New Technologies in Luxury Consumption: Evidences from Research and Implications for Marketing Strategies 3031260813, 9783031260810

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New Technologies in Luxury Consumption Evidences from Research and Implications for Marketing Strategies Andrea Sestino Cesare Amatulli

New Technologies in Luxury Consumption

Andrea Sestino • Cesare Amatulli

New Technologies in Luxury Consumption Evidences from Research and Implications for Marketing Strategies

Andrea Sestino Department of Business Studies University of Rome Tre Rome, Italy Department of Management LUISS Guido Carli University Rome, Italy

Cesare Amatulli Ionian Department of Law Economics, Environment University of Bari “Aldo Moro” Bari, Italy

ISBN 978-3-031-26081-0    ISBN 978-3-031-26082-7 (eBook) https://doi.org/10.1007/978-3-031-26082-7 © The Author(s), under exclusive licence to Springer Nature Switzerland AG 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. Cover pattern © John Rawsterne/patternhead.com This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Foreword

What does technology have to do with the consumption of luxury goods? We normally think of technology in functional or utilitarian terms. Technology helps us do things better than without it. We see technology in terms of usefulness, ease of use, efficiency, and scientific sophistication. Its value seems to be in facilitating the use of products that are associated with it. But luxury consumption resides more in the non-functional aspects of such goods, with the experience and expression of one’s ownership, self-­ identity, and status. Can technology and luxury be bridged? Sestino and Amatulli take the seeming incompatibility of technology and luxury goods and in the process show us that there are hidden synergies between them. Specifically, the authors demonstrate that technology and luxury goods complement each other and enrich consumer experience. Technology also is an unrealized tool of marketing that can be used to create demand for luxury items and gain competitive advantage over rivals. This book goes beyond theory and speculation to present the results of five empirical investigations. The authors show that certain consumer-­ related characteristics moderate the effects of the manipulation of communication focus (low vs. high technology orientation) on willingness to buy luxury goods. The consumer-related characteristics include status consumption, materialism, conspicuous consumption, need for uniqueness, and vanity, where these characteristics relate to internalized (style) versus externalized (status) approaches to luxury. The findings provide essential information for marketers with regard to market segmentation and advertising copy strategies to better reach consumers and induce them v

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to buy luxury items. The results also help marketers to better approach the fit between their products and technological communications in order to influence luxury consumption in effective ways. The Journal of Service Research recently unveiled the basic role of emotions undergirding consumer responses to artificial intelligence marketing tools. Basic emotions, self-conscious emotions, and moral emotions all play unique roles in the consumption of luxury brands that we are only now learning about. Such emotions as pride, envy, regret, joy, delight, anger, sadness, and fear and anxiety have special functions in luxury decision-­making. At the same time, complex structures of emotions, in conjunction with cognitive and social variables, influence luxury consumption. Luxury brands are prone to exhibit brand love, brand hate, and brand coolness in ways that interface with technology and enrich buying, using, and disposing of luxury brands. Sestino and Amatulli launch us on this exciting pursuit of luxury consumption with a rich and foundational perspective for research and practice in this area. New Technologies in Luxury Consumption by Sestino and Amatulli represents an original perspective in a very important direction for future research in luxury goods at both the consumer and managerial levels. Their approach is grounded in the best of theory and methodology and pushes the field very positively in new endeavors. ROSS Business School University of Michigan Ann Arbor, MI, USA November, 2022

Richard P. Bagozzi

Acknowledgments

The authors would like to thank the managers who contributed to the professional content of this book by providing the business case of their companies, including their perspective on the technology implementations in said businesses. Specifically, we thank Ms. Francesca Tosi and Mr. Michele Fioravanti from Pomellato, Ms. Barbara Manto from the Rome Cavalieri Hotel, Ludovic du Plessis from Telmont Champagne, Mr. Michele Paolini and Ms. Cristiana Rivolta from Caffè Florian, and Rolf Blakstad from Blakstad Architects & Design. A sincere appreciation for their kind support also goes to Mr. Shawn White, at Fallen Apple, for his editorial work on the text and to Ms. Liz Barlow, at Palgrave Macmillan, for her constant assistance and patience. Finally, we want to thank Prof. Stefano Puntoni for the time he spent in writing the precious and qualified preface for this book.

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Contents

1 Introduction  1 2 The  Issue of Integrating New Technologies in Luxury Marketing: A Literature Review  7 3 Integrating  Smart Objects and Artificial Intelligence in Luxury Fashion Retail: The Role of Consumers’ Status Consumption Orientation 55 4 Integrating  New Technologies in Luxury Hospitality Experiences: The Effects of Luxury Hotel Communication Focus (Traditionality vs. Modernity), and Consumers’ Materialism 67 5 Integrating  Smart Objects and Artificial Intelligence in Real Estate: Luxury Real Estate Communication Focus (Prestigiousness vs. “smartness”), and the Role of Consumers’ Conspicuous Consumption Orientation 79 6 Integrating  Blockchain Technologies in Wine Industries: The Role of Perceived Self-Service Technologies Quality and Consumers’ Need for Uniqueness 91

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7 Integrating  New Technologies in Aesthetic Clinical Surgery: The Role of Consumers’ Vanity103 8 Conclusions115  Appendix A: Survey Related to the Study in Chap. 3 “Fashion”119  Appendix B: Survey Related to the Study in Chap. 4 “Tourism & Hospitality”123  Appendix C: Survey Related to the Study in Chap. 5 “Real Estate”127 Appendix D: Survey Related to the Study in Chap. 6 “Food”131  Appendix E: Survey Related to the Study in Chap. 7 “Health & Wellness”135 Glossary139 Index143

About the Authors

Andrea  Sestino  is Adjunct Professor of “Competitive Strategy” at the LUISS Guido Carli University in Rome Research Fellow in “Business Management and Marketing” at the University of Rome Tre; Research Assistant in “Technology and Innovation Governance” and “Management and Innovation in Healthcare Services” at the Catholic University of Sacred Heart, Rome, Italy. Andrea holds a Ph.D. in “Business Management and Marketing” at the University of Bari Aldo Moro, and a M.Sc. in “Business Management” at the Sapienza, University of Rome. He has been also Expert Collaborator for the Cabinet of the Italian Minister of Economic Development, in fields related to Artificial Intelligence, Internet of Things applications, and business digitalization, and R&D Specialist in the field of applied industrial research for business digital transition in several private and public research projects. He has written a monograph entitled Non-fungible Tokens (NFTs): Examining the Impact on Consumers and Marketing Strategies, edited by Palgrave Macmillan, and several articles in international peer-reviewed journals, such as Technovation, Technology Analysis & Strategic Management, Technological Forecasting and Social Change, Journal of Learning and Intellectual Capital, Journal of Financial Service Marketing, International Journal of Cultural Heritage & Sustainable Development, International Journal of Healthcare and Pharmaceutical Marketing, British Food Journal, Current Research in Environmental Sustainability, Journal of Sport & Tourism, International Journal of Electronic Trade, Italian Journal of Marketing, Italian Journal of Management, Italian Journal of Marketing, SN Business & Economics, Psychological Reports, xi

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International Journal of Marketing Studies, Technology in Society, Global Business Review. Cesare Amatulli  is Associate Professor of “Marketing” at the University of Bari “Aldo Moro,” Italy. He is Adjunct Professor of “Branding”, “Brand Strategies in Fashion and Luxury Industries” and “Marketing” at LUISS Business School, Rome. He has also been Adjunct Professor of “Marketing and Business Strategies” and “Advanced Marketing” at the University of Milan, Italy. He taught at the EMC Business School, Paris, and at the International University of Monaco (IUM), Monte Carlo. He has been visiting researcher at the Ross School of Business, University of Michigan, USA, and at the University of Hertfordshire, UK. His research focuses on consumer behavior and is based on the methodology of behavioral experiments. His main fields of research are luxury consumption, fashion marketing, sustainable consumption, sustainable luxury, older consumers and cognitive age, branding, new technologies, the role of emotions, word-of-mouth, and tourism marketing. He has written three books in the field of marketing and several articles in major international scientific journals such as the Journal of Consumer Research, International Journal of Research in Marketing Journal of Retailing, Journal of Business Research and Psychology & Marketing.

List of Figures

Fig. 2.1 Fig. 2.2 Fig. 2.3 Fig. 3.1 Fig. 4.1 Fig. 5.1

Fig. 6.1 Fig. 7.1 Fig. 8.1

The five phases of our LDA-based literature review 23 Network visualization of the topic modeling 24 Word cloud simple analysis among the five emerging topics 24 The proposed conceptual model: perceived store technological content and the moderator role of status consumption orientation60 The proposed conceptual model: hotel communication focus (traditionality vs. modernity) and the moderating role of consumers’ materialism 72 The proposed conceptual framework: luxury real estate communication focus (prestigiousness vs. smartness) and the moderator role of consumers’ conspicuous consumption orientation84 The proposed conceptual framework: perceived self-service technology quality and the moderator role of consumers’ need for uniqueness 95 The proposed conceptual model: clinic robotization level and the moderating role of consumers’ vanity 107 Marketing approaches at different levels of internalized/ externalized luxury and at different levels of the communication focus on technology 118

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List of Tables

Table 2.1 The resulting contributions grouped by the five topics discovered (k = 5)23 Table 3.1 Results of the regression analysis (Model 1, Hayes); Study 1, Chapter 3 62 Table 4.1 Results of regression analysis (Model 1, Hayes); Study 2, Chapter 4 75 Table 5.1 Results of regression analysis (Model 1, Hayes); Study 3, Chapter 5 86 Table 6.1 Results of regression analysis (Model 1, Hayes); Study 4, Chapter 6 98 Table 7.1 Results of regression analysis (Model 1, Hayes); Study 5, Chapter 7 109

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CHAPTER 1

Introduction

Abstract  This chapter briefly describes the goal of this book and the fascinating issue of successfully integrating new technologies in luxury industries. Indeed, despite the promising opportunities deriving from new technologies along the service delivery processes, or in the proposition of products characterized by a higher technological content than in the past, by considering the luxury industries and luxury consumers’ peculiarities, the union between the two worlds has been long debated in literature and by practitioners. The luxury industry may now embrace new technological innovations to deliver more value to consumers and to expand audience bases. In the chapter the structure of the book is highlighted, with the literature review and the five experimental studies, together with the main theoretical and managerial implications. Keywords  Luxury consumption • Luxury experiences • New technologies • Innovations • New technological innovation • Luxury industries • Digitalization

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Sestino, C. Amatulli, New Technologies in Luxury Consumption, https://doi.org/10.1007/978-3-031-26082-7_1

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1   The Fascinating World of Luxury and New Technological Innovations This book is intended for both experts and newcomers who want to understand the use of new technologies in the strange and fascinating field of luxury consumption. Advanced technologies represent the latest chapter in luxury’s winding history, although the essential emphasis on the humanities persists. Luxury has always characterized humanities, even though we could say that the “modern” concepts of luxury experience and luxury products have been developed during the period of Louis XIV in France. Indeed, the period between 1660 and 1715 under Louis XIV was a defining moment for France luxury: A national French personality emerged that gave the country a sort of monopoly on culture, style, and art de vivre. Interestingly, it was a deliberate choice of King Louis XIV to make France and Paris the world’s leading reference for elegance and luxury. Then, in the following centuries, luxury became associated with fashion (through the first main couturiers such as Charles Frederick Worth) and then industrialization (thanks to the Made in Italy phenomenon). Only in the 1980s did the LVMH Group apply a marketing approach to luxury, establishing the concept of luxury brands that require “luxury management” (Cavender & Kincade, 2014). Broadly speaking, the idea of luxury is associated with the concepts of craftsmanship, quality, elegance, expensiveness, uniqueness, and prestige (Chevalier & Mazzalovo, 2021). But nowadays, the main asset of a luxury business is its brand. In simple terms, branding represents an opportunity to create and communicate value to a firm’s final customers (Kotler, 2020). Thus, a strong luxury brand is one that conveys high value and is globally recognized. As a consequence, luxury marketing is effectively brand development that involves managers at all levels. Put differently, luxury marketing is a managerial process that seeks to understand customers’ perceptions and behaviors. It aligns with the well-established assumption that luxury is a subjective category that depends on people’s psychological and cultural contexts. In short, there is no luxury if consumers do not perceive it. Against this background, managers must delve into the implications of technological advancements for their brand development. For years, luxury brand managers have adopted a skeptical posture toward technology, largely due to concerns over its effects on uniqueness and prestige. However, the proliferation of the Internet, social media, and e-commerce

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has created a wide, digitally oriented market that is impossible to ignore (Okonkwo, 2010). Therefore, it is important for marketers to not only embrace new technologies but also learn how to assess and control them. More than their peers in other sectors, luxury brand managers must consider the “right way” to use or integrate technology within the luxury branding process. Given the wide array of advanced technologies—including the Internet of Things (IoT), smart objects, Artificial Intelligence (AI), Virtual Reality (VR), and Augment Reality (AR)—there is a high risk that embracing any given technology will dilute the brand. Luxury firms have to evaluate not only the technology’s implications for their products, but also how adoption would position them relative to the mass market (which is broadly viewed as the opposite of luxury). Consequently, this book offers a first discussion on how luxury brand developers can approach such advanced technologies. Specifically, it offers an overview of these technologies’ features, their potentiality, and, most importantly, their effectiveness in attracting and retaining customers. Indeed, managers need to deeply understand their target customers and align those technological features with the characteristics that are most relevant to luxury consumption. For this reason, we incorporate the so-called dichotomy of luxury into “externalized luxury” and “internalized luxury” (Amatulli & Guido, 2012; Guido et  al., 2020). The former refers to luxury consumption mainly driven by ostentation, high prices, status symbols, prestige, materialism, and conspicuousness, while the latter mainly refers to individual style, quality, culture, and personal values. Importantly, our efforts here involve a transversal approach, wherein we consider consumer behavior and technology management across several sectors (fashion, tourism, real estate, food, and wellbeing/healthcare) that are (or will be) key for the luxury industry.

2  Luxury and New Technologies: A New Promising Match? By considering the above premises, this book underlines the idea that luxury brand developers need to better understand their customers before developing and implementing new strategies based on advanced technologies. While new technologies may seem to represent an indisputable added value, they have to be meticulously adapted to customers—whose

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experiences, perceptions, and feelings are, after all, more critical in the luxury market than other contexts. In sum, the relationship between new technologies in luxury marketing represents a delicate issue for luxury brand developers. Technology must be adapted to luxury—must complement and enlarge, rather than define and restrict, luxury. This strategy captures the paradox of luxury marketing (Jaggi & Singh, 2022): Brands must filter the disruptive nature of advanced technologies through a sustainable integration in order to preserve “luxury consciousness”: the prominence of heritage, the central role of creativity, the evergreen human content, even the sense of morality and authenticity. These values are not always consistent with the machine learning processes of Artificial Intelligence or the network seriality of the Internet of Things, which are often the opposite of luxury exclusivity and uniqueness. Digital abundance may give rise to new kinds of luxury experience, but will always be at odds with the foundational idea of luxury. Thus, if managers want to preserve the core meanings and values of luxury, they must first differentiate the needs and goals that characterize luxury consumers. New technologies can then be tailored to those goals in order to personalize the luxury offering and experience. Managers must maintain a commitment to the traditional facets of luxury—such as craftsmanship and human touch—while also embracing the sheer potentiality of new technologies. They must see innovation as an improvement upon, rather than a destruction of, what has come before. In this way, they can enhance their customers’ experience and heighten the value delivered by the brand.

References Amatulli, C., & Guido, G. (2012). Externalised vs. internalised consumption of luxury goods: Propositions and implications for luxury retail marketing. The International Review of Retail, Distribution and Consumer Research, 22(2), 189–207. Cavender, R., & Kincade, D.  H. (2014). Management of a luxury brand: Dimensions and sub-variables from a case study of LVMH. Journal of Fashion Marketing and Management, 18(2), 231–248. Chevalier, M., & Mazzalovo, G. (2021). Luxury brand management in digital and sustainable times. John Wiley & Sons.

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Guido, G., Amatulli, C., Peluso, A.  M., De Matteis, C., Piper, L., & Pino, G. (2020). Measuring internalized versus externalized luxury consumption motivations and consumers’ segmentation. Italian Journal of Marketing, 2020(1), 25–47. Jaggi, S., & Singh, G. (2022). The paradox of luxury in digitalization. In Handbook of research on the platform economy and the evolution of e-commerce (pp. 416–434). IGI Global. Kotler, P. (2020). Marketing and value creation. Journal of Creating Value, 6(1), 10–11. Okonkwo, U. (2010). Beyond the Internet: Mobile technology and innovation for luxury. In Luxury online (pp. 278–306). Palgrave Macmillan.

CHAPTER 2

The Issue of Integrating New Technologies in Luxury Marketing: A Literature Review

Abstract  The rapid diffusion of new technological innovations resulted in lack of knowledge about how luxury and technology may be successfully combined. This chapter aims to provide clarity over the phenomenon of new technological integration in luxury through a comprehensive and systematic literature review. The study considers a corpus of 1196 original contributions through the combination of two established machine learning algorithms (LDA and hierarchical clustering). The analyses sheds light on a structured classification of the various streams of current research and a list of promising emerging trends in the field of fashion, tourism, real estate, and food, together with a focus on minor topics such as luxury wellness, healthcare, automotive, and the most prominent consumers-­ related variables to be investigated. Keywords  Luxury marketing • New technologies • Technology management • Artificial Intelligence • Internet of Things • Machine learning • Blockchain • Data analysis

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Sestino, C. Amatulli, New Technologies in Luxury Consumption, https://doi.org/10.1007/978-3-031-26082-7_2

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1   Introduction Integrating new technologies into luxury experiences is a pressing challenge for marketers and managers. Despite the seeming distance between the worlds of luxury and technology may seem, their combination represents an immense opportunity. As background, it is important to note that the market revenue for luxury amounted to $349.10  billion in 2022, with an expected annual growth rate of 3.72% (CAGR 2022–2027). The luxury fashion segment is the largest, with a market volume of $109.70 billion in 2022. The biggest portion of these revenues is generated in the United States (US $74,670.00m in 2022). Importantly, a recent report (Deloitte, 2022) proposed that 20.8% of total revenue will be generated through online sales or the use of digital tools by 2022—while this figure was partially spurred by the COVID-19 pandemic, it is only expected to rise. Consumers’ fascination for the consumption of rare and unique goods and experiences has fueled the growth of the luxury industry worldwide. Luxury, an ever-evolving concept, has various interpretations in the current scenario. Luxury consumption is often associated with concepts related to elegance, refinement, superfluous, and expensive products (Chevalier & Mazzalovo, 2012), among others. For some, brands that evoke exclusivity (Phau & Prendergast, 2000) define luxury, while for other goods and experiences whose ratios of functional utility to price are low and the reasons of intangible and situational utility to price are high (Nueno & Quelch, 1998) symbolize luxury. Luxury products and luxury experiences are different from non-luxury ones, by the extent to which they exhibit a distinctive mix of three important dimensions of instrumental performance: functionalism, experientialism, and symbolic interactionism (Ko, Costello, & Taylor, 2019). The global luxury goods industry—which includes drinks, fashion, cosmetics, fragrances, watches, jewelry, luggage, and handbags—has been on an upward climb for many years (Donzé & Fujioka, 2018). Luxury goods manufacturers meet consumer demand by focusing on brand, aesthetics, quality materials, superior craftsmanship, and pricing to transform everyday objects into items useful to express their status, that is individuals’ behavioral tendency to value status and acquire and consume products that provide prestige to the individual (O’Cass & McEwen, 2004). Statistics show that the value of the personal luxury goods market worldwide was 283  billion euros, also explaining how,

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despite the pandemic, the luxury market was not particularly affected by any contraction. In this evolving scenario, the integration of new technologies represents a promising business opportunity for the luxury market. Such technologies include the Internet of Things (IoT), smart objects, Artificial Intelligence (AI), Virtual Reality (VR), and Augmented Reality (AR). Indeed, the pervasive digitalization of business processes, together with the transfer of several business activities to online spaces, has enabled unprecedented opportunities for luxury marketers and managers. On this point, we want to distinguish between the terms “digitization” and “digitalization”: The former reflects the process of converting analogical forms to digital ones, while the latter captures the consequences of such a conversion (Ritter & Pedersen, 2020; Vrana & Singh, 2021). With technology “altering the nature of competition resulting in a new competitive landscape” (Ritter & Pedersen, 2020, p.  182), researchers and practitioners alike are looking at how to embrace these advancements to create new value and experiences for consumers (Business of Fashion, 2021). While new technologies could be a fundamental driver of growth and a pathway to novelty, scholars caution that they could also create new meanings and desires around consumption (Seo & Buchanan-Oliver, 2019), likely changing how consumers interact with luxury environments (Kapferer, 2014). That said, research on this topic is still disorganized. Thus, this chapter aims at systematizing the knowledge around the relationship between technological integrations and luxury consumption. Moreover, we outline the gaps in research and highlight the luxury fields that merit investigation, seeking to understand variances in consumer behavior in this domain. The chapter is organized as follows: Sect. 2 introduces the current issues surrounding technology integration in luxury consumption. It also explains the key enabler technologies (or KETs) in this domain: namely, micro and nanoelectronics; nanotechnology and industrial biotechnology; advanced materials; photonics; and advanced manufacturing technologies that seek to increase industrial innovation in order to address societal challenges (European Association University, 2018). In Sect. 3, we discuss the adopted methodological approach, which encompasses the text-mining and topic-modeling procedures. In Sect. 4, we present the most relevant findings from our literature review by focusing on new technology integrations in five promising domains: luxury fashion, tourism, food, real estate, and what we call miscellanea (covering wellness, healthcare, and

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automotive). The last section offers some conclusions and discusses the limitations of this review, followed by an overview of the experimental studies presented in the proceeding chapters.

2  Theoretical Background 2.1   The Relevance of New Technologies and the Digital Transformation Generally speaking, firms can generate greater value both for themselves and for their final consumers (Johannessen & Olsen, 2010; Kiel et  al., 2020) by properly integrating new technologies into their business process. This reengineering operation—the act of recreating a core business process with the goal of improving product output, quality, or cost—typically involves analyzing company workflows and for the purpose of changing or eliminating them (Goksoy et al., 2012). Firms may also redesign their end-products or service offerings to accommodate new technologies (Sestino et al., 2020) and attract new customers. There are multiple reasons to integrate new technologies: They can enrich the design stage and give consumers unique and surprising products and experiences (Bitner & Wang, 2014; Meuter et al., 2010; Sestino et al., 2020); they can be used to capture and analyze data from online interactions for strategic and planning purposes (Erevelles et al., 2016; Xu et  al., 2016); and they can bolster communication strategies through online digital marketing tools such as social media (Stephen, 2016; Tiago & Veríssimo, 2014). Thanks to their advantages, digitization and the resulting tools have transformed both the dynamics of global markets (Batat, 2019) and the traditional consumer experience (Athwal et  al., 2019; Hwang, 2004). Nowadays, competitive firms are those that can blend digital and physical channels rather than just maintain a simple online presence (e.g., on e-commerce platforms or social media, which have utility, but appear insufficient; Chaffey et al., 2019). To clarify, the literature has explained that firms must deeply rethink their business models to integrate digital processes along the entire value chain through appropriate technological grafts (Chaffey & Smith, 2017). These insights are compatible with the Marketing 5.0 paradigm (Kotler, 2021), which is defined as a complex set of available technologies used to support, help, or imitate humans to create, communicate, and increase the value of the customer experience as a

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whole. This marketing approach combines the human centricity of Marketing 3.0 (which affirms consumers’ centrality to marketing strategies; Kotler, Kartajaya, & Setiawan, 2019) with the technological potential of Marketing 4.0 (which imposed a partial translation of business activities to an online context; Dash et  al., 2021; Kotler, Kartajaya, & Hooi, 2019). This marketing approach has become necessary as technologies have evolved: No longer are they limited to surfing the net via smartphones or even exploiting large amounts of online data (so-called Big Data; Erevelles et al., 2016); now, advanced technologies interact with one another with the aim of assisting final consumers and reshaping business processes. Examples of such innovations include Big Data, Artificial Intelligence (AI), natural language processing, robotics, Augmented Reality (AR), Virtual Reality (AR), Internet of Things (IoT), and the blockchain (Kotler et al., 2021; Loonam et al., 2018; Westerman & Bonnet, 2015). 2.2   New Technologies as Key Enablers Factors of Digital Transformation As more and more consumers seek engaging experiences and personalized products, there is an opportunity for brands to leverage new technologies to distinguish themselves (Athwal et  al., 2019; Sülük & Aydin, 2019; Urdea et al., 2021). According to the literature, new technological integrations may increase consumers’ satisfaction with (e.g., as in Chen et al., 2009; Pantano & Viassone, 2015) or acceptance of (e.g., as in Amatulli et al., 2022; Chen et al., 2011; Morgan-Thomas & Veloutsou, 2013) a new experience. Other technologies may suit strategies aimed at increasing brands’ value perception (e.g., as in Niculescu et al., 2019; Ramaswamy & Ozcan, 2016). Technological integrations depend on the concept of enabler technologies: The “equipment and/or methodology that, alone or in combination with associated technologies, provides the means to generate giant leaps in performance and capabilities of the user” (European Commission, 2020). These technology sets provide the means to create lasting progress while inducing radical transformation in a business and its value proposition (Lyakh & Swain, 2019). Among the enabling technologies, these so-called key enabling technologies (KETs) are defined as tools, devices, and resources interconnected with each other and with the Internet. With KETs, companies can

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improve their processes to create added value and drive innovation, and thereby generate competitive advantages (European Commission, 2020). Below, we provide an overview of the most relevant KETs for the luxury domain. 2.2.1 Big Data Big Data (hereafter, BD) refers to the huge amount of structured (e.g., documents, files) and unstructured (e.g., images, video) data generated by and collected through devices and software that are continuously interconnected via the Internet. BD reflects the large and complex data sets resulting from these new sources (De Mauro et al., 2018; Erevelles et al., 2016). More specifically, BD refers to data that contain greater variety (in terms of sources) while having increasing volume (in terms of the sheer amount of generated data) and velocity (in terms of the speed of data generation). BD derives from numerous sources of different natures (De Mauro et al., 2015; Wamba et al., 2015), which can be generally categorized as: (1) commercial transaction systems (e.g., e-commerce or social commerce; Akter & Wamba, 2016); (2) customer databases (e.g., as in companies’ CRMs; Del Vecchio et al., 2021); (3) mobile applications and social networks (e.g., software run on mobile devices such as smartphones, smartwatches; Erevelles et  al., 2016); (4) scientific research repositories containing primary and secondary data; (5) data generated by machines and sensors in real time used in IoT-based environments (e.g., as for those intelligent objects used to restructure both the production processes and the service delivery processes; Marjani et al., 2017; Sestino et al., 2020). An example of this latter is the case of self-service technologies (i.e., an approach where consumers may access resources to find solutions on their own without requiring assistance from a service representative; Bitner, 2001). The resulting data can then be analyzed in its raw form within Big Data systems or processed using data mining tools or special software. The goal is to uncover anomalies, patterns, and correlations within large data sets in order to predict outcomes for marketing purposes (Wamba et al., 2017). 2.2.2 Internet of Things The Internet of Things (hereafter IoT) consists of an ecosystem of intelligent objects capable of communicating with each other via software agents through the Internet. More specifically, IoT reflects the network of

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those physical objects that are imbued with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the Internet (e.g., smartphones, voice assistants, home automation agents, and so on; see Sestino et al., 2020 for a review). The IoT architecture is typically based on three basic elements: (1) the Things, in terms of devices that are physically or wirelessly connected to a network; (2) the Network, which connects all the “things” to the Internet; and (3) the Cloud, which encompasses the servers of a remote data center that store the generated data (Yaqoob et al., 2017). IoT ecosystems now include several widespread devices such as smartphones, smart refrigerators, smartwatches, smart fire alarms, smart door locks, smart bicycles, medical sensors, fitness trackers, smart security systems, and sensors that may be connected to industrial production plants (Madakam et al., 2015). 2.2.3 Artificial Intelligence Artificial Intelligence (hereafter, AI) reflects the ability of a computer to control another computer, device, or robot for the purpose of performing tasks that usually require human intelligence and discernment. AI generally depends on deep data prediction and recognition analysis (see Sestino & De Mauro, 2021 for a review). AI is now present in many business applications such as online shopping and advertising (Kumar et al., 2019). In the retail domain, AI can provide consumers with personalized recommendations based on their previous searches, purchases, or online interactions (Shekhar, 2019). Similarly, AI agents are now included in smartphones, and in IoT software more generally, to provide relevant and personalized services (Zhou et al., 2019). Similarly, the combination of AI and IoT has led to voice assistants (VAs), “software agents that run on purpose-built speaker devices or smartphones”. VAs (e.g., Siri, Alexa) have become ubiquitous thanks to their ability to answer questions, provide recommendations, and help users organize their daily routines. Encouraged by these developments, companies and governments are continuing to explore the potential of AI. For instance, AI is being incorporated into language translation software for both written and spoken text (Ali, 2016). In the field of infrastructure, AI-powered smart objects can learn from individuals’ behaviors to autonomously save energy, while developers of smart cities hope to regulate traffic to improve connectivity,

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reduce traffic jams (Gunge & Yalagi, 2016; Kumar & Qadeer, 2012), and potentially enable self-driving cars (Hong et al., 2021). In the healthcare domain, AI may serve several functions, such as helping to recognize infection from computerized tomography scans (Yu et  al., 2018). For instance, as the COVID-19 pandemic has raged, AI has predicted contagion diffusion by analyzing thermal imaging in airports and elsewhere (Vaishya et al., 2020). 2.2.4 Virtual Reality and Augmented Reality Augmented Reality (hereafter AR) uses new technologies to overlay digital elements, sounds, or other sensory stimuli on the physical world (Rauschnabel et al., 2019). Virtual Reality (hereafter VR), by contrast, is completely virtual: Users wear a headset device—tethered to a computer or game console with a powerful graphics processor (GPU) and CPU (Alcañiz et  al., 2019)—and exert control over a 3D-modeled fictional reality (Bonetti et al., 2018; Sestino, Guido, & Peluso, 2022). Firms can greatly extend the immersion of VR by incorporating inertial sensors, accelerometers, joysticks, and wearable devices (i.e., gloves and visors) (Burke, 2018). Both AR and VR augment individuals’ experiences by blending the real and the digital worlds (Rauschnabel et al., 2019). Examples of such applications can be found in entertainment (e.g., games development; Gómez et al., 2019); education and healthcare (e.g., learning a task, such as surgical operations, within a semi- or fully virtual space; Mantovani et  al., 2003); the automotive sector (e.g., improving individuals’ driving abilities); and even tourism (e.g., allowing people to virtually visit a destination such as a historical site; Sestino, Mantini, & Amatulli, 2022; Yung & Khoo-Lattimore, 2019). Furthermore, the combination of AR and VR is enabling the development of the metaverse (Mystakidis, 2022), which we will explain in detail below. 2.2.5 Blockchain The blockchain is a series of secure and encrypted blocks that are linked through a network (see Sestino, Giraldi, et al., 2022 for a review). Thus, the blockchain appears as a shared, immutable ledger that facilitates the process of recording transactions and tracking assets (Xu et  al., 2019). Because of its structure, any change in the blockchain requires the simultaneous modification of all the blocks in all the places where they are widespread and the simultaneous modification of the links between the blocks.

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Theoretically, a block is a set of aggregated and encrypted data that can be associated with one or more transactions (Gorkhali et  al., 2020). Technically, each block contains a pointer (a “hash”) that can connect it to the previous block in the chain, as well as assign a time stamp (Chi & Zhu, 2017). Assets linked to the blockchain network may be tangible (e.g., houses, cars, cash, land) or intangible (e.g., intellectual property, patents, copyrights, branding). Those assets can also be fungible (e.g., traded for cash) or non-fungible (e.g., traded for original digital items). There are several business applications for the blockchain, but the most relevant ones relate to the worlds of finance (e.g., cryptocurrencies and cryptovalue; White, 2015), secure certification (e.g., in public administration, legal and certificate registers, or supply chain tracking; Xu et  al., 2019), and the emergent domain of non-fungible tokens (NFTs; Sestino, Guido, & Peluso, 2022). In many of these cases, the most apparent opportunity involves certifying stored data for currencies, documents, or digital objects (Xu et al., 2019): This so-called cryptography involves a series of secure communications and exchange techniques that allow only the sender and intended recipient of a message to view its contents (Zhai et al., 2019). Cryptography is used to ensure secure transactions for cryptocurrencies: exclusively digital currencies that lack a central regulatory authority (Phillip et al., 2018). One of the most promising opportunities for the blockchain is NFTs, which are certified digital objects that can be offered, sold, and purchased in the virtual world. NFTs can now contain any type of digital content— whether music, video, clothing, and images (Sestino, Guido, & Peluso, 2022). Due to the secure nature of blockchain technology, each NFT is unique and irreplaceable: The owner of an NFT has exclusive rights to its content. 2.2.6 Metaverse The metaverse is a buzzword right now, but it is a candidate to become one of the most important enabling technologies of the near future. The metaverse represents a melding point between the physical and digital worlds, reflecting a “connected economy” that will create convergence between computers, IoT, mobile devices, visual implants, AI, and the cloud (Cheng et  al., 2022). In short, the metaverse is a parallel reality hosted in virtual spaces (Mystakidis, 2022): With this technology, individuals can enter the digital world through a virtual identity (avatars) and engage in a range of tasks such as socializing, shopping, and sports. The

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metaverse is expected to become an important enabling factor for several industries such as healthcare, automotive, and education. While the technologies and techniques presented above have apparent social and economic value, determining their significance from a marketing standpoint requires analyzing the specific application context (i.e., the business sector). In this book, we focus on the domain of luxury: an important context where such technologies must be integrated very strategically. Because the customer experience is fundamental to luxury, managers must embrace new technologies on the basis of specific knowledge about their customers. Additionally, the centrality of brand value in luxury means that managers must incorporate new technologies while preserving their brand identity and reinforcing the customer experience. In the next section, we describe the main characteristics of the luxury market and of luxury consumption more generally. 2.3   Luxury Market and Luxury Consumption The luxury business is a significant economic engine for several countries. Despite a contraction in 2020 due to the pandemic, the luxury market grew 13% to 15% in 2021 to €1.14  trillion. Thus, the luxury industry seems to be returning to pre-COVID levels, with experts expecting a 6% per annum growth rate between 2022 and 2026. Notably, today’s luxury market encompasses various sectors: from clothing, cars, and cosmetics to wines, hospitality, and other services. Because of its growth potential and sectorial breadth, the luxury market has often been described as “recession proof” and thereby attracted many brands. However, the luxury market is currently facing important changes that both academics and managers are trying to understand. First, there is a general shift in luxury consumption: from tangible products to intangible experiences, especially within more mature markets (Guido et al., 2020). Indeed, today’s luxury is represented just as much by “experiential luxury” (e.g., golf clubs, hotels, and cruises) as by “traditional” product categories (e.g., clothing, watches, and jewelry). Granted, personal luxury goods still represent the core of the global luxury market, in terms of revenues, but there is rising interest in luxury cars, premier hospitality, fine wines, designer furniture, yachts, and fine art (Bain & Company, 2021). This shift in luxury consumption has compelled a reimagining of the marketing approach: from a “traditional” approach—that mainly

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underlines the conspicuous aspects of luxury consumption—to a more “experiential” framework (Batat, 2019). In this evolving scenario, brand developers need to reorient their marketing approach to better match their target customers’ characteristics. To aid this effort, researchers have focused on uncovering the different drivers of luxury consumption. Undoubtedly, luxury consumption flows from positive emotions and memorable experiences, and is particularly associated with pride and personal rewards. For instance, Dubois, Jung, and Ordabayeva (2021) highlighted three pathways that shape consumers’ status-driven desire for luxury: biological, socio-psychological, and structural factors. Regarding the biological drivers, they underlined the effect of testosterone, the social context (Otterbring et  al., 2018), and the arousal produced by another’s presence on the emotional value of luxury products (Pozharliev et  al., 2015). Regarding the socio-­ psychological drivers, literature shows that conservatives who are high in socioeconomic status exhibit a greater desire for luxury products and brands, and that these people seek luxury because it enables them to vertically differentiate from others in the social hierarchy (Kim, Park, & Dubois, 2018). Regarding structural factors, scholars have emphasized that greater income inequality can heighten individuals’ sensitivity to status signals (Walasek, Bhatia, & Brown, 2018). Similarly, Wiedmann et al. (2009) delineated the value-bases segmentation of luxury consumption. Specifically, they shed light on the four latent dimensions behind luxury purchases: financial, functional, individual, and social. The “financial” dimension refers to monetary aspects such as price, resale cost, discount, and investment; the “functional” dimension refers to quality, uniqueness, usability, reliability, and durability; the “individual” dimension is about materialism, hedonism, and self-identity; and finally, the “social” d imension refers to the conspicuousness and prestige that allow consumers to be recognized within a social group. The bulk of the psychological and marketing literature focused on luxury consumption supports an essential dichotomy: luxury consumption that is driven mainly by either status (i.e., externalized luxury) or style (i.e., internalized luxury) (Amatulli & Guido, 2012; Guido et al., 2020). Specifically, externalized luxury treats the associated products—characterized by conspicuousness and ostentation—as status symbols and positional goods (Fionda & Moore, 2009; Truong, 2010; Wu et  al., 2017) that allow consumers to better define or change their social status (e.g., O’Cass & Frost, 2002). By attempting to imitate people they admire and flaunt

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their own purchasing power, externalized consumers seek to achieve their desired social position (Mason, 2001). Likewise, the same consumers crave exclusivity in order to stand out from the masses, and they are often willing to pay high prices to align themselves with the elite (Veblen, 1989). In short, the externalized approach mainly revolves around the dimensions of ostentation (Mason, 2001; Nueno & Quelch, 1998; Vigneron & Johnson, 1999), elitism, emulation, social position (Amatulli & Guido, 2012), and materialism (Belk, 1985; Phau et al., 2001). By comparison, consumers mainly driven by the internalized approach tend to buy luxury to satisfy their individual style, experience intimate emotions, and ultimately reinforce their inner self (Amatulli & Guido, 2012). As such, these consumers pay particular attention to quality and craftsmanship when buying luxury products. They also emphasize brand authenticity and consistency with their personal values. As a consequence, these consumers are attracted more by brands’ stylistic identity than by high prices. Because ostentation is rarely their objective, internalized consumers are typically characterized by a low need for status (Han, Nunes, & Dreze, 2010). In general, such consumers can be classified as “consumers in the know”: more mature buyers who understand the nuances of luxury and recognize luxury products even without brand logos (Guido et al., 2020). This distinction between internalized and externalized luxury is crucial to marketing because the two approaches require completely different marketing strategies. For instance, brands may emphasize products’ price tags and logo prominence for one group, while highlighting artistry or sustainability for the other (Han, Nunes & Dreze, 2010). Naturally, this distinction extends to how luxury brands should integrate and market new technologies. Certainly, the virtual world (e.g., the metaverse, social media, and gaming) will play “an increasingly relevant role in luxury brands’ value propositions” (Bain & Company, 2022). In fact, analysts expect the virtual world to represent 5–10% of the luxury market by the end of 2030 (Bain & Company, 2022). Therefore, luxury brand managers need to understand how to leverage advanced technologies in order to improve their relationships with customers. However, there are several hurdles here. A study from The Boston Consulting Group (2022) illustrates that consumers think that “luxury lags behind other industries when it comes to digital” and that the “digital experience is not on par with the in-store experience.” Additionally, it is becoming more expensive to build customer relationships: Customer

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acquisition costs doubled in 2021 and are expected to increase by 20% per year in the coming years. Interestingly, the same study underlined that “customers see potential in the metaverse,” especially among 18–34 year olds who think “the metaverse can replace social media.” NFTs are also gaining ground as an alternative to physical products. Despite marketers’ surging interest around the role of new technologies in the luxury business, the scientific research is still lacking. In this book, we want to introduce a new discussion that translates consumer behavior studies into insights for luxury brand marketers. To that end, we conducted several experiments aimed at connecting the luxury dichotomy to the integration of new technologies in the luxury business. Before that, though, we synthesized the current literature through a systematic review. The two research questions that guided said review are: RQ1: Which are the main topics related to new technologies and luxury consumption emerging from the most recent literature? RQ2: Which are the main issues requiring further investigation from a consumer behavior perspective? In order to address the two proposed research questions, we performed a literature review leveraging an original combination of established machine learning algorithms (Latent Dirichlet Allocation or LDA, and hierarchical clustering), thus providing the most human-significant topic structures on a list of 1196 considered research original contributions.

3   Methodology 3.1   Phase 1: Keywords Definition In line with previous systematic literature reviews (i.e., De Mauro et al., 2018; Sestino & De Mauro, 2021) and following both Guido et  al. (2018), and Tranfield et al. (2003), we began our analysis by defining a list of keywords related to both the luxury marketing field (i.e., as for “luxury,” “marketing,” “brand,” “luxurification,” “consumers,” “consumption,” “behaviour,” “status consumption,” “conspicuous consumption,” “unicity,” “materialism,” “vanity”) and new technologies (i.e., “new technologies,” “artificial intelligence,” “internet of things,” “iot,” “smart objects,” “blockchain,” “metaverse,” “virtual reality,” “augmented

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reality”). These keywords commonly reoccur in scholarly articles on luxury marketing consumption and new technologies published in the most important management and marketing journals. 3.2   Phase 2: Database Extraction and Querying After selecting the keywords, we launched a query on the Scopus database to extract those contributions and documents dealing with both new technologies and luxury consumption. We searched the paper’s titles and body for singular or joint uses of these terms into the papers’ titles, abstract, keywords, and body of the text. We considered the last decade (i.e., 2010–2021), along with some relevant contributions that appeared by the middle of 2022, in order to capture the most useful technology-related research. We only included English-written documents. A sample query with this approach was: “TITLE-ABS ((“Luxury consumption” or “artificial intelligence”) and (“business” OR “marketing”)) AND PUBYEAR > 2010 AND (LIMIT-TO (DOCTYPE, “ar”) OR LIMIT-TO (DOCTYPE, “cp”)) AND (LIMIT-TO( LANGUAGE, “English”)).” Limiting our search to April 2022, we extracted a list of 2212 published journal articles, book chapters, and conference papers. 3.3   Phase 3: Data Preparation After obtaining the dataset, we then looked for those contributions containing the full terms related to luxury and new technologies (by following our list of keywords) in the titles, which left a sample of 1196 articles. Next, we performed a preliminary data preparation using the Knime software for the purpose of applying the LDA technique by the software Knime (Qundus et al., 2021). First, we used the software to remove white spaces and punctuation from the documents. This left single-word tokens (save for compound words made with intra-word dashes). We then used Porter’s algorithm (1980), to turn all capital letters to lowercase and return the stem of each word with its suffix removed. Finally, we removed common stop words, articles, conjunctions, adverbs, and other non-relevant words (e.g., as those related to copyright information and years).

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3.4   Phase 4: LDA Once the dataset had been cleaned, we applied the LDA technique using the Knime software (Qundus et al., 2021). We chose the LDA technique because it provides a fruitful probabilistic model able to identify the thematic structure of a corpus of documents (Blei, 2012; Delen & Crossland, 2008). By following this approach, we could treat the input text as a collection of observations arising from a generative random process that includes hidden variables. Those variables reflect the topic structure of the documents and may define how the relative presence of words is linked with the topic dealt with in the text. By following such an approach each emerging topic is a probability distribution over terms within the vocabulary made of all the words present in the corpus. Therefore, every document in the corpus (each composed of multiple terms) will be associated with a mixture of k topics; the Dirichlet distribution is thus described by the following formula: K



x

i

i 1

 1 and xi  0i  1,K 



By using the LDA technique, we first obtained a human-­comprehensible number of emerging topics from the considered dataset: Despite the most suitable number of topics is obtained by the application of a text-mining algorithm, the topic validation is assigned to the researchers involved in the literature review. To clarify, the algorithm determines the number of topics, but researchers have to validate them (Blei, 2012; Steyvers & Griffiths, 2007). Secondly, LDA shows the topic proportion for every single document, resulting in a n × k matrix in which the coefficient n represents the number of documents included in the used dataset, while the coefficient n indicates the number of topics. Thirdly, the per-word topic assignment, which is the probability of the existence of each word within each specific topic. Finally, we also obtained the per-corpus topic distribution in order to highlight the overall popularity of each topic within the total set of documents being analyzed. Thus, by following a mixed approach based on Delen and Crossland (2008) and similarly to De Mauro et al. (2018), we had a human evaluator read both the list of topic keywords and consider the documents in the corpus

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displaying a high level of presence of each topic. From this, the evaluator deduced the conceptual content of the topic and assigned it an appropriate name. 3.5   Phase 5: Data Analysis—Emerging Findings and Topic Modeling By following the proposed methodology (see Delen & Crossland, 2008), we determined the number of final k topics by selecting the model capable of providing the most readable output. The researcher(s) evaluated the various agglomeration attempts in order to identify the most understandable one. We ran LDA for all values of k comprises from 6