Matching supply and demand is the major concern of managers who are dealing with remanufacturing business. Most studies in remanufacturing systems have assumed that supply and demand are two independent flows. This assumption is reasonable for new product manufacturing and sales. However, due to the existence of replacement customers, it does not hold for remanufacturing business.
This study investigates the pricing decisions of a remanufacturing firm who are facing both new and replacement demands. A single-period model is developed to evaluate the benefit of adopting a price discrimination policy. It is the first attempt to study the effect of replacement customers in remanufacturing business. For deterministic yield condition, it is shown that the price discrimination policy is applicable if replacement customers have high price sensitivity, while new customers and acquisition customers have low price sensitivity. When yield rate is uncertain, due to the complexity of the problem, a closed-form solution is not attainable. Computational experiments are conducted to compare the profits of different pricing schemes. Factors like yield rate conditions and customers’ price sensitivities are investigated. The numerical results show that both factors are crucial for the firm. The price discrimination policy to replacement customer is no worse than the uniform pricing policy in every case. Furthermore, price discrimination policy is significantly better off when the yield rate of replacement return is high. The payment scheme of return rebates also affects firm’s profit. According to the numerical study, when rebates are only offered to reusable returns, the firm is significantly better off if replacement and acquisition customers both make decisions only based on the nominal repurchasing price.
The present model has assumed deterministic demand function; in practice, however, the demand information is usually imperfect. Consequently, it is meaningful to incorporate random demand into the model. The company will then decide on both pricing strategy and production quantity. It would increase the complexity of the model, but such a model is similar to the newsvendor problem with endogenous demand, which has been extensively studied. The existing results will facilitate the analysis with a remanufacturing problem setting.
There are several other possible extensions for this model. One is to relax the assumption of independence of new customer and replacement customer. In practice, replacement customers may choose to purchase a new product without returning their old one. The demand from this customer segment will then depend on both f and p. It is expected that the optimal pricing policy would be different, but the price discrimination policy should preserve its profitability. A limitation of this model is that the yield rate is taken as the fraction of reusable returns. In practice, return products are usually under different quality conditions and require different remanufacturing costs. The current model would be more realistic if multiple type returns can be incorporated. Besides, one can also consider that the remanufactured products are imperfect substitutes of brand-new products. It is interesting to see how cannibalization effect will change the pricing decisions in such cases. 

Appendix

References

Atasu A, Sarvary M, Van Wassenhove LN (2008) Remanufacturing as a marketing strategy. Manage Sci 54:1731–1746. doi:10.1287/mnsc.1080.0893

Bakal IS, Akcali E (2006) Effects of random yield in remanufacturing with price-sensitive supply and demand. Prod Oper Manage 15:407–420. doi:10.1111/j.1937-5956.2006.tb00254.x

Bayus BL (1991) The consumer durable replacement buyer. J Market 55:42–51

Bollapragada S, Morton TE (1999) Myopic heuristics for the random yield problem. Oper Res 47:713–722. doi:10.1287/opre.47.5.713

Debo LG, Toktay LB, Wassenhove LNV (2006) Joint life-cycle dynamics of new and remanufactured products. Prod Oper Manage 15:498–513. doi:10.1111/j.1937-5956.2006.tb00159.x

Ferrer G (2003) Yield information and supplier responsiveness in remanufacturing operations. Eur J Oper Res 149:540–556. doi:10.1016/S0377-2217(02)00454-X

Fleischmann M, Bloemhof-Ruwaard JM, Dekker R, van der Laan E, van Nunen JA, Wassenhove LNV (1997) Quantitative models for reverse logistics: a review. Eur J Oper Res 103:1–17. doi:10.1016/S0377-2217(97)00230-0

Guide VDR, Jayaraman V (2000) Product acquisition management: current industry practice and a proposed framework. Int J Prod Res 38:3779–3800. doi:10.1080/00207540050176003

Guide VDR, Van Wassenhove LN (2003) Business aspects of closed-loop supply chains. Carnegie Mellon University Press, Pittsburgh

Guide VDR, Van Wassenhove LN (2009) Or forum-the evolution of closed-loop supply chain research. Oper Res 57:10–18. doi:10.1287/opre.1080.0628

Guide VDR, Teunter RH, Van Wassenhove LN (2003) Matching demand and supply to maximize profits from remanufacturing. Manufactur Serv Oper Manage 5:303–316. doi:10.1287/msom.5.4.303.24883

Hsu A, Bassok Y (1999) Random yield and random demand in a production system with downward substitution. Oper Res 47:277–290. doi:10.1287/opre.47.2.277

Inderfurth K, Transchel S (2007) Technical note note on “myopic heuristics for the random yield problem”. Oper Res 55:1183–1186. doi:10.1287/opre.1070.0420

Li Q, Zheng S (2006) Joint inventory replenishment and pricing control for systems with uncertain yield and demand. Oper Res 54:696–705. doi:10.1287/opre.1060.0273

Lo ST, Wee HM, Huang WC (2007) An integrated production-inventory model with imperfect production processes and weibull distribution deterioration under inflation. Int J Prod Econ 106:248–260. doi:10.1016/j.ijpe.2006.06.009

Lund RT, Hauser WM (2010) Remanufacturing - an American perspective. In: 5th international conference on responsive manufacturing - green manufacturing (ICRM 2010), Ningbo, pp 1–6

Mukhopadhyay SK, Ma H (2009) Joint procurement and production decisions in remanufacturing under quality and demand uncertainty. Int J Prod Econ 120:5–17. doi:10.1016/j.ijpe.2008.07.032

Novemsky N, Kahneman D (2005) The boundaries of loss aversion. J Market Res 42:119–128. doi:10.1509/jmkr.42.2.119.62292

Ray S, Boyaci T, Aras N (2005) Optimal prices and trade-in rebates for durable, remanufacturable products. Manufactur Serv Oper Manage 7:208–228. doi:10.1287/msom.1050.0080

Savaskan RC, Bhattacharya S, Van Wassenhove LN (2004) Closed-loop supply chain models with product remanufacturing. Manage Sci 50:239–252. doi:10.1287/mnsc.1030. 0186

Souza GC (2008) Closed-loop supply chains with remanufacturing. INFORMS, Hanover, MD

Tang O, Musa SN, Li J (2012) Dynamic pricing in the newsvendor problem with yield risks. Int J Prod Econ 139:127–134. doi:10.1016/j.ijpe.2011.01.018

Wee H, Yu J, Chen M (2007) Optimal inventory model for items with imperfect quality and shortage backordering. Omega 35:7–11. doi:10.1016/j.omega.2005.01.019

Winer RS (1997) Discounting and its impact on durables buying decisions. Market Lett 8:109–118

Yano CA, Lee HL (1995) Lot sizing with random yields: a review. Oper Res 43:311–334. doi:10.1287/opre.43.2.311

Zhou SX, Yu Y (2011) Optimal product acquisition, pricing, and inventory management for systems with remanufacturing. Oper Res 59:514–521

Zhou SX, Tao Z, Chao X (2011) Optimal control of inventory systems with multiple types of remanufacturable products. Manufactur Serv Oper Manage 13:20–34. doi:10.1287/msom.1100.0298

Zikopoulos C, Tagaras G (2007) Impact of uncertainty in the quality of returns on the profitability of a single-period refurbishing operation. Eur J Oper Res 182:205–225. doi:10.1016/j.ejor.2006.10.025