Abstract
Consumers’ strategic behavior and psychological perception have impact on supply chains. In this paper, we consider a supply chain with one supplier and one retailer to study the influence of disappointment-aversion strategic (DAS) consumers on supply chain members’ decisions and performance. The results of this study show that strategic consumers can reduce the profit levels of such a supply chain, whilst DAS consumers can alleviate this effect. We also study the effectiveness of a quantity commitment strategy for a centralized supply chain when faced with DAS consumers. Under certain conditions, the quantity commitment strategy can further reduce the loss of profit caused by strategic consumers. Then the maximum profit of the centralized supply chain under the quantity commitment strategy is used as a benchmark. We then analyze the coordination efficiency and implementability of a wholesale price contract and a price subsidy contract respectively in a decentralized supply chain. The results show that the wholesale price contract can achieve the optimal profit benchmark of the centralized supply chain, but it can only realize fixed profit allocation to supply chain members; the price subsidy contract can not only achieve the optimal profit of the centralized supply chain but also make arbitrary profit allocation among chain members.
Similar content being viewed by others
References
Arya A, Mittendorf B (2006) Benefits of channel discord in the sale of durable goods. Mark Sci 25(1):91–96
Baron O, Hu M, Najafi-Asadolahi S, Qian Q (2015) Newsvendor selling to loss-averse consumers with stochastic reference points. Manuf Serv Oper Manag 17(4):456–469
Bell DE (1985) Disappointment in decision making under uncertainty. Oper Res 33(1):1–27
Bitran G, Caldentey R (2003) An overview of pricing models for revenue management. Manuf Serv Oper Manag 5(3):203–229
Cachon GP, Swinney R (2009) Purchasing, pricing, and quick response in the presence of strategic consumers. Manage Sci 55(3):497–511
Chen M, Chen ZL (2015) Recent developments in dynamic pricing research: multiple products, competition, and limited demand information. Prod Oper Manag 24(5):704–731
Coase RH (1972) Durability and monopoly. J Law Econ 15(1):143–149
Desai P, Koenigsberg O, Purohit D (2004) Strategic decentralization and channel coordination. Quant Mark Econ 2(1):5–22
Elmaghraby W, Keskinocak P (2003) Dynamic pricing in the presence of inventory considerations: research overview, current practices, and future directions. Manage Sci 49(10):1287–1309
Giannoccaro I, Pontrandolfo P (2004) Supply chain coordination by revenue sharing contracts. Int J Prod Econ 89(2):131–139
Ho T, Tang C, Bell D (1998) Rational shopping behavior and the option value of variable pricing. Manage Sci 44(12):S145–S160
Huang T, Liu Q (2016) Strategic capacity management when customers have boundedly rational expectations. Prod Oper Manag 24(12):1852–1869
Jacobson R, Obermiller C (1990) The formation of expected future price: a reference price for forward-looking consumers. J Consum Res 16(4):420–432
Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica 47(2):263–291
Kőszegi B, Rabin M (2007) Reference-dependent risk attitudes. Am Econ Rev 97(4):1047–1073
Krishna A (1994) The impact of dealing patterns on purchase behavior. Mark Sci 13(4):351–373
Lai G, Debo LG, Sycarza K (2010) Buy now and match later: impact of posterior price matching on profit with strategic consumers. Manuf Serv Oper Manag 12(1):33–55
Levin Y, Mcgill J, Nediak M (2008) Dynamic pricing in the presence of strategic consumers and oligopolistic competition. Manage Sci 55(1):32–46
Li T, Yu M (2017) Coordinating a supply chain when facing strategic consumers. Decis Sci 48(2):336–355
Liu Q, Ryzin GJ (2008) Strategic capacity rationing to induce early purchases. Manage Sci 54(6):1115–1131
Liu Q, Shum S (2013) Pricing and capacity rationing with customer disappointment aversion. Prod Oper Manag 22(5):1269–1286
Loomes G, Sugden R (1986) Disappointment and dynamic consistency in choice under uncertainty. Rev Econ Stud 53(2):271–282
Loomes G, Sugden R (1987) Testing for regret and disappointment in choice under uncertainty. Econ J 97(388a):118–129
Nasser S, Turcic D (2015) To commit or not to commit: revisiting quantity vs. price competition in a differentiated industry. Manage Sci 62:1719–1733
Palsule-Desai OD (2013) Supply chain coordination using revenue-dependent revenue sharing contracts. Omega 41(4):780–796
Ren H, Huang T (2018) Modeling customer bounded rationality in operations management: a review and research opportunities. Comput Oper Res 91:48–58
Song Y, Ray S, Li S (2008) Structural properties of buyback contracts for price-setting newsvendors. Manuf Serv Oper Manag 10(1):1–18
Sonsino D (2008) Disappointment aversion in internet bidding-decisions. Theor Decis 64(2–3):363–393
Su X (2007) Intertemporal pricing with strategic customer behavior. Manage Sci 53(5):726–741
Su X, Zhang F (2008) Strategic customer behavior, commitment, and supply chain performance. Manage Sci 54(10):1759–1773
Swinney R (2013) Selling to strategic consumers when product value is uncertain: the value of matching supply and demand. Manage Sci 57(4):1737–1751
Yang D, Qi E, Li Y (2015) Quick response and supply chain structure with strategic consumers. Omega 52:1–14
Ye T, Sun H (2016) Price-setting newsvendor with strategic consumers. Omega 63:103–110
Yin R, Aviv Y, Pazgal A, Tang CS (2009) Optimal markdown pricing: implications of inventory display formats in the presence of strategic customers. Manage Sci 55(8):1391–1408
Zhang Y, Donohue KL, Cui TH (2016) Contract preferences and performance for the loss-averse supplier: buyback versus revenue sharing. Manage Sci 62:1734–1754
Acknowledgments
This research is supported by the National Natural Science Foundation of China (Grant No. 71871173, 72031009, 71871171, 71501149, 71772143), the National Social Science Foundation of China (Grant No. 20&ZD058) and The Fundamental Research Funds for the Central Universities (WHUT: 2019VI029, 2019III001). The fifth author is grateful for the support by NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (U1709215).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
1.1 Proof for Proposition 1
According to equation (3), the profit function of the alliance is
\(\Pi_{c} (Q,p) = pE(X \wedge Q) + sE(Q - X)^{ + } - cQ\). Substituting \(E(Q - X)^{ + } = Q - E(Q \wedge X)\) into the above formula, we get.
\(\Pi_{c} (Q,p) = (p - s)E(X \wedge Q) - (c - s)Q{ = }(p - s)[\int_{0}^{Q} {xf(x)dx} + \int_{Q}^{ + \infty } {Qf(x)dx} ] - (c - s)Q\).
Since \(\frac{{\partial \Pi_{c} (Q,p)}}{\partial Q} = (p - s)\overline{F} (Q) - (c - s)\) and \(\frac{{\partial^{2} \Pi_{c} (Q,p)}}{{\partial Q^{2} }} = - (p - s)f(Q) < 0\), \(\Pi_{c} (Q,p)\) is a concave function of \(Q\) that has a unique maximum value. Based on the first-order condition, let \(\frac{{\partial \Pi_{c} (Q,p)}}{\partial Q} = 0\), and then \(\overline{F} (Q) = \frac{c - s}{{p - s}}\). From Eq. (4), we can get
Substituting (21) into the above equation, we can get formula (6). Substituting formula (6) into formula (21), we can get formula (7).
1.2 Proof for Proposition 4
We first prove that this contract can achieve the maximum profit benchmark of the centralized supply chain under quantity commitment. That is, the retailer's optimal ordering quantity \(Q_{m} = Q_{q}^{*}\). When the supply chain achieves the maximum profit under the quantity commitment, for the wholesale price contract, the optimal ordering quantity \(Q_{q}^{*}\) and the price \(p^{*}\) are characterized by
Let parameters \(w_{m}\) and \(m\) under the price subsidy contract satisfy
and
where \(\chi > 0\). In this contract, the conditions of RE equilibrium are
Therefore, under the price subsidy contract, the ordering quantity \(Q_{m}\) and price \(p_{m}\) based on the RE equilibrium satisfy
Comparing (22 and 28), if \(p_{m} > p^{*}\), then \(\overline{F} (Q_{m} ) < \overline{F} (Q_{q}^{*} )\); comparing (23 and 29), if \(\overline{F} (Q_{m} ) < \overline{F} (Q_{q}^{*} )\), since when \(0 < k < \overline{k}\), function \((1 - x)\sqrt {1 + kx}\) is a decreasing function of \(x\)(\(0 < x < 1\)), then \(p^{*} > p_{m}\), which contradicts with \(p_{m} > p^{*}\). If \(p_{m} < p^{*}\), it will also lead to a contradiction. Therefore, there must be \(p^{*} = p_{m}\), so that \(\overline{F} (Q_{m} ) = \overline{F} (Q_{q}^{*} )\), and thereby \(Q_{m} = Q_{q}^{*}\). The price subsidy contract can achieve the maximum profit of the centralized supply chain under quantity commitment.
Then we prove that for any \(\lambda \in [0,1]\), when \({{\chi = \lambda } \mathord{\left/ {\vphantom {{\chi = \lambda } {\lambda^{*} }}} \right. \kern-\nulldelimiterspace} {\lambda^{*} }}\), the retailer's profit is \(\lambda \Pi_{q}^{*}\).
Substituting \({{\chi = \lambda } \mathord{\left/ {\vphantom {{\chi = \lambda } {\lambda^{*} }}} \right. \kern-\nulldelimiterspace} {\lambda^{*} }}\) into (24 and 25), we can get \(w_{m} = (1 - \frac{\lambda }{{\lambda^{*} }})p^{*} + \frac{\lambda }{{\lambda^{*} }}w^{*}\), \(m = (1 - \frac{\lambda }{{\lambda^{*} }})(p^{*} - s)\).
Proofs for Proposition 2, 3 and 5 can be easily obtained from the context.
Rights and permissions
About this article
Cite this article
Quan, J., Wang, X., Wang, X. et al. Performance optimization of supply chain based on cooperative contract with disappointment-aversion strategic consumers. Flex Serv Manuf J 34, 408–428 (2022). https://doi.org/10.1007/s10696-021-09419-6
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10696-021-09419-6