Mass Customization and Customer Centricity: In Honor of the Contributions of Cipriano Forza 3031097815, 9783031097812

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Edited by Thomas Aichner · Fabrizio Salvador

Mass Customization and Customer Centricity In Honor of the Contributions of Cipriano Forza

Mass Customization and Customer Centricity

Thomas Aichner  •  Fabrizio Salvador Editors

Mass Customization and Customer Centricity In Honor of the Contributions of Cipriano Forza

Editors Thomas Aichner South Tyrol Business School Bolzano, Italy

Fabrizio Salvador Operations and Technology Management IE Business School IE University Madrid, Spain

ISBN 978-3-031-09781-2    ISBN 978-3-031-09782-9 (eBook) https://doi.org/10.1007/978-3-031-09782-9 © The Editor(s) (if applicable) and The Author(s), under exclusive licence 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 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 Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Professor Cipriano Forza

Foreword: The Academic Story of Cipriano

Late afternoon, June 1992, Monte Berico. There are only three people in the Operations Management Lab at the Institute of Management and Engineering: Cipriano, another Ph.D. student, and me. Cipriano is hunched over his keyboard. The data he’s working on for his doctoral thesis isn’t quite adding up the way he’d like it to. He’s been sitting there for weeks. His mobile rings and his eyes widen when he sees his wife’s name appear on the display: “Where are you?” “I’m … on the way home …” “You said you’d be back early!” Cipriano, abruptly jolted back into the real world, stands up and motions us—as we try to stifle our laughs—to be quiet: “I’ll be home in a few minutes.” He sits back down and continues to tap away at his computer, the phone call already a distant memory. Sometimes, a person’s passion for research is all-consuming. This comedic episode recurred on several occasions, each of which has been etched into my memory. His passion for study and research had taken hold of him definitively the year before when he had visited Professor Roger Schroeder at the Carlson School of Management, the University of Minnesota in August to work on the design of the international survey on WCM (World Class Manufacturing). The study, initially set to involve only Italy, the United States, and Japan, was later extended to other several countries to compare various companies’ practices and performance and to seek out the connections between managerial practices and company performance. vii

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Foreword: The Academic Story of Cipriano

In Minnesota, as Roger Schroeder would say, there are two seasons: winter and August. And so, it was that in the sweltering August heat, Cipriano opted to forego his non-air-conditioned quarters in the college, in favor of sleeping in the much cooler laboratory at the School of Management—with a somewhat precarious setup, perhaps, but near the computer, his inseparable work companion. I was introduced to Roger by Cipriano during a EurOMA (European Operations Management Association) conference that took place in the UK.  Roger later confided in me that he immediately understood that Cipriano was talented, competent, willing, rigorous, and reliable: in short, an ideal partner for the major international WCM project headed up by Roger. The project lasted many years and involved numerous researchers and professors, who were able to develop their skills in terms of method and content. That project gave rise to many important publications. Many Ph.D. students used the WCM data and its research methodologies in their training, as shown in part by their contributions to this book. Countless Ph.D. students of Cipriano now hold positions as professors or researchers in Italy and abroad, or major roles in important organizations. During the various phases involved in the WCM project as well as many other research projects, such as his contact with companies, collection and data analysis, and drafting of reports and publications, Cipriano showed an incredible ability to coordinate teamwork. Over time, we gained a deeper understanding of his qualities and values: his respect for people and the ideas of others, his ability to listen, and his dogged determination in defending his positions where their scientific importance demanded it. And we have always considered him a man of great rigor and method. During the 1990s and early 2000s, we often worked together. We went to international conferences where Cipriano usually presented his papers. It was during these conferences that I garnered a great deal of admiration and astonishment for this man, not only for his fluent English and clear way of presenting his ideas but also for his unrivaled ability to captivate and fascinate his audience as if he were an impassioned actor on the stage of a theater. The source of his boundless charisma is still a mystery to me, but it was unquestionably something completely spontaneous for him.

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After several years spent as a researcher, Cipriano became an associate professor in 1998. The competition took place at the Politecnico di Milano. There were nine professors on the committee in total, three of whom were former presidents of the Italian Association of Management and Engineering (AiIG). The rules at that time involved an examination of the applicants’ scientific qualifications and a university lecture on a topic drawn at random a mere twenty-four hours in advance. The candidates would spend those precious hours anxiously preparing the lecture. Cipriano arrived in Milan with two suitcases of books, as “you never know what topic they might choose.” On the day of the lecture, he made no mention of the night he had just had, but I could tell from his eyes that he had barely slept, instead of devoting himself to preparing for the test to make a good impression on the committee, and rightly so. He also spent three years teaching at the University of Modena and Reggio Emilia. There, too, his willingness to engage with the group and hardworking attitude was evident, as he demonstrated an inexhaustible commitment to research, teaching, and organization in our Department. The competition for full professorship came in 2005 and was held at the University of Bari, though the candidates themselves were not present and instead assessed based on their CV and publications. The competition rules were based on the candidates’ scientific qualifications using many indicators, including Impact Factor. To become a full professor, one must have what is known as “full scientific maturity.” The other candidates never stood a chance—all the indicators for Cipriano’s work were of the highest possible level. The other committee members asked me to pass on their warmest congratulations to the winner. It was a source of great satisfaction and pride for me. We have a saying at the university: “when you become a full professor, you can start to relax.” If there’s one colleague who can prove that wrong, it’s undoubtedly Cipriano. The “dance” continues (even though, as the years go by, he’s less likely to “tread the boards” anywhere) in his activities in the Department and international collaborations, one of particular note being his teaching of research methods at the European Institute for Advanced Studies in Management (EIASM). His commitment to teaching in the Department of Management and Engineering also remains strong, as he strikes up a special relationship

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Foreword: The Academic Story of Cipriano

with his students, eager to provide them with the stimulation and professional preparation they need to meet the challenges of work, life, and the wider world. He also brought an equal and unwavering level of commitment to his post as Director of the Ph.D. School. In recent years, he has cultivated some significant lines of research for which he has become an international point of reference, most notably the phenomenon of “mass customization,” which also appears in this book. While I may have offered a contribution to Cipriano’s growth and education over the years, I have also received a great deal in return from him, both as a person and as a scientist. For this, I am grateful to him. Roberto Filippini Emeritus Professor of Management and Engineering, Ph.D. supervisor of Cipriano Forza

Preface

Presentation This book honors the contributions and remarkable career of Cipriano Forza, Professor of Management Engineering at the University of Padova, Italy. He is a Member of the Scientific Committee of Academic Journal Guide (ABS), an Associate Editor of the Decision Sciences Journal, and a former Associate Editor of the Journal of Operations Management. As one of the world’s foremost researchers in the area of mass customization and operations management, Professor Forza published more than 200 scientific articles with over 10,000 citations on Google Scholar. For his groundbreaking work, he received several awards, including the Dr. Theo Williamson Award for Excellence (1997), best paper awards by Production Planning and Control (2005) and the Journal of Operations Management (2006), the Harry Boer Highly Commended Award (2016), and the EurOMA Fellowship Awards (2021). Besides being a successful researcher and popular university professor, Cipriano Forza is a wonderful individual, an inspiring mentor, and a fun person to be around. The individual stories written by his former Ph.D. students and found at the end of this book will provide the readers a unique glimpse at the life of a beloved supervisor and friend. The two editors of this book have completed their doctoral studies under Cipriano Forza’s supervision and wish to express their gratitude to xi

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their supervisor with this Festschrift. The fact that so many colleagues, friends, and former Ph.D. students answered the call to contribute to this edited book is proof of his reputation and degree of esteem in the scientific community.

Book Contents Leading researchers and practitioners that have been working with the honoree contributed a broad range of findings from conceptual and empirical research about mass customization and personalization to this book. The individual chapters take a customer-centric view on the challenges and opportunities of product and service customization from an operations management, information technology, entrepreneurship, marketing, and organizational perspective. The authors explore key ideas, current developments, as well as future research directions. The first chapter, written by Alessio Trentin and Fabrizio Salvador, conceptually investigates the potential of form postponement for improving a manufacturer’s sales performance depending on its customers’ interrelated preferences for customization and responsiveness. The chapter argues that form postponement can foster customer utility not only and not necessarily by ensuring the rapid delivery of many pre-specified product variants—as typically assumed by prior research—but also by providing customers more time to articulate their needs or by sparing them the trouble of forecasting how their needs will change during the product’s lifespan. A typological theory linking form postponement type, customer utility, and sales performance is hence proposed, which shows that the operations’ ability to apply form postponement can play a much more proactive role than implied by the existing literature in the definition of a manufacturer’s marketing strategy. In the second chapter, Aleksandra M. Staskiewicz and her co-authors Lars Hvam, Anders Haug, and Niels H. Mortensen discuss the role of stock keeping units management in product variety reduction projects. Specifically, the authors study why companies may fail to achieve

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financial benefits in attempts to reducing product variety by investigating an unsuccessful project at a global hearing healthcare company. Chapter 3, by Igor Kalinic, is about the consequences of the internationalization of production on small and medium enterprises’ competitiveness. The author conducts a case study using a mechanical company that offers customized products to international clients and established production subsidiaries abroad. Enrico Sandrin carries out a systematic literature review about inter-­ organizational enablers of mass customization in Chap. 4. By assessing a wide variety of publications, he reveals several interesting insights, such as that the focus in mass customization research is stronger on customers rather than suppliers, for example, in terms of customer integration rather than supplier integration. In his second contribution (Chap. 5), Fabrizio Salvador and his co-­ author Cipriano Forza—who was not aware that this work was going to be published in a book dedicated to himself—report the result of an international research project about the individual competences supporting the ability of a firm to customize efficiently its products. They investigate this topic through a multi-method design entailing 46 interviews to subject matter experts and a survey of 276 managers operating in companies that offer customized products. The study finds that people operating within an organization’s workflow contribute to reducing the efficiency-flexibility trade-off by supporting the execution of three tasks that cannot be fully codified “a-priori,” which the authors label prospecting, blueprinting, and patching. The sixth chapter is about online shopping preferences in mass customization. Paolo Coletti, Thomas Aichner, and Abdel Monim Shaltoni replicated a study from 2008 and compared some key customer perceptions and behavioral intentions with new data from 2021. The results include temporal, age, gender, and other comparisons. In contrast to the other contributions in this book, which are all authored by academic researchers, Chap. 7 was written by a serial entrepreneur and customization evangelist. Paul Blazek, founder and CEO of cyLEDGE Media, Europe’s leading research-driven customization experience agency, shows the evolution of product configurators and

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highlights some lessons that can be learned by focusing on particular customers’ needs. Chiara Grosso explains in Chap. 8 what role customer engagement plays in the online mass customization process. She proposes a conceptual representation of a social interactive feature design to take advantage of word-of-mouth effects and user interaction. The proposed features could result in several advantages, both for customers and mass customizers. Together with Michael Nippa and Amanda Brutto, Thomas Aichner explores a hot topic in Chap. 9 that influences many of today’s advertising decisions: racial diversity. Using a customizable product as stimulus, the authors conducted an online experiment to assess customer’s perceived product value and willingness-to-pay depending on the ethnicity of models used in the advertisement. Chapter 10, authored by Thomas Aichner and Minh Tay Huynh, provides a systematic overview of the central publications of Cipriano Forza. Through a bibliometric analysis, the readers receive an interesting insight into research topics, publication outlets, co-citations, and more. Zoran Anišić, Nenad Medić, and Nikola Suzić contributed a retrospective of the MCP-CE conference, whose scientific committee chairman is Cipriano Forza. This bonus chapter includes a historical overview on this very important bi-annual event that gave many researchers and practitioners a chance to connect with each other and to meet Cipriano Forza. Finally, we collected some personal stories and entertaining anecdotes from Cipriano Forza’s former Ph.D. students. Bolzano, Italy Madrid, Spain 

Thomas Aichner Fabrizio Salvador

Acknowledgments

This Festschrift would not have been possible without the contribution of the authors. In addition, several other people have helped to realize this book and make it a success. First and foremost, we are grateful to Professor Roberto Filippini, who supervised Cipriano Forza when he was a doctoral student. His contribution closes the circle and provides an exclusive view on the career and development of Cipriano Forza from being a Ph.D. student himself to becoming a professor and Ph.D. supervisor. Second, we acknowledge and appreciate the help of those who reviewed the single chapters or earlier drafts of the book and provided valuable feedback. Third, a special thanks goes to the photographer Tamás Thaler, who allowed us to use the snapshot of the honoree. Finally, we thank our universities for providing the needed support with regard to access to databases and other human or financial resources needed to complete this book. Associate Professor of Marketing Former Ph.D. student of Cipriano Forza Professor of Operations Management First Ph.D. student of Cipriano Forza

Thomas Aichner Fabrizio Salvador

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Contents

Part I Managing Mass Customization   1  Revisiting Form Postponement at the Operations-Marketing Interface: Form Postponement Types, Customer Utility and Sales Performance  3 Alessio Trentin and Fabrizio Salvador  The Role of SKU Management in Product Variety Reduction Projects 37 Aleksandra Magdalena Staskiewicz, Lars Hvam, Anders Haug, and Niels Henrik Mortensen  The Internationalization of SME Production: Organizational Challenges and Strategic Opportunities 61 Igor Kalinic  Interorganizational Enablers of Mass Customization: A Literature Review 85 Enrico Sandrin

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 The Ghost in the Machine: A Multi-­method Exploration of the Role of Individuals in the Simultaneous Pursuit of Flexibility and Efficiency101 Fabrizio Salvador and Cipriano Forza Part II Online Sales Configurators and Communication 149  Online Shopping Preferences in Mass Customization: A Comparison Between 2008 and 2021151 Paolo Coletti, Thomas Aichner, and Abdel Monim Shaltoni  Creating Customization Experiences: The Evolution of Product Configurators179 Paul Blazek  Enhancing Users’ Digital Social Interactions While Shopping via Online Sales Configurators211 Chiara Grosso  Impact of Racial Diversity in Advertising on the Perception of Mass-Customized Products by Consumers239 Thomas Aichner, Amanda Brutto, and Michael Nippa Part III Research, Publications and Engagement of Cipriano Forza 273  Bibliometrics and Citation Analysis of the Works of Professor Forza275 Thomas Aichner and Minh Tay Hyunh

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 Retrospective of the MCP-CE Conference in the Period of 2004–2020313 Zoran Anišić, Nikola Suzić, and Nenad Medić  Correction to: Mass Customization and Customer Centricity  C1 Alessio Trentin and Fabrizio Salvador Personal Statements by Former Ph.D. Students335 I ndex347

List of Contributors

Thomas Aichner  South Tyrol Business School, Bolzano, Italy Zoran Anišić  Department of Industrial Engineering and Management, Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia Paul Blazek  cyLEDGE Media GmbH, Vienna, Austria Amanda  Brutto Department of Communication and Economics, Università degli Studi di Modena e Reggio Emilia, Modena, Italy Paolo Coletti  Faculty of Economics and Management, Free University of Bozen-Bolzano, Bolzano, Italy Cipriano  Forza Department of Management and Engineering, University of Padova, Vicenza, Italy Chiara  Grosso Crisp Interuniversity Research Center for Public Services, University of Milano-Bicocca, Milano, Italy Anders  Haug Department of Entrepreneurship and Relationship Management, University of Southern Denmark, Kolding, Denmark Lars  Hvam Department of Management Engineering, Technical University of Denmark, Copenhagen, Denmark

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List of Contributors

Minh  Tay  Hyunh Faculty of Economics and Management, Free University of Bozen-Bolzano, Bolzano, Italy Igor Kalinic  European Innovation Council and SME Executive Agency, European Commission, Brussels, Belgium Nenad Medić  Department of Industrial Engineering and Management, Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia Niels  Henrik  Mortensen Department of Mechanical Engineering, Technical University of Denmark, Copenhagen, Denmark Michael Nippa  Faculty of Economics and Management, Free University of Bozen-Bolzano, Bolzano, Italy Fabrizio  Salvador Operations and Technology Management, IE Business School, IE University, Madrid, Spain Enrico  Sandrin Department of Management and Engineering, University of Padova, Vicenza, Italy Abdel Monim Shaltoni  College of Business, Alfaisal University, Riyadh, Kingdom of Saudi Arabia Aleksandra  Magdalena  Staskiewicz Department of Management Engineering, Technical University of Denmark, Copenhagen, Denmark Nikola  Suzić Department of Industrial Engineering, University of Trento, Trento, Italy Alessio  Trentin Department of Management and Engineering, University of Padova, Vicenza, Italy

List of Figures

Revisiting Form Postponement at the Operations-Marketing Interface: Form Postponement Types, Customer Utility and Sales Performance Fig. 1

Form postponement (FP) types and customer utility function

19

The Role of SKU Management in Product Variety Reduction Projects Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5

Decision steps in the SKU classification method. (Adapted from Van Kampen et al., 2011) Pareto analysis of products in the case company Process changes for a direct distribution to private label customers and centralized SKU numbering Three levels of product variety Implications for research and practice

42 46 48 52 53

The Internationalization of SME Production: Organizational Challenges and Strategic Opportunities Fig. 1

Research framework

66

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List of Figures

Online Shopping Preferences in Mass Customization: A Comparison Between 2008 and 2021 Fig. 1

Boxplots for customers’ willingness to customize a product online and age in 2008 and 2021

167

Creating Customization Experiences: The Evolution of Product Configurators Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9 Fig. 10 Fig. 11 Fig. 12 Fig. 13 Fig. 14 Fig. 15

Industry categories of the Configurator Database 185 Number of products per industry category in the Configurator Database 2019/2020 (n = 1400)186 Number of the most prevalent single products in the Configurator Database 2019/2020 (n = 1400)187 Percentage of responsive (device optimized) configurators by industry, 2016 and 2019/2020 190 Analyzed configurators by industry category 199 Count of responsive (device-optimized) configurators versus not responsive 200 Count of open navigation versus process navigation 201 Analyzed configurators by-product visualization style 201 Analyzed configurators by visualization technology 202 Analyzed configurators by available perspectives 203 Average data transfer size by visualization technology in megabytes204 Count of configurators offering one to five customization options, six to ten and more than ten options 204 Count of configurators with included checkout capabilities versus configurators without 205 Count of configurators with checkout capabilities across all industries excluding Motor Vehicles (n = 61)206 Count of configurators with live price updates versus configurators without 206

  List of Figures 

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Enhancing Users’ Digital Social Interactions While Shopping via Online Sales Configurators Fig. 1

The messy middle in customer journey. (Source: Our elaboration from Rennie et al., 2020) Fig. 2 The multi messy in the shopping via online sales configurators. (Source: Our elaboration from Rennie et al., 2020) Fig. 3 Dyadic interactions user/OSC. (Source: Franke et al., 2008) Fig. 4 Exemplification of connection modalities between OSCs and social software. (Source: Our elaboration) Fig. 5 Users’ need to interact with specific shopping advisors. (Source: Grosso & Forza, 2019) Fig. 6 Timing of users’ need for digital social interactions. (Source: Grosso & Forza, 2019) Fig. 7 Overview of a collaborative co-shopping feature. (Source: Kumar et al., 2016) Fig. 8 K-interactive feature invitation options Fig. 9 K-interactive feature invitation options Fig. 10 K-interactive feature integrated into OSC front end. (Source: Our elaboration)

217 219 220 222 226 226 229 230 231 232

Impact of Racial Diversity in Advertising on the Perception of Mass-Customized Products by Consumers Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6

Fictitious advertisement for customizable shampoo from Shampora with three White-skinned women as models (ad #1) Fictitious advertisement for customizable shampoo from Shampora with two White-skinned women and one Blackskinned woman as models (ad #2) Fictitious advertisement for customizable shampoo from Sambora with two Black-skinned women and one Whiteskinned woman as models (ad #3) Fictitious advertisement for customizable shampoo from Shampora with three Black-skinned women as models (ad #4) Boxplot for perceived functional value (quality perceptions) by ad version Boxplot for perceived emotional value by ad version

253 254 255 256 260 262

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Fig. 7 Fig. 8 Fig. 9

List of Figures

Boxplot for perceived social value by ad version Boxplot for willingness to customize by ad version Boxplot for willingness to pay a higher price by ad version

263 265 266

Bibliometrics and Citation Analysis of the Works of Professor Forza Fig. 1 Fig. 2

Search strategy and papers selection protocol The most influential documents by Professor Forza and the co-authors from bibliographic coupling Fig. 3 The most influential co-authors from bibliographic coupling Fig. 4 The most influential organizations affiliated with Professor Forza and the co-authors Fig. 5 Visualization of co-occurrences of keywords (all years) Fig. 6 Visualization of co-occurrences of keywords from papers published between 1992 and 2000 Fig. 7 Visualization of co-occurrences of keywords from papers published between 2001 and 2010 Fig. 8 Visualization of co-occurrences of keywords from papers published between 2011 and 2021 Fig. 9 Most frequent co-authors based on citation analysis Fig. 10 Map of theme clusters identified from co-citation analysis Fig. 11 Map of the most cited journals by the analyzed papers based on co-­citation analysis Fig. 12 Map of the collaborative network among Professor Forza and the co-authors

278 292 293 294 295 296 297 298 299 300 301 301

Retrospective of the MCP-CE Conference in the Period of 2004–2020 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6

Organizers of the first MCP-CE conference in Rzeszow, Poland (2004)315 Participants of the second MCP-CE conference in Rzeszow, Poland (2006) 316 Participants of the third MCP-CE conference in Palić-Novi Sad, Serbia (2008) 317 Mass Customization and Open Innovation (MC-OI) network 318 APEM journal (Vol. 4, No. 1, 2009) 319 Participants of the fourth MCP-CE conference in Novi Sad, Serbia (2010) 320

  List of Figures 

Fig. 7 Fig. 8 Fig. 9 Fig. 10 Fig. 11 Fig. 12 Fig. 13 Fig. 14 Fig. 15 Fig. 16 Fig. 17 Fig. 18 Fig. 19

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The first joint workshop on Mass Customization and Open Innovation321 Participants of the fifth MCP-CE conference in Novi Sad, Serbia (2012) 322 Participants of the sixth MCP-CE conference, the 1st Doctoral Students Workshop (DSW) and the 16th Configuration Workshop (CWS) 324 The special award to Robert Freund for his exceptional contribution to the MCP-CE community 325 IJIEM journal (Vol. 5, No. 4, 2014) 325 Cipriano Forza (Scientific Committee Chairman), Zoran Anišić (Organizing Committee Chairman) and Paul Blažek (Business Committee Chairman) 326 FIVE STAR Participants (MCP-CE 2016) 327 Panel discussion on digital customer experience 328 Participants of the eighth MCP-CE conference in Novi Sad, Serbia (2018) 329 FIVE STAR Participants (MCP-CE 2018) 330 Participants of the 3rd Doctoral Students Workshop (DSW) 330 Online participants of the ninth MCP-CE conference in Novi Sad, Serbia (2020) 331 The 4th DSW participants 332

List of Tables

Revisiting Form Postponement at the Operations-Marketing Interface: Form Postponement Types, Customer Utility and Sales Performance Table 1 Table 2 Table 3 Table 4

Form postponement (FP) types and uncertainty reduction Variables describing customer preferences for customization Form postponement (FP) types and customers’ preferences for choice (C), adaptability (A), reconfigurability (RC) and responsiveness (RS) Form postponement (FP) types and mass-customization (MC) strategies

11 15 16 21

The Role of SKU Management in Product Variety Reduction Projects Table 1 Table 2 Table 3 Table 4 Table 5

Interviews conducted SKU numbering across customer segments Identified cost factors related to SKU number proliferation Results of SKU reduction in product portfolio Impact analysis of SKU reduction on the cost

44 46 49 50 51

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List of Tables

Interorganizational Enablers of Mass Customization: A Literature Review Table 1 Table 2 Table 3

Interorganizational variables focused on the relationships between a mass-customization organization and its customers Interorganizational variables focused on the relationships between a mass-customization organization and its suppliers Interorganizational variables concerning the relationships between a mass-customization organization and its entire supply chain or other external stakeholders

89 92 94

The Ghost in the Machine: A Multi-method Exploration of the Role of Individuals in the Simultaneous Pursuit of Flexibility and Efficiency Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7

Qualitative study 106 Abilities identification and index construction 109 Distribution of interview excerpts across different customization workflow functions 120 Quantitative study sample description: Frequencies of selected characteristics 123 Item correlations and summary statistics (n = 267)126 (Empirical generalization) Means and mean differences for prospecting, blueprinting and patching tasks across different levels of flexibility and efficiency 131 Differences in the importance of ability to execute customization tasks (prospecting, blueprinting and patching) among six different work functions 132

Online Shopping Preferences in Mass Customization: A Comparison Between 2008 and 2021 Table 1 Table 2 Table 3 Table 4 Table 5

Peer-reviewed articles published between 2000 and 2021 that include (mass) customization/customisation/personalization/ personalisation in the title Survey questions of survey A in 2008 and survey B in 2021 Demographics of survey participants of survey A in 2008 and survey B in 2021 Major Internet activities in 2008 and 2021 Customers’ willingness to customize a product online

156 162 165 165 166

  List of Tables 

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Table 6

Customers’ willingness to customize by online shopping frequency166 Table 7 Customers’ preference to buy from a mass customizer 168 Table 8 Customers’ willingness to switch to an online mass customizer depending on waiting time 169 Table 9 Customers’ willingness to switch to an online mass customizer by online shopping frequency 169 Table 10 Percentage of customers willing to switch from their old brand to a mass-customization brand by product category and gender 170

Creating Customization Experiences: The Evolution of Product Configurators Table 1

List of brand names and URLs of the selected configurators

195

Enhancing Users’ Digital Social Interactions While Shopping via Online Sales Configurators Table 1

OSC and social software connection modalities and variants

223

Impact of Racial Diversity in Advertising on the Perception of Mass-Customized Products by Consumers Table 1 Table 2 Table 3 Table 4 Table 5 Table 6

Demographic data of survey participants Duncan’s multiple range test for perceived functional value (quality perceptions) by ad version Duncan’s multiple range test for perceived emotional value by ad version Duncan’s multiple range test for perceived social value by ad version Duncan’s multiple range test for willingness to customize by ad version Duncan’s multiple range test for willingness to pay a higher price by ad version

259 260 261 263 264 265

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List of Tables

Bibliometrics and Citation Analysis of the Works of Professor Forza Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7

Most contributed topics from 2016 to 2020 279 Data analysis in this work 281 The quantity of articles published from 1992 to 2021 288 Top co-authors of Professor Forza based on common documents289 Top organizations of co-authors based on the number of documents290 Keyword statistics 291 Top five documents based on citations and link strength 298

Part I Managing Mass Customization

Revisiting Form Postponement at the Operations-Marketing Interface: Form Postponement Types, Customer Utility and Sales Performance Alessio Trentin and Fabrizio Salvador

1 Introduction Form postponement (FP) is an instance of the broader principle of postponement that Alderson formulated as early as in 1950 to promote the efficiency of “a marketing flow” (p. 15) or, to use today’s terminology, of a supply chain. This principle proposes that both  “changes in form and identity” and “changes in inventory location” be postponed as much as possible (Alderson, 1950, p.  15). Form postponement (FP) is the term The original version of this chapter has been revised. The term “PLUS_SPI” was corrected to the actual “+” symbol on page 11. The correction to this chapter can be found at https://doi.org/10.1007/978-3-031-09782-9_12.

A. Trentin (*) Department of Management and Engineering, University of Padova, Vicenza, Italy e-mail: [email protected] F. Salvador Operations and Technology Management, IE Business School, IE University, Madrid, Spain © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023, corrected publication 2023 T. Aichner, F. Salvador (eds.), Mass Customization and Customer Centricity, https://doi.org/10.1007/978-3-031-09782-9_1

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A. Trentin and F. Salvador

coined by Zinn and Bowersox (1988) to denote the application of this principle to what Alderson (1950, p. 15) had called “changes in form and identity” and Heskett (1977, p. 87), almost three decades later, had more effectively  termed “commitment of resources to specific end products”. The same concept has also been dubbed in literature as delayed (product) differentiation (e.g., Lee & Tang, 1997; Su et al., 2010), delayed/late customization (e.g., Tibben-Lembke & Bassok, 2005; Ngniatedema et  al., 2015), manufacturing postponement (e.g., Nair, 2005; Kisperska-­Moron & Swierczek, 2011) or simply postponement (e.g., Zinn, 1990; Feitzinger & Lee, 1997). What all these terms have in common is that they refer to the deferral of transformation activities that specialize work-­in-­progress inventory into specific product variants (Forza et al., 2008). We will refer to these manufacturing tasks as product differentiation activities (PDAs). The fundamental benefit with which FP has typically been credited in the academic literature is improvement of a supplier’s efficiency in serving a market that requires the rapid delivery of many product variants (Graman & Sanders, 2009; Choi et al., 2012). The fundamental mechanism behind this widely accepted benefit is the reduction in the supplier’s demand uncertainty (Cavusoglu et al., 2012). If a forecast-driven PDA is postponed until customer order receipt, or at least to a point in time closer to order entry, then the supplier’s uncertainty about the mix of PDA outcomes that the market will demand is eliminated or at least reduced. This decreases the inventory-holding costs that the supplier must incur to guarantee a given customer service level (e.g., Zinn, 1990; Aviv & Federgruen, 2001; Kumar & Wilson, 2009; Wong et al., 2011; Varas et  al., 2018). Savings in inventory are, as observed by Set and Panigrahi (2015), the typical justification offered by the academic literature for the adoption of FP. We contend that this picture of how FP creates value for a supplier is overly simplistic, as it is restricted to the assumption that customers’ utility is increased only through the rapid delivery of many pre-specified product variants, as happens in the strategies of segmented standardization and customized standardization (cf. Lampel & Mintzberg, 1996). Yet, especially in the case of durable and expensive goods, customers’ utility may also be increased by giving customers the possibility to specify product features that will require ad hoc engineering, as happens in the

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strategies of pure customization and tailored customization (cf. Lampel & Mintzberg, 1996). With these strategies, the manufacturing process is order-driven (cf. Lampel & Mintzberg, 1996) and this makes the demand mix uncertainty reduction potential of FP useless. In these contexts, however, customers must anticipate their needs over a longer forecast window because of a longer delivery lead-time and deferring a PDA would give customers more time to explore their needs regarding the product feature(s) created by that activity. We thus argue that, in these contexts, uncertainty reduction does remain the fundamental benefit of FP but, contrary to Bucklin’s (1965) prediction, what FP reduces is uncertainty on the customer’s side. Building on this idea, this work links what customers value in terms of product customization and responsiveness—the latter meant as delivery speed (McCutcheon et al., 1994)—with the type of FP implemented by a supplier, where the FP type is defined by the temporal relationships linking PDA, customer order receipt and product delivery before and after FP implementation (Forza et  al., 2008). By linking different FP types with different customer utility profiles, our typological theory predicts the potential of FP to increase sales, rather than to reduce costs. The results of our conceptual work contribute to the FP literature in several ways. First, by drawing upon a more sophisticated model of customers’ preferences for customization and responsiveness than done by prior FP research, this chapter better integrates customer behavior into FP decisions, as called for by van Hoek (2001). Notably, van Hoek’s (2001) research agenda also included going beyond mere classification schemes of FP applications and mere lists of relevant market characteristics: In his view, in line with Doty and Glick’s (1994, p. 232) observation that “typologies are intended to predict the variance in a specified dependent variable”, more research was needed to develop FP typologies capable of both taking into account the interrelationships among those market contingencies and predicting the specific configuration of contingencies that makes each FP type maximally effective. By identifying the customers’ interrelated preferences for customization and responsiveness that make each FP type most effective in improving a supplier’s sales revenue, our propositions represent a step in the direction indicated by van Hoek (2001) and complement prior typological-theorizing efforts focused on

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the operational-performance outcomes of FP (Forza et al., 2008). Our typological theory also contributes to a richer and, at the same time, more nuanced understanding of the linkage between FP and mass customization (MC), which adds to the still-limited body of research advocating a contingency view of the effectiveness of MC enablers. On a more general level, this chapter adds to the research stream on coordinating marketing and operations decisions in the context of MC, which has so far taken a rather narrow view of FP, one in which FP application is circumscribed to the domain of forecast-driven PDAs. In ensuing sections, we begin with briefly reviewing prior research findings on FP antecedents and consequences to elaborate on the motivations of this study. Subsequently, building on Bucklin’s (1965) work on the combined operation of the principle of postponement with its opposite—the principle of speculation—we propose a broader view of the uncertainty reduction potential of FP.  Successively, we draw upon Duncan’s (1972) work on the sources of environmental uncertainty to connect the uncertainty reduction potential of different FP types with customers’ interrelated preferences for customization and responsiveness and, hence, with suppliers’ sales performance. Subsequently, our typological theory is combined with prior research on the classification of MC strategies to link different FP types to different MC strategies. Finally, the theoretical contributions of our study, as well as its limitations, possible extensions and practical implications, are discussed.

2 Literature Review Prior research has mainly focused on the application of FP to a forecast-­ driven PDA (Forza et al., 2008). If such an activity is postponed until customer order receipt—an instance of what Forza et al. (2008, p. 1070) called “from forecast to order driven FP”—then the supplier’s uncertainty about the mix of PDA outcomes that the market will demand is eliminated (Bucklin, 1965; Zinn & Bowersox, 1988). If, instead, the PDA is deferred to a point in time closer to, but still before, customer order entry—an instance of “remaining forecast driven FP” according to Forza et  al.’s (2008, p.  1071) terminology—then the supplier’s demand mix

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uncertainty is reduced but not eliminated (Alderson, 1950; Whang & Lee, 1998). In both cases, less safety stock is needed to guarantee the same customer service level (Zinn, 1990; Aviv & Federgruen, 2001). The consequent reduction in inventory-holding costs (Forza et al., 2008) is the typical justification offered by the extant literature for the adoption of FP (Set & Panigrahi, 2015). Undeniably, FP may reduce other costs, not related to demand mix uncertainty, such as transportation costs (e.g., Zinn & Bowersox, 1988), custom tariffs (Choi et al., 2012) or cycle stock costs (Van Kampen & Van Donk, 2014), but these benefits are less general and “must be analyzed on a case by case basis” (Lee & Billington, 1994, p. 115). At any rate, for many years the focus of FP research has been on the cost advantages of FP for a monopolistic supplier (Cavusoglu et al., 2012). This does not mean that revenue implications have been ignored. On the contrary, a loss of sales because the postponed PDA adds to the work content of the order fulfillment process, thus lengthening delivery lead-time, was mentioned as a possible effect of FP—meant as from-forecast-to-order-driven FP—as early as in Zinn and Bowersox (1988). However, a major limitation of early research, as far as FP effects on sales revenue are concerned, is its implicitly assuming that a product’s price is exogenous to FP application (Wong & Eyers, 2011; Cavusoglu et al., 2012). More recently, FP research has incorporated a supply chain perspective (Zinn, 2019) and has developed a more sophisticated view of FP benefits by analyzing the case of competitive markets (e.g., Anand & Girotra, 2007), by examining the benefits of FP in terms of enhanced MC capability (e.g., Liu et al., 2010), mitigation of supply risk—besides the traditionally considered demand risk—(e.g., Carbonara & Pellegrino, 2018), and improved environmental performance (e.g., Budiman & Rau, 2019), and by assuming that price, as well as the number of product variants offered in the market, are influenced by FP application (e.g., Wong & Eyers, 2011). More specifically, with reference to the last-mentioned development, prior research has found that from-forecast-to-order-driven FP permits to increase the number of product variants, thus minimizing customers’ dissatisfaction in not having their ideal products (Wong & Eyers, 2011).

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Not unlike the consequences of applying FP to a forecast-driven PDA, so have its antecedents received much attention in literature. These latter are factors that drive or enable the application of FP by respectively amplifying its benefits or mitigating its costs. For many years, the inquiry of FP antecedents has focused on demand characteristics, such as the uncertainty (e.g., Zinn & Bowersox, 1988) and the substitutability (e.g., Zinn, 1990; Aviv & Federgruen, 2001) of the market demands for the different product variants; product factors, such as the unit value (e.g., Zinn & Bowersox, 1988) and the degree of modularity (e.g., Lee & Tang, 1997) of the considered product; and production process characteristics, such as the capital intensity of (e.g., Pagh & Cooper, 1998) and the excess capacity at (e.g., Gupta & Benjaafar, 2004) the considered PDA. More recently, greater attention has been paid to the organizational solutions that facilitate FP, such as the use of lateral relations (Trentin & Forza, 2010) and time-fencing (Trentin et al., 2011) in the production planning process, and to inter-organizational factors, such as supply contract restrictions (Krajewski et al., 2005) and mix and volume flexibilities of the suppliers of raw materials and purchase components (Saghiri & Barnes, 2016). Going back to the demand characteristics that give impulse to FP application—the antecedents that are more relevant to the present study—it is generally accepted in literature that FP implementation is driven by customer need heterogeneity, as reflected by the number of pre-­ specified product variants that a supplier has to offer (van Hoek et al., 1998; Skipworth & Harrison, 2004; Choi et al., 2012; Zinn, 2019), by the need for quick response to customers’ orders (van Hoek et al., 1998; Skipworth & Harrison, 2004; Choi et al., 2012) and by the uncertainty (van Hoek et al., 1998; Skipworth & Harrison, 2004; Zinn, 2019) and the substitutability (Zinn, 2019) of the market demands for the different product variants. These market contingencies dictate that the postponed PDA is performed to forecast or, at most, immediately after the receipt of a customer order in “a short time period” (Harrison & Skipworth, 2008, p. 173) and amplify, for a given customer service level, the safety stock savings produced by the deferment of the PDA (e.g., Zinn, 1990; Aviv & Federgruen, 2001; Varas et al., 2018). In summary, the dominant view is one in which FP reduces a supplier’s demand mix uncertainty whenever customers value product choice but

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are willing to sacrifice the possibility to demand an out-of-range solution in exchange for quick response. Given this dominant view, it comes as no surprise that van Hoek (2001) did not see any room for FP application when customers value customization at the design stage more than responsiveness. When ad hoc engineering is contemplated, the production process—including any PDAs—must be performed to order—as long as the typical constraint “engineering before production” (Rudberg & Wikner, 2004, p. 448) applies—and demand mix uncertainty is thus resolved even before applying FP. The mechanism of demand mix uncertainty reduction continues to play a role in order-driven production environments  only when FP is combined with the downstream relocation of the decoupling point (e.g., Swaminathan & Tayur, 1998, 1999), where the latter is defined as the stock point from which customers are to be supplied (Hoekstra & Romme, 1992; Mason-Jones & Towill, 1999). This downstream relocation shortens delivery lead-time by reducing the order-driven portion of the production process but, per se, could increase inventory-holding costs prohibitively due to the large number of items that should be kept in stock at the decoupling point (Caux et al., 2006). Instead, if this downstream relocation is combined with FP, then the number of stock-­keeping units at the decoupling point is reduced and this alleviates the increase in inventory-holding costs (Su et al., 2010) or may even improve, under very specific assumptions, cost performance (cf. Lee, 1996; Su et al., 2010). Yet, if FP is applied to an order-driven PDA without simultaneously relocating the decoupling point downstream, there is no way the mechanism of demand mix uncertainty reduction can come into play (Forza et al., 2008). Nonetheless, applications of FP in contexts wherein customers were willing to sacrifice responsiveness in exchange for pure customization and FP was not combined with the downstream relocation of the decoupling point are documented in literature, for example, in the telecommunication equipment industry (Hoyt & Lopez-Tello, 2001). Furthermore, there are order-driven production environments, such as in the shipbuilding, construction and aerospace sectors, where keeping a safety stock of a semifinished product is virtually impossible (cf. Meredith & Akinc, 2007). How FP creates value for a supplier in such contexts is a question that, unfortunately, has drawn little attention from researchers, as already observed by Forza et al. (2008).

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3 Form Postponement and Uncertainty Reduction: A Broader Perspective To conceptually investigate the benefits of applying FP to an order-driven PDA, we build on Bucklin’s (1965) observation that uncertainty is progressively shifted from a supplier to its customers as a growing portion of the supplier’s production process becomes order-driven: As this happens, delivery lead-time lengthens and, hence, customers must anticipate their needs over a longer forecast window. Since “forecasts are more wrong the further out they go” (Mather, 1986, p. 95), the customer’s decision on what output of a PDA will maximize his/her utility over the product’s lifespan increases. The supplier can reduce this uncertainty—hereafter referred to as customer’s output utility uncertainty—by deferring the order-driven PDA to a point in time closer to product delivery—an instance of what Forza et  al. (2008, p.  1071) called “remaining order driven FP”. This uncertainty reduction potential of FP materializes if the supplier allows the customer to place a partially specified order and then to specify the output of the PDA just before its execution, according to Wikner and Rudberg’s (2005) concept of customer order decoupling zone. Under this reasonable assumption, the customer’s input about the PDA is required at a later point, which shortens the customer’s forecast window and, hence, reduces his/her output utility uncertainty. Notably, output utility uncertainty is reduced by remaining-order-­ driven FP, but not eliminated. Unless a product is consumed immediately after its purchase or customers are unaware of the possibility that their preferences change during the product’s lifespan, elimination of output utility uncertainty requires two conditions: First, the PDA must be deferred until after product delivery and, second, the customer must be enabled to perform the PDA on demand during the product’s lifespan, according to Ng et al.’s (2015, p. 86) concept of “customer postponement”. This is well illustrated by Brown et al.’s (2000, p. 65) study of “product postponement” at Xilinx, an integrated circuit manufacturer that designed its products to be (re)programmable by customers using software even after the device is installed. Notably, the term “product postponement” emphasizes the fact that customers are provided an “incomplete product” (Ng et al., 2015, p. 79), while the term “customer

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postponement” stresses the point that customization is eventually performed by customers. We further distinguish this type of FP into two categories, depending on whether the PDA that is ultimately transferred to the customer was previously performed by the supplier on a to-order or a to-forecst basis. In the latter case (referred to as “from-forecast-­ driven-to-customer-performed FP” in the following), also the supplier’s demand mix uncertainty is eliminated, while in the former case (hereafter indicated as “from-order-driven-to-customer-performed FP”) only the customer’s output utility uncertainty is eliminated, as the supplier’s demand mix uncertainty is resolved even before applying FP. The above discussion complements the existing literature on the management of uncertainty through FP and outlines a broader picture of the uncertainty reduction potential of FP.  This picture is summarized in Table 1, which builds on the mutually exclusive and collectively exhaustive types of FP defined by Forza et al. (2008). Notably, Bucklin’s (1965) point that FP shifts uncertainty away from the supplier to the customer only applies to from-forecast-to-order-driven Table 1  Form postponement (FP) types and uncertainty reduction Who’s uncertainty concerning what

FP type applied to a PDA

The supplier’s demand mix uncertainty relative to the PDA to which FP is applied

Remaining-forecast-driven FPa Reduced but not eliminated From-forecast-to-order-driven Eliminated FPa Nonexistent Remaining-order-driven FPa From-order-driven-tocustomer-­performed FPa From-forecast-driven-tocustomer-­performed FP (= from-forecast-to-orderdriven FP + from-­order-­ driven-to-customer-­­ performed FP) a

Forza et al. (2008)

The customer’s output utility uncertainty relative to the PDA to which FP is applied Unaltered Increased

Nonexistent

Reduced but not eliminated Eliminated

Eliminated

Eliminated

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FP, since this type of FP lengthens delivery lead-time. As a matter of fact, Bucklin (1965) had restricted Alderson’s (1950) ideaof postponing changes in product identity along a manufacturing and distribution process to a narrower principle, one that advocates that a forecast-driven PDA be deferred until after a customer order is received. If we exclude this type of FP, however, FP never shifts uncertainty forward to the customer and three of the remaining four FP types even reduce/eliminate uncertainty on the customer’s side.

4 Uncertainty Sources and Customers’ Interrelated Preferences for Customization and Responsiveness Once established that each FP type brings about unique benefits in terms of uncertainty reduction, the question of which demand characteristics make these unique benefits most attractive naturally arises. In addressing this question, we focus on sales revenue as the outcome variable of interest and on customers’ interrelated preferences for customization and responsiveness as the contingencies that predict the effectiveness of each FP type in improving sales revenue. Our literature review has shown that prior studies on the performance outcomes of FP have typically modeled customers’ expectations for product customization in terms of choice, defined as the cardinality of a finite set of pre-specified product solutions from which customers can choose.1 If customers expect quick response and, accordingly, those product variants are made to stock, choice becomes a source of supplier’s demand mix uncertainty. Instead, if production is order-driven, demand mix uncertainty is eliminated and shifted to customers in the form of increased output utility uncertainty. However, unless a product is consumed immediately, output utility uncertainty exists even when delivery lead-time is close to zero, because customers must in any case forecast their needs over  This point is consistent with Wong and Lesmono’s (2013, p. 105) prior and more general observation that “most existing studies […] tend to associate the level of customization with the number of product variants”. 1

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the product’s lifespan. Thus, choice is always a source of customer’s output utility uncertainty, unless the product is consumed immediately, while choice may or may not be a source of supplier’s demand mix uncertainty, depending on whether the product variants are created to forecast or to order. Seen through the lens of Duncan’s (1972) work on the environmental sources of uncertainty, choice corresponds to the “complexity” driver, which captures the number of diverse factors that a decision maker perceives as being important in decision-making (Duncan, 1972). Customers’ expectations for customization, however, can go beyond choice (e.g., Wong & Lesmono, 2013) and can increase uncertainty through dynamism, too, as we will argue in the following. Notably, Duncan (1972) distinguished two types of dynamism: the change in the number of the relevant factors, hereafter referred to as “dynamism (new factors)”, and the change in the values of the relevant factors, henceforth denoted as “dynamism (given factors)”. A dynamic source of both supplier’s demand mix uncertainty and customer’s output utility uncertainty is represented by customers’ expectations for adaptability. This is defined as the possibility to demand and obtain an ad hoc solution whenever a customer’s idiosyncratic needs are not fully met by any of a supplier’s pre-specified solutions. Adaptability would make a supplier’s demand mix uncertainty so large that it must be resolved by producing to order. Yet, order-driven production has the drawback of impairing delivery speed because of a fundamental trade-off studied and described by many authors (cf. Akinc & Meredith, 2015). Thus, customers requiring adaptability must be willing to sacrifice responsiveness. Adaptability also increases a customer’s output utility uncertainty, because information regarding how a supplier’s capabilities can best help a customer maximize his/her utility is distributed asymmetrically between supplier and customer and is sticky (von Hippel, 1994). Notably, adaptability corresponds to Duncan’s (1972) dynamism (new factors), because customers’ expectations for adaptability lead to the definition of new product solutions over time. Another dynamic driver of both demand mix uncertainty and output utility uncertainty corresponds to Duncan’s (1972) dynamism (given factors). This distinct source of uncertainty is represented by change in

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customers’ preferences, provided this change regards the preferences for a given set of product solutions, as any change that leads to the request for new solutions falls within the notion of adaptability. If customers are aware that their preferences for a given set of solutions can change, this clearly increases their output utility uncertainty. As a means for reducing such uncertainty, customers may value reconfigurability, defined as the possibility to switch, on demand, among a given set of pre-specified solutions after receiving the product. We say “may value” because this is not always the case (e.g., customers could be willing to buy another solution as their preferences change). On the supply side, if customers’ preferences for a given set of solutions change over time, this makes the aggregate demand for each product variant less predictable. Consequently, a supplier’s demand mix uncertainty increases, unless those variants are made to order. In summary,  the above discussion implies that, while the dominant view in the FP literature is that choice is all customers want in terms of product customization, a less simplistic model should also include adaptability and reconfigurability. Notably, customers’ preferences for choice, adaptability and reconfigurability can vary across different attributes of the same product.2 Thus, these variables must be defined at the attribute level (Table 2), while customers’ expectations for responsiveness clearly cannot, as they refer to the entire product. For the sake of simplicity, we assume that each product attribute is created by a distinct transformation activity.

5 Linking Form Postponement, Customer Utility and Sales Performance: A Typological Theory To simplify our conceptual investigation of how customers’ preferences for choice, adaptability, reconfigurability and responsiveness influence the effectiveness of each FP type in improving a supplier’s sales revenue,  Following the attribute-based marketing approach, we conceptualize any product “as a bundle of well-defined attributes” (Srinivasan et al., 1997). Each product variant is defined by a specific set of levels (or values) of the product’s attributes. 2

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Table 2  Variables describing customer preferences for customization

Variable

Definition

Choice

The number of pre-specified attribute levels from which customers can choose

Related source of uncertainty Uncertainty source (Duncan, definition (Duncan, 1972) 1972) Complexity

The number of diverse factors identified as being important in decision-making Adaptability The possibility to Dynamism Change in the demand and obtain a (new factors) number of the new attribute level factors identified requiring ad hoc as being engineering important in decision-making Reconfigurability The possibility to Dynamism Change in the switch, on demand, (given values of the among a given set of factors) relevant factors pre-specified for the decision attribute levels after product delivery

we assume that these four contingency variables are dichotomous: Customers may expect either “high” or “low” choice and responsiveness, while adaptability and reconfigurability may be required (“yes”) or not (“no”). Under this assumption, there are 2 × 2 × 2 × 2 = 16 possible customer utility profiles, which correspond to as many different combinations of what customers appreciate. Notably, the value of each variable must not be interpreted in isolation, but in the context of the values of the other variables. Accordingly, a “no” value for adaptability is not to deny that, ideally, customers would like pure customization; it only means that, by  acknowledging a trade-off between customization and responsiveness on the supply side (e.g., Mapes et al., 1997; Åhlström & Westbrook, 1999; Squire et al., 2006; Hallgren et al., 2011), customers are willing to sacrifice adaptability for delivery speed. Symmetrically, a “low” value of responsiveness is not to deny that, ideally, customers would like quick response; it simply means that customers are willing to trade delivery speed for a higher degree of product customization. These

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Table 3  Form postponement (FP) types and customers’ preferences for choice (C), adaptability (A), reconfigurability (RC) and responsiveness (RS) Customer utility profile #

C

A

RC RS

1 2 3 4

High Low High Low

No No Yes Yes

No No No No

5

High No No Low

6

Low

7 8

High Yes Yes Low Low Yes Yes Low

9

High No Yes Low

10 Low

High High Low Low

No No Low

No Yes Low

11 High No Yes High 12 Low No Yes High

FP type that maximizes sales revenue under the customer utility profile From-forecast-to-order-driven FP Remaining-forecast-driven FP Remaining-order-driven FP Remaining-order-driven FP (less beneficial than under Profile 3) Remaining-order-driven FP (less beneficial than under Profile 3) Remaining-order-driven FP (less beneficial than under Profile 3) From-order-driven-to-customer-performed FP From-order-driven-to-customer-performed FP (less beneficial than under Profile 7) From-order-driven-to-customer-performed FP (less beneficial than under Profile 7) From-order-driven-to-customer-performed FP (less beneficial than under Profile 7) From-forecast-driven-to-customer-performed FP From-forecast-driven-to-customer-performed FP (less beneficial than under Profile 7)

covariance patterns are recognized in the existing literature (cf. Wong & Lesmono, 2013) and explain why the four profiles combining “yes” adaptability with “high” responsiveness are omitted in Table  3. The remaining profiles are discussed in the following, with the objective of identifying the FP type that maximizes a supplier’s sales revenue under each profile. When customers do not value reconfigurability, transferring a PDA to them (i.e., from-order/forecast-driven-to-customer-performed FP) will reduce a supplier’s revenue, as customers will prefer competing offerings that do not force them to perform product configuration tasks. Consequently, for Profiles 1–6, from-order/forecast-driven-to-customerperformed FP are dominated by the other three FP types. If customers are also willing to sacrifice adaptability for delivery speed (Profiles 1 and 2), a large portion of the production process, if not the entire process, must be performed on a to-forecast basis. This means that there is little room for applying remaining-order-driven FP. As a matter

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of fact, when delivery lead-times are short, the maximum time lapse by which an order-driven PDA can be deferred while remaining order-­ driven is short. Consequently, the ideal FP type must be chosen between remaining-forecast-driven FP and from-forecast-to-order-driven FP. When customers expect quick response but are willing to trade on-­ hand availability of end-products for higher product choice (Profile 1), from-forecast-to-order-driven FP dominates remaining-forecast-driven FP (cf, Harrison & Skipworth, 2008; Wong & Eyers, 2011). As a matter of fact, when the number of attribute levels requested by the market is large, continuing to create the corresponding product features to forecast leads to excess inventory without ensuring the expected level of customer service (Holweg & Pil, 2001; Salvador et al., 2007). Conversely, when customers do not require high product choice (Profile 2), the ideal FP type is remaining-forecast-driven FP, as it preserves on-hand availability of end-products. Suppose now that customers accept low responsiveness in exchange for adaptability (Profiles 3 and 4). In this case, given the constraint “engineering before production”, the PDA must be performed to order. This leaves remaining-order-driven FP as the only option (recall that we are still discussing the case in which customers do not wish reconfigurability). Remaining-order-driven FP improves sales revenue by allowing customers to purchase a partially specified product and then to define the output of the PDA just before its execution. This may be essential to win orders when customers are unable to fully specify, at the time of purchase, the products they need (e.g., Hoyt & Lopez-Tello, 2001). Notably, the uncertainty reduction benefits of remaining-order-driven are less appealing when choice is “low” (Profile 4) rather than “high” (Profile 3), because adding choice to adaptability further increases customers’ output utility uncertainty (cf. previous section). Likewise, this FP type is less appealing when customers are willing to accept low responsiveness even without expecting adaptability (Profiles 5 and 6), as in this case their output utility uncertainty is driven only by choice (cf. previous section) and, therefore, is lower. Now, let us go back to the case in which customers trade responsiveness for adaptability and let us assume that they also value reconfigurability as a means to reduce their output utility uncertainty (Profiles 7–8). Meeting customers’ expectation for reconfigurability necessitates that the

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PDA be passed on to the customers themselves. However, given the simultaneous request for adaptability, reconfigurability here involves a set of attribute levels that is at least in part customer-specific. To accommodate for ad hoc engineering, the PDA to be transferred to customers must clearly be order-driven. Thus, the ideal FP type is from-order-driven-tocustomer-­performed FP. Not unlike remaining-order-driven FP, this FP type is less appealing when choice is “low” (Profile 8) rather than “high” (Profile 7), because adding choice to adaptability further increases customers’ output utility uncertainty (cf. previous section). Similarly, when customer do not require adaptability and their output utility uncertainty is driven only by choice (Profiles 9 and 10), the uncertainty reduction benefits of this FP type are less appealing, as output utility uncertainty is lower. Finally, suppose customers value reconfigurability but are willing to sacrifice adaptability for delivery speed (Profiles 11 and 12). In this case, customers are satisfied with the possibility of switching—on demand after product delivery—among a set of attribute levels that is fully pre-­ specified. As the PDA being transferred to customers does not require ad hoc engineering, it can be forecast-driven. More precisely, it must be forecast-driven if customers’ expectations for quick delivery are to be fully met. Thus, the ideal FP type is from-forecast-driven-to-customer-­­ performed FP, which eliminates both the supplier’s demand mix uncertainty and the customer’s output utility uncertainty. Notably, the uncertainty reduction benefits of this FP type are more appealing when choice is “high” (Profile 11) rather than “low” (Profile 12), because choice increases both the supplier’s demand mix uncertainty and the customer’s output utility uncertainty (cf. previous section). The above arguments allow us to predict which customer utility profile makes each FP type most effective in improving a supplier’s sales revenue. This typological theory linking FP type, customer utility and sales performance is formalized by the following five propositions, which are graphically illustrated in Fig. 1. Proposition 1. Remaining-forecast-driven FP is most effective in increasing a supplier’s sales revenue when customers demand high responsiveness but accept low choice and do not require adaptability or reconfigurability.

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  Revisiting Form Postponement at the Operations-Marketing…  CUSTOMER UTILITY FUNCTION reconfigurability choice

delivery speed

FP TYPE MAXIMIZING SALES REVENUE PDA

Remaining -forecastdriven

adaptability reconfigurability choice

delivery speed

Order Entry tOE

Fromforecastto-orderdriven

Product Delivery tD=0

Before FP

time

PDA After FP

time

PDA Before FP

time

PDA After FP

time

adaptability reconfigurability choice

delivery speed

PDA

Remaining -orderdriven

Before FP time

PDA

After FP

time

adaptability reconfigurability choice

delivery speed adaptability reconfigurability

choice

delivery speed adaptability

Fromorder-tocustomerperformed

PDA Before FP

time

PDA After FP

time

PDA

Fromforecast-tocustomerperformed

Before FP

time

PDA After FP

time

Fig. 1  Form postponement (FP) types and customer utility function

Proposition 2. From-forecast-to-order-driven FP is most effective in increasing a supplier’s sales revenue when customers demand both high responsiveness and high choice but do not require adaptability or reconfigurability. Proposition 3. Remaining-order-driven FP is most effective in increasing a supplier’s sales revenue when customers accept low responsiveness in exchange for both adaptability and high choice but do not require reconfigurability. Proposition 4. From-order-driven-to-customer-performed FP is most effective in increasing a supplier’s sales revenue when customers accept low responsiveness in exchange for adaptability and require both high choice and reconfigurability.

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Proposition 5. From-forecast-driven-to-customer-performed FP is most effective in increasing a supplier’s sales revenue when customers demand high responsiveness, high choice and reconfigurability but do not require adaptability.

6 Linking Form Postponement Types and Mass-Customization Strategies Our typological theory lays the ground for a more nuanced understanding of the linkage between FP and MC. By MC, we mean the ability to overcome the traditional manufacturing trade-offs between product customization—a dimension of flexibility—and cost, delivery and quality performance (cf. Pine et al., 1993; Squire et al., 2006; Trentin et al., 2020).3 That FP enables MC is something prior research has long and repeatedly recognized (e.g., Feitzinger & Lee, 1997; van Hoek et al., 1999; Su et al., 2005; Fogliatto et al., 2012; Zinn, 2019). Different strategies, however, fall under the MC umbrella (cf. Huang et al., 2010; Sandrin et al., 2014), reflecting different types of product customization that customers would value (Gilmore & Pine, 1997). By predicting that different FP types fit with different customer preferences for customization and responsiveness, our typological theory implies that a certain type of FP is not equally effective in enabling any MC strategy. To understand which FP type enables which MC strategy, we build on Lampel and Mintzberg’s (1996) classification of customization strategies, which is commonly understood as being unidimensional but, in fact, relies on the two interrelated criteria: the point of customer involvement in the value chain, capturing which activities along the chain are performed according to an individual customer’s specifications, and the type of customer involvement, reflecting what a customer is supposed to do to get a customized solution. These two criteria are applied in Table 4 not only to Lampel and Mintzberg’s (1996) long-established categories, but also to other renowned taxonomies proposed by Gilmore and Pine (1997), da Silveira  The path toward MC may start either from mass production or from custom manufacturing (Duray, 2002; Squire et al., 2006; Trentin et al., 2012). 3

Design

Point of Value chain customer stage involvement in the value chain (The earliest value chain stage performed according to None an individual customer’s specifications)

Type of customer involvement (What a customer is supposed to do to get a customized product) Nothing but ordering Select a product Create a product a standard product variant from a configuration from predefined a menu of catalog and predefined choice possibly select options and delivery options possibly select delivery options Embedded MC (Pure standardizationa; transparent customization and automatic adaptive customizationb) possibly enabled by Remaining-forecastdriven FP Adapt-to-­order MC (Tailored customizationa; collaborative customizationb; Level-8 MCc; design-perorder/call-off MCd; adapt-toorder and make/ assemble-toordere) enabled by Remaining-orderdriven FP

Take part in the modification of an existing product design and possibly select delivery options

Table 4  Form postponement (FP) types and mass-customization (MC) strategies

Engineerto-­order MC (Pure customizationa; collaborative customizationb; Level-8 MCc; design-perorder/call-off MCd; engineerto-­order and make-to-ordere) enabled by Remaining-orderdriven FP

Take part in the development of a new product design and possibly select delivery options

(continued)

Engineer-to-­order self-MC enabled by From-order-­drivento-customer-­­ performed FP

Take part in the performance of a product differentiation activity and possibly select delivery options

Assembly

Fabrication

Table 4 (continued) Engineer-to-­stock make-to-­order MC (Tailored customizationa; collaborative customizationb; Level-7 MCc; catalogue MCd; engineer-to-stock and make-to-ordere) enabled by Remaining-orderdriven FP Engineer-to-­stock assemble-to-­order MC (Customized standardizationa; collaborative customizationb; Level-6 MCc; catalogue MCd; engineer-to-stock and assemble-to-ordere) enabled by From-forecast-toorder-driven FP

Catalog MC (Segmented standardizationa; Level-3 MCc; catalogue MCd; engineer-to-stock and make-to-stocke) enabled by Remaining-forecastdriven FP

Distribution

b

a

Lampel and Mintzberg (1996) Gilmore and Pine (1997) c da Silveira et al. (2001) d MacCarthy et al. (2003) e Rudberg and Wikner (2004)

Usage

Cosmetic MC (Cosmetic customizationb; Level-3/4/5 MCc; catalogue MCd) enabled by From-forecast-toorder-driven FP

Final processing (e.g., adding a module, packaging, labeling) Engineer-to-­stock finalize-­to-­order MC (Customized standardizationa; collaborative customizationb; Level-4/5 MCc; catalogue MCd) enabled by From-forecast-toorder-driven FP

Self-MC (Pure standardizationa; non-automatic adaptive customizationb; Level-2 MCc) enabled by From-forecast-drivento-customerperformed FP

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et al. (2001), MacCarthy et al. (2003) and Rudberg and Wikner (2004), respectively. The combination of the two abovementioned criteria leads to distinguish ten different MC strategies, which create value for customers (and, hence, for suppliers) by drawing on different customers’ interrelated preferences for customization and responsiveness. If customers value adaptability more than responsiveness, then  they must be involved at the “design” stage and “a genuine partnership” between them and their suppliers needs to be established (Lampel & Mintzberg, 1996, p. 26). Given these customers’ preferences, the corresponding MC strategies (i.e., engineer-­to-order self-MC, engineer-to-order MC and adapt-to-order MC) are enabled—based on our typological theory—by from-order-­ driven-to-customer-performed FP if reconfigurability is required as well (i.e., in the case of engineer-to-order self-MC) and by remaining-order-­ driven FP otherwise. This latter type of FP also facilitates MC when customers accept low responsiveness without expecting adaptability, so that they need not be involved earlier than at the “fabrication” stage, according to the engineer-to-stock make-to-order MC strategy. Instead, when customers are not willing to sacrifice high responsiveness, they must be involved at a later stage and customization takes place within the constraints of pre-engineered product options or variants. Given customers’ expectation for high responsiveness, the corresponding MC strategies (i.e., engineer-to-stock assemble-to-order MC, engineer-­ to-­stock finalize-to-order MC, cosmetic MC, catalog MC and self-MC) are enabled—based on our typological theory—by from-forecast-driven-­ to-customer-performed FP if reconfigurability is required as well (i.e., in the case of self-MC), by remaining-forecast-driven FP if customers accept low choice in exchange for on-hand availability of end-products (i.e., in the case of catalog MC) and by from-forecast-to-order-driven FP otherwise. Notably, the embedded-MC strategy fulfills the needs of individual customers without involving them, that is, “in an indiscernible way” (Gilmore & Pine, 1997, p. 99). For this to be possible, a supplier must be able to determine those needs through its own analysis rather than by involving the customer (Gilmore & Pine, 1997) or a product must be able to “understand” how it should adapt to the customer and then

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reconfigure itself accordingly (Salvador et al., 2009, p. 73). In the latter case, there is no room for benefiting from FP, as the product is completely standardized. By contrast, in the former case, deferring a PDA along the manufacturing and distribution process—as long as the PDA is not passed on to the customer, which would obviously make customization discernible—gives a supplier more time to deepen its knowledge of customers and to move progressively closer to meeting their individual preferences. If the supplier does seize this opportunity, then remaining-forecast-driven FP also facilitates embedded MC. The picture of the FP-MC linkage provided by Table 4 can easily be compared with van Hoek’s (2001) Figure 2 relating postponement applications to different MC approaches, since these latter are classified by van Hoek (2001), too, based on the stage of the value chain at which they can be applied. What is striking in the comparison is that the role of FP in enabling MC was well delineated by van Hoek (2001) for those  MC approaches that involve customers at the mid- or downstream stages of the value chain but was completely overlooked in the case of customer involvement at the upstream stages.4

7 Discussion and Conclusion 7.1 Theoretical Implications By revisiting FP at the interface between operations and marketing, the present study outlines a richer picture of the strategic potential of FP. The extant FP literature certainly does not deny this potential but typically assumes that the rapid delivery of many pre-specified product variants is all customers want. This assumption has led to focusing on the application of FP to forecast-driven PDAs and, hence, to indicating the reduction of a supplier’s demand mix uncertainty, and the consequent savings in safety stock for a given customer service level, as the fundamental  Implementing FP in contexts where customers are involved at the upstream stages of the value chain has nothing to do with the notions of product development postponement or purchasing postponement, which apply the broader principle of postponement to product development or purchasing activities and not to transformation activities (Yang et al., 2004). 4

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mechanism whereby FP creates competitive advantage. This advantage, in other terms, would essentially derive from the pursuit of what Skinner (1969) had pointed out as the traditional manufacturing objective of low costs and high efficiency. Not by chance, the efficiency of a supply chain was exactly what Alderson (1950) aimed to promote by advocating the broader principle of postponement. Our results show that this picture of how FP creates competitive advantage is only a part of the story. Another mechanism comes into play when we account for the possibility that customers trade quick response for out-of-range solutions and/or value the chance of reconfiguring their products on demand during the product’s lifespan. Under this more sophisticated model of customers’ interrelated preferences for customization and responsiveness—a model that responds to van Hoek’s (2001) call for better integrating customer behavior into FP decisions—FP may work as a competitive weapon not only and not necessarily by reducing a supplier’s demand mix uncertainty, but also by decreasing customers’ output utility uncertainty. By reducing such uncertainty, remaining-­ order-­driven FP and from-order/forecast-driven-to-customer-performed FP add new dimensions to customer service, such as allowing customers to place partially unspecified orders and provide full specifications at a later stage in the order fulfillment process. This finding leads to the conclusion that the operations’ ability to apply FP can play a more proactive role than is implied by the existing literature—an externally supportive role, to use Wheelwright and Hayes’s (1985) terminology—in the definition of a firm’s marketing strategy. This conclusion further corroborates the view, well-grounded in the operations strategy literature, that the operations function should be “centrally involved in major decision-­ making in other functions” (Barnes & Rowbotham, 2004, p.  706), including marketing. While the coordination of marketing and operations decisions in the context of the so-called product line design problem has long attracted the attention of researchers (cf. Yano & Dobson, 1998; Ramdas, 2003; Tookanlou & Wong, 2020), only Wong and Eyers (2011) have so far integrated the marketing and operations perspectives in the context of FP decisions and their view of FP is rather narrow: FP coincides with from-forecast-to-order-driven FP.  By considering also

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other four types of FP and by predicting which customer utility profile maximizes the revenue increase potential of each type, our typological theory provides more general guidance for the alignment of FP decisions with market contingencies. By linking FP types, customer utility and sales performance, our propositions also complement prior typological-theorizing efforts focused on the operational-performance outcomes of FP (cf. Forza et al., 2008). By doing so, our propositions represent a step in the direction indicated by van Hoek (2001) of going beyond mere classification schemes of FP applications and beyond mere lists of market characteristics relevant to FP. The objective set by van Hoek (2001, p. 182), in line with Doty and Glick’s (1994) distinction between taxonomies and typologies, was to arrive at “a typology of postponement applications using operating circumstances that impact feasibility and validity of postponement”. Though silent about feasibility, our typological theory contributes to the accomplishment of this goal by predicting what customer preferences for customization and responsiveness make each FP type more effective, or “valid”, for the purpose of improving sales revenue. Finally, our typological theory lays the ground for a richer and, at the same time, more nuanced understanding of the linkage between FP and MC. We say “richer” because the MC-enabling role of FP is no longer restricted to the so-called partial-MC strategies, which involve customers at the assembly stage or downstream (Squire et al., 2006; Huang et al., 2010). On the contrary, this role is now extended to so-called full-MC strategies, which involve customers at the upstream stages of the value chain (Squire et al., 2006; Huang et al., 2010), and may even embrace the embedded-MC strategy. We say “more nuanced” because the long-­ heralded message that FP enables MC is further articulated by showing that different MC strategies require different FP types. Only recently has MC research begun to investigate the contingency effect of the type of MC strategy on the effectiveness of a few enablers of MC (cf. Huang et al., 2010; Sandrin et al., 2018). Our typological theory adds to this still very limited body of knowledge by showing that the effectiveness of FP in enabling MC is contingent on the fit between the type of FP being implemented and the type of MC strategy being pursued.

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7.2 Limitations and Future Research Opportunities As mentioned above, this conceptual work is silent about FP feasibility: We focus on the external fit between FP type and customers’ preferences for customization and responsiveness and leave aside the issue of the internal fit between FP type and suppliers’ resource endowments. Developing a typological theory capable of integrating the revenue implications of FP, tied to its external fit, with its implications in terms of implementation costs, tied to its internal fit, would be the logical continuation of our work. However, we see at least a prerequisite for going ahead in this direction: The vast body of knowledge on the enablers of FP should be systematically reviewed to recognize the fundamental principles behind the myriad of context-specific technological and organizational solutions reported in the literature, so as to ideally arrive at a collectively exhaustive and mutually exclusive set of FP enablers. Another important direction in which our conceptual work should be developed is its empirical testing in a variety of settings. “In the absence of this breadth of experimental evidence,” as Whetten (1989, p. 492) admonished, “we must be realistic regarding the extent of a theorist’s foreknowledge of all the possible limitations on a theory’s applicability.”

7.3 Managerial Implications Despite its limitations, we believe this conceptual work is of use to practitioners in at least two ways. First, in a context in which the customization strategies characterized by an early customer involvement become increasingly important, our work makes the pursuers of such strategies aware that FP brings benefits to them even when it cannot be combined with the downstream relocation of the decoupling point, the case that is typically discussed in the extant literature. As a matter of fact, there are several sectors in which products are engineered-to-order and keeping a safety stock of a semifinished product is virtually impossible. In such contexts, FP offers the important advantage of reducing customers’ output utility uncertainty, thus permitting to add new dimensions to customer service. Second, our work makes practitioners aware that, both in

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order-driven and in forecast-driven production environments, FP decisions should be made at the level of each product attribute for which customers’ preferences for choice, adaptability and reconfigurability are different. Just like a company may need to combine diverse customization approaches (cf. Gilmore & Pine, 1997), so it may also need to simultaneously apply different FP types to different product differentiation features. Notably, what we have assumed in our discussion for the sake of simplicity, namely that each product differentiation attribute is created by a distinct PDA, cannot be taken for granted in practice. Investments in product and process redesign could be necessary to separate the activities that create distinct product differentiation features for which customers’ preferences regarding choice, adaptability and reconfigurability are different. Acknowledgments  The authors acknowledge the financial support from the University of Padova (project IDs DOR2073278/20 and DOR1912535/19).

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Varas, M., Maturana, S., Cholette, S., Mac Cawley, A., & Basso, F. (2018). Assessing the benefits of labelling postponement in an export-focused winery. International Journal of Production Research, 56(12), 4132–4151. von Hippel, E. (1994). “Sticky information” and the locus of problem solving: Implications for innovation. Management Science, 40(4), 429–439. Whang, S., & Lee, H.  L. (1998). Value of postponement. In T.-H.  Ho & C.  S. Tang (Eds.), Product variety management (International Series in Operations Research & Management Science, vol 10) (pp. 65–84). Springer. Wheelwright, S. C., & Hayes, R. H. (1985). Competing through manufacturing. Harvard Business Review, 63(1), 99–109. Whetten, D. A. (1989). What constitutes a theoretical contribution? Academy of Management Review, 14(4), 490–495. Wikner, J., & Rudberg, M. (2005). Introducing a customer order decoupling zone in logistics decision-making. International Journal of Logistics: Research and Applications, 8(3), 211–224. Wong, H., & Eyers, D. (2011). An analytical framework for evaluating the value of enhanced customization: An integrated operations-marketing perspective. International Journal of Production Research, 49(19), 5779–5800. Wong, H., & Lesmono, D. (2013). On the evaluation of product customization strategies in a vertically differentiated market. International Journal of Production Economics, 144(1), 105–117. Wong, H., Potter, A., & Naim, M. (2011). Evaluation of postponement in the soluble coffee supply chain: A case study. International Journal of Production Economics, 131(1), 355–364. Yang, B., Burns, N. D., & Backhouse, C. J. (2004). Management of uncertainty through postponement. International Journal of Production Research, 42(6), 1049–1064. Yano, C., & Dobson, G. (1998). Profit-optimizing product line design, selection and pricing with manufacturing cost consideration. In T.-H.  Ho & C.  S. Tang (Eds.), Product variety management (International Series in Operations Research & Management Science, vol 10) (pp. 145–175). Springer. Zinn, W. (1990). Developing heuristics to estimate the impact of postponement on safety stock. The International Journal of Logistics Management, 1(2), 11–16. Zinn, W. (2019). A historical review of postponement research. Journal of Business Logistics, 40(1), 66–72. Zinn, W., & Bowersox, D. J. (1988). Planning physical distribution with the principle of postponement. Journal of Business Logistics, 9(2), 117–136.

The Role of SKU Management in Product Variety Reduction Projects Aleksandra Magdalena Staskiewicz, Lars Hvam, Anders Haug, and Niels Henrik Mortensen

1 Introduction To accommodate customers’ increasing demands for specialized products, manufacturers are offering an increasing amount of standard and customized products. A study reported an average of 1.7 new products being introduced for each phased-out product (Berman & Korsten, 2010). For many manufacturers, this has resulted in uncontrollable product proliferation, which can produce complexity problems for supply A. M. Staskiewicz • L. Hvam (*) Department of Management Engineering, Technical University of Denmark, Copenhagen, Denmark e-mail: [email protected] A. Haug Department of Entrepreneurship and Relationship Management, University of Southern Denmark, Kolding, Denmark N. H. Mortensen Department of Mechanical Engineering, Technical University of Denmark, Copenhagen, Denmark © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 T. Aichner, F. Salvador (eds.), Mass Customization and Customer Centricity, https://doi.org/10.1007/978-3-031-09782-9_2

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chain managers and have large negative effects on operational performance in terms of cost, time, quality, and delivery performance (Berman & Korsten, 2010; Trattner et al., 2019). In this context, a recent survey found that for manufacturing companies, on average, 75% of their revenues are produced by only 13% of their product portfolio (Hirose et al., 2017). To address the problems of managing product variety, many manufacturers initiate product variety reduction (PVR) programs (Hirose et al., 2017; Adams et al., 2016; Byrne, 2006; Wachinger et al., 2019). Unfortunately, many such initiatives do not achieve the intended financial benefits and may even cause revenues to drop (Byrne, 2006). To support companies in addressing these issues, the literature has produced many approaches, techniques, and tools for reducing product variety (ElMaraghy et al., 2013). A large part of this research has focused on reducing component and module variety (i.e., internal variety) while preserving the variety of end products offered in the marketplace (i.e., external variety) (ElMaraghy et al., 2013; Lyons et al., 2020). On the other hand, such approaches do not pay much attention to the relationship between SKU (stock keeping unit) variety and actual product variety. However, there are reasons to believe that this link could partially explain why some PVR projects fail. This study investigates this assumption through an unsuccessful PVR project launched at an international world-­ leading hearing healthcare company to address SKU information and product variety. The rest of this chapter is organized as follows. Section 2 describes the relevant literature. In Sect. 3, we provide the research method, while Sect. 4 describes the findings from the case study. The discussion in Sect. 5 develops a model that links SKU and product variety. The chapter ends in Sect. 6, which uses the findings to make conclusions.

2 Literature Background Researchers have addressed the topic of product variety from different perspectives, and a significant amount of research has been dedicated to this topic. By contrast, the literature addressing the link between SKU

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management and PVM is rather sparse (according to literature searches conducted in research databases by the authors). Thus, product variety and SKU management are discussed separately here.

2.1 Product Variety Management The concept of “product variety” has been attributed various meanings in the literature (Stäblien et al., 2011; Trattner et al., 2017). In this context, a central distinction is the one between component and product variety, that is, “internal variety” and “external variety,” respectively (Götzfried, 2013). Different measures of internal variety can be found, including a variety of components, modules, and functions (Blackenfelt, 2001; MacDuffie et al., 1996); variety ordered by customers (Stäblien et al., 2011; ElMaraghy et al., 2013; Pil & Holweg, 2004); the number of end products offered to customers (Pine et al., 1993); and SKU variants offered by a firm, which differ in physical properties (e.g., size, weight, or color) and quality from a customer perspective (Ulrich, 2011). Regarding external variety, researchers generally agree that this concerns the number of finished goods that are offered to customers (Stäblien et al., 2011; Trattner et al., 2019; ElMaraghy et al., 2013; Pil & Holweg, 2004; Fisher & Ittner, 1999). Another perspective on product variety concerns the decision-making criteria used in variety creation and implementation (Pil & Holweg, 2004; Ulrich, 2011; Ramdas, 2003). Specifically, “variety creation” involves product design decisions that aim to fulfill customer requirements, whereas “variety implementation” involves the supply chain processes that support the variety creation strategy, that is, decisions related to production strategy, organizational capabilities, order decoupling points, and various day-to-day decisions (Lyons et al., 2020; Ramdas, 2003; Pero & Sianesi, 2009; Ferreira et al., 2018). From a cost perspective, decisions about the creation and implementation of product variety should seek to create synergies among products regarding the underlying product technologies, product functions, components, process technologies, production/distribution processes, and customer segment knowledge (Ramdas, 2003). In this context, a distinction can be made between “created variety,” which concerns the different products that a company

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aims to deliver, and “transported variety,” which concerns the different products that a company delivers as a result of variety-implementation decisions (Pero & Sianesi, 2009). In the product development literature, there are several approaches to creating and managing product variety (Ferreira et al., 2018). This includes topics such as modularization (Duray et al., 2000; Fixson, 2005; Mortensen et al., 2010), product platforms (Boothroyd, 1987; Robertson & Ulrich, 1998; Schuh et al., 2019), mass customization (Pine et al., 1993; Zhang & Tseng, 2007), design for X (DfX) frameworks (Martin & Ishii, 1996; Chiu & Kremer, 2011), component standardization (Ramdas, 2003), product/component commonality (Blecker & Abdelkafi, 2007), cellular manufacturing (Houshyar et al., 2014), concurrent engineering (Kusiak, 1992; Alkan & Harrison, 2019), design structure matrix (DSM) (Primmler & Eppinger, 1994), function heuristics (Stone et al., 1998), modular function deployment (MFD) (Ericsson & Erixon, 1999), and design for variety (DfV) (Martin & Ishii, 2002). The literature also includes various techniques for product modeling, product portfolio analysis, and product architecture development (Harlou, 2006; Haug, 2012; Steward, 1991; Bruun & Mortensen, 2013), which supports the creation of visual representations of products’ structure, elements, interfaces, and their combinations. Such techniques include interface diagrams (Bruun et al., 2013), product family master plans (Harlou, 2006), product variant masters (Hvam et al., 2008), and class diagrams (Haug et al., 2010; Haug, 2010). The literature also offers approaches with a mathematical modeling focus (Stone et al., 1998; Gupta et al., 2013). Lastly, some researchers focus on the modeling of product platforms (Bossen et al., 2017; Zhang et al., 2007; Zhang, 2009) and integrated modeling of products and processes (Levandowski et al., 2015; Michaelis et al., 2015; Zhang, 2015; Brunoe et al., 2018). When applying techniques such as those described above, there is a need to consider product design, manufacturing processes, and supply chain design in an integrated manner (ElMaraghy et al., 2013). This is supported by studies that investigated the link between internal and external variables, which found that a lack of alignment between product development and supply chain design has negative impacts on performance (Pero & Sianesi, 2009; Fixson, 2005; Blackhurst et al., 2005;

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Salvador et al., 2002). By contrast, several empirical studies have found that deeper integration between product development and supply chain management (SCM) processes can produce a sustainable competitive advantage (Ghemawat & Nuevo, 2003; Magretta, 1998; Feitzinger & Lee, 1997).

2.2 SKU Management The concepts of “SKU management” and “product variety management” are often used synonymously in the literature. However, strictly speaking, SKU management is more focused on decisions made later in the product variety management process, after product variety is created and implemented. SKU management approaches reduce the negative impacts of SKU proliferation in supply chains, which concern operational performance in terms of order accuracy and order cycle times, as well as operating and capacity costs (Cocozza, 2020). SKU proliferation may occur for different reasons, including customer demand for more variety and higher service levels, which affect supply chain design, customer segmentation, and inventory lifecycle management (Quelch & Kenny, 1995; Cocozza, 2020). To address SKU proliferation, different approaches to SKU reduction have been developed, one of which is the well-known approach by Enz et al. (2019). Practitioners often use such SKU rationalization approaches to improve their product assortment, in the sense that low-volume and slow-moving product variants are eliminated from their product portfolio (Wilson & Perumal, 2009; Hvam et al., 2020). However, the literature has also pointed out two main disadvantages of SKU reduction approaches (Adams et al., 2016; Mahler & Bahulkar, 2009; Trattner et al., 2019). The first concerns the fact that SKU reduction initiatives seem to be a one-time event, with the proliferation processes occurring afterward. The second problem is that SKU reduction approaches do not adequately consider supply chain complexity and operational performance (Coteller, 2012) because they focus too much on product revenue than other costs (Mahler & Bahulkar, 2009). In other words, sales improvements would often be at the expense of operational performance

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because of increased product complexity as a result of introducing new products (Wan et al., 2012). A central topic in SKU management is “SKU classification,” which is often used during SKU introduction and SKU management in the supply chain to deliver product variety to customers. The purpose of SKU classification work is to classify products systematically by considering their similarity regarding their properties (Van Kampen et al., 2011). The use of SKU classifications in SKU introduction concerns giving an individual alphanumeric code to items that differ regarding style, function, size, color, etc. (Silver et al., 1998). In this context, Van Kampen et al. (2011) developed a model that considers the factors that influence SKU classifications, which identify SKU classes with clearly defined boundaries. However, before SKUs can be classified, decisions must be made regarding SKU characteristics and the classification technique. The interrelationships between these three tasks (Van Kampen et al., 2011) are illustrated in Fig. 1. SKU classification initiatives are often a part of production and supply chain management processes that determine inventory, production, and

Fig. 1  Decision steps in the SKU classification method. (Adapted from Van Kampen et al., 2011)

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supply chain decoupling point strategies for individual SKU categories (Van Kampen et al., 2011; Van Kampen & Pieter van Donk, 2014). Companies often apply a limited number of SKU classes based on differences in their characteristics for better decision-making regarding production, inventory, and customer service decisions, that is, the use of SKU classes rather than SKU numbers for each product. There are several SKU classification techniques, including ABC classification (A-products, B-products, and C-products), which uses either demand volume or demand value to classify product groups (Hvam et al., 2020); FNS (fast, normal, or slow) classification, which uses demand rate (fast, normal, slow) to distinguish between product classes (Martin & Ishii, 1997); and vital, essential, and desirable (VED) classification, which supports managers in determining product criticality (Cavaleri et al., 2012). Sammon and O’Reilly (2013) emphasized the importance of applying common ontologies for product variants and SKU variants while avoiding the creation of an excessive amount of SKU variants. Similarly, Haught et al. (2012) developed an SKU classification process that uses the “design for six sigma” methodology for improving SKU variant data quality to avoid SKU proliferation; Khabazzi et al. (Khabbazi, & Shapi’i, A., Hasan, M.K., Sulaiman, R., Eskandari, A. and Taei-Zadeh, A., 2018) developed an object-oriented procedure to create an SKU coding system based on product characteristics; and Khai-Wee et al. (2006) defined a part numbering system to support decisions in mass customization manufacturing environments by identifying data management efficiency improvements.

3 Methodology To investigate the role of the SKU information in PVR projects, an exploratory approach was employed in the form of a single case study. According to Yin (2018), this type of study can be defined as one that “investigates a contemporary phenomenon [the ‘case’] in-depth and in its real-world context, especially when the boundaries between phenomenon and context may not be clearly evident.” The case chosen for the present study is a world-leading international healthcare product

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Table 1  Interviews conducted Department

Position

Global planning

Director, Demand Planner, Sales and Operations Planning Specialist Director Private Label Manager, International Product Manager Product Portfolio Manager

3

5

1 2

2 1

1

5

Senior Manager

1

2

Business Controller

1

2

Business development Marketing Product portfolio management Global supply chain development Finance

No. a No. b

Number of interviewed employees b Number of interviews a

manufacturer. There are several arguments for choosing this case. First, because of acquisitions of other firms, this company had to manage product data across several separate databases, thus constituting a context that, to a large extent, allows for the phenomenon in focus to be studied—what may be described as extreme case sampling (Yin, 2018). Second, the company had initiated several product information management and reduction projects, which implied that the needed data for the study was available. Third, the company offered wide access to the data and persons involved in the project, allowing for deeper investigations. The data was collected over two months in 2021 using interviews and the company’s enterprise resource planning (ERP) system. Information about the interviews is shown in Table 1.

4 Case Study Findings In 2021, an SKU rationalization project was initiated by product portfolio managers at the case company. Their reason for this was that there appeared to be an opportunity for significant SKU reductions in the product portfolio without significantly affecting the product offerings to customers. The SKU reduction in focus concerned 19% of the hearing aids product portfolio. It also involved possible changes to the way the packaging bills of materials (BOMs) were created in the IT system and

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the distribution strategy of these products. However, before implementing such a project, there was a need to investigate its profitability. To clarify the role of SKU information in PVR, we analyzed the ERP system data and conducted interviews with key stakeholders from the company (Table 1). According to these interviewees, most of the complexity in the product portfolio was a consequence of hearing devices offered to private label customers. To investigate these perceptions, data on hearing device products for one year was collected from the ERP system. This involved product data and sales performance (based on quantity shipped from production). A Pareto analysis (Van Kampen et al., 2011) was then conducted. This analysis organized products into two groups: “main brand” and “private label” products. The analysis showed that high-running products contributed approximately 80% of the sales, while medium-runners contributed approximately 15%, and low-­runners contributed 5%. Lastly, the analysis identified several “dead products,” that is, products that were offered but were not shipped from production in the given period. Figure 2 illustrates the results of the analysis. As shown in Fig. 2, private label products constituted 74.1% of the product portfolio, while only representing 20.4% of the total amount of products shipped from production. We also observed that 35.1% of the total amounts of products were dead private label products (47% of all private label products), and 35.7% of the total amount of products were private label low-runners (48% of all private label products). However, only 3.3% were medium- or high-running private label products (5% of all private label products). These findings were discussed among managers from product portfolio, marketing, and global planning departments, after which a more in-­ depth analysis of the private label product portfolio was initiated. Marketing and product portfolio managers were interviewed to achieve a better understanding of the hearing device product offerings for private label customers. In this context, the product portfolio manager said that he saw the potential to reduce the variety of hearing devices offered to one of the private label customer segments. He also pointed to another problem about the management of SKU information: some products were given different SKU numbers across different customer segments. This is exemplified in Table 2.

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Fig. 2  Pareto analysis of products in the case company Table 2  SKU numbering across customer segments Current product portfolio

Desired product portfolio

SKU no. Product description

SKU no. Product description

112211 112212 112213 112214

A09, MNR T R ALIGO 9 Customer 1 112211 A09, MNR T R ALIGO 9 Customer 2 A09, MNR T R ALIGO 9 Customer 3 A09, MNR T R ALIGO 9 Customer 4

A09, MNR T R ALIGO 9

The multiple SKU numbers for the same products led to misunderstandings about how such products were performing; thus, stakeholders from the product portfolio management department expressed desires to

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have only one SKU number assigned to each product. The interviews revealed the reason for the current SKU numbering approach was that private label customers were provided with individual (branded) packaging; that is, the same product was being sold under different brands. The distribution strategy for private label customers includes manufacturing and packaging processes in central production, with the IT system deciding which packaging bill of material (BOM) to use. The packed products are then shipped to local business units that are then distributed to the respective private label customers. The packaging process in production is automated; thus, the IT system that supports the packaging process is expected to provide information on how to pack the hearing aids for a specific private label customer. The IT system supporting the packaging process has a function that allowed creating a BOM that listed items and quantities that should be packaged based on information on the hearing aid item number and customer number describing local business units from which products are distributed to private label customers. An alternative strategy would be to change the distribution process to direct distribution so that products were shipped directly to private label customers, thereby moving the customer decoupling point closer to the customer. In this case, the IT system in production could create the same packaging BOM based on customer number describing the private label customer rather than local business unit from which products are distributed to private label customer. This implies that hearing aids would no longer need to be differentiated using different SKUs. Figure 3 shows the current process and information flow for creating the packaging BOM in production IT system and the discussed alternative strategy. The solution described in Fig. 3 would, according to the global supply chain development manager, require significant resources, that is, the costs of changing data infrastructure, data conversions, and training of employees. Thus, it was decided that the first step would be to analyze the potential benefits of such a solution. The first step of this analysis was to investigate the relationship between SKU numbers and the actual product assortment, which was done in collaboration with the product portfolio management and marketing specialists. The analysis identified 2438 SKU numbers in the product portfolio, representing 19% of the total

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Fig. 3  Process changes for a direct distribution to private label customers and centralized SKU numbering

hearing aid product portfolio. These 2438 SKU numbers pointed to 237 unique product variants; that is, 2201 SKU numbers were redundant. Next, we tried to identify suitable cost factors and define the scope for the analysis. Based on interviews with a financial controller, we identified the cost factors for manufacturing, distribution, and after-sales processes. To determine which of these cost factors were relevant, we sought to identify where in the supply chain SKU numbers were created. This revealed that the assignment of multiple SKUs for the same product variant proliferation occurred because of packaging customization. In other words, SKU proliferation did not occur in manufacturing processes but at the finished goods stage. Thus, the negative impact of multiple SKUs for the same product variant was mainly related to the inventory of finished goods at the downstream supply chain (i.e., distribution, sales, and after-sales processes). Table 3 shows the identified costs.

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Table 3  Identified cost factors related to SKU number proliferation No. Cost factor 1 2

Inventory holding costs for excessive SKUs Increased costs of detecting, improving, and preventing data quality issues resulting from order fulfillment errors (caused by unclear SKU data), that is:   • Increased costs of handling pick, pack, and ship processes   • Increased costs of order entry and order handling   • Increased costs of issuing credit notes

3 4

5

Increased labeling compliance costs for excessive SKUs Increased transportation costs resulting from denying export documentation due to mismatches between product codes or product descriptions Increased capacity costs of planning production and managing the inventory of excessive SKUs

Regarding the size of the cost types described in Table 3, the interviewed supply chain manager said that the number of errors in the order fulfillment process was negligible and that there were no shipping issues due to excessive product data. Similarly, the interviewed business controller confirmed that compliance and capacity costs of global planning because of SKU proliferation were relatively insignificant compared to the costs of holding inventories. Thus, based on the interviews conducted, it seemed reasonable to assume that distribution, sales, and after-sales processes would not be significantly affected by a reduction of SKU numbers. The product portfolio manager also pointed out that there could be potential savings from label printing with fewer SKU numbers. However, the overall costs of label printing were found to be relatively unsubstantial compared to other cost factors. Therefore, the focus was turned toward the impact of SKU proliferation on inventory costs. The impact of SKU proliferation on inventory holding costs was analyzed by using inventory and sales data from the ERP system. We also included expenses related to holding inventory, such as interest rate paid to banks for loans related to purchases of inventory, building-related expenses, insurances of stock, and costs of obsolescence. In this context, data from 2019 was used, since the 2020 data was greatly impacted by the COVID-19 pandemic.

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Regarding inventory holding costs, a distinction was made between production strategies, that is, make-to-order (MTO) versus make-to-­ stock (MTS) production. The safety stock criteria used by demand planners were also considered. The demand planners said that the ten-day safety stock was based on historical data related to the annual quantity shipped out of production while considering the MTO and MTS production strategies. Thus, the finished MTO products had no inventory holding costs at the finished goods level, as these were shipped right after production, while the MTS products did. However, the MTO products shared the same safety stock criteria as the MTS products at the component level, and since the MTO products were low-running products, they had a negligible impact on the inventory holding costs. Table 4 shows how many SKUs were MTO and MTS products based on their performance in terms of quantity shipped out of production. It should be noted that MTO products were always the “low-runners” and “medium-runners” (as well as the “dead products”), while MTS products were the “high runners.” The analysis assumed that the annual demand would not change after the reduction of SKU numbers; thus, the demand for the pre-SKU reduction scenario was distributed across the product portfolio for the post-SKU reduction scenario. This mapping made it possible to determine the effects of reducing the SKU numbers. We observed that most of the identified private label SKUs were dead or low-­ running products (84%), while there were relatively few high-running products (16%). A reduction of SKU numbers may produce a significant Table 4  Results of SKU reduction in product portfolio Product portfolio performance Category Dead products Low- and medium-­ runners High-runners

Product portfolio Product portfolio before SKU reduction after SKU reduction

Production strategya

Number of SKUs

MTO MTO

1264 787

56 70

MTS

387

111

2438

237

Total number of SKUs

Number of SKUs

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improvement, as the number of dead and low-running SKU numbers would drop (by 31%) in favor of the high-performance products. As shown in Table 5, an SKU number reduction project would reduce the inventory value by 30,486 euros, which was only 0.03% of the total value in production. The savings from having fewer products in safety stock would only be 1398 euros. However, the costs of initiating an SKU reduction project were estimated to be significantly higher than these savings, at least from a short-term perspective. The SKU reduction project described above would involve costs of analysis, design, and implementation of a new system infrastructure, which would include changing the information flow in multiple ERP systems, modifying packaging BOMs, changing processes for the new distribution strategy in business units, and training of local customer service departments. Thus, the project was temporarily abandoned. However, from a long-term perspective, the costs of the poor overview of products should be considered. Therefore, this kind of initiative would likely be included in future system infrastructure changes.

Table 5  Impact analysis of SKU reduction on the cost Product portfolio Product portfolio performance before SKU reduction

Product portfolio after SKU reduction

Annual demand (based on quantity shipped) [euro] Average annual quantity on hand Average annual inventory value [euro] Average annual inventory value for safety stock [euro] Inventory holding cost for safety stock [euro]a Total inventory value in production [euro]b

1,574,332

1,574,332

8738

8258

246,666

216,180

82,115

63,518

6159

4761

99,862,600

99,832,114

a b

Applied inventory rate of 7.25% for inventory holding cost Inventory value = annual quantity on hand * standard cost of hearing aid

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5 Discussion In the case studied, the potential savings from PVR appeared to be insignificant. The short-term savings from reducing the discrepancy between the SKU and product-level variants were also considered insignificant concerning inventory costs, as the company already had a production strategy about low- and high-runners, where high-runners were MTS and low-runners were MTO products. Specifically, the negative impact of having multiple SKUs for the same product variant was mitigated by the MTO production strategy, which implied that there was no need to keep a safety stock for low-running variants. However, reducing SKU-­ product discrepancy would have been associated with several costs associated with initiating, designing, planning, and executing the SKU standardization project. Nevertheless, from a more long-term perspective, there could be a basis for considering changing the SKU management strategy to the one presented in Fig. 3. As illustrated by the case study, product variety can be discussed at three different levels, as shown in Fig. 4. The circles show instances, and the arrows show their mapping. Sometimes, there are SKUs for products that do not exist (e.g., phased-out products), and sometimes, there are several SKUs for one product. There could also be a discrepancy between the actual and “optimal” product variety, implying that certain product variants can be eliminated, which is the focus of PVR projects. As mentioned previously, existing approaches to PVR seem to assume that data on products included in the product assortment is readily available—or at least, they do not consider situations in which information is

Fig. 4  Three levels of product variety

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Fig. 5  Implications for research and practice

not available. However, as shown by the case study, there are two levels of discrepancy that need to be considered in PVR projects. Before considering how the actual product assortment can be reduced, there is a need to clarify and eliminate the discrepancy between the SKU and product-level variants. This is illustrated in Fig. 5.

6 Conclusion To understand the role of SKU management in PVR initiatives, a case study was conducted at a world-leading international healthcare product manufacturer. This study gave rise to two main contributions. First, the case demonstrated that SKU reduction projects do not always produce financial benefits. In the case study, the main reason for a lack of benefits from an SKU reduction project was that the company had an SKU management strategy of dividing products into low-runners and high-runners, which, to some extent, mitigated the negative effects of SKU proliferation. Another main cause for the failure of the SKU reduction project was that the identified SKU proliferation as a consequence of their brand differentiation strategy, indicating that different SKU classifications were applied across multiple production lines (Berman & Korsten, 2010). This implied that an SKU reduction initiative would not produce many benefits, since the product portfolio could not be cut adequately in terms of fixed costs and overhead (Wilson & Perumal, 2009; Byrne, 2006). Thus, the SKU reduction project was abandoned because of its limited benefits. Specifically, the analyses showed that inventory holding

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savings would be insignificant, that is, 1398 euros, which accounted for only 0.03% of the annual inventory value. However, as pointed out by several stakeholders at the company, an SKU reduction initiative could be made possible if a strategy of moving the customer decoupling point closer to the customer was implemented. The second main contribution concerns the development of a model that illustrates two types of discrepancies that need to be considered in PVR projects, that is, the discrepancy between SKU numbers and actual product variants, and the discrepancy between actual product variants and the “optimal” number of product variants. Existing methods for PVR tend to assume that information about the actual product variants is readily available, or at least do not provide guidelines for what to do if this is not the case. However, as illustrated by the case study, analyzing such discrepancies is relevant. Thus, we argue that existing methods for PVR should be extended to include an SKU–product variety discrepancy analysis. For practitioners, the findings of this study may raise awareness of the importance of considering SKU–product variety discrepancy before initiating PVR projects. Such analyses may help identify projects that, from an SKU number perspective, promise but cannot deliver great benefits from PVR, since the apparent superfluous product variety is rather a consequence of SKU numbering issues. It should be emphasized that the present case study was conducted in a large international company, involving different wholesalers with separate product databases, which was a central explanation for the discrepancy between the SKU and product-level variety. Thus, it could be assumed that smaller companies with a greater degree of shared product databases may face smaller problems in this regard. Nevertheless, the phenomenon of mismatches between the SKU and product-level variety is common in such firms (Cocozza, 2020; Fortna., 2021). Thus, the consideration would be relevant in most cases, warranting more studies that would shed light on the matter.

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The Internationalization of SME Production: Organizational Challenges and Strategic Opportunities Igor Kalinic

1 Introduction Due to the rapid changes that have occurred during the last few decades, most companies have been affected at least by some type of international challenge. Sales, marketing, joint ventures, outsourcing, sourcing, research cooperation, international competition, and foreign direct investments are just some samples of the possibilities and the challenges that a company is facing. Year after year, the increasing percentage of foreign direct investments and international trade confirm this. It is generally agreed upon that the increasing globalization trends and international competition are due to three main factors (Fuzzier et al., 2006). First, technological advancements improved transport and made it cheaper, quicker, and safer; it also enhanced communication by making it better, easier, and global. Second, the reduction of trade barriers

I. Kalinic (*) European Innovation Council and SME Executive Agency, European Commission, Brussels, Belgium e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 T. Aichner, F. Salvador (eds.), Mass Customization and Customer Centricity, https://doi.org/10.1007/978-3-031-09782-9_3

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facilitated the exchange of goods and services worldwide and the establishment of new facilities in different countries. Third, the reduction of political barriers allowed the companies to access and operate easier in different, unexplored markets. Initially, mostly only big multinational companies (MNCs) were trading and investing internationally. Later, it became possible also for the small to medium-sized enterprises (SMEs). In 1997, more than 25% of the SMEs around the globe were gaining greater than 10% of their revenues from foreign sources (OECD, 1997; Shrader et al., 2000). Further, OECD’s (1997) study found that year after year the SMEs’ participation in international trade and investments is more relevant and growing. Notwithstanding, 20 years later SMEs tend to be under-represented in international trades, and still, a relatively small part of them are present at an international level (OECD, 2019). For example, the European Union’s SMEs are among the most internationally active; however, only about 26% of them exported services or goods in 2019 (European Commission, 2019). Furthermore, only 4% invested directly in a foreign-­ based company and less than 10% of EU SMEs collaborated with an abroad-based company (European Commission, 2014). Nonetheless, the SME internationalization process merits great attention given the high and increasing relevance of SMEs in the worldwide economic systems. SMEs account for over 90% of firms in most economies; they contribute to industrial upgrading and innovation, and are often the main player for pushing forward the boundaries of new industrial sectors (World Bank, 2011). In most of the developed countries with high-income economies, they contribute between 50% and 60% to total value added and represent 70% of total employment (OECD, 2017). These numbers are even more impressive in the EU with more than 25 million SMEs, that is, 99.8%1 of all the enterprises, 66.6% of employment, and generating 56.4% of added value (European Commission, 2019). Attention to this phenomenon requires specific investigation since it is not possible to directly transfer what we learned from the big multinational companies to the SMEs. Actually, the differences between big companies and SMEs are numerous and not negligible (McDougall et al.,  In the Non-Financial Business Sector (NFBS).

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1994; Knight, 2001; Brouthers & Nakos, 2003; Vachani, 2005; Trautmann et al., 2007). Just to mention some: SMEs have less financial power, MNCs’ organizationally structured is more explicit, MNCs’ management experience is wider and greater, SMEs have a bigger flexibility, SMEs have fewer resources. These differences make the internationalization processes of SMEs different in several aspects from that of the MNCs. In the last three decades, the research has considerably advanced our knowledge on SME internationalization; nevertheless, it focused mainly on how antecedents influence outcomes (for a literature review on the subject, see Keupp & Gassmann, 2009). In their literature review, Jones et al. (2011) noted that the research concentrated on exploring the capabilities moderating and mediating the internationalization process, the firm’s performance, and where and how the firm internationalizes. That happened despite the common understanding that the internationalization is an evolutionary process during which the firms adapt to the new environment (Calof & Beamish, 1995) and that internationalization is a dynamic and bi-directional phenomenon (Johanson & Vahlne, 1977) with internal changes being essential constituents of the internationalization process itself (Welch & Luostarinen, 1988). The research has somehow neglected the impact of the internationalization process (especially the more complex and holistic ones that involve not only commercial expansion but also the establishment of production units abroad) on the organizational elements of the home headquarters and how the company manages the change in order to maintain the previous and acquire new competitive advantages. Christensen (2003) highlighted that “up-stream studies and studies of reproductive entrepreneurs as well as studies of entrepreneurial processes embedded in the internationalization process itself ” have been somehow neglected by the research community. Nummela et al. (2006) stress that “it remains unclear how the key business operations change during internationalization, and what kind of resources and skills—on both the organizational and the individual level—are needed to manage the internationalization process successfully.”2  Van de Ven and Poole (1995, p. 512) define change as “the difference in form, quality or state in an organization over a selected time period.” 2

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Therefore, the goal of the present research is twofold. First, we explore the extent and impact of the internal changes due to the establishment of a production unit abroad. Second, we aim to understand how the company managed the process to develop (further sustainable) competitive advantages.

2 Literature Review Internationalization has been widely studied by many researchers. We can distinguish two main streams: MNC internationalization and SME internationalization. The studies about MNC internationalization began during the 1950s (Fuzzier et al., 2006), and several theories have been presented to explain why firms engage in international operations (Westhead et al., 2001) such as product cycle theory (Vernon, 1966), monopolistic advantage theory (Hymer, 1976), internationalization theory (Buckley & Casson, 1976, 1993), transaction cost theory (Williamson, 1975; Gilroy, 1993), and eclectic theory (Dunning, 1988). The research on SME internationalization started in the early 1970s in the Nordic countries. The main output had been the Uppsala model (U-model) (1977, 1990, 2003). Johanson and Vahlne’s (1977) U-model describes the SMEs internationalization process as “a gradual acquisition, integration, and use of knowledge about foreign markets and operations and a … successively increasing commitment to foreign markets” (Gankema et al., 2000). In this dynamic model, the internationalization of the firm is seen as a process of increasing a company’s international involvement as a result of different types of learning (Fuzzier et al., 2006). Another model developed in those years is the Innovation-related Internationalization Model (I-model) (Cavusgil, 1980; Gankema et al., 2000). “The term ‘innovation-related’ is derived from the work of Rogers (1962, cited in Gankema et al., 2000), in which each subsequent stage of internationalization is considered as an innovation for the firm (Gankema et al., 2000). Their focus is exclusively on the export development process, in particular of small and medium-sized firms” (Fuzzier et al., 2006). Both the U-model and I-model assume that the internationalization

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process starts with sporadic overseas sales and continues with bigger and bigger commitments in the foreign markets through sales. The start-up of overseas production units is seen as eventually the last stage. Those models were increasingly challenged by empirical findings that some SMEs are able to internationalize more rapidly than the models predict (Oviatt & McDougall, 1994, 2005). As a result, a new subfield in international business emerged: “International entrepreneurship” (McDougall & Oviatt, 2000; Peng, 2001). It outlines that knowledge-­ intensive and knowledge-based firms are likely to have an accelerated internationalization focusing their attention particularly upon International New Ventures (INV), “Born global” or “Born-again global” firms (Bell et al., 2003). During recent years, a number of efforts have been done to achieve a deeper understanding of the internationalization processes of SMEs. Many researchers used the network approach (Oviatt & McDougall, 2005), organizational learning theory (De Clercq et al., 2005; Oviatt & McDougall, 2005), and/or Resource-Based View (RBV) (Peng, 2001; Westhead et al., 2001). Given our goal of understanding whether the changes brought sustainable competitive advantage (SCA), RBV results are particularly suitable. The RBV is a theoretical perspective that explains how the control over (new) resources can put a firm in a (sustainable) advantageous position over its competitors (Wernerfelt, 1984; Barney, 1991; Grant, 1991; Peteraf, 1993). Therefore, the use of the RBV in investigating SMEs’ internationalization adds the possibility of a deeper understanding of its strategic implications. In addition, we use elements from the information processing view (IPV) (Galbraith, 1974) to understand how the company manages the change process to improve the firm’s performance. The IPV results are particularly suitable to analyze processes that intrinsically bring an increased complexity which is typical when a firm expands by, for example, establishing new subsidiaries. In the following section, we develop an ad hoc research framework to answer the research questions.

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3 Research Framework We became aware of the specific internationalization process mentioned above during the preliminary part of our study where we performed 25 interviews, 6 case studies, and assisted 11 SMEs during the establishment of a production subsidiary abroad. Consequently, for the preliminary research, we developed a research framework as it is shown in Fig. 1. In the beginning there is an SME. Due to the external (cost, market, normative and/or regulative, geographic, etc.) opportunities/threats, the management/entrepreneur starts performing the internationalization of production. The influence of opportunities and threats continues afterward. SMEs that follow this process start owning, controlling, or being in joint ventures of production units outside the original country often without having had relevant business knowledge of those countries or regions. The process of internationalization, usually, induces some changes inside the organizational elements of the SME. For example, there is a formalization process of the tacit knowledge; the strategic choices become more international-oriented; the managers’ duties and responsibilities are more precisely defined. These changes lead to the modification of some resources/capabilities3 or to the creation of new ones.

Fig. 1  Research framework

 While aware that there are differences between the concepts of resources and capabilities, in this study we use those terms interchangeably. The differentiation would increase complexity without bringing additional value at this point of the exploratory study. 3

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From the preliminary research, we received inputs that indicate that SMEs, while internationalizing the production, improve their capabilities. Thereafter, the improvement of capabilities can bring sustainable competitive advantage to the SMEs that have internationalized their operations in comparison with the ones that stayed local.

4 Method To answer the above-mentioned research questions, we performed a case study. Our contribution is consistent with other works in the field when investigating the same type of questions, that is, the how and why of barely investigated issues (e.g., Oviatt & McDougall, 1995; Bell et al., 2003). Case study research method has a high exploratory power and allows dynamic processes to be more deeply investigated (Eisenhardt, 1989; Yin, 1988). In particular, the case-based method reveals itself particularly useful in those research contexts where previous theory seems to be inadequate or incomplete and thus new theory development is required. This is our case since previous research does not seem capable of explaining the consequences of the internationalization process on the internal elements of an SME. The notion of sustained competitive advantage as a study object requires particular attention to be given to the research design because of the longitudinal perspective needed (Barney et al., 2001). Besides, when the focus is on change processes, longitudinal research is recommended as it permits the identification and observation of processes (Nummela et al., 2006). For this reason, this study takes a retrospective perspective, that is, we do not observe in various point of time the internationalization process coming back to the company from time to time; on the contrary, we ask the company informants to tell us what happened starting from a time precedent to the start of internationalization We identified an SME, from Northeast Italy called Manu-Intl.4 It belongs to the manufacturing industry. We chose Northeast Italy as in this region there is a high concentration of manufacturing SMEs and a  The name and some information about the company have been disguised to ensure anonymity.

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relevant number of them internationalized their operations. In the company, we interviewed two Chief Executive Officers (CEOs), the purchase manager, and the production manager. We developed a semi-opened questionnaire and we tested it in preliminary interviews with eight experts in the internationalization processes of SMEs. We submitted a number of structured questions designed to gather data for classification purposes (firm size, age, export experience, export ratio, first export market/s, current market/s, etc.). In addition, we used a series of open-ended questions to probe the strategic directions of firms and underlying reasons for key internationalization decisions and changes.

5 Manu-Intl and the Internationalization Process Manu-Intl designs, manufactures, and sells a wide range of compressors worldwide. The company was founded in 1992 by four experts in the field. The company started selling abroad in 1995 in the Western Europe. The expansion on the European market was quite rapid and in 1998 established a 50% owned trading company in Romania. Afterward, they started expanding the sales worldwide in Australia, South Korea, and Venezuela through a network of dealers and after-sale service providers. In 2002, they started the internationalization of upstream activities, that is, the establishment of a production subsidiary. At that time, the turnover rose to around 10 million euros; they had 45 employees and the share of the national market was around 60%. Their success continued and five years later the turnover increased to 15 million euros. Also, the number of employees increased (both at home [55] and abroad [20]) and the share of exports grew to 60%. The internationalization of production took place quite late in comparison with other SME mechanical companies in the same region. In 2002, the company went to Bosnia to identify an opportunity to distribute its products in the Balkan area. Earlier, Manu-Intl’s presence in the area was negligible. In 2002, Manu-Intl founded a small local trading company that was already selling the compressors in Bosnia and Serbia.

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Manu-Intl perceived this company as very trustable and considered the idea of producing locally to deal locally. The presence in the local markets was the main reason for which Manu-Intl decided to set up there, even though the low labor cost was a nice advantage. Together, they founded in 2002 in Bosnia a new company, owned 50% by Manu-Intl. The scope of the new company consists in assembling the kits of compressors sent by Manu-Intl, selling the compressors in the local and neighbor markets, and providing the after-sell service. In the beginning, Manu-Intl trained Bosnian employees to assemble the simplest compressors, after three to four years they transferred the know-how in assembling other more complex compressors but still belonged to the low technological segment. The training was performed both in Italy through a short two-week visit of Bosnian workers and in Bosnia through short visits of Italian managers and workers. After this first internationalization of production, the Manu-Intl’s internationalization process continued. During 2006, they established a 50% owned company in Brazil, where they assemble the air compressors for the Brazilian market.

6 Changes and Organizational Implications During the establishment of the production subsidiary abroad, and consequently to it, Manu-Intl performed several internal changes that modified the resources at their disposal. We identified these changes and highlighted the modifications that they bring into the various organizational elements. The organizational elements are adapted from Waterman et al. (1980). As they claim, “the effective organizational change is really the relationship between” structure, strategy, systems, style, staff, organizational capabilities, and shared values5 (Bernardi, 1989). Hereinafter, we describe each change and which organizational element is influenced by  Contrary to the original version (Waterman et al., 1980), we use “organizational capability” instead of “skills” and “shared values” instead of “superordinate goals.” In the first case, the reason lies in the fact that “skills” can be confused between individual and organizational level. In the second case, we consider that “shared values” is closer to the original definition; that is, “a set of values and aspirations, often unwritten, that goes beyond the conventional formal statement of corporate objective.” 5

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it. Some changes influenced more than one element and we are aware that some can be seen from different points of view.

6.1 Formalization The assembling of many products is performed in the foreign subsidiaries with the workers that do not speak Italian. Thus, it was necessary to produce more precise, more detailed, and simpler schemes of the compressors and assembling instructions. It was also necessary to prepare a more complete list of spare parts. Furthermore, this formalization had to be anticipated to make available all the mentioned documents before the assembly process could start. The formalization influenced organizational capabilities (more formalized and more precise procedures) and shared values (developing proactiveness throughout the company to foresee possible upcoming problems).

6.2 Assembling Process The preparation of the assembling process was re-designed, preparing in advance the spare parts and the assembling kits to ship to the foreign subsidiaries. This was made in order to ensure more efficiency and a higher-quality assembly with less-experienced workers. The changes in the assembly process influenced shared values (developing proactiveness and improving efficiency).

6.3 Staff When they started working in Bosnia, there was a problem of communication as the Bosnians could not speak Italian and Italians could not speak the local language. So, Manu-Intl decided to hire a person in administration fluent both in Italian and Serbo-Croatian that could help with translations. Due to the increase in the workload, they also hired more workers in the production department. Further, Manu-Intl hired and changed some

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people in the Sales and Design departments. When changing people they substituted with higher-skilled people. Also, the manager of the Production unit was substituted by a higher-skilled manager. These substitutions are due both to the internationalization as well as the growth of the company, and the distinction is not simple. Hiring influenced staff (more staff with more individual skills), organizational capabilities (departments with more skills), and structure (strengthening of technostructure).

6.4 Design Technology The internationalization process accelerated the switching from 2D to 3D drawings of technical schemes. They started using the 3D drawing more, as the assembling instructions and schemes had to be more precise, simpler, and more detailed. However, the new technology spread quickly across the company; 3D schemes started to be used also for the projection of new machines (not only assembling instructions) and also by the sales team. The CEO estimated that the internationalization of production pushed them to anticipate two to three years of the systematic use of 3D. 3D technology influenced systems (systematic use of 3D drawing) and organizational capabilities (cross-functional use of 3D drawing)

6.5 Communication Technology The abroad subsidiary’s production unit misses some expertise present in the Italian headquarters. They need several and constant technical help. In order to improve the communication between the two production units, the workers were supplied with webcams. Consequently, the workers were able to solve a number of issues without involving managers and, in this way, they improved the cooperation between different plants. Communication technology influenced systems (simplified communication systems) and shared values (bigger cooperation between workers, including low-skilled ones, in different plants).

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6.6 Self-awareness After setting up the first production subsidiary abroad in Bosnia, Manu-­ Intl became aware of the fact that they could do it. This increased their self-confidence and opened the possibility to re-do it somewhere else in the world. The increased awareness influenced shared values (at the beginning several workers and managers were skeptical regarding the internationalization) and strategy (the strategy has been redefined opening to the possibility to establish more production facilities aboard).

6.7 Entrepreneurs’ Mentality When the CEOs established the company, the business horizon was the province, with the aim to grow step by step throughout the region and, consequently, the country, basing their expansion on sales. After the internationalization of production and together with the world globalization process, they changed their mind. According to the CEOs, if they have to establish a new company today, they would plan it as Born Global, organizing it immediately ready for the production and sales internationalization. The change in the entrepreneurs’ mentality influenced shared values (the Manu-Intl, its management, is more globally oriented).

6.8 Workers’ Mentality When the CEO decided to internationalize the operations in Bosnia, a portion of the workers was afraid that the whole production would be transferred abroad and that they would lose their jobs. But this did not happen; vice versa, the production increased (they had to produce and prepare the spare parts also for the Bosnian subsidiary) and, consequently, the number of staff increased both in the production and other departments. Thus, the workers increased open-mindedness, lowering the suspicion toward internationalization. In general, according to the managers, there is a lower aversion toward the change. The different workers’ mentality influenced shared values (lower aversion toward the change).

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6.9 Production Department’s Role Before starting the internationalization of production, the duty of the production department consisted in producing the spare parts and assembling the compressors. After establishing a company in Bosnia, the production department in Italy also has to train Bosnian workers. In addition, they are also asked to supervise and report about the production abroad. This influenced structure (more lateral relations between different production units and additional tasks assigned to the production department at the headquarter), organizational capabilities (production department with more competencies), and systems (different control management, using, also, web technology).

6.9.1 Sourcing Nowadays, it is important for a company to find resources worldwide, where the cost is lower. But, for an SME it is difficult to perform real sourcing in foreign countries as it involves an effective presence in those countries. It can be too costly or it requires human capital (international purchase managers) that an SME does not have. Manu-Intl, having established production and sales units abroad, can purchase efficiently and effectively raw materials and spare parts in those countries. In this way, also specific spare parts for the country-specific products (due to different regulations) are purchased in the local market simplifying the flow of materials. Multinational sourcing influenced strategy (multinational purchase strategy), structure (spread purchase department), and systems (simplification of flows of materials).

6.10 Designing Produced in a specific country, the compressors have to follow the local regulations, but they have to be adapted also to the local climate conditions. Therefore, it is necessary and/or worthy to slightly re-design the compressors for the local market. If the difference contributes to an

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improvement of the compressors or if the cost of the change is negligible, then this change will be brought to all the products. In this way, there is a slowing down of the variety proliferation (standardization of spare parts) and increasing quality with more global products. Multinational design influenced strategy (mass customization), systems (cross-plant design), and organizational capability (multinational design).

6.11 Regulations’ Knowledge Producing in a specific country, the compressors have to follow the local regulations. Being in contact with the local designers and technicians, there is an improvement in the knowledge of the local regulations. That influenced organizational capabilities (more regulations knowledge).

6.12 Market Knowledge When producing industrial machines in a country it is easier to sell in that country for several reasons, among which the company is closer to the clients, the clients feel the product is national, and the possibility of after-sell assistance is greater. By selling more products locally, Manu-Intl achieves more knowledge of the local and regional markets. This influenced organizational capability (more market knowledge). When establishing a production and sales unit abroad, the financial, time, and human resources investments for an SME are notable. Before starting, it is necessary to perform a scrupulous market and business analysis. Manu-Intl improved its analysis methods. The improvement influenced organizational capability (improvement of analysis methods) and systems (data collection).

6.13 Relationship Managers–Workers When the CEOs decided to internationalize the operations in Bosnia, a part of the workers was suspicious of the managers, believing that they would transfer the whole production abroad and, thus, the workers

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would lose their jobs. But, this did not happen; vice versa, the production increased and, consequently, increased the number of staff in the production and other departments. Thus, the relationship between managers and workers improved, and the workers began to have more understanding of the managers’ decisions. After establishing the company in Bosnia, it was necessary for the Italian workers and managers to visit the Bosnian subsidiary to train and assist local workers. During business trips, some of the internal barriers between managers and workers were broken and the mutual understanding improved. The change in relationship influenced style (how management and workers relate to each other).

6.14 Branding Having different plants across the world gives the possibility to present the company in a different way. Now, Manu-Intl appears bigger, as a company that is capable of facing problems in different situations and as a company that can guarantee a continuous service in those countries where it is present with production units. The new branding influenced strategy (a more capable, global, and flexible company).

6.15 Strategic Planning Having the production abroad implies more problems and more complexity. Thus, Manu-Intl started reviewing strategies more frequently. They adjust the direction more in advance. The higher frequency of strategic planning influenced strategy (a bigger scope of strategic possibilities) and shared values (developing anticipating culture). From the analysis, it emerges that the establishment of a production subsidiary in a different country triggered a relevant number of changes. Furthermore, some changes or groups of them can vary the state of some resources/capabilities transforming them into valuable, rare, imperfectly imitable, and not substitutable or, even, create some new resources/capabilities; in other words, the company gained sustainable competitive advantages (SCAs).

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7 Sustainable Competitive Advantages Analyzing the firm’s history and changes and considering the firm’s growth we found that consequently to the internationalization of the production Manu-Intl gained SCAs. Hereinafter, we identify the SCAs— acquired due to the changes caused by the internationalization process— which allowed the company to improve its performance, especially over the similar size competitors that remained local.

7.1 Awareness of Internationalization Possibilities Competing in the industrial equipment industry requires an effective presence in the local market especially to be able to provide customized products and efficient services. For an SME establishing a company abroad able to provide after-sale services can be very demanding from the financial, time, and human resources’ point of view. However, Manu-Intl realized not only that they can do it but also that it pays back. Following the internationalization’s efforts to establish a production subsidiary, Manu-Intl’s managers became aware of the fact that they are able to produce, sell, and provide after-sell service efficiently and effectively both in Italy and in a foreign country. In this way, they re-designed the firm’s strategy. They included the possibility to establish more subsidiaries in different geographical areas able to answer to the specific local needs. Thus, Manu-Intl gains competitiveness through a presence in foreign markets by keeping the typical flexibility of an SME.

7.2 Improved Complexity Management Manu-Intl, selling and producing compressors in different countries, is forced to adapt them to the specific market regulations and the local climatic environment. On the one side, Manu-Intl purchases in the local market-specific spare parts for the country-specific products (due to different regulations). The differentiated part is managed locally avoiding

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the intersection of the fluxes. The logistics fluxes are, thus, kept simple. On the other side, Manu-Intl re-designs slightly some compressors for those markets, but when the difference contributes to an improvement of the compressors or if the cost of the change is negligible, then they transfer this change to all the products. Through spare parts standardization, they reduce the variety of components while providing products tailored to each specific market. Putting together these two aspects, Manu-Intl learned how to manage the increased complexity, maintaining the production flexibility, and improving efficiency.

7.3 Reduced Resistance to Change When CEOs planned to open a new production unit, usually, the workers saw it suspiciously. They considered it a threat to their job as their productivity would be compared. This is particularly stressed when the CEO plans to open a new production unit in a low-cost labor country as Bosnia is. However, consequently, to the positive impacts that the establishment of the production subsidiaries abroad had also to the headquarters, the resistance to change was reduced and the confidence in the management increased. Thus, the entire organization became more dynamic and versatile.

7.4 Augmented International Open-Mindedness Manu-Intl started exporting in 1995. Its export growth was quite rapid, thanks to the contemporary development of a more global management vision. Since the establishment in 2002 of the production subsidiaries abroad, the Italian workers entered into constant almost weekly contact with workers and managers from different countries. The entire production unit became more international and global oriented. They seek solutions outside the boundaries of their own factory and in collaboration with other subsidiaries. As a result, there is an alignment of the workers’ shared values to the management’s international strategic vision.

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7.5 Improved Branding Strategy: International but Flexible Manu-Intl is present with production, sales, and after-sale service in Italy, East Europe, and South America. Therefore, it appears as a multinational company that is capable of facing problems in different situations and as a company that can guarantee a continuous service in those countries where it is present with production units. Through new branding, they acquired a competitive advantage over small-medium competitors as they guarantee the same flexibility and service but on a multinational level. They acquired a competitive advantage over big multinational companies as they guarantee multinational coverage but with the typical flexibility of an SME.

7.6 The Increased Vision of the Future A company is forced to review its strategy more frequently when environmental complexity and problems increase. Manu-Intl started reviewing strategies more frequently as the internationalization process brought many problems and additional complexity. The higher frequency of strategic planning implies a bigger scope of strategic possibilities and adjusting the direction more in advance. Therefore, the management increased the vision of the future despite the increased level of uncertainties and environmental turbulence. They reduced the risk of being damaged by external changes as they considerably increased the capability to manage those changes on a global scale.

8 Discussion and Conclusions As recently noticed by Christensen (2003), “up-stream studies and studies of reproductive entrepreneurs as well as studies of entrepreneurial process embedded in the internationalization process itself ” have been somehow neglected by the research community. Despite the changes that occurred in the last decades and that an increased number of SMEs are

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presented with the opportunity to internationalize their production, we still know little about the changes stimulated by the internationalization of production and the strategic implications (Keupp & Gassmann, 2009; Jones et al., 2011). The purpose of this research is to contribute to filling this gap by addressing some key issues on the agenda regarding the development of the SME internationalization theory. The results of the analysis indicate that the internationalization of the production brought several sustainable competitive advantages over the competitors that stayed local. Considering it together with the number and type of changes induced by the process, we suggest that the internationalization of production for an SME is a phenomenon with both complex implications and potentially positive impacts that go beyond the simple return on investment. Having different production subsidiaries in different countries makes the entire system wider and more complicated. Geographical distance and the involvement of an increased number of sales, logistics, and production departments in the order acquisition and fulfillment of the process orders tend to extend the operational times. Furthermore, working with different languages in countries with different cultural backgrounds, regulations, and norms also brings more complexity. In order to manage the increased complexity, a firm needs to perform several changes (IPV). By the way, a firm establishing a foreign subsidiary can build on those new resources and use economies of scope to develop SCAs over competitors that stayed local. From the research, it emerges that by producing in a market, the company achieves reliability in that market; achieving reliability, market share grows; a bigger market share implies more contacts, and more contacts mean greater market knowledge. In this way, the company sells more; therefore, produces more, and the cycle re-starts. The SCA consists of the virtuous circle that has been formed and that produces, nearly automatically, value in terms of knowledge, brand, and sales. From this perspective, IPV can help in explaining how SMEs’ organization is re-designed during the internationalization of production: internationalization increases complexity and uncertainty, and the company reacts by increasing information processing capability and by limiting the amount of information processed. SMEs adapt the organizational elements and optimize the activities between the parent company and

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subsidiaries. The whole process is quite resource-demanding and complicated. However, the study suggests that the increased sales (and return on investment) are just the tip of the iceberg in terms of a firm’s success. The real advantages over the competitors that stayed local consist of having developed the company from a strategic point of view. An SME with international production is more flexible yet more structured. It is more agile to respond to external threats with an increased global vision but is still capable of offering the customizable products and services. The present research is of exploratory nature. It is necessary to perform a more in-depth analysis to understand the relations between the internationalization of production, changes, resources/capabilities, and SCAs. It is necessary to analyze more cases: firstly, in order to have the possibility to generalize the results; secondly, to compare the results by identifying relevant control variables; and thirdly, to check if there are other changes (consequently to the internationalization of production) that bring SCAs. In order to understand better the achievement of SCA, it is necessary to analyze and compare each company studied with the situation of its competitors. Another limitation of the research consists in the identification of changes. A retrospective research design is always problematic as the respondents’ answers can be biased by time perspective and memory. Besides, it is difficult to separate changes related to the internationalization of production from other changes that occurred in the company. For what concerns the implications, we think that adding the present study to the mainstream theories on SMEs internationalization can bring under the academic community scrutiny a proposal of a specific advancement of this theoretical body, stimulating, thus, the debate on this research topic. This study is an attempt to respond to increasing criticism of the existing theory of internationalization offering a novel perspective to SME internationalization. From the practice point of view, the results stimulate policymakers to encourage the internationalization process of SMEs and stimulate entrepreneurs to consider expanding internationally their production. In fact, the internationalization of production seems to increase the SMEs’ capability to survive in the global world and to grow dimensionally (employees and turnover). For the SMEs, this is an opportunity to redefine organizational structure and strategy letting the firm grow, becoming more structured yet flexible.

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Interorganizational Enablers of Mass Customization: A Literature Review Enrico Sandrin

1 Introduction Many business organizations continue to develop mass-customization capability (MCC) to provide customized products and services that fulfill each customer’s idiosyncratic needs without considerable trade-offs in cost, delivery, and quality (Pine, 1993; Squire et al., 2006; Trentin et al., 2020). Organizations are open systems and operate in a continuous exchange of inputs and outputs with the external environment. Organizations are composed of internal relationships and interdependencies but also of relationships and interdependencies with the external environment where they operate and where they depend for resources (Baum, 2002; Daft, 2020). Organizations obtain resources and information from the outside, process them, and distribute their outputs to the environment (Baum, 2002; Daft, 2020). In this vision of a company as an open system, interorganizational The original version of this chapter has been revised. The term “PLUS_SPI” was corrected to the actual “+” symbol on pages 89, 90, 92, 93, and 94. The correction to this chapter can be found at https://doi.org/10.1007/978-3-031-09782-9_12.

E. Sandrin (*) Department of Management and Engineering, University of Padova, Vicenza, Italy e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023, corrected publication 2023 T. Aichner, F. Salvador (eds.), Mass Customization and Customer Centricity, https://doi.org/10.1007/978-3-031-09782-9_4

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relationships are of strategic importance and are fundamental for organizational capabilities and competitive advantage (Dyer and Singh, 1998; Lavie, 2006). In the context of mass customization, the strategic relevance of the external environment is also suggested by Wang et al. (2015) as they demonstrated that the strategic orientations toward customers, competitors, and innovation improve MCC. In addition, the importance of having open communication and integration along the entire value chain has been recognized since the introduction of the mass-customization concept (Pine, 1993). However, previous research on mass customization has paid relatively less attention to interorganizational-level enablers of MCC compared to its technological- (Fogliatto et  al., 2012; Suzić et  al., 2018) and organizational-­level (Sandrin et  al., 2014, 2018) enablers. Moreover, a structured overview that integrates and discusses previous results on interorganizational variables affecting MCC is lacking. Therefore, the present chapter systematically reviews previous literature on interorganizational variables that affect MCC, provides an overview of the previous research on this topic, and proposes future research opportunities. For this study, an interorganizational variable concerns ties among organizations, be they customers, suppliers, competitors, or other entities (Ebers, 2001), and is a variable concerning relationships among the company and external entities. The results of this study show that the research on interorganizational enablers of MCC has mainly focused on relationships between the company and its customers and suppliers. While there is a consensus of the importance of customer and supplier integration, empirical results showed several unexpected findings. Moreover, interorganizational relationships with other external entities have not been studied in isolation as happened with customers and suppliers. Finally, a universalistic view still dominates this body of knowledge rather than a contingency view of the effectiveness of the proposed solutions in enabling mass customization.

2 Method The present literature review provides an overview of the previously published works on the interorganizational enablers of mass customization. A replicable and transparent process has been followed to minimize bias

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(Tranfield et al., 2003). The search of publications was performed on the Web of Science Core Collection ™ database using the keyword “mass custom*” and selecting the field “topic” (that corresponds to searching title, abstract, author keywords, and keywords plus) on January 4, 2022. The search provided 3838 publications. To focus on publications relevant to business and management research and guarantee a certain level of quality, two other objective criteria were used. First, articles were kept if they are published in outlets that are included in the Q1 and Q2 quartiles of Journal Citation Reports ™ 2020 ranking at least in one category. Second, articles were kept if they are published in outlets that are included in the 4*, 4, and 3 categories of the Academic Journal Guide 2021 of the Chartered Association of Business Schools. This selection phase provided 676 publications. Given that at the interorganizational level the focus is on understanding the relationships and interactions within and among aggregates of organizations (Baum, 2002), for this study, an interorganizational variable concerns ties among organizations, be they customers, suppliers, competitors, or other entities (Ebers, 2001). In particular, this study aims to understand the impacts of the interorganizational relationships between a focal organization and one or more external entities (such as customers, suppliers, competitors, or others) on the MCC of such focal organization. To achieve this goal, this study identified, in the previous literature regarding mass customization, interorganizational variables that are conceptualized as affecting MCC. Articles were included in the analysis if they provide a clear explanation of the link between an interorganizational variable and MCC.  More precisely, papers were retained, for example, if they describe reasons and mechanisms that explain the effect of an interorganizational enabler on MCC, develop propositions on this effect, develop hypotheses on this effect, or test such hypotheses. Conversely, papers were not included in the final sample, for example, if they do not include interorganizational variables, do not explain how and why an interorganizational variable impacts MCC, or explain a link with an interorganizational variable and only an operational performance (e.g., an association only with time performance). At the end of this selection process, the final set of publications comprised fourteen articles.

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Subsequently, the interorganizational variables present in the final set of publications were classified into three main categories. The first category includes interorganizational variables focused on the relationships between a mass customizer and its customers. An example of an interorganizational variable falling into the first category is customer involvement. The second category includes interorganizational variables focused on the relationships between a mass customizer and its suppliers, such as the variable named supplier integration. The third category includes all the other interorganizational variables not previously categorized. For example, in this third category, some variables account for relationships along the entire supply chain, thus capturing relationships with customers and suppliers within the same variable, such as the variable named supply-chain cooperation. Another example of variables falling into the third category are interorganizational variables focused on the relationships between a mass customizer and other external entities (also other than customers and suppliers) or other external stakeholders, such as the variable named external cooperation. Then, for each identified interorganizational variable, it was collected the source reference, the method adopted in the related study (including the statistical approach used, if any), the nature of the links between the interorganizational variable and the MCC, the hypothesized sign of this proposed link, and whether the empirical study (if any) provides empirical support to this proposed link. This task resulted in a structured overview that highlights which interorganizational relationships and which external entities were previously investigated by the selected articles. Also, this overview highlights which method the selected articles used, which kind of link between these interorganizational variables and the MCC they proposed, which of the proposed links they tested in an empirical setting, how they tested these links, and which of these links were supported by the empirical evidence. The structured overviews of these interorganizational variables grouped by categories and sorted by publication date are in Tables 1, 2, and 3 in the Results section. Finally, results and possible research directions are discussed.

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3 Results 3.1 Variables Focused on Relationships with Customers The previous research on mass customization, unsurprisingly, has continuously investigated variables regarding the relationship between a mass customizer and its customers since the introduction of the concept of mass customization, as shown in Table 1. Table 1  Interorganizational variables focused on the relationships between a mass-customization organization and its customers Variable name (Reference) Learning relationships with customers (Pine et al., 1995) Customer integration (Piller et al., 2004) Customer closeness (Tu et al., 2004)

Method

Link between variable and MCC, hypothesized sign (Empirical support)

Conceptual

• Link discussed but not tested, +

Conceptual

• Link discussed but not tested, +

Survey, Covariance-­ •  Direct, + (supported) based structural • Indirect through modularity-­ equation based manufacturing practices, + modeling (supported) (CB-SEM) • CF is 1 of the 6 first-order Customer focus (CF) Survey, CB-SEM (Kristal et al., constructs of the reflective 2010) second-order construct quality management (QM) that is linked to MCC. The link of QM with MCC is: direct, + (supported) • CI is 1 of the 3 first-order Survey, Customer Multivariate involvement (CI) constructs of the reflective analysis of (Trentin et al., second-order construct variance 2012) environmental management (MANOVA) (EM) that is linked to MCC. The link of EM with MCC is: direct, + (supported) (continued)

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Table 1 (continued) Variable name (Reference) Customer integration (Lai et al., 2012)

Customer integration (Jitpaiboon et al., 2013) Customer involvement (CI) (Salvador et al., 2015)

Relational capital (Zhang et al., 2015a) Cognitive capital (Zhang et al., 2015a) Structural capital (Zhang et al., 2015a) Knowledge acquisition from customers (Zhang et al., 2015b)

Method

Link between variable and MCC, hypothesized sign (Empirical support)

Survey, Partial least •  Direct, + (supported) squares structural equation modeling (PLS-SEM) Survey, PLS-SEM •  Direct, + (supported)

Survey, Hierarchical • Direct, + (supported when linear regression flexible manufacturing resources [FMR] and product management tools [PMT] are at their sample means) • Interaction CI*FMR*PMT, + (not supported, significant but negative) Survey, CB-SEM •  Direct, + (not supported)

Survey, CB-SEM

•  Direct, + (supported)

Survey, CB-SEM

• Indirect through relation capital, + (not supported) • Indirect through cognitive capital, + (supported) •  Direct, + (supported) • Indirect through knowledge application, + (supported) • Indirect through knowledge assimilation and knowledge application, + (supported)

Survey, PLS-SEM

Table 1 demonstrates the central role of having relationships with customers to build MCC. Overall, previous empirical research provides strong support in almost all cases for the positive effect of customer-­ related interorganizational variables and MCC.  The strategic role of

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customers and the importance of building relationships with the customers have been recognized since the introduction of the mass-customization concept (Pine, 1993; Pine et al., 1995). By using the words of Pine et al. (1995), a learning relationship with the customer allows individual customers to teach the company more and more about their preferences and needs, giving the company an immense competitive advantage. The relationships with customers have been investigated and characterized with specific emphases in several studies. For example, customer integration is the extent to which customers take into a company’s value-creating activities and processes that had previously been in the domain of the company (Piller et  al., 2004; Jitpaiboon et  al., 2013). According to Tu et al. (2004), customer closeness is the practice of keeping close contact with customers, communicating with customers effectively, and understanding customers’ individual needs. Salvador et  al. (2015) defined customer involvement as the extent to which a manufacturer engages in interactions with its customers to understand and respond to their needs and receive feedback on quality and delivery. Zhang et  al. (2015b) operationalized the knowledge acquisition from customers through different routines and mechanisms of customer interactions such as real-time information sharing, special meetings, and surveys. Despite the heterogeneity of characterization in studying the relationships with the customers, many empirical studies have consistently supported the positive effect of these relationships on MCC, as shown in Table  1 (Tu et  al., 2004; Lai et  al., 2012; Jitpaiboon et  al., 2013; Zhang et al., 2015a, 2015b). However, two studies reported a lack of empirical support for specific positive effects they have hypothesized. An unexpected lack of empirical support is that the complementary effect of the simultaneous presence of customer involvement, flexible manufacturing resources, and product management tools was not supported; on the contrary, the application of all these three MCC antecedents resulted in a cancellation effect (Salvador et al., 2015). Finally, the positive direct effect between relational capital, which is the trust and commitment between a manufacturer and customers, and MCC is not empirically supported (Zhang et al., 2015a). These unexpected results call for more in-depth scrutiny of these links.

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3.2 Variables Focused on Relationships with Suppliers The relationships between a mass-customization company and its suppliers have received particular attention as well, albeit less than relationships with customers, as shown in Table 2. Table 2  Interorganizational variables focused on the relationships between a mass-customization organization and its suppliers Variable name (Reference)

Method

Link between variable and MCC, hypothesized sign (Empirical support)

Survey, • DS is 1 of the 7 first-order constructs Dependable suppliers (DS) (Tu Covariance-­ of the reflective second-order et al., 2001) construct time-based manufacturing based structural practices (TBMP) that is linked to equation MCC. The link of TBMP with MCC is: modeling direct, + (supported) (CB-SEM) Survey, CB-SEM • SI is 1 of the 6 first-order constructs Supplier involvement (SI) of the reflective second-order (Kristal et al., construct quality management (QM) 2010) that is linked to MCC. The link of QM with MCC is: direct, + (supported) • SP is 1 of the 3 first-order constructs Survey, Supplier Multivariate partnership (SP) of the reflective second-order analysis of (Trentin et al., construct environmental variance 2012) management (EM) that is linked to (MANOVA) MCC. The link of EM with MCC is: direct, + (supported) •  Direct, + (not supported) Survey, Partial Supplier least squares integration (Lai structural et al., 2012) equation modeling (PLS-SEM) Survey, PLS-SEM • Indirect through operational Supplier integration performance, + (supported) (Jitpaiboon et al., 2013) Survey, CB-SEM •  Direct, + (supported) Supplier segmentation (Liao et al., 2013) (continued)

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Table 2 (continued) Variable name (Reference) Flexible suppliers (FS) (Salvador et al., 2015)

Method Survey, Hierarchical linear regression

Survey, PLS-SEM Knowledge acquisition from suppliers (Zhang et al., 2015b)

Link between variable and MCC, hypothesized sign (Empirical support) • FS is 1 of the 5 variables of the formative index flexible manufacturing resources (FMR) that is linked to MCC. The links of FMR with MCC are: direct, + (supported when customer involvement [CI] and product management tools [PMT] are at their sample means); interaction CI*FMR*PMT, + (not supported, significant but negative) •  Direct, + (not supported) • Indirect through knowledge application, + (supported) • Indirect through knowledge assimilation and knowledge application, + (supported)

Table 2 reveals that supplier integration can be an enabler of MCC; however, the mechanism through which supplier integration positively influences MCC seems to work differently from customer integration. Previous empirical studies show there is no empirical support for the direct effect of supplier integration on MCC (Lai et al., 2012), but the relationships with suppliers can produce a positive effect on MCC by means of other variables. Previous empirical research suggests that the effect of supplier integration on MCC is fully mediated by operational performance (Jitpaiboon et  al., 2013), and the knowledge acquired from suppliers needs to be at least applied to improve MCC (Zhang et  al., 2015b). Moreover, previous empirical evidence suggests that specific relationships with suppliers positively contribute to MCC when accompanied by other relevant variables such as in the case of time-based manufacturing practices (Tu et al., 2001), quality management (Kristal et al., 2010), environmental management (Trentin et  al., 2012), and flexible manufacturing resources (Salvador et al., 2015). On the other hand, supplier segmentation, which is the practice of applying modularity to a supply base, is empirically supported as an enabler of MCC (Liao et al., 2013).

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3.3 Variables on Relationships with the Entire Supply Chain or Other External Stakeholders Relationships between a mass-customization company and its entire supply chain, which includes customers and suppliers in the same interorganizational variable, or between a mass-customization company and other external stakeholders and entities have received much less attention, as reported in Table 3. Table 3  Interorganizational variables concerning the relationships between a mass-customization organization and its entire supply chain or other external stakeholders Variable name (Reference) External learning (Huang et al., 2008) Environmental management (EM) (Trentin et al., 2012) External cooperation (EC) (Trentin et al., 2012)

Tactical alignment (Liao et al., 2013)

Supply-chain coordination (Zhang et al., 2014)

Method

Link between variable and MCC, hypothesized sign (Empirical support)

Survey, Covariance-­ • Indirect through effective based structural process implementation, + equation modeling (supported) (CB-SEM) Survey, Multivariate •  Direct, + (supported) analysis of variance (MANOVA) Survey, MANOVA • EC is 1 of the 3 first-order constructs of the reflective second-order construct EM that is linked to MCC. The link of EM with MCC is: direct, + (supported) Survey, CB-SEM • Indirect through product modularity design and process modularity design, + (supported) • Indirect through process modularity design, + (supported) • Indirect through postponement practices, + (not supported) Survey, Partial least •  Direct, + (supported) squares structural • Indirect through product equation modeling modularity, + (not supported) (PLS-SEM)

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Table 3 shows MCC is improved when a mass customizer builds a set of mechanisms to coordinate with and learn from the external environment, in particular with both suppliers and customers but also with other external entities (Huang et  al., 2008; Trentin et  al., 2012; Liao et  al., 2013; Zhang et al., 2014). Of note, the effects on MCC of interorganizational relationships with external entities such as competitors or external relevant stakeholders other than suppliers and customers have not been studied separately in order to understand their specific effect on MCC.

4 Discussion and Conclusion The present chapter systematically reviews previous literature on the interorganizational variables that have an effect on MCC.  The present review adopts a new and different focus as compared to previous literature reviews on mass customization (Da Silveira et  al., 2001; Kumar et al., 2007; Fogliatto et al., 2012; Ferguson et al., 2014; Sandrin et al., 2014; Suzić et al., 2018), thus providing specific findings regarding interorganizational enablers of mass customizations that are useful for business practice and research. The choice of adopting an interorganizational focus to study the enablers of MCC is strongly justified by the fact that organizations are open systems composed not only of internal relationships but also of relationships and interdependencies with the external environment in which organizations operate (Baum, 2002; Daft, 2020). Organizations obtain resources and information from the outside, process them, and distribute their outputs to the environment (Baum, 2002; Daft, 2020). In this vision of a company as an open system, interorganizational relationships are of strategic importance and fundamental for the development of organizational capabilities and thus for competitive advantage (Dyer and Singh, 1998; Lavie, 2006). In mass customization, the strategic role of interorganizational relationships is also suggested by the MCC enabling role of the strategic orientations toward customers, competitors, and innovation (Wang et al., 2015). The first evidence that emerges from this literature review is that this body of knowledge is focused mainly on customers and a relatively lesser

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extent, on suppliers. This evidence echoes the key role that customers play in defining a mass-customization strategy (Duray et al., 2000) and the importance of integrating the entire value chain suggested in Pine’s (1993) seminal book. Previous research has also underlined the importance of acquiring external knowledge and learning from the external environment but has not studied separately the specific contribution of different external entities, except for customers and suppliers studied also as distinct variables. Therefore, future research could investigate other connections with external entities that positively affect MCC in isolation from others, such as those related to customer involvement and supplier involvement. Examples of such connections are links with research centers, knowledge and technology transfer institutions, clusters, competitors, surrounding communities, alliances, business ecosystems, and networks of organizations (Daft, 2020). Another important finding to note is while different studies constantly supported the direct effect of customer integration on MCC, a lack of empirical support was detected for the direct effect of supplier integration on MCC. This finding entails that particular attention is recommended when using broad variables that capture distinct constructs to avoid drawbacks related to composite indicators (Greco et al., 2019) and multidimensional constructs (Edwards, 2001). Supplier integration is not the only variable hypothesized to enhance MCC that has not found empirical support. The cases of lack of empirical support provided opportunities for further research as well. For example, further studies could investigate the interrelatedness between interorganizational variables and other organizational, technological, or contextual variables to explain the circumstances under which impacts of interorganizational variables on MCC are significant. Finally, the reviewed body of knowledge is still dominated by a universalistic view rather than a contingency view of the effectiveness of the proposed solutions in enabling mass customization. The adoption of a contingency approach is suitable in the context of mass customization as different mass-customization strategies can be defined, such as the degree of product customization provided to customers (e.g., Da Silveira et al., 2001; Sandrin et al., 2014). As shown by Sandrin (2016), the external factor of demand dynamism drives firms to increase the degree of

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product customization provided to customers. The degree of product customization, in turn, is a fundamental contingency factor when designing organizational structure (Huang et al., 2010), human resource management practices (Sandrin et al., 2018), and supply-chain configuration (Salvador et al., 2004) in a mass-customization context. Therefore, considering contingent effects in mass customization, an important research opportunity is to study these phenomena by adopting a contingency view (Oliver and Ebers, 1998; Koufteros et al., 2005). Acknowledgments  The author acknowledges the financial support from the University of Padova (project IDs BIRD199795 and DOR2102044/21).

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The Ghost in the Machine: A Multi-­method Exploration of the Role of Individuals in the Simultaneous Pursuit of Flexibility and Efficiency Fabrizio Salvador and Cipriano Forza

1 Introduction Flexibility, defined as the capacity of an organization to address novel and uncertain requests of its clients via customized products (Hayes & Wheelwright, 1984), is known to conflict with efficiency; that is, flexible organizations tend to absorb more input factors per unit of output. This trade-off results from multiple causes, among which are structural (Barnett & Freeman, 2001), technological (Woodward, 1965), contractual (Baiman et al., 2001) and behavioral (Pentland, 2003) factors.

F. Salvador (*) Operations and Technology Management, IE Business School, IE University, Madrid, Spain e-mail: [email protected] C. Forza Department of Management and Engineering, University of Padova, Vicenza, Italy © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 T. Aichner, F. Salvador (eds.), Mass Customization and Customer Centricity, https://doi.org/10.1007/978-3-031-09782-9_5

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Nevertheless, the current emphasis on product proliferation strategies (Bayus & Putsis, 1999) such as mass customization (Feitzinger & Lee, 1997), quick response (Richardson, 1996) or efficient customer response (Corsten & Kumar, 2005) shows how organizations need to simultaneously achieve efficiency and flexibility. The need to simultaneously achieve efficiency and effectiveness has prompted manufacturing organizations to substitute labor with capital, specifically investing in production technologies and management approaches that minimize disruptions of the workflow due to variations in customer demand. Flexible manufacturing systems, for example, reduce losses of productivity associated with setups while retaining the typical efficiency of machines (Zammuto & O’Connor, 1992). Information technology supports the rapid and reliable execution of highly variable tasks by using previously codified knowledge (Cowan, 2001). Organizational solutions such as modular organizational forms mitigate the negative effect of task variety on the value chain (Schilling, 2000). Nonetheless, there are limitations to the productivity gains attainable by substituting labor with capital when a truly flexible response to the customer is needed. When customer orders entail truly novel requirements for the organization, reliance on automation and pre-codified order fulfillment routines is impossible. This fact is immediately seen in the business world: the automated order acquisition and fulfillment solutions that are adopted by companies facing moderate levels of customization (Dell Computers, Capital One and MINI Cooper) do not fit the operations of organizations with high levels of customization, such as consulting firms, hospitals or engineering firms. Past research supports the view that increasing productivity under requisite levels of flexibility requires the contribution of human capital (Adler, 1988; Pfeffer, 1994) and the re-alignment of individuals with technical systems (Ettlie, 1988; Marjchrzak, 1986; Snell & Dean, 1992). MacDuffie (1995), for example, found advanced workforce management practices to be significantly higher level within flexible plants relative to mass production plants. Similarly, Snell and Dean Jr. (1992) found that human capital is complementary to advanced manufacturing technology in the metalworking industry, where customization is typical. Adler et al.

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(1999) note the importance of workers in attaining flexibility and identify four organizational design principles set in place by a GM-Toyota joint venture to reconcile efficiency with flexibility at the shop-floor level. In a similar vein, Volberda (1996) posits that managerial tasks are essential for the achievement of efficiency and flexibility. Despite the claim that people play a significant role in determining an organization’s flexibility and efficiency level, to date, we have achieved only a limited grasp of how and why they do so. Firstly, the literature on manufacturing flexibility does not go beyond associating worker cross-­ training to the mitigation of the efficiency-flexibility trade-off (Park & Bobrowski, 1989; Bobrowski & Park, 1993; Koste & Malhotra, 1999; Karuppan & Ganster, 2004) without giving a detailed account on the characteristics of specific tasks employees should be cross-trained. Secondly, while multiple studies have investigated the role of workers in the mitigation of the efficiency-flexibility trade-off, the contribution of operations managers has received limited attention, except for Kathuria and Partovi (1999), who found that supervisors emphasizing flexibility (not flexibility and efficiency simultaneously) rely on relationship-­ oriented workforce management practices and participative leadership. A similar focus is found in Trentin et al. (2019), but this study focuses on mass customization—which assumes that a firm’s offerings are constrained within a predefined solution space (Tseng & Piller, 2003)— thereby limiting the criticality of human agency in order fulfillment. Finally, past research does not explore how manufacturing managers interact with and get support from personnel from other parts of the organization to ensure a flexible and efficient response to customers’ ambiguous and novel requests. This is important because flexibility calls for the development of inter-departmental linkages so that different competencies are linked to address uncertainty (Burns & Stalker, 1961). Therefore, the purpose of this study is to examine in depth the processes through which people involved in the customization workflow contribute to the simultaneous achievement of efficiency and flexibility, as well as the particular abilities that they use to do so. By customization workflow, we mean the system of functional areas that are linked together

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in addressing customers’ novel and ambiguous needs, a process that typically includes sales, engineering and production/logistics areas (Forza & Salvador, 2002; Koufteros et al., 2005). Because people operating in different workflow functions become interdependent when a flexible response to the customer is necessary, we chose not to focus our research exclusively on personnel working in operations, thus extending the scope of the inquiry from that used in previous research (e.g., Kathuria & Partovi, 1999). The scarcity of academic literature dealing with our research question prompted us to engage in a multi-method theory-building effort with an exploratory research design, on the premises that this approach is more appropriate when “how” and “why” type of questions are to be addressed (Edmondson & McManus, 2007; Eisenhardt & Graebner, 2007). Our theory-building effort involves two studies, a qualitative interview study involving 46 subject matter experts and a survey involving 276 managers from 5 countries. The first study aims to tap the mental models (Johnson-­ Laird, 1983) held by the subject matter experts relative to how people operating within the customization workflow contribute to organizational flexibility and efficiency. We provide a more general rationale for our interview-based interpretive model by borrowing the attention-based view of the firm (Ocasio, 1997) as well as theoretical contributions from the organizational memory (Walsh & Ungson, 1991) and organizational improvisation (Moorman & Miner, 1998) literature. The second study is designed to triangulate the interpretive model by eliciting information on the mental models of the second pool of experts using a different method—survey research. This design responds to the recent call for using multiple methods in operations management research (Boyer & Swink, 2008) and to triangulate hypotheses generated through small qualitative samples with larger samples, to mitigate the effect of possible “polar cases” (Salvador & Madiedo, 2021). We finally discuss the limitations and implications of our results for the literature on manufacturing flexibility, ambidexterity and operations strategy.

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2 Study I: Development of an Interpretive Theoretical Model Understanding the role of individuals in mitigating the efficiency-­ flexibility trade-off is a complex task that requires observation of behavior and patterns of action across time as well as on multiple levels (e.g., individual vs. organizational). Given this premise, we decided to address our research question by tapping the mental models of subject matter experts who have been observing across time how people contribute to organizational efficiency and flexibility. Mental models offer an appropriate unit of analysis for our research question for multiple reasons. Firstly, mental models are cognitive structures that managers naturally construct by consolidating observed patterns over time (see Hewstone et al., 2002; Schank & Abelson, 1977); that is, they are based on factual experience (SmithJentsch et al., 2001) rooted in an individual’s past interactions with the environment. Secondly, mental models are parsimonious (Gentner & Stevens, 1983) and thus can be elicited in the short period that an informant can devote to a face-to-face interview or to filling out a questionnaire. Thirdly, although mental models are unique for everyone, it is possible to identify common elements that are shared by individuals and their reference groups: that is, a common culture (Nishida, 1999), gender (Swim et al., 1989) or organization (Harris, 1994). Therefore, individual biases can be overcome by identifying similar patterns across multiple informants’ mental models. We identified and contacted subject matter experts1 with the help of established non-profit institutions that serve the training needs of local companies in Germany, Italy, Slovenia, Spain and the UK. A total of n = 46 informants were interviewed to identify shared patterns across the interviewees’ mental models, while at the same time allowing each interview to go into sufficient depth. The final interview sample includes respondents not only from the different countries but also from companies with different product categories, product price ranges and product complexity, to increase possible generalization of the induced theory. We  Subject matter experts are defined as individuals with substantial experience with the workflow activities needed to sell and deliver a customized product. 1

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Table 1  Qualitative study Turnover resulting from personalized products

Country Italy Spain UK Germany Slovenia Net sales (millions €) 150 Pieces per person (annual) 0–9 10–99 100–999 1000–9999 10,000–99,999 100.000–857,143 N.A.

29% 29% 14% 14% 14% 11% 25% 29% 32% 4% 11% 21% 14% 18% 11% 7% 18%

0–10% 11–50% 51–90% 91–100% N.A. Number of employees