italy”) that has implemented the dynamic segmentation of its market to achieve success in terms of brand loyalty, and increases in the recency, frequency and monetary variables analysed here. The study triangulates multiple sources of evidence, particularly online documentation and in-depth interviews with managers. Findings highlight that the deterministic segmentation makes it possible to customise the relationship with the different customer segments through differentiated contact strategies and that this leads to improved performance both in the short term in terms of sales and in the long-term period in the business-customer relationship.
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The Use of Computer Information Systems (CIS) in the Ready-Made Garment (RMG) Industry in Bangladesh: Applications, Challenges, and Recommendations Md. Mizanur Rahman, Pranto Barua, Md. Saidur Rahaman, and Iqbal Hossain Moral
Abstract
This chapter investigates the use of computer information systems (CIS) in Bangladesh’s ready-made garment (RMG) industry. It also focuses on the potential challenges that could arise during the implementation of CIS. This is a literature review-based study that has been prepared based on recent relevant papers on using CIS on RMG in Bangladesh. The main findings revealed that CIS is a critical competitive tool for ensuring the seamless and effective operation of RMG in Bangladesh. Furthermore, one of the significant problems in implementing the CIS to RMG in Bangladesh is a shortage of trained and motivated employees to conduct the CIS’s functions. To carry out the activity properly and efficiently, regular training is required and some motivational packages for people associated with CIS applications. Finally, higher authorities and policymakers will get a comprehensive picture of the benefits and drawbacks of implementing CIS in Bangladesh’s RMG industry. Keywords
Bangladesh · Computer Information Systems (CIS) · Challenges · Ready-made Garment (RMG)
M. M. Rahman (✉) · P. Barua BRAC Business School, BRAC University, Dhaka, Bangladesh M. S. Rahaman Department of Business Administration, Metropolitan University, Sylhet, Bangladesh I. H. Moral Department of Business Administration, Northern University of Business and Technology Khulna, Khulna, Bangladesh # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_16
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Background
The initial journey of using information and communication technology (ICT) in Bangladesh was in 1960 for nuclear research (Nipa, 2020). Nowadays, the usages of ICT and computers are in every aspect of industrial sector for getting the competitive advantage (Alaskari et al., 2013; Azam, 2015; Dana et al., 2023; Rahman et al., 2022; Salamzadeh et al., 2022). The ready-made garment (RMG) is not far behind when it comes to the use of ICT. Throughout its prolonged journey, the industry has welcomed and reached a crucial adoption milestone for new technology (http://surl. li/dllmg). However, it is essential to make clear that computer information system (CIS) is one of the parts of ICT which includes some components such as hardware, software, network communications, data, people, and processes. Each of the components has some specific roles, and all roles work together under information system (Ahad et al., 2021). In this chapter, the researchers have only focused on the uses of CIS in RMG in Bangladesh. This industry has several departments/divisions, and activities such as ensuring adequate supplies of raw materials, running efficient manufacturing processes, maintaining relationships with national and international distributors, handling payment methods, ensuring customer satisfaction, and overseeing HR (Candra, 2011; Habib et al., 2021; Hossain & Rahman, 2022; Jiang et al., 2022; Nipa, 2020; Ryding et al., 2022). The role of CIS in this sector has grown in importance. Some examples of using CIS in RMG are (a) Employees attendance tracking, (b) time of shipment dispatching, (c) implementation of enterprising resource planning (ERP), (d) computerized cutting machine, (e) FIT approval through online, (f) ERP for inventory tracking in production management, (g) effective communication and getting online solutions through email, Skype, Zoom, Google meet and so on. The RMG sector is undergoing a transformation known as the Fourth Industrial Revolution. In the textile and garment sector, technology has had a significant impact. Bangladesh’s garment sector has gained a new vista of possibilities due to this revolutionary development. Bangladeshi clothing manufacturers have spent a lot of money in the last several years introducing the latest technologies to improve the quality of their products (Talapatra & Uddin, 2018; Textile Today, 2019). Cutting-edge software, laser denim washing technology, and the most recent washing technology have all been trained by Bangladeshi textile manufacturers to reduce clothing waste and the associated negative environmental implications. Bangladesh’s garment sector, of course, has a bright future. Efficiency gains, long-term viability, and an openness to new ideas can all be made possible through technology. A vast part of Bangladesh’s economy has been depending on RMG for the last 25 years, and it has been a leading source of revenue. It makes about $5 billion worth of goods each year by exporting clothes. Approximately three million individuals are employed in the business, 90 per cent female (fibre2fashion.com). Market elements such as the growth of the North American market and the particular market entry into European markets have been essential in the continued success of the RMG (Fibre2Fashion). Bangladesh’s RMG sector is a vital contributor to the country’s economic development. As a result, Bangladesh is the country that makes the most money from the export of sartorial. Attire source
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devotes a significant amount of time and attention to ensuring high-quality products and services. This transfer can be explained by the pay structure of the global apparel sector. According to the recent apparel export information, Bangladesh has reached a new record for textile exports in 2020–2021, despite the coronavirus outbreak and global market closures. Bangladesh exported garments worth USD 31456.73 million. This was a USD 27949.19 million achieved in 2019–2020 (BGMEA, 2021). RMG remarks the CIS is not only a tool for getting competitive advantage but also it (CIS) is an essential instrument for conducting its day-to-day operations smoothly and effectively. As RMG is export oriented, CIS plays a vital role in improving their overall performance and productivity. Besides, the applications of CIS is considered one of the potential tools for ensuring and strengthening the positions in local and international markets. RMG exports contributed 5.87% to GDP in the fiscal year (FY) 1994–95 and increased to 16.57% in FY 2012–13 (Majumder & Ferdaus, 2020). Following that, this contribution started to fall, and it has continued to FY 2017–18. It is highly disappointing that RMG exports contributed 11.17% to GDP in FY2017–18, the lowest contribution in the prior five years (Dhaka Tribune, 2019). According to business experts and trade analysts, sluggish private investment, backdated working techniques, and a lack of business diversity contribute to the RMG sector’s declining trajectory (Textile News, 2019). After that situation, Bangladesh started to think about the implementation of CIS in RMG industry. With the availability of technology, including CIS, significant industrial expansion can occur. Although Bangladesh should not be blind to the fact that technological changes in nature and work organization can impair quality, this has become a subject of concern in recent years (Textile Today, 2019). According to industry officials, on the other hand, a significant amount of money and technological resources have already been dedicated to improving the manufacturing process (Textile Today, 2019). However, in relation to the objective of the chapter, we proposed the following two questions: 1. To what extent the RMG can apply CIS? 2. What are the possible challenges to implement CIS in RMG in Bangladesh? This total chapter is divided into seven key sections: a. Background, b. Methodology, c. Contributions of RMG industry to economic development, d. Application of CIS on RMG industry, e. Challenges to implement CIS in RMG industry, f. Suggestions to overcome from those challenges, and g. Conclusions and implications.
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Methodology
This is a literature review-based study that examines recent and pertinent papers on using computer information systems (CIS) on RMG in Bangladesh. Figure 1 depicts a five-step literature review technique developed by Mascarenhas et al. (2018).
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Key words identification
Information and communication technology (ICT), computer information system (CIS), RMG, challenges of CIS
150 Titles Choose articles from different subject areas 40 articles and websites Every 40 items are critically checked in the this step Critical analysis Most suitable 20 items have been selected 19 items selected from the previous steps Analysis the content based on the objectives Analysis the documents
Fig. 1 Authors’ creation followed by Hoque et al. (2021) and Mascarenhas et al. (2018)
After deciding on the research characteristics and the study’s purpose, the researchers utilized keywords to search for relevant publications in databases such as Scopus, Web of Science, Google Scholar, DOAJ, JSTOR, and other relevant websites, among other sources. The most common keywords were information and communication technology (ICT), computer information system (CIS), RMG, challenges of CIS, and so on. Based on the keywords, initially 150 titles were found. But all of the titles were not relevant in relation to our objectives. In the second step, we selected 40 articles and websites which were more relevant to our topics. After critically analysing those 40 articles and websites, finally we selected 19 articles and websites to complete the content analysis to achieve the chapter’s objectives.
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Rationality of this Study
In 1971, Bangladesh became an independent country. During that time, many economic development experts thought the country would be stuck in a “below poverty level equilibrium trap” for the rest of its life. However, their prediction was quickly refuted when Bangladesh focused on the Ready-made Garment (RMG) industry. This industry introduced our country worldwide as a new tag “Made in Bangladesh”! and became a multi-billion dollar business. Once upon a time, Bangladesh used to be called a “bottomless basket” by cynics, but now it’s a
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“basketful of wonders” (Rahman & Ehasan, 2017). Bangladesh’s RMG industry is now widely considered the country’s most crucial international representative (Adnan et al., 2015; Majumder & Ferdaus, 2020). This sector has made significant contributions due to our country’s economic change. Over the previous three decades, it has experienced remarkable expansion, growing to become the world’s second-largest clothing exporter. In the fiscal year (FY) 2018–19, Bangladesh’s RMG industry accounted for 84.21% of the country’s total exports (BGMEA, 2020). This sector adds to foreign currency revenues and creates jobs, and, perhaps more crucially, empowers women by giving them employment opportunities (Majumder & Ferdaus, 2020). So, simply it is possible to say that this industry is contributing to economic and social development and it is recognized as the heart of Bangladesh’s economy. Bangladesh exported RMGs worth $27949.19 million to the rest of the world in fiscal year (FY) 2019–20, a decrease from the previous FY’s exports of $34133.27 million (BGMEA, 2020). The revenue from RMG exports was $11.40 million in January–April 2019. However, it declined to $8.45 million in the following year (The Business Standard, 2020). Under these conditions, the government’s previously stated goal of close to $50 billion in export income from this industry by 2021 is becoming increasingly unrealistic. The major hurdles now confronting our RMG sector are restricted & inadequate ICT infrastructure, conflicts between RMG owners & employees, energy & gas supply issues, and increased competitiveness in the quota-free international trade market (Islam et al., 2016). Considering the above circumstances, to improve the overall infrastructures of RMG industry in Bangladesh, it is essential to focus on information and communication technology (ICT) including computer information system (CIS).
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CIS’s Application in the RMG
Now, Bangladesh’s garment industry is undergoing a complete transformation and is the fastest expanding sector globally compared to all other garment-producing countries. Now, factories/manufacturers in Bangladesh that deal with attire source are fully automated, which means that processes like ginning, spinning, knitting, weaving, dyeing, finishing, and several other functions increase production and save time in the Bangladesh market. Every factory/buying house/production house is more content to work in an automated mode, as the probability of error is always lower than with human interference. It is generally known that one of the major drivers influencing today’s corporate environment is technological transformation. The global business world is becoming increasingly conscious of the shift. Bangladeshi manufacturers must embrace technology to maintain their position as a top sourcing country for the European Union and other export markets (Textile Today, 2019). Many clothing manufacturers have turned to eco-friendly water-saving technologies to delight their clients, resulting in high-quality goods with the best price-to-value ratio. It is easier to make clothes in Bangladesh than in other parts of the world. Robots are now being used to do everything that used to be done by
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humans, like handling, transport, packaging, loading, etc. Every factory in Bangladesh wants to compete with the rest of the world. This country has seen steady growth in the RMG in the last ten years because it has invested money in cutting-edge technology and skilled workers that other countries do not have. People in Bangladesh will change the business of making clothes in the next decade because they can adapt to a wide range of standards. Bangladesh will change the market in the next decade. CAD/CAM, Sewing, Spreading, Laundry, Finishing, Cutting, Printing, Testing, Knitting, Dyeing, Leisure Technique, and much other advanced equipment are used in most of the industries of the factories that deal with these kinds of things. Bangladesh is a manufacturer or factory that only focuses on ways to save energy and build green. There is a lot of attention paid to Eco green factory, which can meet the needs of international buyers. One of the examples set by Fatullah Apparels, a manufacturer in Bangladesh, has used the benefits of a Management Information System (MIS) to improve the efficiency of its production and add value to its supply chain (Apparel Resources, 2018). This industry now uses management information tools to be more competitive. They are spearheading a significant effort to spread the benefits of these tools to other businesses in the industry that want to change. Consequently, it has implemented Enterprise Resource Planning (ERP) at a high level and essential internet-based (Apparel Resources, 2018) technologies to ensure that quality is maintained throughout the manufacturing and planning processes. Inefficient tasks such as bureaucracy, coordination and communication, and inter-company analysis have been eliminated due to this initiative. It can now make judgements down to the most pleasing degrees of ultimate complexity, which is a significant advancement. Human data entry will be necessary for the time being for particular modules, such as the production of items on a single manufacturing line over a single day and the amount of fabric required to create a single unit of product for the time being. Compared to the previous methods, which depended on several memory-based calculations and had a more significant human error coefficient, this method provides far better data storage. The ERP records the everyday activities of a production line. Anyone can use it to determine a working line’s maximum production capacity. One of the production lines, for example, produced 512 units per day, while the others ranged from 420 to 500. Then know that creating 490 units a day is feasible. Anyone can use it as a benchmark to determine which of my manufacturing lines is doing poorly and where the problem resides (Apparel Resources, 2018). Benchmarking also aids in determining the time required for order delivery, the resources necessary, and, in general, projecting an estimate of the variable costs incurred for order delivery. Calculate the time it will take to deliver an order and add a few days to the delivery time if something goes wrong. It aids the industry in cost-cutting throughout the board (Apparel Resources, 2018). But the control this new system of work provides everyone can push efficiency up to 8%, which is a significant boost (Apparel Resources, 2018). Furthermore, whatever the cost of utilizing information technology solutions may be, it is conceivable to recoup the entire investment within one and a half years of implementation. This procedure is popular because the recovery period is short and has long-lasting benefits. Managers now have the tools to make more accurate
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forecasts by the ERP. The software provides managers with real-time data on the entire production. It forecasts whether the company is secure enough to take chances or whether it should focus more on defensive and cost-cutting initiatives. It aids in the formulation of industry-specific business strategies.
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Challenges in Implementing CIS in Bangladesh’s RMG
The RMG is crucial to Bangladesh’s economic development and socio-economic development. The expansion of this industry, on the other hand, has been endangered for the past few years. The suspension of the Generalized Scheme of Preferences (GSP) facility and the demand from many sectors to improve the infrastructural state of this business have emerged as a significant concern in the industry. The development of CIS infrastructure is also included in developing this industry’s infrastructure. As a result, this study aims to examine the roles and challenges of computer information systems used in the garment sector (Kiron et al. 2021). There are some crucial challenges in implementing CIS in the RMG in Bangladesh. First, there are several reasons why we lag in this field. The main reasons are a lack of conceptualization, a fear of technology, a problem with the infrastructure, a lack of objectively oriented education, and a lack of research and development. Even though the customer frequently mentions compliance and technology adaption, they seldom agree to pay even a small premium for those amenities. Because of this, the owner lacks the courage to spend money on cutting-edge technology 4.0 or higher (http://surl.li/dllmg). The more technologically advanced a society becomes, the more the garment industry comes to rely on computers and other forms of technology for its survival. This implies that when a machine malfunctions or a computer crashes, the garment industry is rendered almost inoperable until the situation is rectified. High reliance on technology places the garment business at a significant disadvantage, as they are more dependent on it than other industries. Second, human workers have less value due to technical advancements in the garment sector, which is a disadvantage. Because machines automate processes and can perform the work of ten people with a single computer, businesses have discovered that they do not need to hire as many people to complete the task at hand. Even if machines and computers continue to improve in terms of efficiency and sophistication, this will continue to be a rising disadvantage of technology and an issue that has global implications. The next point is that it is challenging to run and requires a broad background and executive awareness of the software used in the RMG (e.g., CAD, CAM, ERP/SAP, PDM/PLM, CAS, Fast React, and so on). Regularly recruiting people with the necessary skills and experience to operate this software is a challenge for the garment business. In Bangladesh, there are workers that are inefficient and inexperienced and have difficulty interacting with information technology-based machines. Because most garment employees are unfamiliar with CIM technologies such as software applications, they have difficulty implementing those applications in their workplace (Kiron et al. 2021). Lastly, a
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failure of the network brings everything to a halt. A local area network (LAN), a metropolitan area network (MAN), or a vast area network (WAN) is used to connect every branch, warehouse, and production centre with the Head Office. The online FIT approval, mailing solution, voice chat, and real-time connection with the customer using online solutions like Skype and Video Conference are all accomplished through the internet. A network outage or congestion can hamper these operations (Kiron et al. 2021).
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Overall Discussions
Bangladesh’s RMG industry is recognized as the nation’s most significant and prominent global representative (Majumder & Ferdaus, 2020). This industry has been able to make significant contributions as a result of the change in our country’s economy. Over the past three decades, it has experienced a tremendous growth spurt and is now the second-largest exporter of clothing in the world. For the fiscal year 2018–2019, 84.21% of Bangladesh’s total exports were from the RMG sector (BGMEA, 2020). This sector creates jobs, generates additional money in foreign currencies, and, perhaps most importantly, gives women more agency by giving them employment opportunities (Majumder & Ferdaus, 2020). As a result, it is fair to say that this industry is helping to foster social and economic development and is often regarded as Bangladesh’s main economic driver. Bangladesh’s garment industry is undergoing a complete transformation, and compared to all other nations that create clothing, it is the industry that is growing most quickly globally. Currently, all Bangladeshi manufacturing and apparel producers are automated. In the Bangladesh market, this translates to an increase in production and a decrease in the time spent on procedures like ginning, spinning, knitting, weaving, dyeing, finishing, and a range of other tasks. Among other things, the development of infrastructure for this business incorporates the development of infrastructure for the CIS. Therefore, this study’s goal is to explore the roles that computer information systems play in the apparel business and the challenges they encounter (Kiron et al. 2021). The main obstacles are a lack of conceptualization, a fear of technology, a difficulty with the infrastructure (shorturl.at/BCGI1), a lack of objectively oriented education, and a lack of research and development. Even though the customer frequently mentions compliance and technology adaption, they usually never agree to pay a slight premium for these pleasures. Because of this, the owner lacks the financial wherewithal to purchase cutting-edge technology version 4.0 or higher. Combining human and CIS labour in a joint effort makes it possible to facilitate the expansion of Bangladesh’s clothing sector. People who use information technology applications need to participate in activities that increase their excitement and regular training so that they can do the task in a way that is both effective and efficient. To ensure their workforce is aware of the advantages of adopting CIS, the decision-makers and higher authorities in charge of CIS implementation must make certain proactive efforts. The employees should not consider CIS to be one of their competing companies.
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Suggestions to Overcome Challenges
A collaborative effort between humans and CIS may pave the road for the development of Bangladeshi garment sector. In the earlier section, we highlighted the mentionable challenges to implement CIS in RMG industry in Bangladesh. However, in this section, we are providing some suggestions for policymakers and industry practitioners. We hope the following suggestions will be helpful for the development of RMG industry in Bangladesh. 1. Regular Training is essential along with some motivational packages for those people who involved with information technology applications. So that, they carry out the activity with effective and efficient way. 2. The policy makers and higher authorities need to take some initiatives to understand the employees that the implementation of CIS will bring some advantages for them. The employees should not take CIS as their competitors. It will not reduce their job opportunities anymore. 3. As some of the software are sophisticated thus the authority must be careful for recruiting people with the necessary skills and experience to operate this software smoothly and effectively.
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Conclusion and Implications
This study is one of the leading projects to focus on those concerns to the best of our knowledge. However, based on the considerations mentioned throughout the chapter, CIS implementation is unquestionably beneficial as a tool. It is, nonetheless, required for the RMG industry in Bangladesh to undertake day-to-day business activities. CIS, according to RMG, is a tool for gaining a competitive advantage. It (CIS) is a critical tool for running its day-to-day operations smoothly and efficiently. As RMG is an export-oriented company, CIS is crucial to its overall performance and productivity. Furthermore, CIS applications are seen as a viable instrument for securing and enhancing positions in both domestic and international markets. In terms of contribution, the academicians and researchers will get the current scenario of the implications of CIS on the RMG industry in Bangladesh. Besides, the higher authority and policymakers will also get a clear picture of the prospects and challenges of using CIS in the RMG industry in Bangladesh. Acknowledgement All of the authors would like to express their gratitude to the authors of the cited literature for their assistance and important information.
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Part IV Toward the Future
Enhancing Female Clothing Shopping Experience by the Use of the 3D Body Scanning Technology Daniela Campaniolo, Gianpaolo Vignali, and Daniella Ryding
Abstract
Technology has changed the way consumers shop and drives the move to a multichannel landscape. The COVID-19 crisis has further strengthened technology adoption in different sectors. Shoppers place more importance on sustainability than in the past demonstrating the key role of sustainable business practices. People tend to look for good quality garments to last better for the environment. Although the rise of online shopping presents a huge opportunity for companies to capitalise on, yet, fit and sizes remain an on-going issue. Fashion consumers find it difficult to assess these elements through digital platforms. Indeed, online fashion is the biggest sector for returns with a return average rate of 25% of the majority of retailers, squeezing retailers’ profits and increasing investors’ risks. This paper proposes the use of 3D Body Scanning Technology to leverage this issue. This technology would allow the provision of improved garments characteristics while facilitating the in-store and online experience. It adopts an exploratory approach. A series of 20 customers’ body scans to ascertain the perception of the 3D Body Scanning process. Respondents have been asked to describe this experience straight after the session by completing an D. Campaniolo (✉) Institute of Business, Industry & Leadership, University of Cumbria, Lancaster, UK e-mail: [email protected] G. Vignali Department of Materials, University of Manchester, Manchester, UK e-mail: [email protected] D. Ryding Department of Materials, University of Manchester, Manchester, UK e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_17
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open-ended questionnaire. This has been supplemented by follow-up interviews (relating to whether the results of the body scanning process had had any impact on respondents’ consumption behaviour); Results indicate a positive attitude towards the use of the technology which suggests favourable future application of the technology in a clothing retailing context and contributes knowledge to research literature and theory. Keywords
Consumer behaviour · 3D body scanning technology · Satisfaction · Fit and size
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Introduction
In the last ten years, the fashion industry has undergone intense changes resulting mainly from digitalisation, market demand, the recent covid-19 pandemic and the resulting economic landscape. Digitalisation has been disruptive for specific markets. Fashion consumers are shifting from the traditional in-store experience to a retailer mix in which there is a combination of channels, thus the concept of multichannel (Arrigo, 2018; Idrees et al., 2020a, 2020b; Reid et al., 2016; Ryding et al., 2022; Vignali et al., 2014; Vignali & Reid, 2014). In recent years, it has been paramount for retailers to adapt to those changes. A dramatic portion of consumption is made online resulting in the need for companies to embed in the new shopping narrative for both pure players and brick and mortar (Kushwaha & Shankar, 2013). The global pandemic of coronavirus disease 2019 (Covid-19) has impacted decisively consumer behaviour (Chrimes et al., 2022). As a consequence of the pandemic restrictions on businesses and individuals, the British economy is experiencing some challenges. At the time of writing this paper, there is an inflation rate of 9, 4% (Financial Times, 2022) and a resulting cost of living crisis. Consumer confidence is challenged, and new types of behaviour are emerging from consumers. For instance, a rise in conscious consumerism, which for most fashion shoppers, relates to items that are created to last. Among the main characteristics of durable products, the good fabric, fit and size are the major factors (Mintel, 2021; ONS, 2021). Covid-19 has consolidated the use of technology in the shopping experience, indeed the number of people buying online (Fig. 1) has increased steadily in 2020 (ONS, 2021). To shed light into ways to enhance the clothing shopping experience by the use of the proposed technology, it is pivotal to unfold the fashion retailers’ landscape (Vignali et al., 2019). Furthermore, this is becoming more important in the design of a fashion retailers strategy (Vignali et al., 2010; Vignali & Vignali, 2009). Fashion consumers have to choose from two main kinds of retailers. At one point there is the traditional retailer typology, “slow fashion (SF)”, in which high price
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Source: ONS (2021)
Fig. 1 Source: ONS (2021)
luxury products, from very well-known brands, deliver good quality garments. Collections span from two to four per year, as a consequence of the needed longer lead times. However, research points out that the lingering supply chain may have its drawback for SF as it is slow to adapt to consumers’ trends. As a consequence, inventory would accumulate and garments would need to be sold at lower prices once seasons end (Sellitto et al., 2022). On the other hand, Fast Fashion (FF) provides valuable opportunities for companies to capitalise on the latest trends. Some FF retailers offer numerous collections during a year, up to over new collections every week, resulting from a very effective supply chain validated by shorts design, production and lead time. It is clear that FF retailers can boost revenue levels through the numerous opportunities for customers to buy low price products encouraging impulsive buying. In addition, evidence suggests that retailers can increase annual sales by nearly 5% by providing a new collection with limited stock (Sellitto et al., 2022). Despite this, the idea of fast fashion imposes many limitations. For instance, it does not align with contemporary trends. For consumers, climate change and sustainability are very concerning. Buyers are interested in the concepts of circular economy and sustainable business practices (Liu et al., 2021). Contemporary research points out that consumers generally identify sustainable fashion with high-quality garments that are meant to last in the long term, thus benefiting the environment (Mintel, 2021). Studies exploring customer satisfaction for garments quality argue that fit and size are pivotal factors. Interestingly, these dimensions are also key to secure companies’ profits and customer retention. Clothing return is the main issue for online purchases, and fit and size are among the main reasons for this practice (Januszkiewicz et al., 2017). One must look at the existing technology to find solutions to try to solve the garment fit and size problems. The 3D body scanning technology has been accepted by the fashion industry for nearly a couple of decades. This technology allows the acquisition of numerous exact body measurements (Reid et al., 2020). The research
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to date has tended to focus on the use of this technology from a technical standpoint. For instance, the 3D body scanning together with Computer Aided Design (CAD) would enable the implementation of improved sizing systems and potentially assist mass customisation. However, the conception of new standard sizes resulted dysfunctional for more than 30 different sizes would need to exist to more or less fit women of every size and morphology [12]. Yet, far too little attention has been paid to exploring the perception of this technology in a retailing context. Therefore, this study focuses on exploring the female clothing shopping experience through the use of 3D body scanning technology. This paper begins with a critical review of the literature. It then goes on to methodological implications and findings. Finally, the last section provides conclusions.
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Literature Review
2.1
Female Shopping Experience
According to Solomon et al. (2006:6) consumer behaviour stands for: “the processes involved when individuals or groups select, purchase, use or dispose of products, services, ideas or experiences to satisfy needs and desires”. Normally, this is depicted as a linear step-by-step process consisting of the following 5 stages: problem recognition, search for alternatives, alternate evaluation (during which beliefs may generate attitudes, which in turn may result in a purchase intention) purchase and outcomes (Blackwell et al., 2001). However, insights into data demonstrate the difficulty in depicting a clear picture of the dimensions, which predict decisions and outcomes. In addition, it seems that rapid changes prevalent in the fashion industry prompt a more dynamic nature of the shopping experience for the twenty-first century consumers Court et al. (2009). It is also pivotal to also consider the construct of “customer satisfaction” and its implications for fashion consumers (Ryding, 2015; Ryding et al., 2016).
2.2
Satisfaction for Clothing Shoppers
Customer satisfaction is a widely explored concept in the marketing literature. For clothing shoppers, some suggest (Tiggemann & Lacey, 2009) that fit comfort and fabric are pivotal for women in the UK. Others argue that when a woman is wearing comfortable clothing (with proper fit and size), she feels more confident and generally more sociable with higher self-esteem (Alexander et al., 2005). This may have interesting implications for fashion retailers in their attempt to fulfil customers’ needs.
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Fit and Sizing Dimensions
Although there is no single approach to fit and size in the fashion industry, its key role when buying outfits is widely recognised by scholars and market intelligence firms (Apeagyei, 2010; Mintel, 2013; Song & Ashdown, 2013). While clothing sizing systems maintain a certain level of discrepancy, the feeling is that the reference to bust, waist and hips can be particularly challenging for the differences in body structures and the method used to take those measurements. This can be illustrated with reference to the high street fashion business. When comparing the sizing system within the UK retailers, Gill (2011) points out that the same customer wearing a “Planet” size 12 shirt (Fig. 2) would fit an “All Saints” size 16 shirt. Therefore, it can be argued that differences in the sizing systems would exert a powerful influence on the level of dissatisfaction for consumers. In recent years, retailers struggle with sizing provisions for the change in body shape types and the surge of overweight and obese people in the UK population sustained by the covid-19 pandemic and the changes in lifestyles. This is particularly painful in times when buying online is becoming the norm. When buying online, the uncertainty of garments’ fit elicits specific buyers’ behaviour (Tandon et al., 2021; Vignali et al., 2019). Thus, data suggests that online shoppers may order up to 5 sizes of the same item to leverage this issue. Alternatively, one can buy only from the same retailer whose clothing design is recognised to suit individual necessities. In these circumstances, likely, people’s behaviour is mainly influenced by the dimensions of fit and size and the impact on their
Source: Gill (2011)
Fig. 2 Comparison of sizing spread within UK retailers. Source: Gill (2011)
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satisfaction levels. However, the academic literature neglect to investigate this in depth (Mintel, 2021). The level of dissatisfaction is likely to influence clothing returns rate which impacts highly on companies’ financial performance and limits profits. Evidence suggests that approximately half of those who buy garments online return their items due to poor fit. Some argue that trousers and shoes are the most regularly returned items. The impact of the returns rate is paramount for companies’ end-of-year financial results. ASOS, a leading UK online retailer, advocates that a fall of 1% in returns would probably raise the company’s net earnings by £10 million (Reuters, 2013). This demonstrates the importance of limiting this return rate. Since technology is mainly called to offer alternative solutions, this study claims that the use of 3D body scanning incorporated into retailers’ distribution channels may constitute a solution to current issues in the fashion industry.
2.4
The 3D Body Scanning Technology
Over the last decade, several studies have been exploring the potential of the use of 3D body scanning technology in various fields (Almousa, 2020; Idrees et al., 2020a, 2020b; Rzepka, 2011; Shin & Baytar, 2013). This technology allows the production of a 3D digital replica of the entity scanned together with the unlimited recovery of precise linear, two/three-dimensional measurements of objects. For the fashion industry, this technology has been used for new sizing systems, new pattern-drafting methods, grading systems, 3D draping and virtual clothing (Fu et al., 2022; Petrova & Ashdown, 2008). Table 1 indicates the different models of the 3D body scanner. This study uses the Size Stream body scanning technology. This is a portable device (Gill et al., 2016; Size Stream, 2017) and most importantly, it is not sensitive to light or colour variation, thus facilitating the scanning process. Respondents can wear any colour of underwear, whereas with different models this would not be allowed (Size Stream, 2021). There is not a clear understating of the perception of both consumers and retailers of the 3D body scanning technology (Faust & Carrier, 2014;).
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3D Body Scanning Technology for Fashion Retailers
There are several advantages of the use of the 3D body scanning technology for fashion retailers as this facilitates the design and development stage of the clothing manufacturing process. First, it reduces costs, by limiting the time needed to market products. Second, it allows users to freely explore different concepts and produce new garment designs.
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Table 1 Body scanning typologies Type of body scanner Laser scanning Structured or White-Light scanning Human Solutions (formally TechMath) Cyberware (Digisize)
Wilson (TriForm/ TriBody) Telmat (SYMCAD) [TC]2 Body Measurement System: Size Stream
Characteristics Body scanners based on laser technology are able to scan about 60,000 points per second. Body scanners with structured light technology work with projectors. They project a series of white-light stripes on to the subject and are captured via cameras (Istook & Hwang, 2001). Human Solutions’s 3D body scanner (e.g. Vitus Smart XXL) is based on laser technology. Data can be exported in ASCII, OBJ, STL and DXF formats (Human Solutions, 2009). The scanning process captures an array of digitised points represented by x, y and z coordinates for shape. 3D rendering tools allow the operator to view the 3D scan data immediately on completion of the scan (Cyberware, 2009). These body scanners use white light to capture the 3D scan data in approximately 12 seconds via 8 camera views. Resulting 3D scans can be saved in different output formats (Wilks & Wilson, 2009). A set of white-light stripes is projected onto the subject for data capture (Telmat Industrie, 2009). TC]2’s Nx16 body scanner system is a 3D measuring system that utilises optical lenses that produce a digital copy of surface geometry of the body. This model utilises Infrared Depth Sensor (not sensitive to light or colour variation). Instant Scan Mode of 0.2 second duration 4D scan mode (scanning at 10 frames per second).
Source: adapted from Apeagyei (2010); Size Stream (2017)
By seeing designs matching specific body shapes, the designer can make changes in the early stages of the process that can reduce the industry’s carbon footprint. Most importantly, this technology can be used with 3d printing and virtual try on. Though the following list is not exhaustive, it can describe the main benefits for the fashion supply chain: • it can diminish the number of required steps • it can accelerate garments’ design and production • it can reduce the cost of labour • it can reduce waste by helping to tackle climate change • it can modify in 3D CAD designs • it can help create a rapid prototype • it can help with the provision of customised garments and limiting inventory by focusing on-demand production (Arribas & Alfaro, 2018; Islam, 2020; Lectra, 2018). One may argue that the more we can match the empowered consumers’ expectations, the better would be the implications for businesses. Nowadays consumers are looking for a unique journey across every single touchpoint and channel, perhaps retailers can use this technology to feed into their narrative.
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3
Methodology
3.1
Research Approach and Research Design
This study adopts an interpretivist stance, thus an inductive logic of inquiry. According to Suddaby (2006), the overall assumption of interpretivist ontology is that social actors create their own reality driven by their inner perception although the attempts of imposition from the external world. Likewise, several respondents are investigated to elicit the causal conditions that characterise the researched phenomenon. 20 female customers’ body scans are conducted to establish the perception of the 3D Body Scanning process. Respondents are probed after completing this experience by the use of an openended questionnaire. Then, follow-up interviews are conducted to further investigate the impact of this experience in the medium term. The research design is illustrated in Fig. 3 below.
3.2
Stage 1 and Stage 2
In stage 1 respondents needed to experience the 3D body scanning process. This entailed to unfold their perceptions to contribute to an understanding of the introduction of this technology in a retailing context (Kim & LaBat, 2013), as reiterated in the literature review section, there is limited research to support this (Song & Ashdown, 2013). Therefore, to get real and immediate sensations form female respondents, an open-ended questionnaire is administered straight after the 3D body scanning experience. Then, stage 2 involves in-depth interviews to shed lights on themes resulting from the previous state of the research. The interview was unstructured up to a point to capture new ideas and new themes.
Fig. 3 The research design
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Data Analysis
Subjects have been scanned at the state-of-the-art size stream body scanning at the University of Manchester. They were carefully educated about the body scanning experience following a protocol available in the extant body scanning literature (Appendix 1). Then, an open-ended questionnaire was administered straight after the use of the technology. Respondents were given privacy to avoid any bias and to write their responses manually. Participant responses were allocated to set questions and then included into Microsoft Excel to deduce its score after all the questionnaire results were imputed. Data were examined by qualitative content analysis. As argued by Bryman and Bell (2011), the use of this approach is suitable for quantifying and counting manifest words in a transcript and lead into counting the raw data content (Zhang & Wildemuth, 2009). Female descriptions have been listed and organised in relation to low or high frequency. Subsequently, follow-up interviews aimed to shed light on respondents’ buying process and further investigate their perception of the usage of the 3D body scanning technology.
3.4
Participants
Up to now, the research on women’s experiences in body scanning usage has tended to focus on specific demographics. Table 2 below depicts scholar’ publications on body scanning and demonstrates limited research on female age group 35 to 54. The work of Loker et al. (2004) focused on the acceptance of the 3D body scanning technology for female respondents with the same age group. However, differences in geographical application (USA) and the over than a decade date of publication emphasise the need for additional probing. Women within this age brackets, attaining metabolic and physiological rise and fall (e.g. pregnancy, menopause) affecting body fat distribution, are subject to changes in their body shape’s characteristics. Current research (ONS, 2017) shows growth in the numbers of mothers having children I this period of their life. Spending power is also an important point to consider for this category of consumer (Kang & Park-Poaps, 2010; Parment, 2013), particularly for the ones falling into the AB socioeconomic group (Experian, 2019; Mintel, 2017). Table 2 Body scanning usage publications Sample size 20 women mixed method Quantitative study 203 females participants Ninety-one women quantitative study
Age distribution 18–45 34–55 years 18 and 81 years
Authors Grogan et al. (2013) Loker et al. (2004) Grogan et al. (2016)
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Non-probability sample strategies have been used in this study (Saunders et al., 2019) given the aim of the paper. Following an interpretivist stance, this research used a non-probability sampling strategy, categorised as convenient. As Creswell & Creswell (2018) suggest, non-probability sampling is a method of selecting units from a population using a subjective method rather than a random selection. The sample size was also coherent with previous research (Creswell & Creswell 2018) suggesting a number of interviews in the range of 15 to 25. Respondents’ criteria were the following: female; UK residents; Aged 35 to 5; A, B socioeconomic group; willing to be body scanned; Online/multichannel clothing fashion shoppers. A number of 20 voluntary respondents were recruited. Each respondent was asked to bring other people with the same characteristics (snowball sampling) as pointed out in the methodological literature (Saunders et al., 2019). A pilot study was conducted through few in-depth interviews. A number of 25 voluntary respondents were recruited. Twenty in-depth interviews with clothing fashion consumers were conducted, consistent with previous research in similar studies (Brakus et al., 2009; Romeo & Lee, 2015; Xia & Istook, 2017).
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Findings and Discussion
4.1
Stage 1: The Body Scanning Experience
Participants in this study have been using the 3D body scanning technology located at the University of Manchester. Following this process, the main themes developed by represented women’s experience of the use of the 3D body scanning experience were the following: positive, negative and neutral emotions. The reader can ascertain from Fig. 4 below that the great majority is positive. Main key descriptions were developed from the participants following the scanning experiences. Resulting in positive emotions: interesting, easy, informative and quick (Fig. 4). Table 3 depicts the main positive emotions mentioned by the respondents in describing the 3D body scanning experience. Table 4 depicts the negative and neutral emotions mentioned by the respondents in describing the 3D body scanning experience. To summarise, the main emotions coming from the process were positive emotions (Table 3). Limited negative and neutral emotions were also reported by the participants (Table 4).
4.2
Satisfaction with RTW Fit of Garments
Table 5 below shows the results obtained from the analysis of the level of satisfaction and non-satisfaction of respondents about the ready-to-wear (RTW) garment.
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Fig. 4 Description of body scanning experience: emotions
Table 3 Descriptions of the body scanning experience: positive emotions
Description Interesting Easy Informative Quick Exciting Useful Simple Fun Very interesting Accurate Stress free Positive
Frequency High High High High Medium Medium Medium Medium Low Low Low Low
Table 4 Descriptions of the body scanning experience: negative and neutral emotions Description You don’t know what’s happening + you can’t see anything. This impact just 10% of my experience Shocking Regarding size Modest
Frequency Low Low Low Low
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Table 5 RTW garments and satisfaction/non-satisfaction Satisfied with RTW Generally I am happy
Themes happy
Normally my size fits well on me
Fitting well
Non-Satisfied with RTW not satisfied . . .never fits my body shape sizing is different with retailers . . .so shopping online challenging
Generally I know what size to buy and it is normally between two sizes
Knowing to be in-between sizes
They do not fit well and vary per retailer
Flattering and comfortable
Comfortable
It fits some parts well and not others
I choose styles which suits me and shop in stores which are for my age group (45–54) Fit nice and sliming
Buying in my age group stores Fit nice
They most fit me and they are good value for money
Mostly fit & Good value for money Good fit Mostly fit well
Sometimes they fit and sometimes they do not fit Unflattering and uncomfortable Too small and tight
They would fit and look better Yes, mostly
Too long and too tight Waist is often tight and loose around hips My arms are usually too big to fit
The hinges are too deep sometimes They are too long and in the arms and waist is always too big I’m tall and long arms Too big on hips and too small on shoulders
Themes Never fits my body shape Sizing inconsistency Issue for online buying Size inconsistency
Not fit well Disregarding body proportions Fitting inconsistencies Uncomfortable Tight & Small
Long & Tight Upper lower body issues Body proportion issue inconsistencies
Body proportion issues Body proportion issues
It is apparent from this table that satisfied respondents rely on explicit styles to align with garment fit. Instead, non-satisfaction is attributed to sizing inconsistencies among retailers, measurements above or below real body measurements, issues with non-common
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body typology (e.g. petite, tall) and issues with body shape inconsistencies. These findings were further explored in the following stage of the research. The overall response to this part of the investigation purports a negative perception of the RTW garments mostly attributed to issues with the consistency among retailers and misalignment with real body proportions and body shapes.
4.3
Stage 2: Respondent’s Interviews
The follow-up interview with consumers aimed to further acknowledge their perception of the use of the 3D body scanning device.
4.4
Step 1: Description of the Scanning Experience
4.4.1 3D Body Scanning Experience: The Positives The great majority of respondents reported positive comments about the body scanning experience. A common emerging theme was “getting measurements” which echoes their desire to gather real body measurements. Interestingly, a striking result emerges from the data is that respondents would like to use the technology to improve their shopping experience and to facilitate size choices. In addition, some respondents mentioned to have used the printout of the body scanning technology to hand-make garments by themselves or by third parties (tailor-made garments). As it can be noted from the following quotes:
This research suggests that the 3D body scanning experience is considered time effective with the shopping experience. Some categories that emerged are: “reducing time and effort”, as quoted below:
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Some women said that using this technology would lead to informed decisions when buying clothes. Thus, the following quotes are reported:
Another important aspect mentioned by the participants was the opportunity to socialise and interact when attending these body scanning events:
Perhaps, to attract people to their stores, retailers may use this technology strategically. Another important point mentioned by the women participating in this study was the reference to the way body shape changes when ageing and the way this technology can support women accordingly.
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To conclude, this study argues that customers perceive positively the 3D body scanning experience. Respondents described this experience with the use mostly the following expressions: descriptions getting measurements, reducing time and effort and informing purchase. Drawbacks have also been reported. These are valuable in terms of future development of the device in a retailing context.
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3D Body Scanning Experience: The Negatives
With the negatives linked with the scanning experience, participants stated: “The 3D body image, privacy issues, accuracy and fit. Seeing all the measurements and selfperception”. This study argues that the greater concern with using this technology is the printed image resulting from the process. Participants mentioned “it was dramatic, you don’t see yourself like that!”, “I look dumpier” . I looked bigger that I I think I’m a head. “I got my head drown on that a bit. “Oh my God I look like a Teletubby”. Another emerging important issue was “privacy”. There was an overall concern with who could use their data, as they mentioned:
On the positive side, 3D body scanning measurements may be preferred over the manual way. Because of less contact, it seems to be appreciated, although the measurements’ accuracy has been questioned by some respondents.
The use of this tool to ascertain garment fit has also been probed. This study suggests the importance of other elements, like the style of the garment, rather than measurements, in the evaluation of the fit of clothes.
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Some concerns by respondents seem also to be related to the difference between the real self and the perception of the self. The visual of the measurements as per printout seems to have a negative perception on respondents.
Again, this highlights the importance of the visual of the 3D image, providing an opportunity for improvement of the technology. This thesis shows that the length of the scan influences the outcomes of the scanning experience. Respondents have to stand still in the right posture in order to be scanned.
This suggests that the amount of time spent should be checked regularly. To conclude, the following Table 6 shows the findings from the section. Table 6 sheds light on some negative aspects that may offer opportunities for improvement with the use of this technology. Also, interesting findings relate to participants’ description of key concerns: the accuracy of measurements, fit evaluation, privacy, the visual resulting from the scanning experience, seeing the measurements and the duration of the scanning experience. Finally, a key theme emerging from this stage of the study is the “printout of the body scanning” that will be considered in the next section.
Table 6 The body scanning experience: Positive and negative elements Positive Getting measurements Information purchase Reducing time and effort Having told what to expect Checking the size Physical conditions Relationships/socialising
References 9 4 4 1 1 1 1
Negative 3D body scanning image Privacy Seeing measurements Length of the scan Accuracy Fit
References 3 3 2 1 1 1
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Body Scanning Printout
This study shows a negative perception of the printout resulting from the body scanning experience that may lead to behavioural change as a consequence producing results which corroborate the findings of previous work in this field (Grogan et al., 2017).
6.1
Using the Printout
As already stated, at the end of the scanning session, respondents have been provided with a printout of their measurements. When questioning the use they have done with this handout participants mentioned:
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To summarise, this research points out that participants did not refer to the printout for online fashion transactions. Rather, the printout was used to check personal measurements and fitness regimes. A great number of participants shared the visual with friends. An overall emerging expectation from the 3D body scanning experience was to get “true, and accurate measurements of oneself”. This is something worth considering whether thinking to incorporate this technology into a retailing landscape. In addition, participants exhibited an interest in using the measurements to assist in tailored dresses.
Probes relating to using the printout in a retailing context show respondents’ interest in using this as a point of reference to leverage size inconsistency issues. As the reference to particular garments demonstrated: dresses, jeans, lingerie.
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Summary of the Theme “The Printout from the Body Scanning”
This section of the study has pointed out that one of the main negatives to be considered by practitioners is the image of the 3D model resulting from the 3D body scanning protocol. Respondents used the printout to share this with friends and families for discussion on personal body measurements and body proportions. And then, respondents mentioned that there were too many measurements in the printout giving them some confusion on how to use these for. Perhaps, providing additional
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information would be sensible. Last but not least, this study suggests that women do not seem not to be confident with using those measurements online.
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The 3D Body Scanning Technology in a Retailing Context
The possible use of this device in a retailing environment was also investigated.
This shows the overall enthusiasm from respondents and their interest in incorporating this tool into the retailing landscape. Nevertheless, some concerns have been articulated as sensitive concerns.
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Theoretical Contribution
This paper enriches the extant literature on body scanning. Although there are previous studies that have investigated the use of 3D body scanning technology in various fields (Rzepka, 2011; Shin & Baytar, 2013: Almousa, 2020), few of them have put efforts into exploring the perception of the body scanning experience for female consumers. This study advances the understanding of female fashion shoppers’ attitudes towards the use of this technology.
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Practical Contributions
This study contributes to shedding light on female users’ perceptions of the use of 3D body scanning technology in a retailing context. Retailers can apply these outcomes to their strategies. It has demonstrated that incorporating the technology in a retailing context may lead to more information in terms of consumers’ body measurements. Thus, a more positive brand perception in the long term could lead to increased customer loyalty.
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Conclusion
This study begins with unfolding the consumers’ buying behaviour, and how the use of the 3D body scanning technology is perceived by those participants. This study has explored the perception of the use of 3D body scanning for female consumers. The results highlight that there are issues with satisfaction with the fit and size of RTW garments and women feel issues with the consistency among retailers and misalignment with real body proportions and body shapes. Respondents demonstrated interest in the use of the technology in a retailing environment. Positives and negative aspects have also been highlighted. The main contribution of this paper comes from the exploratory probing of the perception of the 3D body scanning literature, improving the conceptual definition of the 3D body scanning constructs for retailers.
Appendix 1 Scanning Session Protocol (Gill et al., 2014) 1. Explanation of the body scanning process and details of consent Each participant has the opportunity to have the scanning process explained to them and be referred to the systematic procedure detailing the process from start to finish. The systematic guide and a copy of the consent form are provided for the participant to read before scanning. The consent form is retained, though a blank copy is available on the website for scrutiny by participants. A general body scanning information sheet, and a sheet related to specific scan projects, is provided to each participant before scanning. The general information sheet indicates the type of underwear that should be worn during the scan process and the types of scan outputs that will be provided. Scanning is only undertaken by trained personnel, whose names will be recorded on the consent form and all scanning is the responsibility of a member of university staff whose contact details are made available to participants. 2. Participants complete their record in the database An encrypted and password protected database available on a single PC is used to record identifying and contextual data separate from any scanned image. This is then backed up to encrypted and password protected hard disks that are kept at separate secured locations. The database can only be accessed by members of the scanning team with a password and will store personal details of each participant; as well as manual measurements not recorded by the scanner.
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Completion of each participant database record generates a unique code that is used to name the scan file and retain anonymity of the scan participant whilst linking the scan file to the database entry. 3. Print and sign the consent form (participant and scanning personnel) A copy of the consent form is then printed from the database and once read is initialled and signed by the participant and the names of both scanning personnel are recorded. The signed copy of the consent form has details of the manual measurements recorded on it and after completion of the scan is stored in a secure location. A blank copy of the consent form is available for each participant online. 4. Manual measurements taken prior to the scanning process To enable full analysis of the scan data a number of manual measurements are taken: • [D2] Height—the shoes are removed for this measurement • [D3] Head Circumference—taken to help understand garment opening requirements • [D4] Min Max hand—taken to help understand garment opening requirements • [D5] Hand length—taken as a reference for garment opening requirements Measurements are taken manually in accordance with detailed methods that are available for the participants to view before giving consent and during the process. 5. Using a private changing cubicle, change into underwear and record weight Participants are directed to a private changing cubicle adjoining the body scanner and requested to change down to their underwear. Should the scanner be located where this is not possible, then participants are provided with a gown for privacy to wear when travelling between the changing cubicle and scanner. Participants are instructed to step onto the weighing scales in the private changing area and the scanning personnel from a remote screen record weight. Participants are asked if they would like to know their weight and have it recorded on the output. Due to the nature of the scanner, it is explained that underwear must be close fitting as detailed on the information sheet. Appropriate underwear is made available to wear over or in place of the participants own, should they not have close fitting underwear. At no point should the participant be undressed whilst in view of the scanning personnel or other participants.
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6. Enter the scanner booth and adopt the scan posture Before entering the scanning booth, the scan position of the body is explained to the participant and a definition provided for their reference. The participant is then instructed to enter the scanning booth and adopt the required scan posture. Whilst the participant is in the scan booth (and before the scanner is activated), the scanning personnel inputs the unique code from the consent form to name the scan file. This retains the anonymity of the participant but allows the scan to be matched with the details in the participant record during analysis. The participant stands in the scan position and has their scan captured, remaining in the scan booth until the scan is complete and a usable image is collected; approximately one minute. Once the scan has been captured, it is checked on screen, and if a rescan is necessary, it has been communicated to the participant verbally. Once a suitable scan is captured, then the participant returns to the changing area/ cubicle to get dressed. 7. Leave scanner booth and get dressed in the private changing area On completion of the scan, the participant re-enters the changing area (directly connected to the scanning booth) and dresses in their original clothing in full privacy. On leaving the changing area the participant is offered a copy of their scan data printed out showing a front, back and side view and displaying their measurements.
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Simulating the Synergistic Experiences of Customers in Show-Rooming and Web-Rooming Retail Channels Louise F. Reid, Gianpaolo Vignali, Katharine Barker, Sadia Idrees, and Helen Hann
Abstract
This chapter presents a method to capture a real-life customer decision-making process by inducing a synergy of different senses and simulation of showrooming and web-rooming environments (Machavolu and Raju, MITS, International Journal of Business Research 1:1–14, 2014; Mehra et al., Showrooming and the competition between store and online retailers, 2013; Reid et al., International Journal of Business and Globalisation 17:364–383, 2016; Schiffman and Wisenblit, Consumer Behavior. Pearson Education Limited, 2015). These multiple-channel purchasing platforms and their accompanying set-ups have to be studied and understood as they can either promote or deter customer purchasing behaviours. Prior studies that have attempted to explore customer behaviour in decision-making processes of buying a product have not been able to effectively capture real-life settings of show-rooming and web-rooming platforms and their resulting experiences due to controlled experimental conditions of the buying environment (Arora and Sahney, International Journal of Retail and L. F. Reid (✉) University of Gloucestershire, Cheltenham, UK e-mail: [email protected] G. Vignali · S. Idrees Department of Materials, Engineering Building A, University of Manchester, Manchester, UK e-mail: [email protected]; [email protected] K. Barker Alliance Manchester Business School, in the Innovation, Management and Policy Division, University of Manchester, Manchester, UK e-mail: [email protected] H. Hann Department of Materials, School of Natural Sciences at Faculty of Science & Engineering, University of Manchester, Engineering Building A, Manchester, UK e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_18
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Distribution Management 45:762–781, 2017). This study will consider this gap and seek to address reviews of participants in multisensory show-rooming and web-rooming environments in real-life settings. Thus, photographic and video data collection method (Collier, American Anthropologist 59:843–859) and data matrix techniques (Nadin and Cassell, Essential Guide to Qualitative Methods in Organisational Research. SAGE, 2004) to analyse the data were employed in different dimensions of both the virtual and retail environments. A simulated environment of the store—which was a highlighted brand from focused group discussions—and home space were designed for reviewing customer behaviour using smart devices (Rompay et al., Psychology in Marketing 29:919–92, 2012). The store incorporated design layout such as dimensions, visuals, lighting, and wall-layout as well as the employment of space, auditory, olfactory, tactile dimensions to engage participants. Additionally, in the home space, non-responsive set-ups were designed via the elimination of the presence of warm/cool colours, to leave predominantly green spaces to allow for effective engagement with smart devices. These mock set-ups were used to conduct reviews of participants and their engagement within those spaces, to find the most suitable and comfortable multisensory environment and experience, to enhance the likelihood of purchase (Spence et al., Psychology and Marketing 31:472–488, 2014). Findings from this study illustrate the importance of the dimensions of home and retail spaces as well as the impact that multisensory experiences have on purchasing decisions. This is important since it informs not only customer experience but also their purchasing performances in the real retail industry. Keywords
Showroom · Web-rooming · Omni-channel · Consumer behaviour · Simulated environment
1
Introduction
Consumers garment evaluation and purchasing process has evolved due to the availability of multiple-channel retailing environments and retailers’ efforts to create a seamless shopping journey across their channels (Barnes, 2013; Verhoef et al., 2015). These strategic channel developments provoked the evolution of multiple and cross channel purchasing behaviour from consumers that academic authors named ‘show-rooming’ and ‘web-rooming’ (Machavolu & Raju, 2014; Mehra et al., 2013; Reid et al., 2016; Schiffman & Wisenblit, 2015). When consumers browse in physical stores and purchase online, this can be defined as ‘show-rooming’, whereas when consumers browse online and purchase in physical stores, this is defined as ‘web-rooming’ (Machavolu & Raju, 2014; Mehra et al., 2013; Reid et al., 2016; Schiffman & Wisenblit, 2015). These phenomena occur due to the incentives offered by online retail channels (Reid et al., 2016), for instance price comparisons
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(Schiffman & Wisenblit, 2015) and quality evaluations (Gensler et al., 2017) can be prevented by sales staff efficiency in physical stores (Rapp et al., 2015). It is evident that tensions presented within these channels prevail (Reid et al., 2016); however, methodologies employed rely on consumers knowledge of their purchase behaviour, explore individual channel behaviour (Blazquez, 2014), and exclude observation where subconscious actions prevail (Reid et al., 2015). Furthermore, channelswitching behaviour can result in lost sales for retailers if consumers are enticed by competitors while moving across channels (Reid et al., 2016). An understanding of purchase behaviour in ‘show-rooming’ and ‘web-rooming’ contexts requires further exploration. Both physical and atmospheric dimensions require consideration in retail store design and stimulus response contexts (Donovan & Rossiter, 1982; Kaltechava & Weitz, 2006; Kotler, 1974; Turley & Milliman, 2000). Factors such as colour choice (Bellizzi et al., 1983; Lam, 2001), music (Chebat et al., 2001), sales staff (Baker et al., 1992; Sharma & Stafford, 2000), marketing materials (Alpert et al., 2005), and scent (Spence et al., 2014), all influence the consumers mood and subsequent purchase behaviour in retail stores. As technology is playing a pivotal role within consumers channel engagement (online and offline), provision of these dimensions should be included (Kissane, 2017; Stein & Ramaseshan, 2016). In online environments, humans integrate multiple senses which can moderate how an environment is interpreted (Grunwald, 2008). The influence of the external environment on behaviour presents implications for online studies. Given mobile and web pages can be accessed anywhere, the environment that the testing is conducted within may moderate the consumers motivation. Physical environment studies only provide the variables that influence behaviour in offline environments (Spence et al., 2014) and online studies only consider the interaction with the device (Arora & Sahney, 2017; Reid et al., 2016), not the external environment for the experience. Relevant stimuli, within a congruent environment, are therefore essential to comprehend true behavioural dimensions of consumer decision-making for a specific target market and individual retailer. Multiple-channel purchasing platforms and their accompanying set-ups are therefore studied and understood in this chapter as they can either promote or deter customer purchasing behaviours. Prior studies that have attempted to explore customer behaviour in product decision-making have not considered real-life settings whereby show-rooming and web-rooming can occur (Arora & Sahney, 2017). This chapter has contributed in presenting an approach to simulation of true to life settings with an aim to conduct reviews of participants in multisensory show-rooming and web-rooming environments. This will answer the following research questions: How do shoppers respond to online stimuli in a store environment? How do shoppers respond to online stimuli in their home environment? These questions are key for retailers in the design of their strategies to entice consumers to shop (Vignali et al., 2010; Vignali & Vignali, 2009).
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Literature Review
The literature review comprises of the discussion of recent emerging trend of showrooming and web-rooming and the importance of decision-making process of consumers in the omni-channel process model context with store environment dimensions and online environment.
2.1
Show-rooming and Web-rooming
Multiple-channel purchasing, where consumers browse in physical stores and purchase online (‘show-rooming’) or browse online and purchase in physical stores (‘web-rooming’), has emerged as a growing trend (Machavolu & Raju, 2014; Mehra et al., 2013; Reid et al., 2016; Schiffman & Wisenblit, 2015). Schiffman and Wisenblit (2015) indicate show-rooming occurs due to the availability of mobile purchasing platforms where consumers can search for lower prices online after selecting products in stores. Machavolu and Raju’s (2014) study agrees with this process; however, their research focusses on electrical products available through multiple retailers. Gensler et al. (2017) found show-rooming is induced by price and perceived higher quality online. However, Rapp et al. (2015) and Gensler et al. (2017) indicate show-rooming behaviour can be prevented through sales person behaviours and strategies. A range of motivations and prevention tactics therefore prevail. The opposite, ‘web-rooming’ or ‘e-rooming’, where customers browse on retailers’ websites but visit stores to make a purchase. This presents detriment, as the movement between channels creates the opportunity for marketing or other stimuli to attract the customer’s focus to an alternative garment or retailer (Blackwell et al., 2006). Currently, technology acceptance literature (Lian & Yen, 2014; Reid et al., 2020; Vignali et al., 2019; Zhou et al., 2007) explores the factors that prevent or encourage online purchase, however, do not consider the importance of individual product selection criteria or the use of criteria throughout the multiple-channel process. Moreover, show-rooming (Gensler et al., 2017; Rapp et al., 2015) studies focus on generic drivers in purchase and web-rooming studies are not empirically tested (Arora & Sahney, 2017) or explore the holistic web-rooming process (Flavian et al., 2017). Discrepancies within information provision that induce this behaviour and the consumers holistic process of evaluation in a garment context are not considered. Reid et al. (2016) explored consumers’ motivations to engage in show-rooming or web-rooming within apparel purchases. The findings of this research indicate motivations for channel-switching contrasted with other industries explored within literature (Machavolu & Raju, 2014). Garment selection criteria were not significantly related to show-rooming and web-rooming behaviours (Reid et al., 2016). Channel-switching occurred due to consumers inability to complete a full garment evaluation in online channels and inability to search for price discounts or price reductions in physical channels (Reid et al., 2016). The lack of understanding of the customers evaluative process is therefore essential to understand the
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multiple-channel evaluation process. As clothing purchase is a high-involvement decision process (Blazquez, 2014), when determinant criteria in either channel cannot be assessed dissatisfaction can occur (Ajzen & Fishbein, 2000). This results in lost sales for retailers and forms negative attitudes that influence future purchase behaviour (Ajzen & Fishbein, 2000). Reid’s et al. (2016) findings indicate both channels present discrepancies that need to be resolved to improve service provisions for consumers, maintain physical platform performance, and grow the online channel. Furthermore, Reid et al. (2016) identified service dimensions of retailers’ provisions as a core focus to prevent channel-switching that results in lost sales for retailers. Understanding the consumers process of garment evaluation is essential to overcome this discrepancy and progress towards an omni-channel integration.
2.2
Omni-channel Model
Barnes (2013) and Verhoef et al. (2015) define omni-channel retailing as the synergy of all retail channels and customer touchpoints in a way that optimises customer experience and retailer performance. These propositions support Pauwels and Neslin (2015) and Cao and Li’s (2015) indication that efficient integration is related to enhanced retailer performance. The provision of the omni-channel retailing formats aims to address the differences prevalent between physical (Ryding et al., 2015) and online retail platforms (Verhoef et al., 2015). Barnes (2013) suggests consumers spend 15 to 30% more in multiple-channel environments and spend a further 20% in an omni-channel context, which agrees with Pauwels and Neslin (2015) and Cao and Li’s (2015) findings. Omni-channel integration therefore presents a profitable solution for retailers that can be achieved through improved service provision. To address the discrepancies within current channel provisions, it is essential to understand consumers garment evaluation process to allow retailers to progress towards omni-channel models. Despite the benefits of integration, Loureiro and Roschk (2014) found building consumer loyalty was motivated by different variables in online and offline platforms. Greater focus was attributed to information in online contexts and graphic design offline (Loureiro & Roschk, 2014). Different information or cues may therefore be required by consumers in different environments (Loureiro & Roschk, 2014). A clearer understanding of the consumer garment evaluation process is therefore essential and is an existing gap this chapter aims to fill. Loureiro and Roschk (2014) explained variance prevailed due to the higher perceived insecurity on the internet than in physical stores, where sensory dimensions of products can confirm garment suitability (Spears & Yazdanparast, 2014). This is supported by Rodriguez-Torrico’s et al. (2017) need for touch construct, which is used as an information source in physical platforms. Information design is therefore of greater importance in online platforms (Loureiro & Roschk, 2014). Different emotional cues are therefore required within each environment. Davis et al. (2017) indicate females use online platforms for goal-directed activities
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not experiential dimensions prevalent within physical stores. Loureiro and Roschk (2014) additionally found more information is required online as the sensory variables that provoke episodic memory are not always activated by virtual stimuli and a review of further information is required. Criteria within consumers’ garment evaluations applied throughout over ‘56 touchpoints’ (Barnes, 2013, p. 201) therefore vary by stimulus and the type of information provided. Trevinal and Stenger’s extensive literature review illustrates that consumer behaviour literature focusses predominantly upon consumption experience, shopping experience, and online customer experience. Research therefore relates to consumer behaviour in separate channels, which is consistent with apparel research (Blazquez, 2014). Limitations within existing literature exist as channel behaviour is only understood individually and not as an integrated multiple-channel journey. This chapter aims to establish the environmental dimensions required to further understanding consumer purchase behaviour.
2.3
Store Environment Dimensions
Both physical and atmospheric dimensions are key elements in retail store design (Donovan & Rossiter, 1982; Kaltechava & Weitz, 2006; Kotler, 1974; Turley & Milliman, 2000). Studies have traditionally explored the influence of isolated, controllable dimensions on consumer purchase behaviour (Spence et al., 2014; Turley & Milliman, 2000). However, Verhoef et al. (2009) suggest customers experience retail environments holistically through a combination of physical, psychological, and social cues. A multi-dimensional experience therefore exists that should be explored to unfold a true representation of consumer purchase behaviour. Spence’s et al.’s (2014) review of sensory atmospheric theory and Grunwald (2008) present the importance of the integration of these variables and the different sensory dimensions in purchase behaviour. All the dimensions presented within a store simulation should therefore represent the preferences of the target demographic in relation to physical, psychological, and social determinants. Furthermore, Stein and Ramaseshan (2016) introduced the technological dimensions that exist. As technology is playing a pivotal role within consumers channel engagement, provision of these dimensions is also essential (Kissane, 2017). Retail environment studies have identified the implications of colour choice (Bellizzi et al., 1983; Lam, 2001), music level and type (Chebat et al., 2001), influences of sales staff (Baker et al., 1992; Sharma & Stafford, 2000), marketing materials (Alpert et al., 2005), and the integration of colour and scent (Spence et al., 2014) providing guidelines for the design of a retail environment. The findings of these author’s studies should be considered in the development of environments to ensure hedonic needs are met and relevant cues are presented to understand consumers’ garment evaluation process (Spence et al., 2014). These dimensions only present the variables that influence behaviour not a process for simulation. Further research is therefore required to achieve a congruent experimental
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environment as ethical restriction prevents recording in live retail store and literature discovered was published between 1983–2005 (Saunders et al., 2012). Clarification of the presence of these dimensions in a live store environment is therefore an evident gap in literature to address. Verhoef et al. (2009) indicate that merchandise variety is a core consideration in the portrayal of brand image and Mantrala et al. (2009) outline the importance of effective allocation and range architecture for the performance of retail stores. However, they do not illustrate an approach for identifying representative range architectures or stimuli for experimental research. Selection of relevant garment stimuli to create a congruent sensory experience is therefore crucial. These gaps shall be addressed within the methodological approach of this chapter. Product schema congruity (Meyers-levy & Tybout, 1989) influences the consumer’s level of product involvement and determines their style of information processing (Blackwell et al., 2006). A relevant garment therefore elicits a different process of evaluation than one that is irrelevant to consumers’ lifestyles. Furthermore, consumers encode information and conduct evaluations based on semantic assimilations with prior or current experience (Puccinelli et al., 2009). Relevant stimuli, within a congruent environment, are therefore essential to comprehend true behavioural dimensions of consumer decision-making for a specific target market. Rompay et al. (2012) suggest goal-directed consumers prefer a spacious environment and free-form layout (Wu et al., 2014). It is therefore imperative to present a simulated retail environment, range architecture, and relevant stimulus in experimental methods to understand consumers’ process of garment evaluation.
2.4
Online Environments
Grunwald (2008) indicates humans integrate multiple senses which can moderated how an environment is interpreted. The influence of the external environment on behaviour therefore presents implication for online studies as even though devices are mobile and web pages can be accessed anywhere, the environment testing is conducted within may moderate the consumers motivation. Spence explains that within home environments visual appraisal is the core stimulus that influences behaviour. Singh (2006) suggests contrasting beliefs exist in relation to the influence of colour. Some believe responses are stable whereas others indicate they influence behaviour due to cultural, gender, and age-related factors (Singh, 2006). A suitable external (e.g., space to engage with technology) environment is therefore essential to unfold online dimensions of garment evaluation (Vignali and Reid (2014); Vignali et al. (2014)). Mid-spectrum green and white are the only non-responsive colours (Labrecque et al., 2013; Lam, 2001; Wegman & Said, 2011). Adoption of these colour schemes is therefore important as colour saturation (purity) (Labrecque et al., 2013) and colour warmth induce arousal (warm colours) or relaxation (cool colours) (Labrecque et al., 2013; Lam, 2001). Congruence of environment design in relation to sensory cues is key (Labrecque et al., 2013). It is therefore important to ensure the
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environment is relevant to the target consumer, is congruent in design and non-responsive in relation to colour choice.
3
Methodology
To identify the dimensions for virtual and of physical retail environments provided by a UK mid-market retailer to develop a relevant simulation for consumer garment evaluation. The data has been collected in two stages. The methodology adopted of stage 1 and stage 2 data collection has been discussed below.
3.1
Environment Design: Store Review (Stage 1)
The purpose of the store review phase was to discover the dimensions of a live retailer store and develop a simulation. A simulation was developed as Verhoef et al. (2009) found consumers experience retail environments in a holistic perceptual way. This includes the combination of physical, psychological, and social cues (Verhoef et al., 2009). It is therefore essential to establish the key dimensions of the physical store and the experiential features that may influence the consumer. Retailer selection was completed through a purposive sampling technique within a heterogeneous method (Saunders et al., 2012). This approach was chosen to select an unfamiliar but relevant brand to increase the level of risk in selection (Saunders et al., 2012). Risk enhances the depth of the decision process, meaning participants evaluative process is more extensive and increase the coverage of criterion applied (Rajagopalan & Heitmeyer, 2005). A retailer catering to the 18–35 female market was therefore selected as this was one of the least popular retailers to purchase dresses, which was identified during a focus group (Reid, 2017) and provided the most neutral branding to ensure only the garments would provoke a response from participants (Labrecque et al., 2013; Lam, 2001).
3.1.1 Data Collection (Stage 1) To achieve a holistic representation of a store, both structured observation, photo and video elicitation methods following Collier (1957) method of photographic surveying were identified. Spence et al. (2014) indicate the importance of the integration of the five senses within the store environment. Turley and Milliman (2000) presented the physical variables to consider and Stein and Ramaseshan (2016) illustrated the technological elements. A data matrix was developed to guide the identification of key dimensions for the store simulation from academic literature. Labrecque et al. (2013) indicate a congruent environment is essential to allow participants to feel comfortable and Puccinelli et al. (2009) indicate consumers encode information and conduct evaluations based on semantic assimilations. The retailer was therefore approached and only this brand was included within the research. To ensure the dimensions of the photographs taken captured the visual
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dimensions of the store, professional photographer Helen Hann was consulted and agreed to capture the images under the researcher instruction. Photography of all dimensions outlined within the data matrix was conducted, physical measurements of the spaces between fixtures and product heights and filming of the environment to establish a holistic overview. The process was completed while the store was closed. A holistic appraisal of the environment was therefore achieved which was relevant as the mock store would only contain the participant and researcher.
3.2
Environment Design: Home Environment (Stage 2)
The home environment review was developed based on Verhoef et al.’s (2009) indication that environments can influence the consumers decision-making process based on sensory dimensions. This related to store environments however, as 84% of consumers prefer to purchase online on a laptop or desktop computer (Mintel, 2017), a suitable environment was required. A non-responsive space was selected to prevent induction of responses that are evident from store review literature (Spence et al., 2014). Furthermore, Spence’s study of the home for ICI indicated visual dimensions are the most influential. Suitable retailer for appraisal was identified through Mintel (2015a).
3.2.1 Data Collection (Stage 2) The data collection technique draws upon Collier’s (1957) method of photographic review within a purposive (homogenous) sampling strategy (Saunders et al., 2012). To achieve this, relevant retailers for the target demographic were identified relevant to purchasing homeware (Mintel, 2015b). Five high street homeware brands were included within this analysis. These brands’ visual representation of their home environment images was identified and reviewed through their public webpages. This presented seventy-six room designs to review (other brands did not provide layouts). Labrecque et al. (2013) indicated the core determinant of participants responses was colour as this can induce conscious and unconscious reactions to stimuli. Colour dimensions to review were therefore integrated into a data matrix and it was identified a green and white colour scheme was required to present a non-responsive space. Development of the data matrix followed Nadin and Cassell’s (2004) technique, which allowed the data to present within a concise method using an a priori template from existing theory (Nadin & Cassell, 2004). Two dimensions were presented for initial screening of suitable room layouts. This presented dominant colours through their warm or cool dominance (Lam, 2001) and colour hue (Labrecque et al., 2013). The dominant colour based on visual review was identified to determine suitability. Eight suitable rooms for review were presented. The integration of different room dimensions was also imperative as sensory dimensions influence information processing and congruent environments that reflect colour choices are required to prevent responses to the room (Labrecque et al., 2013). For instance, green presents an environmental theme that should be
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complemented with plants or floral images to re-iterate the colour associations (Labrecque et al., 2013; Wegman & Said, 2011). The sensory dimensions used for the store review phase in terms of the five senses (Spence et al., 2014), technological elements (Stein & Ramaseshan, 2016), and room contents (Labrecque et al., 2013). Each photograph was reviewed, and dimensions were recorded using Nadin and Cassell’s (2004) data matrix technique. Where colours that provoked responses existed in rooms, this resulted in rejection and green dominant rooms were selected as they present environmental associations that are non-responsive (Labrecque et al., 2013; Lam, 2001; Wegman & Said, 2011). Two rooms were then selected based on their green dominance and amendments were made. Upon building this space a full health and safety risk assessment was completed and approved.
4
Data Analysis
The data has been analysed in two stages. The data analysis of stage 1 and stage 2 has been discussed below.
4.1
Environment Design: Store Review (Stage 1)
The data was analysed using an adaptation of Nadin and Cassell’s (2004) data matrix technique. A descriptive matrix was adopted and developed through academic theory and the integration of descriptive information under each heading. A visual appraisal of the images following Collier (1957) approach was adopted that involved using photographs to establish key consistencies. This presented core dimensions to replicate the store layout. Mantrala et al. (2009) and Morgan (2011) illustrate the importance of visual display within brand representation. The visual merchandising layout and integration of garment types were therefore recorded separately. Rompay et al. (2012) indicate environment layout influences consumer purchasing behaviour and Wu et al. (2014) indicate free-form layouts are preferred within a goal-directed scenario. The chosen brand was therefore a suitable selection and illustrated the importance of replicating the brand’s visual merchandising technique. Analysis of visual merchandising involved the review of prominent wall spaces (gold areas) and determination of their suitability based on the garment types selected within the focus groups findings. The layout of these was therefore adopted and replicated within the store. The results of this research informed the design of the simulated store environment.
4.2
Store Development
The store simulation was initially built, this involved the physical assembly of the space and the development of the sensory dimensions based on the store review was
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only relevant to the technique described within this chapter. Upon space allocation, the space was cleared, and store equipment sourced and purchased. The next stage involved layout design based on the equipment sourced and assembly through work requested via the University of Manchester Estates Department. The space was then painted in line with the brand’s colour scheme. Two walls were painted white as due to the small space allocated, this was necessary to make it less claustrophobic (Labrecque et al., 2013). A wooden floor was then laid to replicate the feeling of the floor under participants feet and sewing technician Fiona Colton made curtains to segment the area from the body scanner located on the other side of the room. Made-to-measure mannequin plinths and a small cash desk to house the iMacs required for recording were then designed and sourced. Fairgrieve and Mclurg Ltd. provided this equipment in support of this research. Brackets for recording were then placed at each corner of the room. Risk assessments of the space were then conducted and signed off by the Health and Safety Manager. The body scanner area was included that was required for the study.
4.3
Store and Home Space Design/Layout
4.3.1 Store Dimensions The store space was designed to house the shopping experiments. The space available was 338 cm by 250 cm and included a fitting room cubicle of 99 cm by 99 cm. The initial phase of the store review identified the space around fixtures to allow participants sufficient space to engage with garments within the store. It was established a minimum of 80 cm was required between the fixture and walls. The space available within the mock store was therefore insufficient to house floor fixtures or central key locks, therefore appraisal of wall fixtures only was included within the product evaluation. The review was structured using five senses and indicated key decisions made within the simulated store design. Only gold walls are presented in this section as these locations’ present new themes before stock depletion occurs (Morgan, 2011). This approach therefore ensured a holistic range display could be simulated. 4.3.2 Visual Colour was the initial variable reviewed. The brand presented light grey walls with silver steel fixtures, wooden props, and a wooden floor panel on a grey stone floor. A feature brick wall also existed within the centre of the store with standalone silver steel uprights.
4.4
Simulated Store
This colour scheme was replicated within the mock store through a back light grey wall with white side walls. White walls were used to visually open the space due to
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limited square footage. Fixtures selected were silver uprights, straight arms, and long bars.
4.4.1 Lighting and Holistic Store Fixtures These were different from the brand’s style as these could not be sourced but replicated the visual representation of the space. The store lighting was bright white, double layer lighting achieved through inbuilt ceiling spotlighting clusters per 100 cm of the store and six rectangular lower-level lighting on panels throughout the centre of the store. The lighting layout achieved a shadowing effect with garments on the wall and highlighted key garment features. The watt of bulbs and their intensity was not disclosed by the store. 4.4.2 Lighting The store lighting was replicated using spotlights in addition to the floor light. This replicated the shadowing effect on garments to achieve a consistent visual replication. 4.4.3 Researcher Uniform Sales staff were dressed in gold area key themes and wore make up and perfume with styled hair. Staff therefore reflected the core brand’s styling presented in visual graphic displays. During the observation phase interactions with staff were very professional and they reacted within a positive, upbeat, and engaging way. The researcher replicated this by dressing in the core colour of the main wall. A vest and black jeans were selected to prevent any influence on the participants choice of dress and green was selected to reduce the response to the researcher as green is a neutral colour (Spence et al., 2014). This outfit was worn for all interviews to achieve consistency within participant’s responses and experience. 4.4.4 Garments The brand’s decor reflected the brands core urban image. The brands holistic product collections merchandising strategy within a free-form store layout replicated this image. Mannequins were spaced in key looks throughout the store. Gold walls were merchandised using a symmetrical front appraisal layout where every second upright was front appraised and side hanging thereafter. Three walls were presented within the gold area of Wall 1, 10, and 11. Three options were presented to replicate this within the simulated store. Wall 10 and 11 were selected for simulation based on the combination of fabric types within the walls. This was considered as it is a core variable within the dresses template and focus group phase. Wall 10 included two chiffon/georgette, one georgette (dull satin look), two leather/leather look and one single jersey dress. Wall 11 included one plain weave (linen look), one plain weave (cotton look), and one chiffon dress. These combinations provided consistent fabric combinations with garments selected by focus group participants as suitable for the occasion (Reid, 2017).
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4.4.5 Wall Layouts Furthermore, each wall layouts included footwear and jackets that participants indicated they would require wearing with these dress types. The layouts simulated were therefore replicated within the mock store. The key sightlines for wall 10 required to be inverted due to the door positioning of the simulated store’s room. The garments selected reflected an abstract (wall 10) and floral theme (wall 11) where key prints were carried through the store layout with solid colours to balance the wall design. This was replicated within the store. 4.4.6 Key Looks and Mannequins Walls were merchandised using straight arms, step-arms, and side hanging short and long bars. To establish a suitable density of stock within these spaces, the number of units (one dress) and options (style of dress) was calculated within this review. This resulted in 1.28 options per straight arm, 2.125 options on a step arm, 2.83 options long bar, 3 options on a T-bar, 2.14 options on a glass shelf, and 1 wooden shelf. Each option contained an average of 5.29 units. One option was therefore selected for each straight arm and two per long bar within the simulated store. Due to cost restrictions of the project only 3 garments per option could be purchased. Within store layout, key heights were identified and replicated to ensure participants could engage with the space in a way that is familiar to live retailers. To achieve this, the highest product hanging was calculated as 205 cm, highest shelf with product was 190.3 cm, lowest shelf with product was 23 cm, and fitting room rail height was 151.5 cm high and places in the centre of the panel. Wall fixtures used were 41 cm long straight arm, long bars of 120 cm width by 41 cm depth and glass shelves of 120 cm width by 41 cm depth. These fixtures were the only type available for purchase and key heights were used as guidance within the layout of the simulated store. Three heights of mannequin plinths were used to entice the consumer throughout the store and engage at different heights with key mannequin styles. Key sightlines on wall fixtures were achieved through front appraised product and accessories on high shelves to engage with consumer. These were replicated through a key look in the simulated store using purpose-built mannequin plinths. These reflected key themes located close to the mannequins. Replication in the store was achieved by dressing mannequins in garments from the smaller wall to create a key look. 4.4.7 Physical Dimensions Core physical dimensions and furniture included a metal cash desk, steel floor fixtures, wall displays, gondola with jewellery and accessories, a fitting room area, and window displays. The cash desk area was replicated within the mock store using a wooden purpose-built cash desk (due to limited space). Auditory, Olfactory, Tactile, and Taste Dimensions Music was the main source of auditory engagement and drowned out talking within the store. Current music was played on a loop basis in addition to the sound of air-conditioning systems. The music volume was not measured as due to the
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presence of recording devices in the simulated store, this could not be replicated. The music played with the mock store was identified using a mobile application from the live store. Music was played throughout the interviews at a low level and the extractor fan was put on to replicate the sound of air-conditioning. Olfactory dimensions involved the smell of staff perfume, new garments, and air-conditioning within this store. This was replicated within the store space through the presence of new garments and the researcher’s perfume. The tactile store dimensions include predominantly steel fixtures, a metal cash desk, glass and stone table, glass, and wooden shelves. These created an urban and sleek image through cold and pointed edges that reflect the brand and allowed the garments to stand out. A simulation of this was achieved by using metal uprights and hanging straight arms and long bars. Wooden features were included through mannequin plinths and a cash desk, painted grey to simulate the metal variables. Temperature was another variable, however, could not be controlled in the space provided. No food or drink offerings were evident within the store, therefore taste was not a variable within the store environment on this occasion. Technological Dimensions Technological engagement dimensions included tills with ordering functions from other channels and tablets for ordering garments at the fitting room or on the shop floor. This was replicated using an iPad and iPhone recorded through imacs within the purpose-built cash desk. Relevant devices could therefore be engaged with by the participant or researcher throughout the process upon the participant’s cue. Communicative Dimensions Discount promotions were evident throughout the store but were excluded in the evaluation as price may moderate the consumers decision process. The cash desk included gift card and return policy signage and a large graphic behind the cash desk and on specific walls. The graphic was replicated through a mounted image behind the cash desk. Models within the brand’s image wore neutral-coloured garments within a two-tone background. Photography of a female in a pale pink dress on a white brick wall and dark contrasting grey floor replicated this within the simulated store. Motivation Quotations The brand presented motivation quotations within fitting room walls which were replicated within the store through a mounted image. Process Variables The core processes evident within the store was the fitting room area, till point space and mirrors throughout the shop floor and fitting room. The simulated store replicated this through a fitting room cubicle, cash desk area, and hanging garments. All senses and variables were evident within the brand except for taste. A replication of all sensory features could therefore be included within the store simulation to achieve as close to a live environment as possible for the interview
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phase. Virtual environments could be used in a real setting, these were therefore made available to consumers through tablets and phones within the store.
4.5
Environment Design: Home Environment (Stage 2)
A home space was developed to create a non-responsive space for participants to engage with online platforms. A non-responsive space was designed through a secondary analysis to ensure the environment developed only induced engagement with the devices and the evaluation process that occurred during the experiment/ interview. Seventy-six suitable rooms for review were identified based on homeware stores the target customers would shop within. Images of each room were visually appraised using a photo-elicitation method. Each photograph’s suitability was reviewed based on dominant colours, warm or cool, and high or low saturation colour dominance. The sample included twenty-eight warm, nine black, fourteen cool, eight mid-spectrums, one cool/warm and sixteen rooms included only furniture units. Eight suitable mid-spectrum rooms were presented to review. Each room was analysed, and all features were listed. The rooms were reviewed for the presence or warm and cool colours and rejected upon this basis (room 9, 54, 11, 32, 3, 6). Only room 31 and 4 presented a green dominance however, amendments were required to remove warm features. Room 31 was selected as removal of yellow would leave a white colour scheme only and would involve adding green features than may moderate the room’s congruence. To ensure the environment is congruent, the key variables were replicated, and amendments were made to remove yellow and brown features and a mid-spectrum green was identified for inclusion (as high and low saturated colours provoke responses). The core features of the room selected, and amendments made are outlined in Table 1. All dimensions outlined in Table 1 were included except for the bookshelf (due to space). A desk was added to house the iMac required to record the iPad or iPhone devices in the home space and ensure the computer did not look out of place. A mirror was included for the online trying on phase and brackets for recording using iPads attached to the boards. Virtual environments could therefore be used in a real setting. These were therefore made available to consumers within tablet, phone, and laptop devices.
4.6
Discussion and Conclusion
A simulated environment of the store—which was a highlighted brand from focused group discussions—and home space were designed for reviewing customer behaviour using smart devices (Rompay et al., 2012). To establish store simulation by physical assembly and development of sensory dimensions, the chosen store has been reviewed in terms of its store dimensions and visual colours. The review was structured using five senses and indicated key decisions made within the simulated
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Table 1 Room visual items and substitutions Choose room and substitutions Visual Items required Smooth deep green matt paint (60%) and white matt paint (40%), wood decorative, white matt skirting Two single seaters, bright yellow smooth woven chairs
Yellow and white medium, all over print matt and woven cushion (type not visible) Soft and short hair, green, grey, yellow, brown, and light green irregular repeat and size stripe rug (medium) Cream wool (rough) knitted throw (medium) Single tier, two brown wood, smooth and hard oval interlocking tables (small/very small). Inside/on top: two green small glasses and one jug of water (large). Cream lamp shade on silver stand (smooth and hard, large shade). Varnished (smooth and hard) wood floor (light brown), small panels White (wood) with nine shelves (open, cluttered). Inside/on top: Books (various sizes, upright and side-ways), One small wide green box, One small brown square box, Large, Short vase (grey), White bowl. White (smooth and hard) TV Unit, two shelves wide with three sections (inner two shelves within). Inside/on top: Large wide screen TV on TV Stand and CD cases, SKY (of other brand box) and small wide brown box on inner shelves. Medium/large smooth green leafy plant One white solid door (smooth and hard) Auditory Olfactory Texture Taste Technology Communication Process variables
Substitutions Substitute for mid-green feature wall and white walls around Substitute bright yellow for white. May need to substitute for a sofa as chairs are expensive and may not be available in white (others are cream) Substitute for green/white printed cushion to contrast white chairs. Choose a mid-green colour Choose a suitable stripe or if not possible printed green shades rug (exclude brown). Cream/white knitted throw. May need green if looks too white against sofa. Substitute for white tables with green jug and glasses.
Substitute for white/green depending on room balance Light wood floor/white if possible. Replicate white book shelf where possible
Replicate where possible if required substitute for glass TV table and coffee table
Replicate Replicate if required TV Plants Included in visual description Water TV and CDs TV Turn on lamp, water plant, drink water, read books, listen to CDs, use throw
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store design. The simulated store has been established by employing the physical, psychological, and social cues by Verhoef et al. (2009) which supports that consumers experience retail environments in a holistic perceptual way. The lighting of the simulated store has been enhanced by replicating the store lighting with spotlights in addition to the floor light. This replicated the shadowing effect on garments to achieve a consistent visual replication. The garments were arranged in the mock-up store for instance, walls 10 and 11 were selected for simulation based on the combination of fabric types within the walls. This was considered as it is a core variable within prior research (Reid, 2017). Wall 10 included two chiffon/georgette, one georgette (dull satin look), two leather/ leather look, and one single jersey dress. Wall 11 included one plain weave (linen look), one plain weave (cotton look), and one chiffon dress. These combinations provided consistent fabric combinations with garments selected by focus group participants as suitable for the occasion (Reid, 2017). The wall layouts have been enhanced in the simulated store such as the garments selected reflected an abstract (wall 10) and floral theme (wall 11) where key prints were carried through the store layout with solid colours to balance the wall design. The researcher replicated this by dressing in the core colour of the main wall. The vest and black jeans were selected for sales staff to prevent any influence on the participants choice of dress and green was selected to reduce the response to the researcher as green is a neutral colour (Spence et al., 2014). Moreover, for visual representation of clothes on the mannequin three heights of mannequin plinths were used to entice the consumer throughout the store and engage at different heights with key mannequin styles. Key sightlines on wall fixtures were achieved through front appraised product and accessories on high shelves to engage with consumer. These were replicated through a key look in the simulated store using purpose-built mannequin plinths. These reflected key themes located close to the mannequins. Replication in the store was achieved by dressing mannequins in garments from the smaller wall to create a key look. The physical dimensions in the mock set-up of store were enhanced with the auditory, olfactory, tactile, and taste dimensions. Music was the main source of auditory engagement and drowned out talking within the store. The music played with the mock store was identified using a mobile application from the live store. Music was played throughout the interviews at a low level and the extractor fan was put on to replicate the sound of air-conditioning. Olfactory dimensions involved the smell of staff perfume, new garments, and air-conditioning within this store. This was replicated within the store space through the presence of new garments and the researcher’s perfume. The tactile store dimensions include predominantly steel fixtures, a metal cash desk, glass and stone table, glass, and wooden shelves. A simulation of this was achieved by using metal uprights and hanging straight arms and long bars. Wooden features were included through mannequin plinths and a cash desk, painted grey to simulate the metal variables. Temperature was another variable, however, could not be controlled in the space provided. No food or drink offerings were evident within the store, therefore taste was not a variable within the store environment on this occasion.
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Technological dimensions were also considered important and the establishment of mock set-ups which was replicated using an iPad and iPhone recorded through imacs within the purpose-built cash desk. Relevant devices could therefore be engaged with by the participant or researcher throughout the process upon the participant’s cue. The communicative dimensions were enhanced by replicating the graphic through a mounted image behind the cash desk. Models within the brand’s images wore neutral-coloured garments within a two-tone background. Photography of a female in a pale pink dress on a white brick wall and dark contrasting grey floor replicated this within the simulated store. Motivation Quotations presented by the brand within fitting room walls which were replicated within the store through a mounted image. The process variables in the simulated store are replicated through a fitting room cubicle, cash desk area, and hanging garments. All senses and variables were evident within the brand except for taste. A replication of all sensory features could therefore be included within the store simulation to achieve as close to a live environment as possible for the interview phase. Virtual environments could be used in a real setting, these were therefore made available to consumers through tablets and phones within the store. Additionally, in the home space, non-responsive set-ups were designed via the elimination of the presence of warm/cool colours, to leave predominantly green spaces to allow for effective engagement with smart devices (Table 1). These mock set-ups were used to conduct reviews of participants and their engagement within those spaces, to find the most suitable and comfortable multisensory environment and experience, to enhance the likelihood of purchase (Spence et al., 2014). Findings from this study illustrate the significance of the dimensions of home and store spaces as well as the impact that multisensory experiences have on purchasing decisions. This is important since it informs not only customer experience but also their purchasing performances in the real retail industry.
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Understanding the Application of AI-enabled Chatbots in Luxury Fashion Retailing Ni Zeng, Gianpaolo Vignali, and Daniella Ryding
Abstract
In recent years, chatbots, also known as dialogue/conversational systems/agents, have gotten a lot of attention and have been widely used in the fashion industry, facilitating interaction between customers and brands while also changing customer value. Furthermore, fashion brands are using chatbots to deliver personalised customer experiences because of the development of e-commerce. Despite the numerous advancements made in recent decades, chatbot technology is still in its early stages. It appears that there is still a temporal gap between what AI-chatbots might be capable of and their actual implementation. Thus, it is important that both retailers and academies understand the opportunities and challenges of using chatbot technologies. Based on this situation, the aims of this chapter are to provide readers with an initial understanding of the application of chatbot technologies in luxury fashion retail and the opportunities and challenges of chatbot technologies. To achieve the research aims, this chapter introduces the origins and background information about chatbot technology and its application in the fashion industry and critically evaluates the literature on the application of chatbot technology in the fashion industry. In addition, this chapter highlights and identifies the opportunities and challenges of chatbots in the luxury fashion industry. Finally, this chapter proposes eight relevant topics that have been addressed by text-based chatbot research in recent years, with a particular focus on luxury fashion retailing.
N. Zeng (✉) · G. Vignali Department of Materials, University of Manchester, Manchester, UK e-mail: [email protected]; [email protected] D. Ryding Department of Materials, University of Manchester, Manchester, UK e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_19
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Keywords
AI · Chatbots · Fashion industry · Technology innovation · Customer experience · e-commerce
1
Introduction
In recent years, artificial intelligence-enabled technologies have dramatically changed retail environments and will continue to affect retail environment in future (Guha et al., 2021; Shankar, 2018; Vignali et al., 2019). Not only in the in-store environment, but also online shopping (Chrimes et al., 2022; Idrees et al., 2020; Reid et al., 2016; Vignali et al., 2014; Vignali & Reid, 2014). In particular, technological innovation in artificial intelligence provides a novel way of digital marketing and customer service, which is reshaping the customer experience (Hoyer et al., 2020). Customer experience in the retail environment is about the interactions among consumers, products (Ryding et al., 2015), the environment and retailers, which is holistic in nature and involves emotional, cognitive, social, and physical responses to the retail environment (Verhoef et al., 2009). They also mention that the factors under retailer control (e.g., atmospherics, price, etc.) and other factors that cannot be controlled by retailers (e.g., shopping motivations, etc.) could affect the customer experience. For example, chatbots as a factor controlled by the retailers are one of the widely used AI-enabled technologies in retail setting that have acquired the attention of scholars (Pantano & Pizzi, 2020; Rapp et al., 2021; Youn & Jin, 2021). Because of the rapid growth of e-commerce over the last decade, traditional brickand-mortar stores are no longer the only choice for consumers and this is becoming an important strategy for retailers to consider (Vignali et al., 2010; Vignali & Vignali, 2009). However, as there are no salespeople during the online shopping process, it is difficult for consumers to get an immediate response from online retailers. Although some websites provide online human services, it is hard to offer 24/7 online human services. Chatbots as conversational agents could provide 24/7 personalised customer service, which appeals to the millennial consumer (Ryding et al., 2022). Based on the research of the official websites of luxury brands (Dior, Gucci, Burberry and Louis Vuitton), it could be found that the luxury industry is also following the trend by using digital systems that provide 24/7 client assistance via chatbots. According to our research, the application of chatbots varies from country to country. For example, the chatbot is no longer available at Burberry in the UK, but customers in China could use a chatbot called “Deer Assistant”, which has an animated avatar via WeChat. Luxury fashion retailers are increasingly realising that it is important to communicate with customers in the online environment and use chatbots as a marketing strategy. It is necessary to research chatbot services in luxury fashion retail (Chung et al., 2020). Thus, this chapter focuses specifically on the luxury fashion retail context. Customer service frequently employs chatbots for selecting relevant information, facilitating imagination, providing personalised product recommendations, and
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offering better customer service (Hoyer et al., 2020). The chatbot could provide more personalised services in the retail environment, due to its better understanding of consumer behaviour and preferences (Pantano & Pizzi, 2020). When a customer interacts with a chatbot, it generates different types of responses (Hoyer et al., 2020). These reactions and experiences might influence customer satisfaction, loyalty, word of mouth, favourable purchase intentions, continued use intention of chatbot services, and customer engagement (Cheng & Jiang, 2020; Chung et al., 2020; Yen & Chiang, 2021). Because artificial intelligence is becoming more and more important, it is important to understand the strengths and weaknesses of digital assistants (Huang & Rust, 2017). Past studies have focused on the acceptance of chatbots (Rese et al., 2020), the role of technology-enabled chatbots (Tran et al., 2021), and the impact of chatbots (Pantano & Pizzi, 2020), while a comprehensive overview of research into customer–chatbot interaction in a retail setting is still lacking (Adamopoulou & Moussiades, 2020; Rapp et al., 2021). Nevertheless, there is still a gap between the potential functions of chatbots and the actual implementation of chatbots (Pantano & Pizzi, 2020). Furthermore, it is crucial to understand why customers accept or reject the use of chatbots. In this chapter, the literature review part introduces the concept of chatbots and discusses the current state of research on the impact of text-based chatbots on customer experience. Moreover, this chapter presents the actual implementation of chatbots in retail setting, precisely focusing on the luxury fashion industry. This chapter summarises eight research themes (technology acceptance of customers, customer experience, emotional responses, perceived value, customer satisfaction, purchase intention, anthropomorphic and communication issues) on the influence of chatbots on customer experience by combining the literature review with actual applications of chatbots. Finally, this chapter outlines the opportunities and challenges of chatbots in the luxury fashion industry. Several pivotal contributions have been made in this chapter. First, this chapter introduces the definition of chatbot and provides a critical review of the related literature. Second, this chapter discusses the application of chatbots in the fashion industry and how the chatbots are transforming customer experience. Furthermore, based on this discussion, the opportunities and challenges will be presented. Moreover, this chapter proposes 8 relevant topics that have been addressed by text-based chatbot research in retail, including technology acceptance of customers, customer experience, emotional responses, perceived value, customer satisfaction, purchase intention, anthropomorphic and communication issues. Finally, this chapter points out future research directions and research questions. However, regarding language processing, there are two different types of conversational chatbots: one is text-based chatbots and the other is voice-based chatbots (Rese et al., 2020). The most popular chatbots are text-based chatbots in the fashion industry, so this chapter will focus on them.
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Theoretical Positioning
2.1
AI-Chatbot Origins, Definition, Evolution, and Research Gaps
In academia, the notion of artificial intelligence (AI) has been defined ambiguously. According to Bock et al. (2020), the common issue with current definitions of AI is that they assume human intelligence controls artificial intelligence. Actually, AI might excess the capabilities of human intelligence, because AI is not the same as the human brain, which could predict trend patterns, trends, and purposes through big data and deep learning. However, the definition of Kaplan and Haenlein (2019) distinguishes AI from AI-enabled technologies and outlines the domain of AI. They describe AI as “the ability of a system to interpret external data correctly, to learn from such data, and use those learning s to achieve specific goals and tasks through flexible adaptation (Kaplan & Haenlein, 2019: 17)”. Furthermore, considering the common issues have been mentioned before and with a specific focus on the definition of AI in service, Bock et al. (2020: 813) define service AI as “the configuration of technology to provide value in the internal and external service environments through flexible adaptation enabled by sensing, learning, decisionmaking and actions”. Notably, one of the newest AI trends is the usage of programmer that engages with customers in a dialogue format, simulating human speech, which are known as “Chatbots” (Yen & Chiang, 2021). The development of textbased conversation systems began in the 1960s. In 1966, Joseph Weizenbaum introduced a program called Eliza, which simulated the behaviour of Rogerian therapist. For the first time, humans and computers were able to interact in natural language via text. In addition, Weizenbaum (1966) found that humans were happy to use Eliza. Chatbots are one type of AI-enabled technology, which is a kind of virtual assistant software that simulates human conversations by communicating with users via voice or text (Hoyer et al., 2020). Chatbots are also described as “any software application that engages in a dialogue with a human using natural language” (Dale, 2016: 813). Regarding the forms of chatbots, they could be divided into three types: chatbots with animated pictures, chatbots with interactive 3D avatars, and anthropomorphic chatbots (Youn & Jin, 2021). Regarding the categories of chatbots, there are seven categories of chatbots, including knowledge domain, service provided, goals, response generation method, human-aid, permissions, and communication channel (Adamopoulou & Moussiades, 2020). Chatbots are also known as virtual assistants and conversational assistants (Rapp et al., 2021). Furthermore, three previous research directions in the field of AI-enabled chatbots are summarised by Pantano and Pizzi (2020). First, the role of technology-enabled chatbots. Second, the features of virtual assistants (Chatbots) and their influence on customer interaction. Third, the impact of the anthropomorphism of virtual assistants (Chatbots) on consumer behaviour. Moreover, recent research indicates that more studies are still needed to examine the influencing factor of acceptance of chatbots (Rese et al., 2020). Table 1 highlights the current research related to AI-enabled chatbots.
Key words AI; consumption value theory; purchase intensions
Online customer assistance; Artificial intelligence (AI); chatbot; Online retailing
Artificial intelligence (AI); service Artificial intelligence; chatbots; chatbot performance; human– computer interaction; performance goals; customer experience
Authors Sohn et al. (2020)
Pantano and Pizzi (2020).
Bock et al. (2020) Przegalinska et al. (2019)
Literature review Experimental research survey
Literature review Patent analysis
Method Experimental research; quantitative research
Table 1 Research on chatbots and AI/AI-enabled chatbots
(continued)
Finding 1. Functional, social, and epistemic consumption values positively affect willingness to pay in the GAN-generated products. Relative to non-GAN-generated products, willingness to pay is significantly higher for GAN-generated products. 2. Moreover, evaluations of functional value, emotional value, and willingness to pay are highest when GAN technology is used, but not disclosed. 1. Their findings show the increasing technology push towards the adoption of new conversational agents based on natural language. 2. Their findings also emphasise the extent to which the research and development efforts are attempting to improve artificial intelligence systems that characterise chatbots. 3. They point out that technology advancements are mainly focusing on: Firstly, improving chatbot ability to automatically draw inferences on users starting from multiple data sources. Secondly, using knowledge of consumers adaptively to provide more customised solutions. 4. Their results show the tight relationship between analytical skills of the digital assistants and their ability to automatically interact with the users. 1. This paper presents an integrated definition of service AI. 2. They identify some key research opportunities related to service AI. 1. They propose novel methods of tracking human–chatbot interactions and measuring chatbot performance that take into consideration ethical concerns, particularly trust. 2. They propose methodology that links neuroscientific methods, text mining, and machine learning. 3. They argue that trust is the focal point of successful human–chatbot interaction and assess how trust as a relevant category is being redefined with the advent of deep learning supported chatbots. 4. They propose a novel method of analysing the content of messages produced in human–chatbot interactions. 5. Their results contribute to build better social bots for interaction in business or commercial environments.
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Key words AI-chatbot user experience; Parasocial interaction; customer relationship management; brand personality; feeling economy
Conversational agents; chatbots; machine learning; business industry
Authors Youn and Jin (2021).
Bavaresco et al. (2020)
Table 1 (continued)
Literature review
Method Experiment research
Finding 1. They find that chatbots can form virtual assistantship versus virtual friendship with customers. 2. They find that chatbots can represent a brand in customer relationship management (CRM). 3. They find that brand personality perception and parasocial interaction (PSI) affect CRM. 4.They find that virtual friend chatbots induce stronger PSI than virtual assistant chatbots. 5. Technopians and luddites respond differently to AI-manifested brand personality. 1. This article presents a systematic literature review that encompasses these areas looking through the use of machine learning to improve the field of business. 2. This article emphasises business perspectives such as domains, goals, and challenges, and computational methods for self-learning, personalisation, and response generation of conversational agents.
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This AI-chatbot technology is already being used in many industries and has been shown to have a positive influence on a wide range of sectors, such as healthcare (ter Stal et al., 2020), banking (Trivedi, 2019), insurance (Nuruzzaman & Hussain, 2020), and education (Hiremath et al., 2018). The retail industry is no exception either but there are some specifics. In contrast, Rese et al. (2020) point out that customers are quite hesitant to use chatbots at various stages of the customer journey in online retail. To successfully introduce new technology into retail settings, it is vital to understand the opportunities and challenges.
2.1.1 The Application of AI-Chatbot in Luxury Fashion Retail Luxury brands could attract consumers at an emotional level, provide hedonic value, and multisensorial appeal, due to higher materials, experiences, and symbolic value they offer (Pantano et al., 2018). Consequently, luxury fashion retailers believe that the use of technology is against the value of luxury, so they have historically resisted the application of technology (Pantano et al., 2022). Recently, due to market and competitor pressures, luxury fashion retailers have also begun to embrace technological advancements to enhance the customer experience and use it as a marketing strategy. Burberry, Louis Vuitton and Gucci are now generally known as bestpractice examples of luxury brands whose technological advancements have had a significant influence on the customer experience (Chung et al., 2020; Lee & Choi, 2017). Luxury fashion retailers are increasingly incorporating chatbots into customer service for providing better customer experience (Li & Shin, 2022), because it allows luxury fashion retailers to reach their customers 24/7 through platforms like Facebook Messenger, official app and website, WhatsApp, and WeChat (Yen & Chiang, 2021). This chapter section will discuss some cases of luxury brands that have embraced technological innovations and practically focused on AI-enabled chatbot technology. According to the luxury brands that have deployed chatbots listed in the present literature, including Burberry, Louis Vuitton, and Gucci (Chung et al., 2020), online research has been conducted via official websites, Facebook, WeChat, and the Mini program platform. The aim of this study is to investigate the usage of chatbots by luxury brands over the years. In addition to the luxury brands mentioned in the literature, authors have investigated the chatbot usage of Dior, Chanel, and Hermès in both the UK and China. Our research shows that Chanel and Hermès have not applied chatbots on these four platforms, but they have human customer service that is not available 24/7. According to Chung et al. (2020), Gucci launched a chatbot with Chinese language services and good knowledge of collection information. However, this service is not available in China now. Furthermore, Dior launched an AI-chatbot assistant called “Dior Insider” through Facebook in 2017, which could provide personalised recommendations about skincare and makeup. This service has now been replaced by a human customer service that is not available 24/7. It is worth mentioning that customers can still communicate with the virtual assistant via the official Facebook messenger of Dior, but it only provides product information and the virtual try-on
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function. Besides, there are no other chatbot services on other platforms either. However, Burberry and Louis Vuitton are still using chatbots. In the following paragraphs, more detail information on the application of chatbots in Burberry and Louis Vuitton will be introduced. Burberry In the 2016 London fashion week, Burberry launched a chatbot on Facebook Messenger. The Burberry chatbot is an automatic communication tool that can understand human language and respond to customer questions by providing option buttons. Customers could find more information about the collection by clicking the “Browse the collection” button and the nearest store location via Chatbot. Customers could easily switch to live chat with a Burberry consultant. And the “Shop now” button is directly linked to the Burberry website. Furthermore, the Burberry chatbot could offer recommendations based on customer preferences. The application of Chatbots provides a more personalised interaction and shopping experience for customers (Chung et al., 2020). Unfortunately, the Burberry chatbot is not available on Facebook Messenger. On the contrary, in China, the Burberry chatbots even have animated avatars. It could provide some automated responses via WeChat and the official website. For example, customers could personalise products via chatbot, ask for a size guide, and track their order. In addition, they mentioned that more functions are developing. Louis Vuitton In the UK, the Louis Vuitton virtual assistant is available on the official website and Facebook messenger. It can provide customers with detailed information about the product and sales services. In addition, the LV virtual assistant could make suggestions about product repair and offer after-sales services for customers. In China, customers could only interact with the virtual assistant on the Louis Vuitton official website and the functions are the same as in the UK. It is worth mentioning that although there are no chatbot services on WeChat, the mini programme of LV can use algorithms to extract personalised features based on the customer’s profile for providing personalised recommendations and product displays. To sum up, it seems that the use of chatbots is declining, but it varies from country to country. In fact, chatbot advancements offer a new form of interaction between customers and retailers, which enhances the shopping experience and delivers better personalised customer service in the online environment (Pizzi et al., 2021). Additionally, chatbots provide a channel that allows retailers to interact with their customers anytime and anywhere through different platforms (Yen & Chiang, 2021). Thus, the application of chatbots is necessary, but further research is needed to find out how they affect things and how to make them work better and make the customer experience better. In the following section, the current literature related to the impact of chatbots on customer experience will be discussed.
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The Effect of Chatbots on Customer Experience and Consumer Behaviours
3.1
Chatbots Is Reshaping Retail Environment and Enhancing Customer Experience
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The unique nature of luxury brands suggests that the marketing strategy of this industry will be different from other sectors. They are not just selling quality products, performance, and authenticity, but also the experience (Atwal & Williams, 2009). Customer experience is a classical concept in the marketing area that both academia and industry have always been interested in this concept. Especially in the luxury industry, customer experience plays an important role in luxury retail (Atwal & Williams, 2009). Customer experience refers to the multidimensional responses of customers towards the service of firms (Schmitt, 1999; Siebert et al., 2020). Recently, technology innovation is reshaping luxury consumption habits and customer experience (Chung et al., 2020; Ko et al., 2016; Shankar, 2018). Although luxury brands consider the application of technology to be contrary to the values of luxury brands, they are forced by market pressure and the COVID-19 pandemic to use technologies to provide a better customer experience (Pantano et al., 2022). Chatbots are one of the technological advancements dramatically changing the customer experience (Hoyer et al., 2020), luxury fashion retailers also adopt chatbots for offering 24/7 customer service (Chung et al., 2020). Thus, this section will discuss the existing research between chatbots and customer experience. In retail, customers could ask chatbots shopping-related questions and get answers in natural language without having to wait for a salesperson or use other automated formats of communication (Rese et al., 2020). The most significant advantage of retail chatbots is not mobility, but rather personalisation. Because chatbots can store massive quantities of customer data and learn from prior encounters, the chatbot may adjust its replies and recommendations to create a personalised customer experience (Forbes, 2017). However, chatbots have the capacity to handle a large number of consumer demands at once, but they may affect consumers’ perceived control of the interaction, which might lead to dissatisfaction with the online recommendations (Pizzi et al., 2021). While the use of chatbots has declined in recent years, research focused on the impact of chatbots on customers experience in different industries is increasing (Table 2). It could be conducted from the table above, customer satisfaction and purchase intention are frequently investigated as the outcomes. However, only the research of Chung et al. (2020) particularly focuses on luxury retail. Thus, further research on luxury retail is needed. Furthermore, these studies also have significant theoretical and empirical contributions to developing the chatbot performance. For instance, the more agents show human-like characteristics and behaviours, the more customers would like to interact with the digital assistants (Pantano & Pizzi, 2020). Furthermore, the impact of anthropomorphism on product evaluation has been debated in academia. Velasco et al. (2021) research demonstrate that anthropomorphic chatbots
Utilitarian factors: Authenticity of conversation and perceived usefulness; hedonic factor: Perceived enjoyment
User gratifications theory TAM
Rese et al. (2020)
User satisfaction; utilitarian (information); hedonic (entertainment; technology (media appeal); social (social presence)
Interaction; entertainment; trendiness; customisation; problemsolving; communication quality
User gratifications theory
Cheng and Jiang (2020)
Customer experience dimension Trust; credibility; competence; anthropomorphism; social presence; informativeness
Chung et al. (2020)
Theory/Model Human–computer interaction
Authors Yen and Chiang (2021)
Finding 1. The results show that credibility, competence, anthropomorphism, social presence, and informativeness have an impact on consumer’s trust in chatbots, in turn, have an influence on purchase intention. 2. The findings demonstrate that the dorsolateral prefrontal cortex and the superior temporal gyrus are significantly related to building a trust relationship inferring by chatbots to influence subsequent behaviour. Predicted users’ 1. Their results indicate that utilitarian (information), hedonic satisfaction; continued (entertainment), technology (media appeal), and social (social presence) use intention of chatbot gratifications obtained from chatbot use positively predicted users’ services; customer satisfaction with chatbot services of their selected brand. loyalty 2. Perceived privacy risk associated with chatbot use reduced user satisfaction. 3. Their results demonstrate that user satisfaction positively affected both the continued use intention of chatbot services and customer loyalty. Satisfaction 1. Customer satisfaction with luxury retail brand e-service agents requires perceptions of quality communication. 2. Their study results can be a guideline for fashion brands to ensure appropriate marketing efforts through e-services. 3. Digital service assistance tools can help build positive customer relationships even though e-service agents do not fully communicate with customers. 1.Both utilitarian factors such as “authenticity of conversation” and The acceptance of “perceived usefulness,” as well as hedonic factors such as “perceived chatbot; privacy enjoyment”, positively influence the acceptance of “Emma”. concerns 2. Privacy concerns and the immaturity of the technology had a negative effect on usage intention and frequency.
Consequence Purchase intension
Table 2 The research related to chatbots and customer experience
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Efficiency-flexibility ambidexterity; patronage behaviour
Perceived costs of non-personalised; privacy concerns; AI-chatbots’ customeroriented behaviours
Fan et al. (2022)
SOR model, rational choice theory
Satisfaction; intention to use
Intimacy; trust; interactional enjoyment
The continued use of chatbots; purchase intension
Lee and Uncertainty Choi (2017). reduction theory, computers-aresocial-actors (CASA) paradigm
Experiential innovativeness
Consumer responses
Social presence, retailer innovativeness, self-determination
Velasco et al. (2021)
Jiang et al. (2022)
1. Their results show that the social presence of chatbots exerts a direct and positive impact on retailer experience innovativeness and intimacy. 2. Their results show that retailer experiential innovativeness, intimacy, and sense of empowerment mediate the influence of the social presence of chatbots on consumers’ behavioural intentions. 3. Their results show that the cute communication styles in the low-level social presence are very conducive for promoting the relationships between social presence and experiential innovativeness. 1. This research employed a meta-analysis. 2. Their results show that when the salience of uncertainty is high (e.g., when consumers purchase experience products, when consumers come from countries with high uncertainty avoidance), anthropomorphic appeals are more influential than non-anthropomorphic appeals. 1. Their results show that perceived trust and interactional enjoyment are significant mediators in the relationship between communication variables and user satisfaction. 2. Their results show that reciprocity is a stronger variable than selfdisclosure in predicting relationship building between an agent and a user. 3. Their results show that user satisfaction is an influential factor of intention to use. 1. Their research shows a complex relationship between chatbots’ customer-oriented behaviours and their efficiency–flexibility ambidexterity. 2. Their results show that the negative imbalance effect is stronger as customers’ perceptions of non-personalisation costs decrease and privacy concerns increase, while opportunity cost has no significant influence on the negative imbalance effect. 3. Their results also reveal that efficiency–flexibility ambidexterity partially mediates the relationship between chatbots’ (im)balanced customer-oriented behaviours and customer patronage.
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are more influential than non-anthropomorphic chatbots on product evaluation by using meta-analysis method. However, an empirical research result illustrates that anthropomorphic chatbots lead to lower psychological reactance and ultimately lower customer satisfaction (Pizzi et al., 2021). The reason for this difference may be related to the uncanny effect. It is a hypothesis that humanoid technologies that seem almost, but not exactly, like actual humans will have a negative effect on emotional responses (Mori, 1970). Customer satisfaction and purchase intention are commonly mentioned in current literature. Thus, studies that take customer satisfaction and purchase intention into account as results will be discussed in the following sections.
3.2
Customer Satisfaction
Chatbots are transforming the way luxury brands manage their interactions with customers, and as a result, the consumer experience is being reshaped (Chung et al., 2020). Luxury fashion retailers are investing in chatbots to improve the customer experience. Customer satisfaction as one of the key results of technology-enhanced customer experience has been highlighted in the literature, which needs to be further investigated (Hoyer et al., 2020). Customer satisfaction is a pivotal element of successful business and should not be ignored. Consider the topic of this chapter, it is necessary to further discuss the studies related to the effect of chatbots on customer satisfaction. The research by Hoyer et al. (2020) proposes that retailers are constantly updating algorithms to provide increasingly personalised recommendations on what products to choose, which could help customers make better choices. As a consequence, these recommendations could improve customer satisfaction. Furthermore, an empirical study by Pizzi et al. (2021) demonstrates that “non-anthropomorphic chatbots increase reactance, which enhances choice difficulty, leading to more choice certainty that improves perceived performance, which ultimately positively affects satisfaction”. Additionally, the relationship between consumer choice satisfaction and digital-assistant appearance is significantly mediated by reactance, choice difficulty, choice certainty, and perceived performance in the choice task, which is moderated by the initiation of assistants. On the contrary, chatbots might have an influence on consumers’ perceived control of the interaction, which might lead to dissatisfaction with the online recommendation (André et al., 2018). It could be concluded that if chatbots fail to provide satisfactory recommendations, it will cause negative responses in customers and may subsequently negatively affect customer satisfaction. Besides, the usability of chatbots (Chen et al., 2021), seeking online customer support (McLean & Wilson, 2016), emotion, hedonic value, utilitarian value, and trust have all been demonstrated to have an impact on customer satisfaction.
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Purchase Intention
The other noteworthy topic is purchase intention. Sands et al. (2020) demonstrated that the service script and service interaction of chatbots can enhance purchase intention. They designed experimental research in which a total of 262 US consumers were randomly allocated to 2 (service script: education, entertainment) x 2 scenarios (service interaction: human, chatbot). Their results show that the chatbot interactions have a positive effect on emotions and rapport and ultimately enhance purchase intention. Furthermore, they recommend that the chatbot engage with customers in an entertaining script rather than an educational one. Similarly, Jiang et al. (2022) examine the relationship between the social characteristics of chatbots and purchase intention. First, the social presence of chatbots has a positive influence on experiential innovativeness and intimacy, and then experiential innovativeness, intimacy, and sense of empowerment mediate the influence of the social presence of anthropomorphic chatbots on purchase intentions. Moreover, this study examines how communication styles of chatbots moderate the influence of social presence on purchase behaviour. The research sample critical is Chinese consumers, so this research also provides a different demographic perception. Conversely, the research from Luo et al. (2019) finds that a disclosed chatbot will reduce the purchase rate, but this negative effect could be mitigated by a late disclosure timing strategy and customer prior AI experience. However, their field experiment was conducted by an internet-based financial services company in Asia. The financial industry is different from other industries in that consumers will be more cautious about financial products and services. The reason for the drop-in purchase rates might be that employing a chatbot can feel like a scam call. Further research could be done in different industries. It is worth to mention that Rapp et al. (2021) reviewed 83 articles from different industries that examine the interaction of customers and text-based chatbots, and they categorised five recurring themes, including technology acceptance of users, user experience, conversational issues, emotional experience and expression, and humanness. Their findings highlight that emotion and humanness play an important role in the customer–chatbot interaction. Based on this study and specific focus on the luxury fashion industry, the authors propose eight high frequency topics relevant to the luxury fashion industry, including technology acceptance of customers, customer experience, emotional responses, perceived value, customer satisfaction, purchase intention, anthropomorphic and communication issues.
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Findings and Discussion
This section presents a discussion of the findings based on the literature review. The findings outline the opportunity and challenge of the application of chatbots in luxury fashion retail, also identify future research directions. The contributions of this chapter focus on opportunities, challenges, and future research directions towards chatbots in luxury fashion retail.
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Opportunities of the Application of Chatbot
Chatbot technology could lead to a number of benefits for consumers throughout their shopping journey, including collecting better information, providing recommendations, and enabling better customer service (Hoyer et al., 2020). Chatbots are beneficial in a variety of other industries, including education, business and e-commerce, health, and entertainment. Based on the current literature, the following opportunities have been discussed: Improved Customer Service Retailers are effectively using chatbots to support customers through their shopping journey (Pizzi et al., 2021). Chatbots are an example of AI-enabled technology that can analyse and understand data, learn from data, and use that learning to achieve specified objectives and activities (Hoyer et al., 2020). For example, chatbots could sell and process orders directly to customers without the need for human interaction. They could also expertly work with customers to help them achieve their buying goals (Pantano & Pizzi, 2020). The application of chatbots allows luxury fashion retailers to reach their customers anywhere and anytime and respond quickly (Pantano & Pizzi, 2020), which could make luxury customers feel like they are receiving personalised service 24 hours a day, 7 days a week. Therefore, the employment of chatbots may save the time of customers (Chung et al., 2020) and bring convenience for their customers. Furthermore, luxury customers expect exclusive experiences in both online and offline contexts (Chung et al., 2020). Chatbots could provide personalised recommendations based on the purchase performance of customers, previous purchase information, and historical conversations in the online environment (Hoyer et al., 2020), which could meet the expectations of luxury customers. In addition, when customers shop in luxury online stores, chatbots can be a helpful tool to increase convenience (Li & Shin, 2022). It is possible to conclude that chatbot features such as recommendation systems, problem-solving, quick responses, saving time and providing useful information could enhance customer service and provide customers with a better holistic experience in luxury fashion retail. Increased Customer Engagement In recent years, the concept of customer engagement has become increasingly important in both academia and industry (Agrawal & Mittal, 2022; Colombi et al., 2018; Grewal et al., 2017). Customer engagement is a multidimensional construct, including cognitive, emotional, and behavioural dimensions (Bowden, 2009). Customers will become more engaged with brands when there is an emotional connection between brands and their customers, which will ultimately result in a variety of consumer behaviours (Pansari & Kumar, 2017). Guha et al. (2021) propose that chatbots could interact with customers and improve their engagement with brands. For instance, chatbots provide customers with more engaging answers, respond to their problems more quickly, and provide customers with more comfortable and efficient support while interactive with them (Brandtzaeg & Følstad, 2017).
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Compared to static content search in frequently asked questions (FAQs) lists, chatbots are more approachable and attractive to luxury customers. Monitoring Customer Data and Gaining Insights According to Li and Shin (2022), luxury customers would anticipate more personalised brand experiences. The system of chatbots could monitor customer historical and present data. The data uncertainty may be reduced by historical knowledge since new information is generated when old data is combined. This technique contributes to the enrichment of chatbot knowledge bases and also provides new insights for customer decision-making processes (Bavaresco et al., 2020). Thus, the application of chatbots could provide luxury customers with a more personalised experience. Cost Saving Chatbots make it possible to communicate with customers online to assist them during the online buying experience at a lower cost than human customer service (Pizzi et al., 2021). Due to their ability to lower the operation costs of customer service, chatbots are increasingly used in businesses (Adamopoulou & Moussiades, 2020). It is worth noting that chatbots should be used to assist human sales rather than to replace them, especially in the luxury fashion industry where the presence of human customer service is still important.
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Challenge of the Application of Chatbot
Technology is a two-edged sword that presents both opportunities and challenges. Bavaresco et al. (2020) believe that the future challenges of chatbots have two main types in the business domain: 1. the performance of chatbots. 2. the emotional, cognitive, behavioural responses towards chatbots. Privacy Concerns The security of data is a major concern for both retailers and customers. The expanding use of digital technology by both online and brick-and-mortar stores has significantly enhanced privacy concerns among customers (Pizzi & Scarpi, 2020). As could be seen in Table 2, privacy concern as an influencing factor is also frequently mentioned in research related to chatbots. According to Taylor et al. (2015), privacy concerns are a psychological condition of anxiety stemming from the negative effects of losing privacy. Current research demonstrates that privacy concerns have a negative effect on the acceptance of chatbots, use intensions of chatbots and consumer behaviour (Cheng & Jiang, 2020; Rese et al., 2020). It may also result in complaints and negative reviews.
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Failure to Serve Although chatbot technology has advanced significantly, there are still certain drawbacks. One of the most significant and frequently occurring issues is that chatbots failure to understand the customer intentions or provide appropriate responses. Lack of a chatbot strategy may be the cause of customer dissatisfaction, which may result in failure to guide the customers effectively and difficulty achieving communication goals (Adamopoulou & Moussiades, 2020). As a result, an unpleasant customer–chatbot interaction may turn away customers. According to Lee and Choi (2017), their results show that user satisfaction is an influential factor in intention to use. In similarity, Cheng and Jiang (2020) demonstrate that user satisfaction affects both the continued use intention of chatbot services and customer loyalty. Thus, failure to service is main issue, which needs to solve immediately.
4.3
Future Research Directions
Because chatbots are a novel marketing tool that is still in its early phases for both academics and industries, further study is needed to properly grasp how to leverage them successfully. In this chapter, eight main themes (technology acceptance of customers, customer experience, emotional responses, perceived value, customer satisfaction, purchase intention, anthropomorphic and communication issues) on the role and influence of chatbots on luxury retail have been proposed. Some of research topics have been investigated in relevant literature, but most of the topics have not been extended to luxury retail context. Hence, future research could focus on these eight themes. Moreover, this section presents several more specific research directions and questions. 1. Because the majority of empirical research on text-based chatbots has been conducted in the laboratory (Rapp et al., 2021), future studies should employ a qualitative or quantitative approach based on the real-world customer experience context rather than experimental research. Furthermore, further research, including true customer–chatbot interaction, might increase the generalisability of results. Specifically, future studies may use qualitative methods to acquire deep insights into the interaction between customers and chatbots. 2. Future research could explicitly measure the communication quality of chatbots in luxury fashion retail by comparing participant responses when they knew and did not know their interaction partner was a chatbot. Additionally, miscommunication is one factor in an unsatisfying chatbot conversation. Future research might investigate the influence of other independent variables, such as the lack of a tangible interface or trust in automated communication systems (Sheehan et al., 2020). 3. Future research could focus on the chatbots service recovery. 4. Based on our investigation, the use of chatbots in the luxury fashion industry is declining. Thus, future research could focus on why it is declining and how to
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improve the performance of chatbots. Furthermore, it would be interesting to investigate the dark side of chatbots in the luxury fashion industry. 5. Few of research on chatbots based on the luxury fashion industry. Thus, future research might pay attention to the 8 main research themes (technology acceptance of customers, customer experience, emotional responses, perceived value, customer satisfaction, purchase intention, anthropomorphic and communication issues) that we have proposed. For instance, few studies have directly examined the influence of luxury chatbot–customer interface design on customer brand experiences (Li & Shin, 2022). Besides, future research should particularly focus on the social presence or social characteristics of chatbots. Finally, demographic studies such as cultural and gender-related research are needed (Landim et al., 2021). 6. Future perspectives for AI-enabled chatbots in the luxury fashion industry and their integration with other Industry 4.0 technologies.
5
Limitation
Several limitations should be considered when interpreting the research findings presented in this chapter. Firstly, the generalisation of the results is limited, because only 26 articles related to the influence of chatbots (the rest of the literature is not focused on chatbot technology or the use of chatbots in the retail sector) have been reviewed and the examples only focus on the luxury fashion industry. Secondly, the aim of this chapter was to identify the opportunities and challenges, focusing on the application and influence of chatbots on the luxury fashion industry. However, this study ignored industry reports and only looked at articles from major conferences and journals. In fact, the industry report is also informative and more relevant to the current state of the industry. Thirdly, our example did not examine other important luxury goods segments such as watches, jewellery, and beauty and department stores. Chatbots in these sectors might be different from those in fashion and accessories and different from the official websites of brands and the websites of department stores. Fourthly, this chapter merely discusses the current challenges, but it does not address solutions.
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The Opportunities & Challenges of the Metaverse for Fashion Brands Courtney Chrimes and Rosy Boardman
Abstract
Immersive technologies such as augmented and virtual reality, gaming platforms, blockchain, and non-fungible tokens (NFTs) enable brands to converge virtual and physical realities leading to the much-anticipated arrival of the metaverse. Tipped to be the next phase of the current internet, the metaverse is envisioned to be a more immersive alternative reality that brands and consumers can enter. While mass adoption of a fully-realised metaverse has yet to come, the adoption of immersive technologies is starting to materialise in fashion brands’ marketing strategies. Fashion brands must learn how to leverage these new technologies in order to keep up with changing consumer behaviour and stay ahead of their competitors. This conceptual chapter discusses the opportunities and challenges faced by fashion brands as they start to enter the metaverse. Opportunities that brands can grasp include the creation of new brand-consumer immersive experiences, community building, new revenue streams, new forms of influencer marketing, and the traceability of products. Challenges that brands face encompass data privacy, diversity and inclusion, technological reliability, and adoption issues. Keywords
Metaverse · Immersive Technologies · Fashion · Augmented Reality · Marketing
C. Chrimes · R. Boardman (✉) Department of Materials, University of Manchester, Manchester, UK e-mail: [email protected]; [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_20
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Introduction
With increasingly advanced digital technologies, coupled with the shortening of technology life cycles and changes in customer demand, companies need to constantly reimagine their business models in order to remain competitive in a rapidly changing environment (Kraus et al., 2022). With consumers spending more time online than ever before, brands must rethink how they promote and market products in the digital realm, as well as offer more immersive and unique experiences for consumers. The pandemic has accelerated a collective desire to reimagine ways in which people can engage with each other, resulting in brands investing in technologies and digital spaces, also termed ‘the metaverse’, to court sociallydistanced audiences and embolden shared brand experiences (WGSN, 2021a). Originally coined in 1992 by science fiction writer Neal Stephenson in his novel ‘Snow Crash’, the metaverse refers to a shared reality embedded in technology and web interactions (Stephens, 2021) and has been gaining increasing traction since 2020 (Kim, 2021). Mainstream curiosity concerning the metaverse peaked when Facebook rebranded to ‘Meta’ in October 2021 (Forbes, 2022b). However, the term ‘metaverse’ remains ambiguous for both academics and marketers, suggesting further investigation into this phenomenon is required. It is predicted that the metaverse will entirely transform all forms of interaction between consumers and brands. Indeed, whereas the internet today enables brands to push and pull 2D information in an asynchronous way, the metaverse provides a persistent, shared virtual world that users can access through various devices, platforms, and media touchpoints resulting in synchronous interactions between consumers and brands alike (Stephens, 2021). Hence, the metaverse is often discussed in relation to Web 3.0, a decentralised internet that places the onus on community and user control (Van Rijmenam, 2022). It is important to note that the metaverse is still in its infancy and the window of opportunity to build immersive virtual worlds, stores, and societies is beginning to unfold. With the metaverse being perceived to be the biggest industrial revolution the world has ever seen, there is great demand for brands to create and define their own space in the metaverse. However, further research is needed to provide an understanding of the potential uses and capabilities of the metaverse, especially as these new technologies start to mature (Kraus et al., 2022). What remains unknown is how fashion brands can navigate this space effectively, which is what this chapter aims to explore. To date, there is a lack of discussion about the opportunities and challenges of the metaverse in the academic literature (Zhao et al., 2022). This chapter intends to contribute to the literature by reviewing both academic and market research on immersive technologies and the metaverse in relation to the fashion industry, thereby enhancing academics’ understanding of this phenomenon and laying the foundations for future research in this area. Section 2 will begin by operationalising the metaverse with consideration of how fashion brands are beginning to enter this new digital space through the application of various technologies. Section 3 will provide details of the methodology we used to critically review both academic and market studies in relation to the metaverse in
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order to inform the findings detailed in Sects. 4 and 5, relating to both the opportunities and challenges of the metaverse for fashion brands. Section 6 synthesises the key findings into a model, providing a future research agenda for academics interested in researching the metaverse. Finally, Sect. 7 provides a brief summary of the main contributions, implications, and limitations of this chapter.
2
The Metaverse
The aim of this section is to synthesise the definition of the metaverse and provide insights into what ways brands are currently experimenting with the metaverse. The term ‘metaverse’ derives from the prefix ‘meta’ meaning ‘beyond’, alluding to the proposition that it is a space which builds upon and extends our current reality. The metaverse is conceptualised as an interconnected, 3D virtual world that overlaps with or provides an alternative to physical reality and is inhabited by avatars of real people (Kim, 2021; Bain, 2022a). It is important to note that the metaverse is not merely another medium, rather it is a convergence of all technological advances, including Web 1.0 (the internet in its basic form), Web 2.0 (social media and smart mobile), and mixed realities (AR, VR) (Kim, 2021), which enables multisensory interactions with digital objects, people, and virtual spaces (Mystakidis, 2022). Hence, the metaverse is a growing manifestation of Web 3.0. While Web 3.0 is not an entirely new concept (Tim Berners-Lee coined the term to describe a smarter, more open Internet), the materialisation of Web 3.0 is becoming an integral part of brands’ marketing strategies, resulting in a transformation of power dynamics between consumers and brands. Hence, as Web 3.0 gives consumers full control over their experiences and data (WGSN, 2022c), brands must reconsider their marketing strategies and encourage further consumer co-creation. Although still in its infancy with limited research investigating its feasibility, the metaverse is poised to become the fabric that ties society and culture together through third-platform places and services. Hence, it signifies the ultimate merging of digital and physical reality (WGSN, 2020). Yet, to date, there is no clear consensus on the official definition of the metaverse (Dwivedi et al., 2022). In 2007, The Metaverse Roadmap was published, predicting that in ten years the internet would be an immersive, always-on experience of physical and digital worlds based on the emerging technologies at the time: augmented reality, lifelogging, virtual worlds, and mirror worlds (Terdiman 2007; Kim, 2021). In 2020, WGSN first introduced the term metaverse in their Research Radar report, highlighting that the metaverse has unique characteristics in that it is persistent, has a fully functioning economy, and offers a space where content and digital assets are seamlessly carried across platforms as well as phygital (physical and digital) realms (WGSN, 2020), a proposition later supported by Dwivedi et al. (2022). Kim (2021, p. 142) proposed a working definition of the metaverse as, ‘[. . .] an interoperated persistent network of shared virtual environments where people can interact synchronously through their avatars with other agents and objects’. Although this definition will evolve with time, it is clear that a fully-realised metaverse will provide more fluid and unified
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virtual experiences, whereby users can access a multitude of sites and platforms (e.g., social media, e-commerce sites, apps, etc.) simultaneously without having to ‘hop’ between offline and offline channels interchangeably (Kraus et al., 2022). Consequently, as the metaverse promises a seamless shopping experience, marketers must consider how they can advance their omnichannel strategies to offer holistic and consistent brand experiences at various touchpoints across the customer purchasing journey. Presently, brands are beginning to establish a presence in the metaverse in two ways. The first is by investing in specific digital tools and technologies, such as AR, VR, NFTs, and gamification to create brand-owned experiences. An example of this approach can be evidenced by Burberry’s development of a brand-owned gaming app, ‘B-Bounce’, which enables users to dress a character in one of three iconic Burberry monogram jackets and receive points in the form of TB logos as players advance through the game. Players also have a chance to obtain a physical Burberry jacket for free (High Snobiety, 2021). However, this approach has resulted in a series of metaverse destinations offering various activities including socialising, shopping, working, and gaming operating in silos (Forbes, 2022a, b). Hence, to make the spread of digital spaces feel less fragmented, brands are starting to partner with platforms such as Discord, Roblox, and Twitch to connect users to metaverse destinations and each other (WGSN, 2020). This approach significantly reduces risks attached to entering the metaverse, as brands can collaborate with established gaming platforms by either becoming sponsors within sporting events or by offering a direct-to-avatar model, enabling users to buy virtual clothing for their avatars directly from the brand. Interestingly, this approach is starting to materialise in luxury brands’ marketing strategies (Oh & Nah, 2021), which will be explored in detail within the chapter. To summarise, the metaverse remains a grey area for consumers and brands alike and so brands must carefully deliberate how they can anchor the metaverse into their branding strategies and which entry to market will incur the least risk.
2.1
Non-Fungible Tokens (NFTs)
According to Dwivedi et al. (2022), crypto-assets, such as non-fungible tokens (NFTs), are prevalent building blocks of the metaverse economy. NFTs are digital assets that cannot be replicated and so they are authentic and traceable in the blockchain and can be exchanged digitally for realised economic and non-economic goals (Chandra, 2022; The Interline, 2021). NFTs possess the following distinctive characteristics: 1. Uniqueness: non-fungible means one-of-a-kind and so an NFT is the original version of a digital asset. Only one of its kind exists in the blockchain. 2. Authenticity: the data of each NFT is stored on the blockchain, which cannot be changed, nor replicated once the NFT has been minted (Wang et al., 2021). NFTs act as evidence of ownership (Drapers, 2022a).
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3. Collectability: NFTs closely align with the gaming world in that consumers can collect one-of-a-kind digital assets with cryptocurrency. NFTs are becoming nearer to mainstream consciousness. Google trends documented that in 2022 the number of global searches for ‘NFTs’ soared by 9900% (Drapers, 2022a, b, c), accordingly it is unsurprising that a growing number of brands are jumping to adopt. NFTs enable fashion brands to extend their product offerings to the virtual world (Dwivedi et al., 2022). Luxury brands in particular are moving faster than ever into this realm (Joy et al., 2022). For example, Burberry partnered with Mythical Games’ multiplayer online Blankos Block Party to create a limited edition NFT game character, Sharky B, to be purchased in-game (High Snobiety, 2021). Burberry’s rationale for this NFT creation was to bridge the gap between gaming and fashion, enabling players to immerse themselves more in the brand and its products. Additionally, in 2021, Dolce & Gabbana unveiled a ninepiece NFT collection produced in collaboration with UNXD in which five items of the collection were physical and four items were made bespoke specifically for the metaverse (Vogue, 2021a). The collection sold for $5.7 million (Vogue, 2021a, b, c), emphasising the potential this market has for business growth. Interestingly, it is not only luxury brands that are experimenting with NFTs. BoohooMan launched its first digital NFT collection in December 2021, comprising eight 3D clothing NFTs that consumers could win by entering a competition (Drapers, 2021b). Adidas has also released a collection of digital and physical items sold as NFTs produced with collaborators such as Bored Ape Yatch Club (Dezeen, 2021). It is noticeable from the above case studies that NFTs are boosting brand affection and nurturing loyalty through an interactive and hyper-personalised experience. NFTs are valuable in the context of fashion due to their scarcity. Indeed, commodity theory suggests that when consumers perceive resources to be scarce, the desirability to obtain the resource is heightened with the hope that it will differentiate them from other consumers (Sharma & Alter, 2012). Consequently, as promoting scarcity is often a key motivation behind marketing, it is unsurprising that increasingly brands are creating NFTs to generate a sense of FOMO (fear of missing out). At the time of writing this chapter, the future and value of NFTs are vague. Some have predicted that in the years ahead luxury brands will not be able to prosper if they remain to trade in real-life spaces alone, suggesting phygital trade will be a necessity. Moreover, NFTs have also been advocated to be a potential solution to sustainability issues within the fashion industry, as they reduce physical production. However, it is important to acknowledge that the amount of data NFTs generate does not come without its own set of challenges (Benson, 2021). Indeed, the carbon emissions produced from storing, generating, and wasting data on the blockchain have not been given enough attention within a sustainability context (Patsavellas & Salonitis, 2019). Hence, as the carbon footprint consequences of the blockchain and NFTs have not been holistically investigated (Briem et al., 2019), brands must remain cautious. Despite the aforementioned, it is evident that marketers and brands are beginning to view NFTs as a new frontier for driving consumer engagement (WGSN, 2022b), as they promise scarcity and uniqueness making them a valuable
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marketing tactic for brands. NFTs will be further discussed later in this chapter in relation to community building.
2.2
Gamification
Gamification is a marketing strategy that applies ‘game-like thinking’ to non-gaming industries and has the potential to change how brands communicate with consumers (Chen et al., 2022). It allows consumers to digitally engage with brands through games, competitions, and virtual experiences (Drapers, 2019). As such, gamification can help foster engagement between the brand, the consumer, and the product (Boardman & Chrimes, 2022). While gamification has been discussed at length within interactive marketing literature, its industry application is only just starting to gain gravitas (Hofacker et al., 2016; Nobre & Ferreira, 2017). As of 2022, 2.96 billion people are playing video games globally (Lebow, 2021) and the value of the video game market is predicted to surpass 200 billion US dollars by 2023 (Statista, 2021). Consequently, marketers are beginning to recognise the marketing potential of gamification and are starting to collaborate with gaming platforms, such as Roblox and Fortnite with the hope of increasing revenue from in-game purchases and advertising. The hype around gamification within the fashion industry is unsurprising given the psychology behind gaming. Video games are incredibly consuming, and this level of engagement is usually sustained over a period of time (Insley & Nunan, 2014). Players are often motivated to return to the game to advance to the next level, acquire more points, or receive awards (Hofacker et al., 2016). Indeed, it is this intense desire to return to the game which has led marketers to realise the potential that infusing gaming elements into their communication strategies can have in garnering customer engagement and loyalty (Hofacker et al., 2016), which is the ultimate goal of marketing. Hence, by incorporating gaming elements, brands can reach and engage new audiences as well as offer an experience that encourages the consumer to repeat their visit. The metaverse has grown out of gaming (Joy et al., 2022). Indeed, global recognition of the metaverse started with Roblox (Zhao et al., 2022), a gaming platform that allows users to create, conceive, and share user-generated worlds (The Guardian, 2019). In 2021, Gucci unveiled a virtual piazza in Roblox called ‘Gucci Garden’ whereby visitors could explore a virtual counterpart of the Archetypes exhibition in Florence for a limited time (2 weeks). The virtual exhibition included a concept store featuring the latest Gucci products that users could buy for their Roblox avatars (Lockwood, 2022). Additionally, luxury brand Balenciaga showcased its fall 2021 collection in the form of an online video game, Afterworld: The Age of Tomorrow, allowing players to virtually navigate through the collection (Forbes, 2021b). Scholarly research corroborates the beneficial implications of using gamification as part of a brand’s communication strategy, with Zhao et al. (2022) unveiling that virtual games offer high realism while promoting sharing and sociality. Accordingly, brands must recognise the value of gamification and rethink how
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they can engross their audiences by providing more stimulating experiences. In sum, if deployed appropriately, gamification is a visionary branding tool that can facilitate consumer interaction and participation in brand co-creation experiences (Nobre & Ferreira, 2017).
2.3
Digital Clothing
In preparation for the metaverse, fashion brands are imagining how consumers will exhibit themselves in the virtual space, leading to the creation of digital collections. Digital collections are clothes made of pixels worn in digital photographs only (Choufan, 2022). They consist of items that are purely digital and are superimposed on people using Augmented Reality (AR) to create images of them wearing outfits. Digital clothing gained mainstream attention when a virtual dress created by Dapper Labs and designed by The Fabricant sold for $9500 (Lieber, 2019), resulting in the materialisation of a new virtual fashion market. Brands are beginning to capitalise on this market opportunity by giving consumers the chance to wear branded clothes in virtual spaces. Several brands are already experimenting with digital collections. In 2018, Carlings, a Scandinavian fashion brand introduced a 19-piece virtual capsule collection. Consumers who purchased digital garments were required to submit a photo of themselves and the virtual product was digitally tailored to their bodies. More recently, H&M collaborated with Dress-X, a digital clothing platform, to launch its first-ever virtual clothing collection (WGSN, 2022a, b, c, d, e, f, g, h). H&M’s rationale behind this new market venture was to promote body inclusivity, as AR technology can superimpose any garment onto any body type, removing societal body standards from the brand’s promotional material. As consumers spend more time online, the way they present themselves will become the main priority, resulting in a higher demand for virtual clothing collections and so brands must respond accordingly by monitoring consumer sentiment towards digital collections. With the metaverse being dubbed as the most social network of all (Drapers, 2022a, b, c), consumers will want their digital selves to look the part. Amid growing concerns around sustainability in the fashion industry, digital clothing collections are also perceived to offer a viable solution for reducing textile waste in the fashion industry, as no physical garment is created (WGSN, 2022a, b, c, d, e, f, g, h). As consumer demand for fast fashion is now so difficult to predict, fashion buyers often overbuy items based on overly optimistic sales forecasts, with many clothes ending up in landfill as a result (Boardman et al., 2020a). Furthermore, Dazed reported that the production of a digital garment produces 97% less CO2 and saves 3300 litres of water per garment on average (Benson, 2021). This is particularly important, especially for influencers who receive masses of free clothing items from brands to promote on their social channels. Hence, AR can be a useful tool for digitally dressing influencers without producing and disposing of a physical garment (Joy et al., 2022). That said, questions still exist
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concerning whether this new virtual marketplace is a fad or if marketers should invest in order to future-proof brands.
2.3.1 Virtual Avatar Skins In gaming worlds players are able to buy ‘skins’ (e.g., outfits) for their digital avatars (Lieber, 2019). Social media giant Meta is launching an online store to sell fashion for its virtual avatars, with luxury brands such as Balenciaga, Prada, and Thom Browne being some of the first brands to join (Bain, 2022b). Avatars can wear designer outfits across Instagram, Facebook, and Messenger (Bain, 2022b) enabling users to showcase their identity and fashion style online. This highlights a brand-new revenue stream for fashion brands: the selling of virtual fashion products for avatars (also known as avatar skins) as well as digital fashion items for people on social media. Indeed, in June 2021, a digital Gucci Dionysus bag sold for 350,000 Roblox, the virtual currency of Roblox, equating to £3020. The exclusive bag was sold as part of the ‘Gucci Garden Experience’ held in the Roblox gaming metaverse to attract the attention of the Gen-Z demographic (Forbes, 2021a, b). It is apparent that brands are beginning to capitalise on these virtual opportunities, providing consumers with branded experiences that transcend the physical realm. A further example of a fashion brand entering this space is Ralph Lauren who recently launched a 50-piece virtual clothing collection available to purchase in the social networking app Zepeto, allowing users to build customised avatars and interact in digital spaces (Deeley, 2021). Hence, with virtual skins being set to be a large driver of revenue for fashion brands (Bain, 2022a), fashion brands should consider this strategic approach carefully, especially in relation to brand identity and target audience.
2.4
Augmented Reality (AR)
Augmented Reality (AR) permits real and computer-generated information to be amalgamated into the user’s view of the physical world, so that they appear to be one environment (Olsson et al., 2013; Boardman et al., 2020b). Fashion brands are experimenting with AR by overlaying digital products onto consumers’ bodies or in real-life surroundings in real-time via a mobile device or computer monitor (Plotkina & Saurel, 2019; Lee & Xu, 2020). This approach allows consumers to virtually try items on and is predicted to become customary in the next few years. For example, in 2020, UGG teamed up with Croud and Snapchat to create an AR filter which allowed consumers to ‘try on’ the ‘Fluff Yeah’ style to help consumers see what it looked like when they were at home during lockdown (Drapers, 2021a, b). The AR ‘try-on’ Snapchat filter was very successful for UGG as it helped to drive brand engagement, reach new consumers, and drive sales (Drapers, 2021a, b). Additionally, Kim (2021) found AR features add enjoyment to the shopping experience, which in turn increases purchase intentions, further highlighting its ability to convert browsers into consumers.
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Alongside digital try-on, AR can also be used by brands for immersive storytelling and to foster co-created experiences for consumers (Silvestri, 2022). For instance, in an attempt to connect better with Gen-Z for the release of its Kangol 1990s inspired campaign, H&M launched an Instagram-driven campaign featuring British singer Mable (Vogue, 2020a, b). The brand introduced six AR filters on the social platform permitting users to create and share their own videos with followers. Not only did this enable consumers to bring the brand to life in their personal environment, but it also fostered relations between consumers making them feel part of a community. Consequently, the campaign generated over 4000 views on H&M’s feed highlighting the potential of AR in driving brand awareness.
2.5
Virtual Reality (VR) & Digital Catwalk Shows
Virtual Reality (VR) provides a 3D immersive illusion, which is computer generated and is accessible via specialist headsets (Boardman et al., 2020b), such as Oculus Rift, Samsung Gear, and more recently Google Cardboard. VR enables consumers to be transported to a different universe and so it is highly probable that people will gain access to the metaverse via VR headsets. One of the most successful implementations of VR was by Balenciaga who presented its dystopian A/W2021 collection as a virtual reality runway show through Oculus glasses, which were individually sent to 330 guests worldwide (Vogue, 2020a, b). The experience was celebrated for its ability to make users feel as though they were physically present at the catwalk show. Hence, VR offers an exciting potential for fashion brands to have greater reach and engagement in comparison with physical ones (Drapers, 2022a, b, c). In March 2022, the first ‘Metaverse Fashion Week’ took place, with designer brands, such as Rebecca Minkoff dressing virtual influencers with their latest digital collections (Drapers, 2022a, b, c). This highlights the potential of a new way of engaging with consumers and getting them excited about products.
2.6
Haptic Technologies
The next iteration of VR features haptic technologies. Haptic technologies are already gaining traction in the gaming industry with Sony announcing the PlayStation VR2, which comes with a VR headset paired with VR2 Sense controllers that act as adaptive triggers (WGSN, 2022c). With the addition of haptic technologies, fashion brands will be able to experiment with sensory marketing enabling consumers to smell and feel products in such a way that it almost replicates a physical in-store experience. While this may seem ambitious, France is already designing a Skinetic vest for the metaverse, aiming to make VR experiences feel more realistic. Therefore, brands who are already experimenting with VR should consider how haptic technologies can bring palpable experiences to areas of the body when used in conjunction with a headset.
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However, brands must be cautious when experimenting with AR and VR. There have been numerous failed forays into ‘the next big thing’ when it comes to technology over the last 30 years. For example, AR-enabled smart mirrors were forecasted to become the future of retail through the creation of a virtual fitting room, yet this was short-lived due to the technological improvements in smartphone apps which offer the user the same AR experience as smart mirrors (Sivaram et al., 2021). Moreover, VR has also been found to cause motion sickness as well as producing unrealistic, cartoon-like renditions. For example, the first ‘Metaverse Fashion Week’ was attended by many of the industry’s top brands, such as Dolce & Gabbana, Tommy Hilfiger, Puma, and Forever 21, yet the experience was scrutinised as being ‘frustratingly glitchy and lag-heavy’ (Drapers, 2022a, b, c). Thus, the success of the metaverse depends heavily on users being provided with a realistic and rich experience (Zhao et al., 2022) and so brands must invest in advanced technology to prioritise the user experience.
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Methodology
A narrative literature review was conducted to synthesise current opportunities and challenges facing fashion brands intending to enter the metaverse. Narrative reviews are appropriate to employ if the topic under investigation has been explored by various groups of researchers from diverse disciplines (Wong et al., 2013). Indeed, research concerning facets of the metaverse (i.e. AR, AI VR, NFTs) is plentiful and often examined in isolation as opposed to considering all variables holistically, which this chapter aims to achieve. Moreover, this chapter does not seek generalisations (Paré et al., 2015) but offers a comprehensive discussion of the implications surrounding a burgeoning marketing area, the metaverse. Hence, a narrative review approach was deemed suitable.
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Findings: Potential Opportunities of the Metaverse for Fashion Brands
4.1
Community Building
The unique nature of the metaverse environment is set to change brand–consumer interactions and could transform how consumers process, perceive, and respond to advertising (Kim, 2021). The metaverse is largely an untapped area for fashion brands, presenting a new opportunity to build authentic social spaces for like-minded communities, away from mainstream public feeds (e.g., Instagram, Facebook). With the metaverse, the internet is moving from mass media to a mass of niches, enabling brands to tap into these niches and create meaningful and personalised experiences. The primary reason why social media became habitual is that social platforms are first and foremost about community—the collective participation of members who together create value (Tuten & Solomon, 2017), which led marketers to increase
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social media brand communities to connect consumers (Dwivedi et al., 2021). Brands already successful on social platforms possess great experience in cultivating a community and can bring that community on board with them into new endeavours (e.g., metaverse). Interestingly, the fashion industry is currently witnessing the rise of smaller more authentic brand communities on emerging platforms, such as Twitch, Discord, and Reddit, all of which foster a stronger brand community in comparison with mainstream social platforms. For example, Discord is a voice and chat platform where users join conversation servers, sometimes through exclusive invites, and talk to other members about niche topics (Vogue, 2021a, b, c). While Discord is predominantly a gaming platform, 78% of its users visit the platform for non-gaming purposes (WGSN, 2021a, b, c), highlighting the potential for brands to garner stronger social ties through relational marketing on this platform. As the metaverse advances, questions are mounting concerning how these niche brand communities can be created in an open, decentralised space. NFTs can be used to provide social access to brand communities, creating an exclusive club that only owners of the NFTs have access to (Bain, 2022a). This is how The Hundreds, Adidas, and Gucci are using NFTs, as a form of a membership programme, as they can act as unique identifiers for their owners (Bain, 2022a). Therefore, brands can use NFTs to provide privileges and perks, such as freebies and exclusive access to new products (Bain, 2022a), thereby rewarding their loyal consumers. Fashion brands must understand that value is no longer derived through a one-way brand proposition, instead, it is garnered through collaborative co-creation between brands and all stakeholders, including brand communities and consumers (Merz et al., 2009). Consequently, brands must nurture authentic communities in the metaverse by providing a gated community where members can come together, socialise, and share their love for the brand. Indeed, Laroche et al. (2012) found that brand communities established on social media platforms fostered brand trust, which, in turn, positively affected brand loyalty. However, further research should test this model to examine whether brand communities in the metaverse can produce similar positive outcomes and generate brand loyalty.
4.2
Virtual Influencers: New Form of Influencer Marketing
Influencer marketing has been an extremely popular marketing strategy for fashion brands over the last decade, but the metaverse presents the next stage in its evolution, with the use of virtual influencers. Indeed, Dwivedi et al. (2022) posit that as the metaverse advances, consumers will increasingly interact with non-human brand representatives, also known as AI ‘branded influencers’ who will provide a more tailored and personalised virtual brand experience. Virtual influencers consist of characters generated by tech design agencies or brand themselves to build their own profile on social media or promote fashion brands (Drapers, 2022a, b, c). There is a difference between virtual influencers and avatars, despite both being digital creations. An avatar is a digital asset representing a computer-generated character
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that can either look like a human or not (Drapers, 2022a, b, c). A virtual influencer is a digital character used for influencer activities and purposes, such as live-streaming (Drapers, 2022a, b, c). Virtual influencers are created to look like real people, and this industry is now booming all over the world. Indeed, influencers such as Shudu, Lil Miquela and Candy are being used by fashion brands to communicate with consumers in a more immersive way. For example, Lil Miquela, developed in 2016 by tech design agency Brud, is described as a ‘19-year-old robot living in LA’ on her Instagram account, which has 3 million followers (Drapers, 2022a, b, c). Fashion brands Prada and Calvin Klein have paid to dress the virtual influencer, contributing to Lil Miquela’s reported net income of $11.7 m (£9.5 m) in 2020 (Drapers, 2022a, b, c). There are currently over 150 virtual influencers online, according to virtualhumans.org, a site that tracks news on virtual humans (Vogue, 2021a, b, c), with some charging brands up to $8500 (£6900) per post (Drapers, 2022a, b, c). Both high-street and luxury brands are jumping on the virtual influencer bandwagon, from Dior to Pretty Little Thing and Nike (Drapers, 2022a, b, c). Industry reports have argued that virtual influencers cost considerably less than regular influencers, are 100% controllable, and are the ideal spokesperson when the brand wants to communicate its views on topics such as diversity and inclusion or sustainability (WGSN, 2021a, b, c). Interestingly, it has been found that on Instagram alone, consumers have three times the engagement rate with virtual influencers compared to real-life influencers (Baklanov, 2019), highlighting their marketing potential. The advantages of using virtual influencers are that the brand could appear to be innovative, allowing them to be more creative, executing ideas that would not be possible in the physical world (Drapers, 2022a, b, c). Furthermore, marketing platform HypeAuditor states that virtual influencers can produce three times the engagement rate on their posts as regular influencers (Drapers, 2022a, b, c). As previously alluded to, brands have more control over virtual influencers than they do human influencers, with no risk of bad PR crises or bad behaviour that can happen with human influencers (Drapers, 2022a, b, c). This level of control is increased when brands create their own virtual influencers. In 2021, Prada produced its first virtual model, Candy, to relaunch its fragrance, Prada Candy, in a campaign called ‘ReThink Reality’, whereby the digital model interacted with a human model in a series of TikTok videos (Drapers, 2022a, b, c). Hence, it is apparent that virtual influencers, such as Candy, are revolutionising modern influencer marketing (Sands et al., 2022). However, if brands create their own virtual influencers, they must make them realistic and interesting in order to promote engagement with consumers, as it will be hard to compete with real-life influencers who have back-stories and personalities and are people that consumers genuinely aspire to and look to for inspiration (Drapers, 2022a, b, c). As such, it will be challenging for virtual influencers to provoke the same kind of feelings as real influencers do.
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Findings: Potential Challenges of the Metaverse for Fashion Brands
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How to Enter the Metaverse?
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Currently, there are approximately 50 different providers of worlds within the metaverse, so it is hard for retailers to know which ones to choose (Murad & Smale, 2022). At this moment in time, the most popular providers are The Sandbox, Decentraland, Voxels, and Somnium Space, plus Meta’s own Horizon Worlds (Murad & Smale, 2022). Therefore, retailers are having to make educated guesses on which of these worlds will become the key providers of the metaverse and which may cease to exist in the future (Murad & Smale, 2022). Brands need to devise effective strategies on popular platforms or make their own platforms engaging and accessible.
5.2
Data Privacy & Trust
Data and privacy concerns will continue to be at the forefront of brands’ and consumers’ minds when entering the metaverse, which if not vigilantly protected may impede mass acceptance. Prior research has already addressed the potential mishaps that could take place in the metaverse relating to privacy breaches including the mismanagement of massive data streams and unfair outcomes of AI algorithms (Wang et al., 2022; Park & Kim, 2022). For example, Dwivedi et al. (2022) acknowledge that consumer data, including biometric data, facial expressions, eye movement, geographical location, and other personal information would be readily accessible in the metaverse. The fashion industry has already witnessed numerous ethical complications associated with emerging technologies, including the hijacking of wearable devices or cloud storage (Wang et al., 2022) and the misuse of AI to encourage overconsumption on social media platforms by tailoring content based on user engagement. Hence, privacy and trust must be a priority for brands, especially when acquiring consumer data in the metaverse (Saas, 2022). Innovations around the metaverse will be subject to global data protection regulations and new privacy laws (Saas, 2022), which are still yet to be established. Consequently, brands need to be cautious when collecting and storing users’ data and ensure that safeguards and knowledgeable people are in place in the legal, development, and security teams (Saas, 2022). This may include the recruitment of new types of staff and expertise, such as private attorneys, ethicists, and data scientists (Saas, 2022). Market research demonstrates that investing in strong privacy programmes can generate loyal consumers that trust the brand (Saas, 2022) and so an effective way for brands to earn consumer trust is by being wholly transparent about data collection practices (Saas, 2022). However, as the metaverse continues to evolve, the ways in which brands can collect, use, and apply consumer data remain a grey area.
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Identity & Gender
For brands to successfully establish visibility in the metaverse, consumers also must be present in these virtual spaces in the form of an avatar—a digital representation of self. Hence, the metaverse has been praised for providing a space that enables people to create and explore identities, especially gender, more safely through avatar customisation (Park & Kim, 2022). However, the implications of experimenting with gender in the metaverse are nebulous. While some argue that avatar customisation can help solve discrimination pertaining to gender (Dwivedi et al., 2022), others contend that built-in societal biases remain problematic with accusations of limited options for non-binary avatar representations (Vogue Business, 2022). Research has found that currently, avatar-based pre-sets and digital clothing options are incredibly binary, restricting users’ expression of gender to male or female only (Vogue Business, 2022), signifying that there is still significant progress to be made. Consequently, there is a growing demand for more diverse options for gender expression when appearing in virtual spaces. Scholarly research has already highlighted the importance of avatars for trans and gender-diverse users operating in online spaces, with Morgan et al. (2020) revealing that people often use avatars to cultivate and rehearse their preferred gender identities as a precursor to disclosing it in the offline world. The study further found that users often feel neglected in virtual spaces due to the constrictions of conventional notions of binary gender perceptions (Morgan et al., 2020), suggesting gender representation through avatar creation should be a key consideration for brands hoping to reach and acquire consumers. It is important to note that some brands are responding to concerns relating to gender representation in the metaverse. Indeed, Nyx Makeup has recently collaborated with People of Crypto Lab, a new metaverse-focused diversity lab, to launch a non-binary NFT collection and Pride event (Vogue Business, 2022). Additionally, users who select a non-binary avatar can customise their gender identity and sexual orientation. As consumers become progressively diverse, they expect to see themselves authentically reflected in brands’ marketing communications (WGSN, 2022a, b, c, d, e, f, g, h). Indeed, a recent survey found that 70% of respondents expressed that gender representation within a virtual world was critical (Calandra, 2022). Subsequently, to future-proof their marketing strategies, brands must ensure consumers can explore, create, and express their identities safely without negative encounters.
5.4
Diversity, Inclusion, & Cultural Appropriation
As little is known about the metaverse, rules and norms are still being established, making conversations around digital diversity even more imperative. As the metaverse is a decentralised space, the implementation of a robust EDI (equality, diversity, and inclusivity) strategy remains ambiguous. In the past, diversity in fashion often meant a ‘token acknowledgement that not every woman is a six-foot-
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tall blonde Caucasian’ by the inclusion of one non-white model in a photoshoot from time to time (Solomon & Mrad, 2022, p.73). This is no longer acceptable, and the fashion industry is now having to make strides to catch up with the global push towards more inclusivity (Solomon & Mrad, 2022). For instance, brands have been questioned about the lack of diversity among virtual influencers that they are working with (Drapers, 2022a, b, c). Now more than ever, consumers are demanding that brands cultivate diversity within their marketing communications and so brands are viewing the metaverse as an opportunity to include more diverse models in their promotional material by creating avatars from various cultures and ethnicities. However, this approach has sparked criticism, with academics and industry practitioners warning against ‘identity tourism’ and ‘digital blackface’ (Vogue, 2021a, b, c). Digital blackface refers to a non-black person using a black avatar to navigate around a digital space (Stark, 2018). Alternatively, identity tourism is the broader practice of choosing a digital character outside of one’s own identity (Vogue, 2021a, b, c). Conversations about identity tourism are plentiful when it comes to digital diversity. Indeed, scholarly research has found that within fashion communication, Black avatars often act as digital canvases that brands use to project marketing messages about racial diversity with the hope of diversifying their image without involving nor compensating real Black people (Sobande, 2021). Moreover, the introduction of Shudu Gram, a Black CGI model created by white British photographer Cameron-James Wilson caused outrage in 2018, with critics accusing Wilson of cultural appropriation. Hence, when creating avatars to feature in marketing campaigns, brands must ensure the approach is authentic and truly representative to ensure a more equitable representation in the metaverse. The practice of replacing real-life models with avatars in the metaverse will remain a contentious issue, requiring meticulous consideration from brands when entering this new digital space. Inclusive marketing will remain a pertinent topic as brands transition to the metaverse and so it is paramount that experts and programmers from various ethnicities and cultural backgrounds take the lead in designing spaces in the metaverse to capture consumer loyalty and shape the narrative around EDI in a decentralised space. Thus, culture needs to be a serious consideration for fashion brands when marketing in the metaverse and they should seek out experts in these areas to ensure inclusivity and cultural sensitivity, as well as a thorough understanding of the market (Saas, 2022).
5.5
Technology Adoption by Brands & Consumers
The chapter thus far has delineated potential opportunities and challenges for brands preparing to enter the metaverse, yet a critical aspect that remains dubious is whether both consumers and brands are willing to accept and adopt these various technologies. Being afraid of technology is not a novel concept. Indeed, people hid from electricity when it was first invented (WGSN, 2022c) and so new
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technologies, especially within the fashion industry, are often met with resistance from consumers. This digital hesitancy has resulted in a plethora of scholarly articles applying Davis’s (1989) Technology Acceptance Model (TAM) to explore consumers’ acceptance, and intention to use various technologies. Hence, as the metaverse is still evolving, further research should apply the TAM model to scope initial acceptance of the metaverse, as it is only when brands and consumers perceive the various digital components that make up the metaverse to be useful and easy to use that mass adoption will prevail. A further challenge lies in ensuring that brands have the technology and infrastructure in place so that employees can learn new technological skills. The fashion industry has been criticised for being slower to adopt technology in comparison with other industries. Hence, before any attempt is made to penetrate the metaverse, fashion brands must ensure that they are proficient in the software and that their employees possess the digital skill set required to enter this digital space effectively. As already addressed in the chapter, most digital components that are envisioned to compose the metaverse require specific technical skill sets such as back-end coding, 3D designing, and AI capabilities, which will require extra training and financial resources. Indeed, fashion brands may even need to employ new types of employees that are technology-focused to ensure they penetrate this realm appropriately.
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Summary and Future Research Agenda
The findings from the narrative review suggest that the metaverse can provide several innovative opportunities for promoting and communicating products, services, and brands. Interestingly, despite only gaining recent popularity within the fashion industry, many ethical and societal implications have emerged concerning the metaverse, including gender and race representation through avatar creation and data protection. Hence, marketers and scholars must be aware of these potential barriers before devising their marketing plans. To this end, additional research into the value of immersive technologies and how they affect consumer behaviour is necessary. Thus, drawing on secondary research captured through the narrative literature review, this chapter contributes to the literature by providing a future research agenda for academics as well as a summary of the key opportunities and challenges for practitioners (Fig. 1).
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Contributions and Limitations
This chapter has critically appraised the challenges and opportunities that are currently emerging as the metaverse takes shape and recommends the Technology Acceptance Model (Davis, 1989) as a theoretical framework for new research into this area. The authors pose new concerns that have not yet been addressed in prior literature. The model developed (Fig. 1) proposes future research avenues and
Brand Equity Brand Satisfaction Brand Loyalty Consumer Sentiment Community Engagement Source Credibility Social Ties Purchase Intentions Congruence
Technology Acceptance Innovation Adoption Sociotechnical Perspective Consumer-Decision Making Upward Social Comparison Theory Shopper Motivations (Utilitarian & Hedonic)
Does consumer decision-making differ across various cultures, genders, and ages? What are the behavioural motivations and internal drivers for entering specific metaverse spaces? What are the specific privacy and security risks associated with the metaverse, and how can brands overcome such concerns? Are metaverse technologies easy to use and perceived as useful in assisting the consumer's buying journey? What are the motivations behind undertaking deviant behaviours in the metaverse?
Measures & Theories
How do metaverse communities affect brand trust, satisfaction, and loyalty? What are the main drivers of NFT / digital purchases? What characteristics do virtual influencers have, and how do these compare to real-life influencers? How can brands measure the success of virtual influencers? What factors contribute to the parasocial relationship between virtual influencers and followers?
Research Questions
Fig. 1 Future research directions for academics investigating the metaverse
Challenges Entering the Metaverse Data and Privacy Concerns EDI & Cultural Appropriation Gender & Identity Adoption & User Experiences
Opportunities Community Building Community Membership (Collectable NFTs) Collaborative Co-creation New Form of Influencer Marketing
Opportunities & Challenges
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questions that can be used in further studies, thereby providing directions for academics and practitioners alike in such a new and novel area. To the best of our knowledge, this work constitutes the first narrative review of the opportunities and challenges posed by the metaverse, providing new insights into marketing literature and industry stakeholders. Specifically, the findings can help future studies test the empirical and practical implications discussed in this chapter. The main limitation of this chapter is the lack of existing academic studies focused on the metaverse itself. With the metaverse being such a new concept, it is hard to know for certain what form it may take and so there may be further opportunities that we have not considered. However, this does not detract from the main contribution of this chapter, which is to provide a future research agenda for academics wanting to investigate the metaverse based on an extensive review of academic and industry publications relating to the key technologies, such as AR and VR, that will likely be used to enter the metaverse.
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Understanding Social Media & Future Experience Norliana Jailani and Gianpaolo Vignali
Abstract
Marketers intensely continue to capture economic value by leveraging social media platforms besides improving customer experience. Social media has transformed how fashion is designed, presented, reported, and consumed. The growing attention to customer experience arises in parallel with the complex customer journeys, in which myriad touchpoints interaction is comprehensively used between firms and customers in multiple channels and media. Despite centring on customer experience for sustainable growth, little is known about the future experience across the customer journey (pre-purchase, purchase, and post-purchase). This chapter attempts to contribute to the existing Lemon and Verhoef (J Market 80:69–96, 2016) model by providing attention to the limited role of future experience in shaping customer experiences. The authors suggest that social media stimulus influences customers’ initial expectations and builds one’s future experience. Hence, this study aims to delineate the role social media stimuli can play in shaping future experiences, thus producing a novelty in conceptualising future experience. Accordingly, a broad critical literature review provides an extant theory contributing to the proposed model. Findings illustrate that owned social media (OSM) and earned social media (ESM) are the key dimensions contributing to future experiences. OSM denotes a brand’s content sharing through its online social network assets. ESM discusses the brand-related content created by consumers through online social networks. The findings of this study are likely to provide valuable insights into the literature development and offer key managerial implications in the fashion industry. Thus, this chapter suggests future work development as future experience is a relatively new “greenfield” area for future research. N. Jailani (✉) · G. Vignali Department of Materials, University of Manchester, Manchester, UK e-mail: [email protected]; [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_21
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Keywords
Social media · Customer experience · Future experience · Owned social media · Earned social media
1
Introduction
The importance of customer experience is unfolding (Hochstein et al., 2020) resulting a more complex journey, as the interaction through myriad touchpoints with firms involves various media and channels (Stein & Ramaseshan, 2016) (e.g., searching for information through a TV commercial, social media—Facebook or Instagram before buying a dress for a special cultural celebration). The customer experience flows interactively and dynamically from pre-purchase to purchase to post-purchase, often lasting days or weeks (Lemon & Verhoef, 2016; Maechler et al., 2016). Today, people see the world via a digital lens where experience can be perceived in the future (Forrester, 2016) through mainly the internet (Financial Times, 2017), and organisations acknowledge the potential of social media platforms as the benefit of linking to the outside-in approach, better information facilitation while empowering customers (Roma & Aloini, 2019). This chapter adopts the Customer Journey Experience Process Model from Lemon and Verhoef (2016), which conceptualises “customer experience as a multidimensional construct focusing on customer’s cognitive, emotional, behavioural, sensorial, and social responses to a firm’s offerings during the customer’s entire purchase journey”. Despite the popularity of customer experience competitiveness, research, however, little is known about future experience and the relationship with customer experience in the purchase phases of the customer journey. Thus, the researcher feels a gap in the model where the future experience loop is not incorporated into the customer journey. This study aims to delineate the role social media stimuli can play in shaping future experiences, thus producing a novelty in conceptualising future experiences. Future experiences can be derived from past customer experiences (Verhoef et al., 2009; Klaus & Maklan, 2013) and expectations (Lee & Thorson, 2008; Law et al., 2009; Verhoef et al., 2009; Blázquez, 2014; Forrester, 2016; Lawrence, 2016; Fernández et al., 2018; Hanaysha, 2018; Min et al., 2019) that are spread across multiple platforms. Social media is known for delivering a unique and valuable brand experience apart from the importance of exchanging information (Zollo et al., 2020). Scholars denote consumers are attracted to social media marketing activity (SMMA) as this touchpoint is able to gratify intellectual (problem-solving) experiences, behavioural, affective, and sensory (Tafesse, 2016; Zollo et al., 2020), and these influence how people utilise and react with brands and media (Gao & Feng, 2016; Tafesse, 2016). Previous research originates social media potential in improving customer trust, customer intimacy (Han & Kim, 2020), willingness to pay price at a premium, brand awareness, loyalty (Kim & Lee, 2019), brand equity, value equity, and relationship equity (Kim & Ko, 2012). From a conceptual perspective, these
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Fig. 2 Future experience conceptual framework (author’s own)
experiences influence current and future experiences (Kuehnl et al., 2019) and are naturally dynamic (Lemon & Verhoef, 2016). The fashion industry prominently contributes to one of the biggest segments of the world economy, representing 2% of the global gross domestic product with an estimated 3 trillion dollars (Wang et al., 2019a, b; Gu et al., 2020), with over 33.0 million employees (Wang et al., 2019a, b). The growth of this industry affects one’s social life in every aspect, causing visible changes in society (Wiedmann et al., 2012), climate, politics (Sandvik & Stubbs, 2019), economics (Jain & Mishra, 2020), and cultural landscapes (Godart, 2018). London Fashion Week generated “clout” in their 2014 show and received mentions on social media for over half a million, a massive success at the top fashion events (Hsiao et al., 2020). In addition, Dolce & Gabbana fashion shows offered front seat-special invitations to fashion bloggers for real-time content on social media (Singh & Banerjee, 2018), which yields a different experience from the norm for the bloggers and viewers. The objectives of the above-discussed gaps are: (a) to critically review social media in relation to experience and propose a relevant definition of future experience for a more explicit conceptualisation and (b) to identify sources of future experience for literature advancement and marketing strategies planning. This chapter contributes significantly to social media marketing and customer experience literature. Besides, the chapter offers implications to marketers that support understanding the term by adding value to social media marketing goals. The chapter is arranged as follows. First, it confers a broad critical literature review on social media and experience theory in Sect. 2. Then, it proposed a conceptual model and interrelated theories (Fig. 2) in Sect. 3, followed by the chapter’s contribution to the theory and managerial implications, limitations, and further research possibilities in Sect. 4.
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The study begins by setting out the understanding of social media. Second, it delves into the term ‘experience’ that underlies the creation of the concept and definition of ‘future experience’. Researchers consider starting with the notion of ‘experience’ by the classical studies on the subject from the 1950s, leading to the latest well-grounded findings from Lemon and Verhoef (2016), which aligns with current phenomena and is widely used as an underpinning definition in recent academic studies. It then explores the gap from the Lemon and Verhoef (2016) Customer Journey and Experience Process Model, adapting the Expectation-Confirmation/Disconfirmation Theory (Oliver, 1977, 1980) and establishing arguments for which, in consequence, the development of ‘future experience’ conceptualisation. Third, it proposes suggestions on the sources of ‘future experience’ by classifying the nature of the phenomenon in establishing the general frame derived from the social media stimulus.
2
Literature Review
2.1
Social Media
Social media is a digital environment presented as apps and websites from a collection of software-based digital technologies—in which digital content is sent and received through online social networks. Strategically, social media is essential for accessing customers and establishing individual connections (Appel et al., 2020; Dwivedi et al., 2021). These platforms are central in the making of online brand communities, which are mainly of two types: (a) company-hosted and (b) consumerinitiated brand communities (Nambisan & Baron, 2009; Kim & Ko, 2012). Facebook, Instagram, and Twitter features are the primary platform of social media that can be practically termed a type of digital marketing channel for communication with customers through advertising. Customer experience is more social in nature, and interactions with firms have changed through myriad touchpoints in multiple channels and media (Lemon & Verhoef, 2016). From this perspective, social media are more digital places where humans perform substantial parts of their lives—more about what they do in these environments. Social media in marketing is often thought of as a form of (online) word of mouth (WOM) and is tented to be mainly about information sharing (Appel et al., 2020). It is argued that social media is one of the myriad touchpoints; the fashion retailer benefits from these essential tools to connect with customers by engaging, sharing advice and ideas, product reviews, and providing a route to generate transactional traffic (Dias et al., 2017). It is vital to acknowledge social media classification to understand its uses (Table 1).
2.1.1 Social Networking Sites (SNS) SNS is sites or services that facilitate establishing and maintaining one’s relationships via online platforms. Follow, ‘like’, or group forming with individual ties gradually leads to larger social formations. These networks are shaped around
Understanding Social Media & Future Experience Table 1 Social media classification
Type Social networking sites
Blogs Micro-blogs Photo-sharing sites
Content communities
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Social media channel Facebook Google+ LinkedIn Blogger WordPress Twitter Tumblr Instagram Pinterest Flickr YouTube
perceived mutual interest in organisations or events. They can be ego-centred to people (McArthur et al., 2018), enabling users to exchange information, observe and interact, hence, presenting a paradigm shift in word-of-mouth communications (Heggde & Shainesh, 2018). Facebook sites encourage social sharing content with others using tools, features, and applications provided by this SNS (Smith et al., 2012; Heggde & Shainesh, 2018). Due to its overlapping classification, Instagram (IG) is recognised as a free social networking platform and multimedia sharing application (Edwards & Esposito, 2019).
2.1.2 Blogs Blogs encompass social and interactive elements of user engagement (Chaffey, 2016) that enable internet users to discuss topics of interest for content creation (Liu et al., 2007; Keng & Ting, 2009) and information dissemination (Wilde, 2008) in the blogosphere. Besides, due to their perceived credibility, blogs are an effective interpersonal communication channel influencing customers’ decision-making (Kulmala et al., 2013; Hahn & Lee, 2014). Blogs allow users to document personal content akin to an online records diary (Nardi et al., 2004; Liu et al., 2007; Chittenden, 2010; Park et al., 2010), life events and commentaries, and thoughts on a limited audience, i.e., family and friends (Keng & Ting, 2009). 2.1.3 Micro-Blogs Micro-blogging is a popular form of social media that enables broadcasting news in text messaging format with brief updates in short character limits (Murphy, 2008). Micro-blogs allow people to update their status by publishing short text, photos, and audio fragments while communicating between two or more persons, sharing information, and asking questions. Twitter is perceived as the most commonly associated micro-blog platform in today’s online environment used by consumers and retailers (Burton et al., 2011; Mirkovski et al., 2018). Example: Twitter Twitter was founded in 2006 (Murphy, 2008), in which “tweets”, reply, and “retweet” posts publication was limited to 140 characters (Smith et al., 2012). In
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September 2017, Twitter expanded the character limit to 280, and people Tweeted more efficiently and often (Rosen, 2017).
2.1.4 Photo-Sharing Sites Image-sharing sites allow users to publish their images or images from the web. Example: Instagram A social networking app enables users to take pictures, edit them with various digital filters, and share them with the audience. In addition, Instagram offers videosharing and Instagram stories (Clement, 2019a). In 2021, a report showed 1.21 billion monthly active users worldwide, with 28 per cent of the world’s internet users (Dixon, 2022). In fashion, with over 28 million followers, the French fashion house Chanel is the leading brand on the social media platform, followed by Louis Vuitton, Gucci, and Dior (Clement, 2019a). 2.1.5 Content Communities Content communities such as YouTube (www.youtube.com), Flickr (www.flickr. com), Imagr (http://imgur.com), Tumblr (www.tumblr.com), and Daily Motion (www.dailymotion.com) are sites that allow users to share multimedia content (Cross, 2014). Other users can search and view descriptions on images, videos, music, or other content. Comment feature added value to these sites as users can share their thoughts on a page displaying content and link to other social media sites like Facebook and Twitter (Cross, 2014). Example: YouTube YouTube was launched in 2005 and is arguably the most prominent online video platform globally. YouTube contains music videos, TV clips, video blogs, gaming videos, language learning to DIY (do-it-yourself) activities, educational content, and many more featuring a variation of corporate media and user-generated (Clement, 2019b). Fashion designers have turned to Instagram due to hashtag exposure, which puts content onto a news feed database. It alters how brand content is designed, disseminated, and consumed (Appel et al., 2020). Moreover, the use of Instagram helps fashion designers reach a broad audience spectrum with the advantage of a free form of advertising from social media. Instagram connects and communicates more with like-minded followers, and brands often make live stories for more personal sharing with fans while discovering new people and things. Besides, the Instagram shop feature creates a more commerce-friendly shopping experience with social media than other applications (Cheung & Choi, 2022). Social media establish value on the customers’ journey experience, and emotions associated with fashion brands in social media may affect individuals’ usage and actions towards the media and brands (Khan, 2022). Lemon and Verhoef (2016) denote customer experience process flows from pre-purchase (including search) to purchase to post-purchase; it is iterative and dynamic. This process incorporates past experiences (including previous purchases) and external factors. In each stage, customers experience touchpoints, only some of which are under the firm’s control. Scholars conceptualised the total customer experience as a dynamic process and
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proposed extensively reporting social media’s effects on customer experience. Prior to the comprehensive conceptualisation of future experience, it is vital to acknowledge early literature on the experience and customer experience.
2.2
Experience
In the early days, the attention to experience was driven by the broader notion that “what people really desire are not products but satisfying experiences” (Abbott, 1955; Alderson, 1957). In the 1980s, experiential theorists fortified a wider understanding, identifying the important aspects of experience and decision-making which involve emotion (e.g., Hirschman & Holbrook, 1982; Holbrook & Hirschman, 1982; Thompson et al., 1989). Pine et al. (1999), the marketing practice conceptualised the idea that “experiences” need to be purchased to enable the customer to “spend time enjoying a series of memorable events that a company stages . . . to engage him in an inherently personal way” and the notion differs from goods and services. In buying decisions, individual buying selections are further influenced by psychological factors that originate from changes in a person’s behaviour in learning activities—experiential and conceptual (McDaniel et al., 2011) and rational and emotional (Amstrong et al., 2017). According to learning theorists, most human behaviour is learned (Kotler & Keller, 2016; Arghode et al., 2017). Learning occurs through the interplay of drives, cues, stimuli, reinforcement, and responses (Kotler & Keller, 2016; Arghode et al., 2017). Individuals will reflect on the good and bad memories of the past experiences with a product or a brand and consider their choices as they anticipate future experiences.
2.3
Customer Experience
In recent years, “customer experience” has become a universally used phrase though businesses perceive improving their customer experience as a competitive differentiator. Scholars assume that multiple touchpoints along a customer journey create ease of living or feasibility, which constitutes a vital aspect of any customer experience (Kuehnl et al., 2019). Favourably, social media improves customer experience, and satisfaction as the interplay of the touchpoints is likely to shape customer attitudes (Stephen & Galak, 2012). However, from a conceptual standpoint, experiences are dynamic in nature (Lemon & Verhoef, 2016), and therefore past experiences may influence both current and future experiences (Kuehnl et al., 2019). Service and retailing management initially considered customer experience as a construct in the marketing literature and not a separate concept (Parasuraman et al., 1988; Verhoef et al., 2007). Instead, researchers focused on measuring service quality and customer satisfaction (Parasuraman et al., 1988; Verhoef et al., 2007). In contrast, theorists Hirschman and Holbrook (1982) notion that consumption has
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Table 2 Concept of experience Characterisation of the concept of customer experience Holbrook and “Experiential perspective is phenomenological in spirit and regards Hirschman (1982) consumption as a primarily subjective state of consciousness with various symbolic meanings, hedonic responses, and aesthetic criteria. Consumption experience can be seen as a flow”. Pine et al. (1999) “Experiences are events that engage individuals in a personal way and derive from the individual’s prior state of mind and being”. Experience has four realms (entertainment, educational, aesthetic, and escapist); the richest experiences include aspects of all of them”. Schmitt (1999) “A multidimensional view and identifies five types of experiences: Sensory (sense), affective (feel), cognitive (think), physical (act), and social-identity (relate) experiences”. McCarthy and Wright “Considering technology as an experience, identify what they call the (2004) four threads of experience, ideas that help us to think more clearly about technology as experience; the sensual, the emotional, the compositional, and the spatio-temporal”. Edvardsson et al. “Service experience is “a service process that creates the customer’s (2005) cognitive, emotional, and behavioural responses, resulting in a mental mark, a memory (in line with Johnston and Clark (2001)”. Meyer and Schwager “Customer experience is the internal and subjective response (2007) customers have to any direct or indirect contact with a company. Direct contact generally occurs in the course of purchase, use, and service and is usually initiated by the customer. Indirect contact most often involves unplanned encounters with representations of a company’s products, services, or brands and takes the form of wordof-mouth recommendations or criticism, advertising, news reports, reviews, and so forth”. Verhoef et al. (2009) “Explicitly define customer experience in a retailing context as a multidimensional construct and specifically state that the customer experience construct is holistic in nature and involves the customer’s cognitive, affective, emotional, social, and physical responses to the retailer”. Lemke et al. (2011) “Includes pre- and post-service encounter/purchase/consumption experiences, addresses emotional as well as functional dimensions of quality, and includes the customer’s social context. Includes the assessment of value-in-use, is formed over multiple channels, and varies with context”. De Keyser et al. (2015) “Comprised of the cognitive, emotional, physical, sensorial, spiritual, and social elements that mark the customer’s direct or indirect interaction with (an) another market actor (s)”.
experiential facets (Babin et al., 1994). Scholar Schmitt (1999) discovered that firms generate experiential marketing by making customers think, act, feel, sense, and relate to an organisation and its brands. Organisations should orchestrate all the “clues” that individuals notice in the purchasing process to provide customers with a satisfactory experience (Berry et al., 2002) (Table 2). Technology is classified as an experience by McCarthy and Wright (2004), denoting the four threads of experience: the sensual, the emotional, the
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compositional, and the spatio-temporal. Customer experience is viewed from multiple perspectives that integrate design, delivery, and management—the firm is responsible for designing and crafting an experience for the customer to receive (Berry et al., 2002; Stuart & Tax, 2004). From the customer’s viewpoint (Schmitt, 2011) or a co-creation standpoint, customer experience is the customer’s interaction with other actors in a broader ecosystem, which is deemed a culmination while identifying the customer’s role in the coconstruction of the experience (Prahalad & Ramaswamy, 2003; Chandler & Lusch, 2015; De Keyser et al., 2015). Scholars and practitioners generally agree that the total customer experience is a multidimensional construct that encompasses emotional, cognitive, behavioural, sensorial, and social components (Schmitt, 1999; Verhoef et al., 2009). Though brand (Brakus et al., 2009) or technology (McCarthy & Wright, 2004) may relate to specific facets of the contribution, called touchpoints (Schmitt, 2003; Homburg et al., 2015), it consists of association with an individual between the firm and the customer at distinct points in the experience. These collections of touchpoints in multiple phases build up the experience and affect the customer’s decision process or purchase journey (Puccinelli et al., 2009; Verhoef et al., 2009). Through the synthesis of experience and academic literature, the researcher has found that the definition of Lemon and Verhoef (2016) aligns with current phenomena and is widely used as an underpinning definition in recent academic studies. Lemon and Verhoef (2016) thus conclude that “customer experience is a multidimensional construct focusing on a customer’s cognitive, emotional, behavioural, sensorial, and social responses to a firm’s offerings during the customer’s entire purchase journey”. The definition is considered appropriate in this study as it involves the nature of the experience that is felt to be realistic and in line with the research conducted. This definition will be discussed further in this chapter.
2.3.1 Social Media and Customer Experience Fashion retailers are investing in experiential retailing to deliver unique retail experience journeys to inspire customers to dwell as consumer behaviour in decision-making has shifted from the rational to the emotional and experiential (Watson & Yan, 2007). In today’s fashion environment, the evolution of interactive customer-engaging online fashion e-retailing for fashion consumption offers significant experiences to the customer. Customers utilise websites for browsing, creating, sharing, and purchasing, and these experiential activities diffuse into the experienced-centric model (Chen et al., 2012). The development of communication technologies has now empowered the fashion world, particularly through the support of social media (Kim, 2012; Hsiao et al., 2019; Kim & Lee, 2019; Liu et al., 2019). The involvement of online interaction (Chen et al., 2012) and exchanges that include physical and mental engagement create one’s experience (Pine et al., 1999). For instance, luxury brands are known for one-to-one relationships with customers, implicating uniqueness and exclusivity; however, today, they adopted social media to manage the brands’ persona (Kim & Ko, 2012, 2019; Liu et al., 2019) realising the intensity to engage and connect with potential consumers (Koivisto & Mattila, 2018). Meanwhile, many fashion designers extensively utilise the social media
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landscape and become owners of small and medium enterprises (SMEs) by creating their private labels (Kachba et al., 2012) to achieve a certain level of market penetration (Braojos-Gomez et al., 2015). Entertainment is important as most generations grew up with technology, while in-store shopping receives less attention in the present (Ordun, 2015; Kenwood, 2019). The younger generation is considered digital natives (Prensky, 2001) and spends their lives in a digital environment that significantly impacts how they live and work with information technology (Bennett et al., 2008; Wesner & Miller, 2008). The need for retail-tainment has never been more compelling (Kenwood, 2019) as customers hunt for unique experiences and emotional rewards over more practical concerns. Retail-tainment, also known as immersive or experiential retail, leveraging technology involves interactive and customer-relevant concepts, from social media to the Internet of Things (IoT) to virtual reality (VR), in building brand extensions around community participation (Kenwood, 2019). With the growth of social media, this chapter raises the question on the role that social media can play in shaping future experiences, thus producing a novelty in conceptualising future experiences as to how social media translates information and serves as a guide for customers to interpret their future experiences with their brand of selection.
2.3.2 Customer Journey and Touchpoint Design: Model Adopted This section underlines the model from Lemon and Verhoef (2016) adopted in this chapter. Figure 1 shows the process model of the current customer experience and customer journey that involves three stages: pre-purchase, purchase and postpurchase, and the feedback loop. Each function is discussed in this model; however, in the customer journey, the researcher feels there is a gap in the model where the future experience loop (X) is not incorporated. Future experiences can be derived from customers’ past experiences and expectations spread across multiple platforms (Lemon & Verhoef, 2016). In this study, researchers are interested in the social media platform as social media is the most popular medium today, for disseminating relevant information, especially in the fashion world. Lemon and Verhoef (2016) designate customer experience process flows from pre-purchase (including search) to purchase to post-purchase, which is interactive and dynamic. Lemon and Verhoef (2016) also conceptualise customer experience as a customer’s ‘journey’ with the firm over time during the purchase cycle across multiple touchpoints. This process incorporates external factors and passes experiences, including the activity of previous purchases (Klaus et al., 2013). Customers experience touchpoints in each process flow; pre-purchase, purchase, and post-purchase, which some are under the firm’s control. Customer interaction with firms’ facilitated technologies may appear at various touchpoints across the purchasing journey either with the retailer-facilitated technology (e.g., company websites, company mobile applications, self-service technology, kiosks, point-ofsale technology, etc.), or unaffiliated technology, such as social media and other websites, may influence the customers’ experience. This process may serve as a guide to empirically modelling the effects of different touchpoints on the customer’s
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Fig. 1 Research gap (X): A process model for customer journey and experience (Lemon & Verhoef, 2016)
experience and empirically examining customer experiences over time during the customer journey (Stein & Ramaseshan, 2016).
Customer Journey Customer experience can be conceptualised in three overall stages: pre-purchase, purchase, and post-purchase, consistent with prior research (Howard & Sheth, 1969; Puccinelli et al., 2009). Pre-purchase
Pre-purchase is the first stage in the customer journey that integrates customer interaction with the brand and environment prior to the buying activity. Need recognition, search, and consideration are the classes of pre-purchase behaviour identified in the traditional marketing literature (Lemon & Verhoef, 2016). Based on the theory, pre-purchase includes the customer’s entire experience before purchase. This stage encompasses the initial customer’s experience in achieving certain goal/need/impulse recognition to the consideration of satisfying that goal/need/ impulse with a purchase (Hoyer, 1984; Pieters et al., 1995). Social media is associated with creating and sharing information or interaction on the website or application that facilitates users to engage in social networking activities (Piskorski et al., 2014). Similarly, other scholars posit that social media environments significantly impact buying decisions (Shim et al., 2001; Power & Phillips-Wren, 2011; Amstrong et al., 2017; Kim & Lee, 2019).
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Purchase
In this second stage, purchase activity involves interaction between the customers, the brand, and its environment, thus receiving significant attention in the marketing literature (Kotler & Keller, 2016). Traditionally, consumers seek advice from friends and family when making informed purchase decisions or turn to marketer-generated information such as advertisements for reviews (King et al., 2014). Today, making statements in informal communication settings is possible via computer-mediated contexts where consumers share information anonymously about products and services, and statements are visible to the entire internet community. (Kane et al., 2009). Electronic Word of Mouth (eWOM) is thus capable of reaching and influencing thousands of potential customers (Martin & Lueg, 2013). Post-purchase
Post-purchase is the final stage in the process model following the actual purchase, where the customer interacts with the brand and its environment. Consumption and usage of the product (Holbrook & Hirschman, 1982), post-purchase engagement, and service requests are the behaviours included in this stage (Lemon & Verhoef, 2016). Every subsequent decision in the category shapes the experience in the postpurchase, so the journey is an on-going cycle that inspires repeat purchases and loyalty (Court et al., 2009). In fashion, social media textual and visual posting with hashtags allows users to exchange apparel information voluntarily on user experience, personal reviews, and customer feedback with the brand (Abidin, 2016) while engaging with customers to lure existing clients into buying more in the future (Varuni, 2014). Customer Touchpoints Previous studies propose that different customer touchpoints within the customer journey can be acknowledged (Baxendale et al., 2015); before, during, and after the experience of a product or service (Maechler et al., 2016). Brand-Owned Touchpoints
The firm designed, managed, and controlled these touchpoints for customer interactions during the experience journey. Websites, advertising, loyalty programs, and all brand-owned media are part of the touchpoints, and any elements of the brand-controlled marketing mix, such as attributes of products, price, packaging, salesforce, service, and convenience are some other brand-owned touchpoints (Lemon & Verhoef, 2016; Kuehnl et al., 2019). Partner-Owned Touchpoints
Customer interactions during the experience can include these touchpoints from marketing agencies, communication channel partners, multi-channel distribution partners, and multi-vendor loyalty program partners that are jointly designed, managed, or controlled by the firm and one or more partners (Lemon & Verhoef, 2016; Batra, 2018).
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Customer-Owned Touchpoints
These touchpoints refer to customer actions that are out of others’ influence or control; neither the firm nor its partners and these actions are part of the overall customer experience. For example, customers consider their needs and preferences during the pre-purchase process (Lemon & Verhoef, 2016). Common examples of touchpoints include Point of Sale (POS) (e.g., purchasing foods from the supermarket), online store purchases (e.g., electronics purchase from an online-only vendor), and all activities associated with website visits (e.g., searching for products from an online vendor, Facebook ‘likes’), numerous types of smartphone and other mobile device interactions and music piped through the store (Loshin & Reifer, 2013). These include pleasant odours pumped out to the street from a restaurant, visual cues incorporating signs, layout, and even mannerisms and gestures (Loshin & Reifer, 2013). Social/External Touchpoints
The roles of others in these touchpoints are significant as customers are surrounded by external touchpoints in their experience journey. Peer influences, other customers, independent information sources, and the environment may influence the customer journey experience. Peers possibly exert influence in all three stages of the experience, solicited or unsolicited (Lemon & Verhoef, 2016). Evidence shows that experience is influenced by the social environment (Lin & Liang, 2011). Within the marketing literature, third-party information sources like social media and review sites (e.g., TripAdvisor) have gained strong attention to influence consumers (Manchanda et al., 2006; Lemon & Verhoef, 2016). Furthermore, sometimes they have closely considered partner touchpoints (Lemon & Verhoef, 2016) and associated with the brand or firm (Manchanda et al., 2006). As discussed in the beginning, focusing on customer experience is one of the most critical factors in improving a company’s economic growth (Klaus, 2015; De Keyser et al., 2020). Most recently, the importance of the customer journey has been emphasised to ensure that customers receive the best possible customer end-to-end journey (Lemon & Verhoef, 2016; Maechler et al., 2016; Siebert et al., 2020). The journey is an on-going cycle, inspiring loyalty and repeat purchases (Court et al., 2009). Figure 2 shows the process model of the current customer experience and customer journey that involves three stages pre-purchase, purchase, and postpurchase, and the feedback loop. Each function has been discussed in this chapter. However, the researcher feels a gap in the model where the future experience loop (X) is not incorporated into the customer journey. Future experiences can be derived from customers’ past experiences and expectations spread across multiple platforms. In this study, the researcher is interested in the social media platform as social media is the most popular medium for disseminating relevant information, especially in the fashion world.
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Future Experience
It is vital to understand tomorrow’s customer experience to compete with this sophisticated growing complexity in business (Hernandez et al., 2018). Despite the increasing attention towards customer experience, the definition of future experience is still vague. Limited studies focusing on the future experience as the exploration towards future experience are restricted with empirical validation, and measuring the impact of future experience on the customer purchase journey remains a problem. This section discusses the definition of future experience and the determinants that constitute future experience based on literature findings. Based on English dictionaries (Oxford English Dictionary, 2000; MerriamWebster, 2020), the definitions of future are (Table 3): The authors’ findings suggest that the ‘future’ is an expectation of advancement or progressive development (Merriam-Webster, 2020). The attention to the study of expectation obtain values from various research, and this phenomenon has been widely observed (Flake et al., 2000; Parcell, 2007; Verhoef et al., 2009; Blázquez, 2014; Wang et al., 2018). Previous literature conceptualised several criteria associated with expectations based on the reality of experience that involves an individual’s behaviour influenced by the psychological factor (McDaniel et al., 2011; Amstrong et al., 2017). Learning theorists remark that the interplay of drives, stimuli, cues, reinforcement, and responses develops most human behaviour and is learned (Amstrong et al., 2017; Arghode et al., 2017). Theorists conceptualised customer experience in three stages: pre-purchase, purchase, and post-purchase (Howard & Sheth, 1969; Neslin et al., 2006; Puccinelli et al., 2009; Lemon & Verhoef, 2016). The post-purchase stage involves afterpurchase aspects that lead to feedback arising from the customer’s purchase experience that is associated with the product, service, or brand itself (Fig. 1). In this stage, customers evaluate their purchase experience by making comparisons with their pre-purchase expectation, leading to satisfaction or dissatisfaction. Consumers verify the similarity ratio based on their product experience and other consumers’ testimonials or information (Colicev et al., 2018). Expectation-Confirmation Theory by Oliver (1980) describes customer expectation as used to generate a definite reference to a specific service for comparative judgement. In the preliminary effort to conceptualise the understanding of future experience, the authors suggest to underpinned the Expectation-Confirmation Theory (Oliver, 1980) following the Stimulus-Organism-Response (S-O-R) paradigm developed by Table 3 Definitions of ‘future’ Definitions Oxford English Dictionary, 2000 Merriam-Webster, 2020
(the future): a. Time to come; future time. for the future: in all future time b. What will happen in the future 1a. Time that is to come b. What is going to happen 2. An expectation of advancement or progressive development
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Mehrabian and Russell (1974) (Fig. 2). The S-O-R paradigm suggests that environmental attributes (Stimulus) affect one’s emotional states (Organism), which causes approach or avoidance behaviour (Response). Social media cause changes to individuals’ cognitive processes (acts as an organism), which stimulates one’s future experience. Thus, the researcher conceptualises future experience as a customer’s initial expectation with a firm time to time influenced by the interplay of drives, stimuli, cues, responses, and reinforcement through sensory information derived from the media environments throughout the purchase journey.
3.1
Expectation-Confirmation Theory/Expectation Disconfirmation Theory (Oliver, 1977, 1980)
Oliver (1980) described the expectation-confirmation theory; first, customer expectations generate a definite reference to a specific service for comparative judgement. The service performance after using the service develops the customer’s perception. Then, a confirmation procedure is executed based on the perceived performance and specific reference formed in the early phase. Furthermore, when the expectations match the perceived performance, confirmation happens. Based on this evaluation, the positive customer perspective results from positive disconfirmation and basic confirmation (Anderson, 1973). The theory implementation in this study is appropriate as there are similarities in context since there is an inadequate model or theory of future experience in the literature. The understanding of future experience in this regard is limited to the exploration of expectation due to the rationale of the phenomenon of study, which is yet to explore the whole model (Table 4 and Fig. 3).
Table 4 Expectation-confirmation theory Anderson (1973)
Taylor and Durand (1979)
Oliver (1980)
Qazi et al. (2017)
Expectations are said to be positively disconfirmed if performance is better than expected, confirmed if the product performs as anticipated and negatively disconfirmed when the product performs worse than expected. Expectations influence intentions to purchase in two ways— directly and indirectly through posttrial judgements of affect. Expectations may directly influence consumers’ intentions to purchase, and the extent to which these expectations may indirectly influence intentions to purchase through their impact on the consumer’s affective evaluations. Expectations lead to consumer satisfaction. Positive disconfirmation produces greater satisfaction when product performance surpasses expectations. Simple confirmation and moderate satisfaction are predicted if performance is similar to expectations. The higher (lower) expectation levels result in higher (lower) satisfaction levels resulting in higher (lower) satisfaction levels independent of positive or negative disconfirmation. Regular, comparative, and suggestive opinions have a positive effect on raising users’ expectations. At the post-purchase stage, the study predicted a strong relationship between expectation, performance, and disconfirmation.
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Fig. 3 Expectation-confirmation theory (Oliver, 1980)
The Environment (S)
Sense modality variables (e.g., color and temperature)
Information rate (Characterizing the spatial and temporal relationships among the stimulus components of an environment)
Primary Emotional Responses (O)
Pleasure Arousal Dominance
Behavioral Responses Approach-Avoidance (R)
(Which includes physical approach, exploration, affiliation, performance, or other verbal and non-verbal communications of preference)
Characteristic emotions associated with personality
Fig. 4 Stimulus-Organism-Response (S-O-R) Framework (Mehrabian & Russell, 1974)
3.2
Stimulus-Organism-Response (S-O-R) Framework
The Stimulus-Organism-Response (S-O-R) paradigm developed by Mehrabian and Russell (1974) was a framework to study the effects of the environment on behaviour used by environmental psychologists. Donovan and Rossiter (1982) later adopted the model for retail contexts to study shopping behaviour and its impact on retail environments. Mehrabian and Russell’s (1974) original S-O-R paradigm suggests that environmental attributes (Stimulus) affect people’s emotional states (Organism), which in turn causes approach or avoidance behaviour (Response) (Fig. 4). The S-O-R framework is widely used in other fields that discuss behavioural understanding in a research setting, for example, in tourism and social shopping sites (Lunardo & Roux, 2015; Chang, 2017; Leong et al., 2018; Wang et al., 2019a, b; Kim et al., 2020; Pal et al., 2020; Tang & Zhang, 2020). Several recent studies link stimulus and online environmental stimuli and their effectiveness in evaluating a
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behaviour (Chang, 2017; Krasonikolakis et al., 2018; Connell et al., 2019; Pal et al., 2020). The adoption of the model in this study is still relevant as there are considerable researchers underpinned this concept in their research, and some comprise digital and information technology aspects (Liu et al., 2016; Yao & Cao, 2017; Chen & Yao, 2018; Kumar et al., 2018) (Fig. 5). Holbrook and Hirschman (1982) have introduced, defined, and linked multisensory experience constructs from an experiential perspective and suggested that emotive and fantasy imagery responds to various consumption processes. The consumer behaviour logic flow models proposed by Holbrook and Hirschman (1982) are positioned by the Stimulus-Organism-Response (S-O-R) framework of environmental psychology (Mehrabian & Russell, 1974). The S-O-R advocates that the stimulus (various environmental and consumer inputs) is proposed by an intervening response system (organism) that may result in their behaviours (response), such as activity, usage, and consumption experience (Koo & Ju, 2010). The understanding of future experience in this regard is limited to exploring Stimulus and Organism due to the rationale of the phenomenon of study yet to explore the Response phase. Stimulus in this study denotes the use of social media as an independent variable affecting the organism’s responses.
3.3
Sources of Future Experience
This study accentuates sources of future experience in establishing a general frame for comparative judgements derived from the social media stimulus. The earlier literature discussion on social media denotes two types of online brand communities: (a) company-hosted and (b) consumer-initiated brand communities (Nambisan & Baron, 2009; Kim et al., 2012). Generally, social media offers ways for customers to enhance the impression of certain products and brands in information searching activities (Muntinga et al., 2011) that derives from the brands’ effort or social networks. Customers’ experience has dynamic effects as customers repeatedly experience change over time with a product or after a specific experience (Lemon & Verhoef, 2016). Brand-owned, partner-owned, customer-owned, and social/external touchpoints (Lemon & Verhoef, 2016) are parts of the source of future experience. This chapter acknowledges owned and earned social media (Kotler & Keller, 2016; Colicev et al., 2018) as the basis for describing the context due to its social media setting.
3.3.1 Owned Social Media Owned Social Media (OSM) denotes any online communications created, shared, and controlled by a brand through their social networks property, such as an Instagram account, Facebook fan page, and YouTube channel (Colicev et al., 2018; Kuehnl et al., 2019). Experience creates long-lasting impressions on consumer memory (Schmitt, 1999) when they search, buy, receive, and consume products or services (Lemon & Verhoef, 2016), generally on standard product features, with different negative or positive valence (Khan et al., 2019). During the product or
Cognition Fantasy Imagery Creative play Free Association
Experiential Perspective
Cognition Belief from direct interaction Knowledge Structure Comparisons against schemas & memory Thought Generation
Information Processing Perspective
Organism
Affect Emotions Feelings
Affect Attitudes Preferences
Source: Adopted from Holbrook and Hirschman (1982b), Mehrabian and Russell (1974)
Consumer Inputs Situation Involvement, motivation Demographic characteristics Gender, age Personal traits Innovativeness, skillfulness, self-efficacy
Environmental Inputs Ambient cues Audio-visual elements Design cues System quality, content, convenience Social cues Peer-to-peer interaction, social influence
Stimulus
Response
Behavior Usage Consumption Experience Activities Perceived resource expenditure
Behavior Buying Purchase Decision Choice Actual resource expenditure
Stimulus-Organism-Response Framework: Information Processing System/Experiential System
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Fig. 5 S-O-R framework: information processing systems/experiential system (Li et al., 2012)
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service search, the online environment may evoke one’s brand experience and not restrict to the physical settings (Khan et al., 2019; Morgan-Thomas & Veloutsou, 2013; Zollo et al., 2020). The advancement of internet-related technologies generates opportunities for potential customers to interact and have experience with the brands’ websites and social media pages (Dwivedi et al., 2021). According to Morgan-Thomas and Veloutsou (2013), online brand experience is described as a customer’s “holistic response to the stimuli within the website environment,” and establishing a good rapport with customers can be immediate (Khan et al., 2019).
3.3.2 Earned Social Media Earned Social Media (ESM) refers to media activity that a company does not directly or organically generate. Customers typically create, consume, and disseminate through online social networks (Colicev et al., 2018), including an Instagram mention or even a resharing of the brands’ blog post. Recently, influencers have been popular among customers. They are people and organisations with expert knowledge and social influence in their respective fields. Contents from the influencers (e.g., activists, social media famous, role models, trendsetters) are ideally testimonials advertising in which they promote the products/brands and a potential buyer themselves (Brown & Hayes, 2008). It is discussed that influencers share their stories with their followers to establish strong ties, and these followers are ready to be the audience and listen to any postings about a particular brand (Fink et al., 2018). Recommendations from friends (WOM) develop greater trust than advertisements (Herr et al., 1991). It is also argued that eWOM social advertising with friends referrals (social endorsement) increases one’s attention on the product or brand (Windels et al., 2018). Positive reviews from friends and family indicate the quality of advertised products and brands (Deraz, 2019), increasing customers’ expectations of brands. This chapter suggests that the context from the previous studies of OSM and ESM contributes to the determinants of future experience. Customers who view relevant content on social media platforms elicit psychological influence in generating visualisation and initial expectation during the purchase journey (Table 5).
4
Discussion and Conclusions
The study discusses social media’s role in leveraging digital technology in fashion within the customer journey with the aim to delineate a novelty in conceptualising future experiences. This chapter also considered the parameter that builds one’s imagery and clues in shaping their future experience. The findings suggest that customers’ past experience or metaphor generated from the social media stimulus touchpoints leads to the customer’s initial expectation with a firm from time to time throughout the purchase journey. Besides, owned social media (OSM) and earned social media (ESM) contributions delineate future experiences.
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Table 5 Owned social media and earned social media Type Owned
Definition Set of communication related to the media activity generated and controlled by the company or its agents
Earned
Set of communication related to the media activity generated by the third-party such as journalists or customers, and not by the company or its agents
4.1
• Online Examples • Brand-owned social networks accounts • Brand website • Brand blog • Content in online communities or social networks (e.g., reposts, mentions, status updates, tweets) • Publicity mentions in digital media channels (e.g., professional blogs) • Online reviews and ratings • Online WOM referrals (e.g., website invitations)
Theoretical Implications
This chapter adds to the social media marketing literature in subsequent ways. The present chapter demonstrates the effort to sufficiently understand ‘future experience’ and classify the sources of future experience derived from social media touchpoints based on the previous literature findings. First, the discussion on social media and classification contributes to understanding this touchpoint. Social media helps fashion retailers generate transactional traffic and is an essential tool for communicating, sharing ideas creatively and engagingly, advice, and product reviews (Dias et al., 2017). Customer experiences are more social in nature (Lemon & Verhoef, 2016). This chapter proposes the definition of future and experience from the previous scholars, and the integrated view of future experience within the adaptive S-O-R conceptual framework and Expectation-Confirmation Theory is presented, and hope will be helpful in (1) organising what is known in the area (2) stimulating future research. Learning theorists denote that most human behaviour is learned (Kotler & Keller, 2016; Arghode et al., 2017). Learning occurs through the interplay of drives, cues, stimuli, reinforcement, and responses (Kotler & Keller, 2016; Arghode et al., 2017). Individuals will reflect on the good and bad memories of the past experiences with a product or a brand and consider their choices as they anticipate future experiences. To the best of our knowledge, this study is the first to investigate this term, thus extending customer experience literature and its importance in the customer journey context. Second, the current findings on the future experience mechanisms add to the social media research the degree to which the social media touchpoints link varies due to the immense knowledge from the brands’ and customers’ social media activity. This analysis suggests that the brands (company-hosted) and a collection of information from family, friends, and influencers (consumer-initiated) are likely to initiate one’s ways of thinking and learning about their experiences. Generally, social media offers ways for customers to enhance the impression of certain products and brands in information searching activities (Muntinga et al., 2011) that derives from the brands’ effort or social networks. This finding advances the literature,
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which argues that the organism is the mediator variable and responds to the vital research calls in the social media marketing and experiences literature.
4.2
Managerial Implications
The understanding of the study offers implications for the managers, primarily those involved in managing its social media marketing campaigns. First, this study informs marketers to understand future experiences within the purchase journey. The term has been used, but the concept has not been studied more carefully, and limited literature supports this term. This finding will help marketers to be more focused when planning appropriate social media activities, taking into account the context of the purchase journey. For instance, managers should create more alluring and engaging stimuli such as text, images, videos, and live streams on their social media brand pages with a clear focus, pleasing brand experiences to create for their targeted customer segment, and inviting the customers to be unthinking to repost or co-create the activities. Customers should value the content from the brands’ social media page, unconsciously allowing customers to remember, fantasise, and imagine what they will experience in the future throughout the purchase journey. Thus, these outcomes intend to notify marketers to strategically plan and manage their social media marketing activities due to their significant role in determining consumer responses and providing learning opportunities. Second, understanding the social media generational effect in planning and executing effective marketing strategies in social media is much useful and required (Zollo et al., 2020). The study distinguishes these two sub-groups in the social media platforms, contributing to the learning activities from the social media content. Social managers need to plan and design social media marketing campaigns cautiously, not only for the brands themselves, thus persuading customers to have the intention to repost and share what they have learned from the past. Due to that, this chapter suggests that social media managers develop engaging content for customers at a higher level. The meaningful and unique brand experience resulting from high engagement efforts towards social media marketing activities may subsequently develop consumer responses towards the brand.
4.3
Limitations and Further Research Possibilities
In the era of Industry 4.0 Technologies where the Internet of Things (IoT) is the growing trend, marketers need to respond faster to the possible touchpoints and social media activities that will significantly benefit the firm’s economy of scale. Although the human experience has been studied for hundreds or thousands of years, the field of future experience within the customer journey context provides less evidence. It is a relatively new ‘greenfield’ area for future research. From the adopted customer journey model that underpinned the conceptualisation, the future experience loop is not incorporated. Thus, empirical stands need to test the framework in
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future research. Second, it is worth investigating and testing the term in the external environment context that involves myriad touchpoints during the purchase journey and experience in the store.
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The Impact of Virtual Interactivity on Shopper Behaviour Meera Dulabh, Delia Vazquez, Daniella Ryding, Alex Casson, and Myriam Caratù
Abstract
The objective of this chapter is to contribute to the understanding of consumers’ levels of interactivity based around the ‘Online Store Environment Framework’. To this aim, the study has adopted a qualitative and quantitative methodology combined with a neuromarketing test: to measure engagement in 3 distinct surveys within three different samples made up of UK female shoppers aged 18–30. In this study, electroencephalography (EEG) has been used to monitor the cerebral activity of a smaller sample whilst interacting with an online fashion retailer (ASOS.com). A theoretical framework has been designed, and a Structural Equation Model (SEM) has been used to statistically confirm it. SEM results reveal strong associations to a video task demonstrating arousal and absorption as well as a social media task showing absorption. Further, the EEG data—related to engagement and emotions—have been tested with ANOVA and correlations. Findings suggest that browsing a website does not necessarily require high levels of attention, while the participation to social media elicits high levels of emotion. Within them, interaction with videos has stimulated high levels of engagement. Thus, suggesting that social media and video content combined in the form of live
M. Dulabh University of Manchester, Manchester, UK D. Vazquez (✉) · D. Ryding Department of Materials, University of Manchester, Manchester, UK e-mail: [email protected]; [email protected] A. Casson Department of Electronic and Electrical, The University of Manchester, Manchester, UK e-mail: [email protected] M. Caratù Faculty of Economics, UNINT– Università degli Studi Internazionali di Roma, Rome, RM, Italy e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Brandstrup et al. (eds.), The Garment Economy, Springer Texts in Business and Economics, https://doi.org/10.1007/978-3-031-33302-6_22
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selling platforms are most advantageous to consumers evoking emotion and engagement leading to purchase/re-visit intention. The relevance of this article lies on its originality: for the first time, a pure-play fashion retailer has been analysed with both traditional and neuroscientific methods. Findings have implications on the managerial side, as they address emerging future virtual shopping in the metaverse to which there is likelihood of consumers buying more fashion products in the digital world compared to the real world. Keywords
Consumer engagement · Interactivity · Online retail websites · Electroencephalography · Neuromarketing
1
Introduction
Online retailing has grown exponentially over the last two decades, (Mintel Reports, 2021a, b). 2020 was a unique year for the retail sector as the COVID-19 pandemic forced many non-essential stores to close. This closure of stores accelerated online sales by 46.9% making up 27.5% of all retail sales (Mintel Reports, 2021a). Before the acceleration to online shopping due to the pandemic, consumers also agreed with the statement that ‘Growth in online shopping is responsible for stores closing’ which lends further support for the surge of e-commerce usage for consumers leading to a greater reliance on online shopping (Mintel, 2018; Mintel Reports, 2021a). Retailers who have been more active online such as Boohoo or ASOS have benefited from the shift to buying online (Mintel Reports, 2021c). 40% of consumers enjoy clothes shopping online meaning that shoppers will turn to e-commerce options even if they don’t have a specific need (Mintel Reports, 2021b). Sales have increased within fashion apparel, occupying 53% of sales among 16- to 24-year-old females thus supporting the emerging trend of shopping through social media platforms with the younger Gen Y and Z generations also known as ‘sellsummers’ (Mintel Reports, 2013, 2021a; Mintel, 2018). Additionally, social media is a tool that comprises at least 3.8 billion users worldwide in 2022, with 200 billion users using it per day for business reasons (Ric & Benazić, 2022). Among social media platforms, Instagram is specific for photo and video sharing (stories) popular for connecting content via hashtags and appropriate for fashion marketing (ShaneSimpson et al., 2018). The growth of social interactivity online has allowed brands to gain a deeper understanding of consumer’s needs, by listening and communicating directly with them (Caratu et al., in press). Some scholars (Išoraite, 2016) have recognised that quite a few elements of website interactivity—such as keyword search and personalisation—have a significant impact on consumer satisfaction. Other academics (Currim et al., 2015; Noci, 2018) testimony that neuromarketing and some of its tools (EEG, eye-tracking, etc.) are the best methods to understand how
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Fig. 1 Online Store Environment Framework (OSEF) Re-drawn based upon Manganari et al. (2009)
this satisfaction occurs in consumers’ brains, body and behaviour, since today brand experience has become no more physical but phy-gital (physical and digital). This blend of physical and physiological for brand experience can otherwise be viewed as utilitarian and hedonistic (Hirschman & Holbrook, 1982; Mehmetoglu & Engen, 2011), because it involves both our physical emotions and brain activity. As online shopping increases, the demand for meeting consumer needs with convenience (utilitarianism) and experiential (hedonism) online experiences also seems to increase (Bui & Kemp, 2013). Sensorial elements such as light, music, sound, layout, touch, smell and interaction with other shoppers or staff members in physical retail stores are elements known to evoke positive emotion leading to positive consequences such as purchase intentions (Kotler, 1973). To date, exact sensory elements from a physical store are not present in online stores, instead interactivity with the real-time continuous feedback (Hoffman & Novak, 1996) between a computer and user is one way to currently re-create sensory and emotional experiences (Huang, 2003). Popular interactive elements ‘Virtual Atmospherics’ (colour, text, fonts), ‘Virtual Theatrics’ (animation, videos, multimedia), ‘Virtual Layout and design’ (menu formats) and ‘Virtual Social Presence’ (web counters, social media) have been characterised by an ‘Online Store Environment Framework’ (OSEF) devised by Manganari et al. (2009), represented in Fig. 1. The abovementioned elements are typically measured via the StimulusOrganism-Response (S-O-R) framework, which have been traditional marketing frameworks for measuring emotional states to stimulus of shopping environments to see if they cause approach and withdrawal (Mehrabian & Russell, 1974). Traditional marketing literature reports emotion from visual appearances of atmospherics (Fiore & Kim, 2007); however, engagement is an alternative way to measure behaviour to these environments which houses cognition, behaviour and emotion (CBE) rather than just emotion on its own (Hollebeek et al., 2014). This scope is in line with marketing literature concerning consumer engagement in social media: the CBE model, by Hollebeek et al. (2014) (a construct implemented in marketing theory with relevant declinations—like those of Van Doorn et al.
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(2010)—which has been evidenced to contain cognitive, emotional and behavioural components that constitute to a Cognitive Behavioural Engagement framework); thus, it makes sense to use the CBE to measure engagement to online interactive elements characterised by the OSEF for this research. As well as measuring engagement via the CBE traditional marketing frameworks, engagement can also be measured in the brain. To measure this variable, the present study has adopted a neuromarketing technique, using the measurement of electrical brain activity known as the EEG (electroencephalogram) with Davidsons model of asymmetry harnessing the approach/withdrawal algorithm to measure pleasantness and Pope et al.’s (1995) engagement algorithm to measure engagement. Thus, the main aim of the neuromarketing test has been to explore the impact of consumer engagement to interactive features in online fashion shopping environments (social media and videos) by measuring brain responses. This is of particular interest since—although there is evidence of successful experiments in neuro-retail (neuromarketing applied to retail) for physical shopping environments (Cherubino et al., 2017)—there is currently a gap in research when it comes to measuring behaviour to online shopping environments. This study sheds light on this by providing useful insights to retailers, practitioners and (neuro) marketers on how to design effective engaging retail websites.
2
Background: Literature Review
The in-store experience post-Covid-19 era There is no doubt that the retail industry has transformed into a digital world especially within the last few years to which the pandemic has accelerated this evolution (Ranjan & Read, 2016). After the outbreak of Covid-19, many retailers have faced difficult challenges in interacting with their consumers on-site. In Italy, for instance, severe social and economic measures were adopted to keep most workers safe (Baldwin & Di Mauro, 2020), including locking down several industrial sectors (Barbieri et al., 2022). The social distancing measures not only impacted employees, who were under risk of infection while selling the products (Koh, 2020; Fernandes, 2020), but also consumers. A recent survey (Richards & Rickard, 2020) shows how people will be more prone nowadays to buy in the technology-driven point of sales, such as in those supermarkets where technology can allow social distancing (e.g. Amazon Go) or online.
2.1
Online Fashion Brands
Keeping social distancing and reaching a wider target audience could be why many stores have decided to go online, or many brands to sell their labels through websites like Zalando or ASOS. Not by chance, ASOS navigated the unprecedented challenges during the Covid-19 pandemic by growing total sales to 19%, which means £3263.5 M—an increase of £109.0 M on the previous year (ASOS, 2020).
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Instant gratification, fast communication and co-creation characterise the brands that stand out compared to those that do not (Ranjan & Read, 2016). To stand out, brands must interact with consumers in new ways, one way to do this would be product story telling where the brand and consumer can interact personally. An example of this comes from Cherubino et al. (2017) where people in a supermarket were more likely to memorise and buy fruit/vegetables after an interaction with farmers in person who told them the story of the products. This just shows how instrumental face-to-face product storytelling is to consumers’ decision making when purchasing products.
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Multisensory Features and Neuro-retail
Neuro-tools can bolster our comprehension of how humans experience various physical servicescape elements, such as sounds, taste, touch, smell and visual aspects, as well as their digital counterparts (Bolton et al., 2018). The emergence of neuromarketing as a technology-driven tool for service design has been recently explored by Verhulst et al. (2020). They emphasised the importance of multisensory environments in which humans are exposed to various cues. Neuro-tools may help us disentangle which elements have the largest impact on consumer behaviour with emphasis to the emotional journey. Paired up with in-store scents, lighting or sound we can further our understanding about how emotions interact in a multisensory experience. Furthermore, EEG equipment can be used in combination to show the effects of emotions, attention and cognition. One such example relates to how cognitive load can influence the breadth of visual attention in the search process (Wang et al., 2014). The use of objective indicators such as eye trackers allows to better capture the multitude of stimuli. In addition, thanks to the technological progress and the development of innovative solutions applied to neuroimaging, they are increasingly less invasive and wearable devices (Di Flumeri et al., 2019) and their value is related to the accessibility, the time of analysis, the costs of both the equipment and the personnel time and the portable nature (Herrera et al., 2012). Conversely, other neuro-tools such as functional Magnetic Resonance Imaging (fMRI) investigate specific physical cues such as those which stimulate reward areas in the human brain. Martinez-Levy et al. (2022) also confirm that the integration of EEG with an eye-tracker and heart rate monitor to measure cognition and emotion was successful in finding empathy to charity adverts. Marín-Morales et al. (2018) further validate this point in that they discovered that mental effort and an emotional index comprising of galvanic skin response, heart rate monitoring and EEG to product placement in music videos are high compared to videos without it. EEG Interactivity assessed with technology-driven methods therefore becomes a key trend for service marketers that needs to be explored further.
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Online Interactivity in Retail
Online shopping cart abandonment reflects the act of leaving a product in an online shopping cart without completing the purchase and has increased by 95% since the advent of the pandemic. The reason for this can be due to the website not matching consumer needs, price differences, bad reviews, or confusing website design (Wang et al., 2022). Thus, interactivity on shopping websites can help to boost sales. According to Kim and Nihem (2009), websites that provide useful information and an interactive medium help consumers to purchase, attract and retain. In fact, financial data has shown that technological innovation on luxury fashion websites determines the ‘winners’ from the ‘losers’. In other words, personalised interactive experiences with functional benefits formulate positive attitudes with consumers when they shop online. Online interaction is important especially for keeping up with technological advancements in the era of Web 3.0 otherwise known as the metaverse to which the crossover between physical and digital worlds leads to new levels of interactivity (Kshetri, 2022). Instagram is a social media platform with interactive tools such as ‘likes’, ‘commenting’, ‘stories’, ‘reels’, ‘lives’ and ‘hashtags’, etc. This makes communication with other users or even brands easy as it is direct (Ric & Benazić, 2022). Bozkurt et al. (2021) confirm that when consumers perceive a brand to be highly interactive, they are more likely to purchase a product or positively influence their family or friends towards that brand. Kim et al. (2021) lend support for technological advancements in online shopping interactivity as they found perceived usefulness and perceived enjoyment present when browsing a VR Ikea store thus creating positive behavioural intentions. In the same vein, as the metaverse is now becoming parallel to the real world, more individuals will increasingly re-create their real lives in digital formats. Some brands such as Fabricant studio, Nike, Adidas, Gap, Gucci, etc. allow consumers to co-create and purchase digital clothing which can be bought via cryptocurrency or alongside physical products from their virtual stores. Nonetheless, VR retail is now a new format to purchase in an omnichannel way alongside physical stores (Dwivedi et al., 2022). With all of this in mind, the new hi-tech shopper needs to be emotionally engaged too, and engagement usually goes through interaction with consumer service staff, which is hard to keep when going online.
2.4
Engagement from a Marketing Perspective
With all of this in mind, it makes sense in this study to examine pure-play retailers such as ASOS with engagement which involves Cognition, Behaviour and Emotion (3 variables of the CBE model). Figure 2 is adapted from Hollebeek et al. (2014) which visually depicts from their framework the multi-faceted nature of consumer engagement. Here, we have just drawn out the cognitive, emotional and behavioural aspects of this.
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Fig. 2 Re-drawn CBE Framework, by Hollebeek et al. (2014)
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Engagement from a Neuroscientific Perspective
As well as engagement being a key topic in marketing literature, in neuromarketing literature there have been some studies that investigate engagement with EEG, especially in media and online shopping interactive environments. Table 1 represents a summary of the most significant ones, which used different formulas and devices. Engagement occurs in the front of the brain otherwise known as the prefrontal cortex. The prefrontal cortex plays a role in affective behaviour and judgement, lesions to this area result in impairment of executive functions such as decision making, organisation and planning (Afifi & Bergman, 1998). Neuroimaging studies have shown higher engagement level processes to be associated in the frontal part of the brain involved in emotion and cognition as well as the temporal part of the brain involved in accessing memories with the consensus being, the more engaged a consumer is, the more likely they are to draw from memories (Fugate, 2007). Davidson’s model of motivation proposes that the brain is divided into both the approach (left side of brain) and withdrawal (right side of brain) (Davidson, 1998). Davidson et al. (1990) discovered differences between positive and negative emotions associated with pleasure and withdrawal and found that happiness was activated in the left side of the brain the most. The levels of Frontal Alpha Asymmetry (FAA) between the different sides of the brain are considered as a consistent index of approach activation (Schmeichel & Demaree, 2010). Additionally, approach/withdrawal (or pleasantness) is an emotional neuromarketing index based on the idea that there is a left-right asymmetry of the frontal electroencephalography (EEG) signals (Davidson et al., 1990). HarmonJones (2003) suggested that relatively greater activity in the left frontal region is
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Table 1 Engagement with EEG: neuromarketing literature review. (Alpha = 8–12 Hz, Beta = 12–25, Theta = 4–8 Hz range. NB: some studies may use slightly different bounds for the frequency bands)
Author McMahan et al. (2015)
Pope et al. (1995)
Type of engagement Engagement in gaming
Algorithm(s) Frontal Theta/ Parietal Alpha; and Beta/(Alpha + Theta)
EEG device Emotiv
Frequency band/ channels Measured in AF3, AF4, F3, F4, F7, F8, F5 and F6
Adaptive automation with a visual tracking task
1/Theta; and Beta/(Alpha + Theta)
Biopac EEG100A
Measured in Cz, Pz, P3 and P4
–
Beta/(Alpha + Theta)
–
Engagement in online news reading
Frontal alpha asymmetry (FAA). Frontal alpha in the left hemisphere and frontal alpha in the right hemisphere
Emotive
Measured in Cz, T5, P3, Pz, P4, O1 and O2 Measured in FC3, F3 and F7 (left) and FC4, F4 and F8 (right)
Findings Engagement levels increased during gaming ‘death’ events compared to general game play events 1/Theta yielded the highest index of engagement. 200 samples per second Closed loop method enabled an index of engagement EEG as well as entropy analysis revealed motivational components of emotion associated with engagement. Negative emotion evoked behavioural avoidance
associated with either positive emotional experience or the motivational drive to approach an object; and vice versa, greater activity in the right frontal region of the brain is associated with the motivational drive to avoid an object or a stimulus (in this case, an advertisement). The formula for Approach-Withdrawal (AW) is given by Coan and Allen (2004) as Emotion = log√ðRight AlphaÞ - log√ðLeft AlphaÞ
ð1Þ
Asymmetry scores for emotional processing was conducted by subtracting the natural log of left hemisphere alpha power from the natural log of right hemisphere alpha in the brain. It must be noted that when measuring emotion in the brain with these algorithms, a negative scenario would expect a negative emotion/negative
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Fig. 3 Engagement areas in the brain and corresponding EEG channels. Brain picture taken from https://publicdomainvectors.org/ under copyright free CC0 licence
result. However, in the context of information interaction, people who consume both positive and negative information could be equally engaged—even if engaged in a negative way (Arapakis et al., 2014). This, therefore, leads researchers to conclude that future research on user engagement should apply an approach/avoidance model of motivation rather than the more commonly used bi-factorial model of emotions (Arapakis et al., 2014). The brain default network lends support for activation when participants are not focused on tasks demanding attention which can constitute to disengagement or mind wandering/boredom (Greicius et al., 2003). The nucleus accumbens (NAcc) is a key node in the brain related to reward processing and this triggers approach behaviour (Knutson & Cooper, 2005). Figure 3 summarises parts of the brain associated with engagement. From the diagram mainly the front and back part of the brain is activated when looking at interactive media.
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Neuromarketing and Behaviour
As previously mentioned, electroencephalogram (EEG) is a non-invasive method for monitoring, recording and analysing neural activity in the brain. Electrodes attached to the head detect the electrical fields associated with brain activity (Casson et al., 2018). Attention is found in the frontal and visual areas evidenced when reading news articles (Arapakis et al., 2014) and when looking at luxury products (Goto et al., 2017; Pozharliev et al., 2015). Positive arousal (alertness) in the front and left hemisphere of the brain is evidenced when watching movies in the cinema (Barnett & Cerf, 2017), and approach behaviours are evidenced in the left hemisphere of the brain during group interactivity such as sending tweets during a live show (Dmochowski et al., 2014). The application of EEG, combined with survey-based studies, is a growing area in marketing research. Plassmann et al. (2015) purport that this combination allows for the implicit measurement of physiological processes thus providing insights into individual differences. EEG, combined with other traditional market research techniques, can uncover processes that consumers are
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not consciously aware of, thereby providing deeper insights into emotion and potentially, predictive behaviour (Pozharliev et al., 2015). Traditionally, engagement has been measured in marketing research using Likert scales (O’Brien & Toms, 2010), but usually there is no unified measurement. In the same vein, engagement measurements in EEG research are limited to education and video gaming literature (Fredricks et al., 2004; Brennan et al., 2014).
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Neuromarketing and Online Shopping
Since online retailing has increased exponentially within the last decade (Dannenberg et al., 2020; Pantano et al., 2022; Roggeveen & Sethuraman, 2020) and websites are becoming more interactive as technology advances, it is important for retailers’ strategies to consider the concept of interaction. Rubab et al. (2018) note that online shopping is growing rapidly ‘which can be riskier than brick & mortar shopping, because in an online shopping context, atmospherics are subsumed in the computer boundary. So far little is known about how this crossing point affects consumers’ purchase intention’. But as these decisions can be subconscious, retailers will benefit from using biometric measurements for emotion and engagement. Only a handful of EEG studies report online shopping behaviour. Yılmaz et al. (2014) measured behaviour via preference of shoes with ‘likes’ or ‘dislikes’ using an EEG to which they found that females took longer to decide between 6 photographs of high heeled shoes. This concept postulates that the more time we spend looking at an object means that we are more likely to click on that object which is similar to how customers click on clothing items they like on a virtual catwalk (Atalay et al., 2012). Liang et al. (2021) used survey and EEG methods to 8 shopping websites in China, they found that websites with better quality created better flow experiences which in turn had positive effects on user satisfaction.
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Research Methodology
Research methodology suitable to measure variables in the context of this research include surveys and neuro-retail experiments. Surveys allow large sample sizes which can be evaluated to validate a theoretical framework via Structural Equation Modelling (SEM) analysed in SPSS and AMOS. In contrast EEG can provide higher sensitivity to the phenomena, allowing to obtain statistically significant effects even with a smaller sample size (e.g. collecting data and analysing it with MATLAB) (Vozzi et al., 2021). The two approaches can thus provide complementary information (Martinez-Peñaranda et al., 2013). Questionnaires and interviews are the tried, proven and well-accepted methodology for understanding consumer behaviour. Combining traditional marketing measures with EEG will provide less interruption and can be measured directly rather than relying on what subjects tell us of what they are thinking (Sheth, 2011).
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Fig. 4 Examples of the protocol for three survey tasks
The target demographic for both studies are female UK consumers, with online shopping experience aged 18–30. The website ASOS (https://www.asos.com) was used for the tasks in the study. All procedures were approved by the University of Manchester Research Ethics Committee, application number 15351.
3.1
Study One: Measuring Consumer Responses with Surveys
Participants have been recruited through a company ‘Dynata’ via purposive sampling. Three separate surveys have been administered which are related to the ‘Virtual Atmospherics’ (N = 261), ‘Virtual Theatrics’ (N = 266) and ‘Virtual Social Presence’ (N = 264) tasks. Surveys have been formed via a website called ‘Survey Gizmo’. All surveys contained 38 questions (see appendix for these questions together with the original source of them). They contain single select answer options for demographic topics and Likert scale options for behavioural topics with clickable hyperlinks directed to the task to perform. The protocol participants underwent via survey is shown in Fig. 4 which demonstrates the three separate surveys used with a different sample of participants. All surveys contain the same questions but with the relevant hyperlink directed to that task. The Virtual Atmospherics task involves the respondent browsing for at least 5 ‘Jackets’ on ASOS and adding these to their basket, tallying up their spend in pounds (£). The Virtual Theatrics task involves the respondent visiting Facebook ASOS video page and watching a short number of videos. The Virtual Social Presence task three involved the participant to log into their Instagram account if they had one and participate with ASOS Instagram page by liking, commenting, sharing and reading comments on that page. After each task, participants then answered questions about their experience of that task.
3.2
Study Two: Measuring Physiological Responses with EEG Data
This study has used purposive and snowball sampling to recruit (N = 21) participants.
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Fig. 5 Protocol Screens
Figure 5 shows the protocol for the EEG study, which follows the same pattern as the survey protocol whereby each experiment had three tasks ‘Virtual Atmospherics’ (browsing the ASOS website for jackets), ‘Virtual Theatrics’ (watching ASOS catwalks on the jackets they chose from the ASOS website and ASOS YouTube content), ‘Virtual Social Presence’ (participating in the ASOS Instagram page interacting with likes, comments and sharing). The total experiment lasted for 70 minutes, including electrode set-up and removal time. In this, participants spent on average 8 minutes viewing stimuli in each of the categories. In between every task, baseline engagement and emotion were measured for 30 seconds with a blank screen in order to capture a neutral baseline activity in the brain before the next task began. Figure 6 shows how this experiment was set up. We looked at EEG frequency bands Beta/Alpha + Theta with Theta/Alpha on frontal midline and parietal locations, and Theta on frontal locations. While performing the tasks, the participant was wearing an EEG cap with 12 electrodes (actiCHamp, Brain Products, Germany).
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Browsing Task
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Fig. 6 The experimental set-up for this study
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Hypothesis Development and Theoretical Framework
Literature exploring online engagement between retailers and consumers is limited and somewhat disjointed, in this study is comprised of four key areas: (1) online shopping environments, (2) consumer engagement frameworks, (3) multi-method studies with EEG and surveys, (4) engagement measurements (scale items and algorithms) analysed in parallel. We decided to combine these elements as a new theoretical framework to make them less disjointed and usable for online environments. Our rationale above shows that we grouped involvement as antecedents of consumer engagement (according to the CBE framework, in Fig. 2) and sub-grouped them in three categories—according to the OSEF, Virtual Atmospherics, Virtual Theatrics and Virtual Social Presence shown in Fig. 1. Afterwards, we developed several hypotheses (Table 2) which was to be conducted via survey methods first to confirm our theoretical framework. These survey results informed the EEG hypothesis (Fig. 7).
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Table 2 Survey hypotheses for this study Interactivity Virtual atmospherics
Hypothesis number H1 H1a
H1b Virtual theatrics
H2 H2a H2b H2c H2d
Virtual social presence
H3 H3a
H3b
Hypothesis There is a high positive level of involvement when browsing a website Participants who are more involved whilst browsing involvement when browsing a website exhibit high levels of focused attention of a positive nature There is a link between focused attention and purchase intention of a positive nature when browsing a website There is a high level of involvement of a positive nature when watching a video Participants who are more involved whilst watching a video exhibit high levels of pleasure of a positive nature. Participants who are more involved whilst watching a video exhibit high levels of arousal of a positive nature. There is a link between pleasure and re-visit intention of a positive nature when watching a video There is a link between arousal and re-visit intention of a positive nature when watching a video There is a high level of involvement of a positive nature present when participating in social media Participants who are more involved whilst participating in social media exhibit high levels of absorption of a positive nature There is a link between absorption and re-visit intention of a positive nature when participating in social media
Fig. 7 The theoretical framework for this study. Adapted from various sources: Hollebeek et al. (2014), Van Doorn et al. (2010) and O’Brien and Toms (2010)
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Data Analysis and Results
5.1
Survey 1: Virtual Atmospherics Did Not Show a Positive Result with a Match to EEG Results To Be Fully Reported
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During the task of browsing an interactive fashion website these results did not match EEG results and the hypothesis was not fully supported, thus the SEM results will be mentioned only briefly here. These results suggest a mediocre model fit indicating that the overall model fit is sufficient (X2 = 758.71, df = 317, RMSEA = 0.73, CFI = 0.928, SRMR = 0.0746, NFI = 0.883. H1a which was INV → FOCUSED_ATTENTION and H1b which was FOCUSED ATTENTION → PURCHASE_INTENTION did not support the hypothesis and focused attention as a construct was removed from results and unreported. The reason behind this could be that complex websites are found to distract attention, when faced with an abundance of information, respondents are unable to absorb it implying that browsing ASOS could have been complex to use or had too many distractions (Huang, 2003). This is consistent with the information overload perspective which suggests a negative relation between complexity and deep attention (Hoffman & Novak, 1996; Hwang & Lin, 1999).
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Survey 2: Virtual Theatrics
These results suggest adequate model fit (X2 = 396.68, df = 201, RMSEA = 0.073, CFI = 0.947, SRMR = 0.0550, NFI = 0.914). Hypotheses supported were H2: presence of high involvement when watching a video, H2a: INV → PLEASURE and H2d: AROUSAL→RE-VISIT_INTENTION. Emotion did feature significantly in this model. Table 3 demonstrates that all paths in the model have significance demonstrated from the p-value. Significant relationships included PLEASURE→AROUSAL, INV → ABSORPTION, ABSORPTION → RE-VISIT_INTENTION. These novel relationships are visually displayed below in Fig. 8. Results show that regarding the emotion link, pleasure is associated with arousal (0.70***) and it is arousal that has a relationship with purchase intention (0.68***). Thus, the more absorbed a consumer is when watching a video, the more likely they will visit the ASOS video Facebook page again. The findings suggest that arousal acts as a heuristic cue for positive emotions and subsequently creates a positive relationship of pleasure (Bagozzi, 1997; Davis et al., 2008).
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Survey 3: Virtual Social Presence
These results suggest a good model fit as majority of thresholds were satisfied (X2 = 337.39, df = 142, RMSEA = 0.072, CFI = 0.956, SRMR = 0.0457, NFI = 0.927).
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Table 3 Significance between relationships for virtual theatrics Pleasure Absorption Arousal ReVisit_Intention ReVisit_Intention