隨著零售業和網路的快速發展，顧客可以從線下通路轉換到線上購物，使得線下零售商失去了許多潛在客源。線上市場的增加，意味著來自世界各地的客戶有著不同的品味、偏好和生活方式。然而線上零售商，如eBay 和 Zalando，卻面臨嚴重地產品購買後需求不符的風險，並且越來越多的顧客希望能購買客製化產品以滿足他們的需求。為了提高獲利，線下零售商可以因此推出大量客製化服務，讓顧客購買符合自己需求的產品。線下零售商能依據顧客不同的偏好提供產品，來搶奪線上零售商的顧客。大量客製化可以讓線下零售商滿足消費者異質性的偏好。
本研究延伸了 Hotelling 模型來分析線下零售商以大量客製化策略，來與線上零售商競爭販售相同產品。本研究探討了顧客偏好異質性是如何影響供應鏈的表現。Hotelling 模型則是被用來描述線下與線上零售商在地理位置上的差別。此外，本研究加入了縱軸來表示顧客對於產品特定屬性的異質性需求偏好。線下零售商在什麼時候應該實行大量客製化策略，為本研究的所要探討的目標。本研究有兩個主要的發現，第一為大量客製化可以有效幫助線下零售商對抗線上零售業的蓬勃發展。第二為在考量消費者需求有所偏好的情況下，選擇執行大量客製化策略能為線下零售商的利潤上升。大量客製化策略影響線下零售商的利潤，取決於不符合需求成本因子，而大量客製化成本則會降低線下零售商的利潤損失。

With the rapid development of the retailer and internet, customers switch from the offline to the online purchase channels, which has caused the offline retail to lose many potential customers. As online sales increase, customers worldwide have different tastes, preferences, and lifestyles. But the online retailer such as eBay and Zalando can present a significantly higher risk of a post-purchase product taste mismatch, and more customers want to purchase customization products to meet their taste. To further increase the offline retail’s profit, the offline retail can start to implement mass customization, which means each customer can purchase what product they want, so the offline retailer can provide products according to the preferences of heterogeneous tastes customers and can take over the online retail customers. Mass customization enables the offline retailer to satisfy heterogeneous customer taste preferences.

We extend the Hotelling model to analyze mass customization as a strategy for the offline retailer to compete with the online retailer that sells the same product. We investigate how customer’s heterogeneous taste preferences affect the supply chain’s performance. The Hotelling model is used to demonstrate the offline retailer and the online retailer differentiation in their geographic location. Besides, we incorporate a vertical line to represent customer’s heterogeneous taste preferences for certain product characteristics. We aim to find when the offline retailer can implement mass customization. We reach two major conclusions. First, a mass customization strategy may be an effective means for the offline retailer to mitigate the development of the online retailer. Second, the offline retailer’s profit grows, which means the mass customization strategy can lead to higher profit than the non-mass customization strategy under consideration of customer taste preference. The impact of mass customization on offline retailer’s profit depends on the mismatch cost factor ?, and mass customization cost ?? will reduce the loss of the offline retailer’s profit.

Ali, M. F. A., & Abbas, K. A. J. (2020). The Role of Mass Customization Product in Enhancing Consumer’s Intention towards Loyalty through Perceived Product Design Efforts. International Journal of Innovation, 14(10), 13.

Alptekinoğlu, A., & Corbett, C. J. (2008). Mass Customization vs. Mass Production: Variety and Price Competition. Manufacturing & Service Operations Management, 10(2), 204–217. https://doi.org/10.1287/msom.1070.0155

Amaldoss, W., & He, C. (2018). Reference-Dependent Utility, Product Variety, and Price Competition. Management Science, 64(9), 4302–4316. https://doi.org/10.1287/mnsc.2017.2834

Andree, K. (2011). Product differentiation and spatial agglomeration in a unidirectional Cournot model. Letters in Spatial and Resource Sciences, 4(3), 167–172. https://doi.org/10.1007/s12076-011-0060-1

Balakrishnan, A., Sundaresan, S., & Zhang, B. (2014). Browse-and-Switch: Retail-Online Competition under Value Uncertainty. Production and Operations Management, 23(7), 1129–1145. https://doi.org/10.1111/poms.12165

Basak, S., Basu, P., Avittathur, B., & Sikdar, S. (2017). A game theoretic analysis of multichannel retail in the context of “showrooming.” Decision Support Systems, 103, 34–45. https://doi.org/10.1016/j.dss.2017.09.002

Bell, D. R., Gallino, S., & Moreno, A. (2018). Offline Showrooms in Omnichannel Retail: Demand and Operational Benefits. Management Science, 64(4), 1629–1651. https://doi.org/10.1287/mnsc.2016.2684

Cao, J., So, K. C., & Yin, S. (2016). Impact of an “online-to-store” channel on demand allocation, pricing and profitability. European Journal of Operational Research, 248(1), 234–245. https://doi.org/10.1016/j.ejor.2015.07.014

Chai, L., Wu, D. D., Dolgui, A., & Duan, Y. (2020). Pricing strategy for B&M store in a dual-channel supply chain based on hotelling model. International Journal of Production Research, 1–14. https://doi.org/10.1080/00207543.2020.1787536

Chakraborty, R., Lee, J., Bagchi-Sen, S., Upadhyaya, S., & Raghav Rao, H. (2016). Online shopping intention in the context of data breach in online retail stores: An examination of older and younger adults. Decision Support Systems, 83, 47–56. https://doi.org/10.1016/j.dss.2015.12.007

Chen, J., & Chen, B. (2016). Competing with customer returns policies. International Journal of Production Research, 54(7), 2093–2107. https://doi.org/10.1080/00207543.2015.1106019

Chen, J., & Chen, B. (2019). When should the offline retailer implement price matching? European Journal of Operational Research, 277(3), 996–1009. https://doi.org/10.1016/j.ejor.2019.03.013

Choi, T.-M., Ma, C., Shen, B., & Sun, Q. (2019). Optimal pricing in mass customization supply chains with risk-averse agents and retail competition. Omega, 88, 150–161. https://doi.org/10.1016/j.omega.2018.08.004

Feng, Q., & Shanthikumar, J. G. (2018). How Research in Production and Operations Management May Evolve in the Era of Big Data. Production and Operations Management, 27(9), 1670–1684. https://doi.org/10.1111/poms.12836

Fogliatto, F. S., da Silveira, G. J. C., & Borenstein, D. (2012). The mass customization decade: An updated review of the literature. International Journal of Production Economics, 138(1), 14–25. https://doi.org/10.1016/j.ijpe.2012.03.002

Gao, F., & Su, X. (2017). Online and Offline Information for Omnichannel Retailing. Manufacturing & Service Operations Management, 19(1), 84–98. https://doi.org/10.1287/msom.2016.0593

Hong, Y. (Kevin), & Pavlou, P. A. (2014). Product Fit Uncertainty in Online Markets: Nature, Effects, and Antecedents. Information Systems Research, 25(2), 328–344. https://doi.org/10.1287/isre.2014.0520

Hotelling, H. (1929). Stability in Competition. The Economic Journal, 39(153), 41–57. https://doi.org/10.2307/2224214

Jiang, K., Lee, H. L., & Seifert, R. W. (2006). Satisfying customer preferences via mass customization and mass production. IIE Transactions, 38(1), 25–38. https://doi.org/10.1080/07408170500346386

Li, H., & Peng, T. (2020). How Does Heterogeneous Consumer Behavior Affect Pricing Strategies of Retailers? IEEE Access, 8, 165018–165033. https://doi.org/10.1109/ACCESS.2020.3022491

Liu, C., Dan, Y., Dan, B., & Xu, G. (2020). Cooperative strategy for a dual-channel supply chain with the influence of free-riding customers. Electronic Commerce Research and Applications, 43, 101001. https://doi.org/10.1016/j.elerap.2020.101001

Liu, Y., & Zhang, Z. J. (2006). Research Note—The Benefits of Personalized Pricing in a Channel. Marketing Science, 25(1), 97–105. https://doi.org/10.1287/mksc.1050.0120

Mehra, A., Kumar, S., & Raju, J. S. (2018). Competitive Strategies for Brick-and-Mortar Stores to Counter “Showrooming.” Management Science, 64(7), 3076–3090. https://doi.org/10.1287/mnsc.2017.2764

Merle, A., Chandon, J.-L., Roux, E., & Alizon, F. (2010). Perceived Value of the Mass-Customized Product and Mass Customization Experience for Individual Consumers. Production and Operations Management, 19(5), 503–514. https://doi.org/10.1111/j.1937-5956.2010.01131.x

Ofek, E., Katona, Z., & Sarvary, M. (2010). “Bricks and Clicks”: The Impact of Product Returns on the Strategies of Multichannel Retailers. Marketing Science, 30(1), 42–60. https://doi.org/10.1287/mksc.1100.0588

Piller, F. T., Lindgens, E., & Steiner, F. (2012). Mass Customization at Adidas: Three Strategic Capabilities to Implement Mass Customization. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1994981

Pu, X., Gong, L., & Han, X. (2017). Consumer free riding: Coordinating sales effort in a dual-channel supply chain. Electronic Commerce Research and Applications, 22, 1–12. https://doi.org/10.1016/j.elerap.2016.11.002

Shao, X.-F. (2020). What is the right production strategy for horizontally differentiated product: Standardization or mass customization? International Journal of Production Economics, 223, 107527. https://doi.org/10.1016/j.ijpe.2019.107527

Syam, N. B., & Kumar, N. (2006). On Customized Goods, Standard Goods, and Competition. Marketing Science, 25(5), 525–537. https://doi.org/10.1287/mksc.1060.0199

Syam, N. B., Ruan, R., & Hess, J. D. (2005). Customized Products: A Competitive Analysis. Marketing Science, 24(4), 569–584. https://doi.org/10.1287/mksc.1050.0128

The Deloitte Consumer Review: Made to Order: The Rise of Mass Personalisation. (2015). Deloitte. https://books.google.com.tw/books?id=mRe3tQEACAAJ

Tookanlou, P. B., & Wong, H. W. (2020). Product line design with vertical and horizontal consumer heterogeneity: The effect of distribution channel structure on the optimal quality and customization levels. European Journal of Marketing, 55(1), 95–131. https://doi.org/10.1108/EJM-04-2019-0333

U.S. Department of Commerce. (2020). Quarterly Retail E-Commerce Sales 3rd Quarter 2020. 2.

Wang, N., Zhang, T., Zhu, X., & Li, P. (2021). Online-offline competitive pricing with reference price effect. Journal of the Operational Research Society, 72(3), 642–653. https://doi.org/10.1080/01605682.2019.1696154

Wang, S., Luo, T., & Chang, D. (2021). Pricing Strategies of Multichannel Apparel Supply Chain Based on Showrooming and Information Sharing. Mathematical Problems in Engineering, 2021, 1–23. https://doi.org/10.1155/2021/6659200

Wu, L.-Y., Chen, K.-Y., Chen, P.-Y., & Cheng, S.-L. (2014). Perceived value, transaction cost, and repurchase-intention in online shopping: A relational exchange perspective. Journal of Business Research, 67(1), 2768–2776. https://doi.org/10.1016/j.jbusres.2012.09.007

Xia, N., & Rajagopalan, S. (2009). Standard vs. Custom Products: Variety, Lead Time, and Price Competition. Marketing Science, 28(5), 887–900. https://doi.org/10.1287/mksc.1080.0456

Xiao, T., Choi, T.-M., & Cheng, T. C. E. (2014). Product variety and channel structure strategy for a retailer-Stackelberg supply chain. European Journal of Operational Research, 233(1), 114–124. https://doi.org/10.1016/j.ejor.2013.08.038

Xiao, T., & Shi, J. (2016). Consumer returns reduction and information revelation mechanism for a supply chain. Annals of Operations Research, 240(2), 661–681. https://doi.org/10.1007/s10479-014-1592-8

Yazdani, A., Çil, E. B., & Pangburn, M. S. (2020). What if Hotelling’s Firms Can Mass Customize? Decision Sciences, 51(2), 395–422. https://doi.org/10.1111/deci.12428

Zhou, Y.-W., Guo, J., & Zhou, W. (2018). Pricing/service strategies for a dual-channel supply chain with free riding and service-cost sharing. International Journal of Production Economics, 196, 198–210. https://doi.org/10.1016/j.ijpe.2017.11.014