Will the presence of ‘fashion knockoffs’ benefit the original-designer-label product supply chain?

Abstract

Fashion knockoffs, which refer to the copycat behaviours of some brands in fashion apparel, are widely seen. It is commonly believed that the presence of fashion knockoffs harms the original-designer-label (ODL) product seller. Motivated by the industrial interviews and real-world observations, we build game-theoretical models to examine the impacts of fashion knockoffs on the ODL product supply chain and its agents with the consideration of risk attitudes. Explicitly, in the basic model, we consider a common manufacturer producing for both a knockoff product seller and a risk sensitive ODL product seller. The ODL product seller and the knockoff product seller make pricing decisions to optimise their own profits. We interestingly find that the presence of fashion knockoffs benefits the ODL product supply chain and its agents when (i) the ODL product seller is risk averse and the ratio of demand uncertainty is relatively small or (ii) the ODL product seller is risk seeking and the ratio of demand uncertainty is sufficiently large. The findings indicate that a risk averse (seeking) ODL product seller is more prone to benefit from the presence of fashion knockoffs when selling fashionable (classic) products.

KEYWORDS:

• Supply chain management
• fashion knockoff
• production operations
• supply chain structure
• risk attitude

Acknowledgements

The authors sincerely thank Elaine Fung’s (the former manager in Li and Fung) kind support and inputs to this study. We also sincerely thank Shirley Shi, Jessica Sun, Sophia Zhang, Ling Chan, Kun Zhang, Jiaixin Lin, Annie Luo, Yami Sun and Windy Wen for their helpful comments on an earlier version of this paper. The analysis conducted in this paper is mainly done by Wang and Xu, under the advice of Choi and Shen. Authorship listing follows surnames in the respective groups (students Wang and Xu; advisors Choi and Shen).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

1 We quote it from references. This does not represent our views.

2 This study only considers the risk attitude of the ODL product seller (but not the knockoff product seller or the manufacturer) mainly for two reasons: First, the focal point of this study is the ODL product seller. We did not want to distract readers’ attention to other agents. Second, if we consider all supply chain agents’ risk attitudes, there will be too many analytical thresholds that we cannot derive closed-form results for further analysis.

3 To avoid confusion, we use ‘seller’ to represent the brand owner and “manufacturer” to represent the factory in this paper.

4 The mechanism is that the manufacturer sets the wholesale price by multiplying a profit margin with the cost of goods manufactured (COGM). COGM usually includes (i) material cost, (ii) labor cost, and (iii) additional costs and overhead, which can be easily figured out by the manufacturer. The importance of standard markup policy is also highlighted in the literature. As pointed out by Noble and Gruca (1999), the standard markup wholesale pricing policy is one of the most widely used pricing strategies in the retailing industry. The intuition behind is that a normal markup over cost provides a simple pricing guideline to profitability (Wang, Lau, and Lau 2013).

5 Note that the markup rate varies across industries, e.g., the markup rate is relatively high in the fashion industry.

6 Note that there are other alternative optimization objectives which can also be employed to model risk related optimization objective. See Shi et al. (2011) for profit satisficing objective and others (Shi, Zhao, and Xia 2010).

7 We analytically find that G can be either positive or negative.

8 We only show the sufficient condition (rather than the necessary and sufficient condition) here is to ensure mathematical trackability.

9 We also consider the case where the wholesale price is endogenously given in Online Appendix C. We did not put it in the mainbody since the results are too messy and cannot derive clear insights. Moreover, we consider the case where there are different manufacturers with the non-standard markup wholesale pricing policy in Online Appendix D.

10 The ODL product supply chain consists of manufacturer 1 and the ODL product seller.

11 You may refer to Online Appendix A for more details.

Additional information

Funding

This paper is partially supported by National Science Foundation of China [grant number: 72271050, 71832001].

Notes on contributors

Yingjia Wang

Yingjia Wang received her Ph.D. from The Hong Kong Polytechnic University. She is a lecturer at Business School in University of Shanghai for Science and Technology, Shanghai. She has published research papers in leading journals such as International Journal of Production Research, Transportation Research Part E, Annals of Operational Research. Her research focuses on supply chain management.

Xiaoyan Xu

Xiaoyan Xu is a Ph.D. student in Department of Industrial Systems Engineering, The Hong Kong Polytechnic University. She has published research papers in leading journals such as Production and Operations Management, Decision Sciences, IEEE Transactions (various), IISE Transactions, International Journal of Production Economics, International Journal of Production Research, Transportation Research Part E, etc. Her research interests focus on marketing and operations interfaces. Her doctoral dissertation research explores operations management problems associated with COVID-19 and the new normal.

Tsan-Ming Choi

Tsan-Ming Choi received the Ph.D. degree in operations and supply chain management from Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong in 2002. He is currently Chair in Operations and Supply Chain Management, and Director of the Centre for Supply Chain Research at University of Liverpool Management School. Prof. Choi has published extensively in leading journals in the fields of operations management, engineering management, logistics and supply chain management. He is currently serving the profession as the Co-Editor-in-Chief of Transportation Research Part E: Logistics and Transportation Review, a Department Editor of IEEE Transactions on Engineering Management, a Senior Editor of Production and Operations Management, and Decision Support Systems, and an Associate Editor of Decision Sciences, and IEEE Transactions on Systems, Man and Cybernetics – Systems. He is also a member of the Engineering Panel of Research Grants Council of Hong Kong. Over the past two decades, he has taught at The Chinese University of Hong Kong, The Hong Kong Polytechnic University, National Taiwan University, and University of Liverpool Management School.

Bin Shen

Bin Shen is currently a Professor in Glorious Sun School of Business and Management in Donghua University, Shanghai. He is Humboldt Fellow in Germany. He has published more than 70 research articles in leading journals, such as Production and Operations Management, Journal of Business Research, Supply Chain Management: An International Journal, Technological Forecasting and Social Change, International Journal of Production Economics, etc. His research interests focus on supply chain management, sustainability, and operations-marketing interface.