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Annals of Operations Research

, Volume 206, Issue 1, pp 59–74 | Cite as

The impact of customer returns on supply chain decisions under various channel interactions

  • Jing ChenEmail author
  • Peter C. Bell
Article

Abstract

We examine a supply chain in which a manufacturer supplies a single product to a retailer who faces two forms of customer returns. We compare the impact of these two forms of customer returns on the decisions and profits of the manufacturer and the retailer under various types of channel interaction: Manufacturer Stackelberg (MS), Vertical Nash (VN), and Retailer Stackelberg (RS). We find that when the level of customer returns that are proportional to quantity sold is extremely high, the retailer prefers the MS rather than the RS channel interaction. We also examine the impact of the asymmetric customer returns information on the decisions of the manufacturer and the retailer and on profits under MS and VN channel interactions. We show that in the MS case, the retailer can decide whether or not to share customer returns information with its manufacturer without knowing the manufacturer’s estimates of customer returns and in the VN case, both the retailer and the manufacturer can decide whether or not to share/acquire the information based on observation of the other’s behavior. The issues of sharing this information are also discussed.

Keywords

Managing customer returns Channel interaction Information sharing 

References

  1. Anderson, E. T., Hansen, K., & Simister, D. (2009a). The option value of returns: theory and empirical evidence. Marketing Science, 28, 405–423. CrossRefGoogle Scholar
  2. Anderson, E. T., Hansen, K., Simister, D., & Wang, L. K. (2009b). How are demand and returns related? Theory and empirical evidence. Working paper, Kellogg School of Management, Northwestern University. Google Scholar
  3. Biederman, D. (2005). Many happy returns. Journal of Commerce, December, 1–3. Google Scholar
  4. Blanchard, D. (2005). Moving forward in reverse. Logistics Today, 46, 1. Google Scholar
  5. Blanchard, D. (2007). Supply chains also work reverse. Industry Week, May 1. Google Scholar
  6. Bonifield, C., Cole, C., & Schultz, R. (2010). Product returns on the internet: a case of mixed signals? Journal of Business Research, 63, 1058–1065. CrossRefGoogle Scholar
  7. Chen, J. (2011). The impact of sharing customer returns information in a supply chain with/without a buyback policy. European Journal of Operational Research, 213, 478–488. CrossRefGoogle Scholar
  8. Chen, J., & Bell, P. C. (2009). The impact of customer returns on pricing and order decisions. European Journal of Operational Research, 195, 280–295. CrossRefGoogle Scholar
  9. Chiang, W. K., Chhajed, D., & Hess, J. (2003). Direct marketing, indirect revenues: a strategic analysis of dual-channel supply chain design. Management Science, 49, 1–20. CrossRefGoogle Scholar
  10. Choi, C. S. (1991). Price competition in a channel structure with a common retailer. Marketing Science, 10, 271–296. CrossRefGoogle Scholar
  11. Choi, T. M., & Sethi, S. (2010). Innovative quick response programmes: a review. International Journal of Production Economics, 127, 1–12. CrossRefGoogle Scholar
  12. Esmaeili, M., Aryanezhad, M., & Zeephongsekul, P. (2009). A game theory approach in seller-buyer supply chain. European Journal of Operational Research, 195, 442–448. CrossRefGoogle Scholar
  13. Ferguson, M., Guide, M. Jr., & Souza, G.C. (2006). Supply chain coordination for false failure returns. Manufacturing & Service Operations Management, 8, 376–393. CrossRefGoogle Scholar
  14. Fiala, P. (2005). Information sharing in supply chain. Omega, 33, 419–423. CrossRefGoogle Scholar
  15. Hess, J., & Mayhew, G. (1997). Modeling merchandise returns in direct marketing. Journal of Direct Marketing, 11, 20–35. CrossRefGoogle Scholar
  16. Jeuland, A., & Shugan, S. (1983). Managing channel profits. Marketing Science, 2, 239–272. CrossRefGoogle Scholar
  17. Ketzenberg, M. E., Rosenzweig, E. D., Marucheck, A. E., & Metters, R. D. (2007). A framework for the value of information in inventory replenishment. European Journal of Operational Research, 182, 1230–1250. CrossRefGoogle Scholar
  18. Lau, H. S., & Lau, A. (1999). Manufacturer’s pricing strategy and return policy for a single period commodity. European Journal of Operational Research, 116, 291–304. CrossRefGoogle Scholar
  19. Lau, A., Lau, H. S., & Zhou, Y. W. (2007). A stochastic and asymmetric information framework for a dominant manufacturer supply chain. European Journal of Operational Research, 176, 295–316. CrossRefGoogle Scholar
  20. Lee, E., & Staelin, R. (1997). Vertical strategic interaction: implications for channel pricing strategy. Marketing Science, 16, 185–207. CrossRefGoogle Scholar
  21. McGuire, T., & Staelin, R. (1983). An industry equilibrium analysis of downstream vertical integration. Marketing Science, 2, 161–191. CrossRefGoogle Scholar
  22. Mitra, S. (2007). Revenue management for remanufactured products. Omega, 35, 553–562. CrossRefGoogle Scholar
  23. Mostard, J., & Teunter, R. (2006). The newsboy problem with resalable returns: a single period model and case study. European Journal of Operational Research, 169, 81–96. CrossRefGoogle Scholar
  24. Pasternack, B. A. (1985). Optimal pricing and returns policies for perishable commodities. Marketing Science, 4, 166–176. CrossRefGoogle Scholar
  25. Petersen, A., & Kumar, V. (2010). Can product returns make you money? MIT Sloan Management Review, 51, 85–89. Google Scholar
  26. Pralle, A., & Stalk, G. Jr. (2006). Returns: the ugly ducklings of retail. The Boston Consulting Group’s report. Google Scholar
  27. Rogers, D. S., & Tibben-Lembke, R. S. (1999). Going backwards: reverse logistics trends and practices. Pittsburgh: Reverse Logistics Executive Council. Google Scholar
  28. Rogers, D. S., Lambert, D. M., Croxton, K., & Garcia-Dastugue, S. (2002). The returns management process. International Journal of Logistics Management, 13, 1–18. CrossRefGoogle Scholar
  29. Roy, C. (2009). Debunking the myths of customer returns and the use of liquidation channels. Retail/Catalog Online Integration. http://www.retailonlineintegration.com/article/debunking-myths-customer-returns-use-liquidation-channels-409310/1.
  30. Sciarrotta, T. (2003). How PHILIPS reduced returns. Supply Chain Management Review, 7, 32–38. Google Scholar
  31. Strauss, M. (2006). Returns a $10-billion pain. Globe and Mail, November, B-7. Google Scholar
  32. Vlachos, D., & Dekker, R. (2003). Return handling options and order quantities for single period products. European Journal of Operational Research, 151, 38–52. CrossRefGoogle Scholar
  33. Wang, J., Lau, H. S., & Lau, A. (2009). When should a manufacturer share truthful manufacturing cost information with a dominant retailer? European Journal of Operational Research, 197, 266–286. CrossRefGoogle Scholar
  34. Yao, D. Q., & Liu, J. J. (2005). Competitive pricing of mixed retail and e-tail distribution channels. Omega, 33, 235–247. CrossRefGoogle Scholar
  35. Yuan, X. M., & Cheung, K. L. (1996). Modeling returns of merchandise in an inventory system. OR Spektrum, 20, 147–154. Google Scholar
  36. Yue, X., & Raghunathan, S. (2006). The impacts of the full returns policy on a supply chain with information asymmetry. European Journal of Operational Research, 180, 630–647. CrossRefGoogle Scholar
  37. Loss Prevention Research Council (2008). Customer returns in the retail industry. Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Faculty of Business and EconomicsUniversity of WinnipegWinnipegCanada
  2. 2.Richard Ivey School of BusinessUniversity of Western OntarioLondonCanada

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