Abstract
We consider a supply chain in which a distributor procures from a manufacturer a type of fresh product, which has to undergo long distance transportation before reaching the market. In addition to the risk caused by random fluctuations of the market demand, the distributor also faces the risk that the product procured may decay and deteriorate during transportation. The market demand for the product depends on its level of freshness and the distributor’s selling price. The manufacturer has to determine his wholesale price based on its effect on the order quantity of the distributor, whereas the distributor has to determine his order quantity and selling price, based on the wholesale price, the likely loss of the product in long distance transportation, the product’s level of freshness when it reaches the market, and the possible demand for the product. We develop a model to formulate this problem, and derive each party’s optimal decisions in both uncoordinated and coordinated situations. We introduce a new incentive scheme to facilitate the coordination of the two parties, which comprises two parts: (1) the manufacturer offers his wholesale price as a function of the actual transportation time and price discount in the market; and (2) the manufacturer compensates the distributor for any unsold unit of the product. We show that this incentive scheme can induce the distributor to order up to the quantity required to maximize the total benefit of the centralized system, and both parties will all be better off than in the uncoordinated case. Computational studies are also conducted, which reveal some interesting managerial insights.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Agrawal, V., & Seshadri, S. (2000). Risk intermediation in supply chains. IIE Transactions, 32(9), 819–831.
Anupindi, R., & Bassok, Y. (1999). Supply contracts with quantity commitments and stochastic demand. In S. Tayur, M. Magazine, & R. Ganeshan (Eds.), Quantitative models for supply chain management (pp. 197–232). Boston: Kluwer.
Barlow, R. E., & Proschan, F. (1965). Mathematical theory of reliability. New York: Wiley.
Bernstein, F., & Federgruen, A. (2005). Decentralized supply chains with competing retailers under demand uncertainty. Management Science, 51(1), 18–29.
Bookbinder, J. H., & Cakanyildirim, M. (1999). Random lead times and expedited orders in (Q, r) inventory systems. European Journal of Operational Research, 115, 300–313.
Cachon, G. P. (2003). Supply chain coordination with contracts. Chapter 6. In S. Graves & T. Kok, Handbooks in operations research and managment science: Supply chain management. New York: North-Holland publishers.
Cachon, G. P., & Lariviere, M. A. (2005). Supply chain coordination with revenue-sharing contracts: strengths and limitations. Management Science, 1, 30–44.
Cai, X., Chen, J., Xiao, Y., & Xu, X. (2010). Optimization and coordination of fresh product supply chains with freshness-keeping effort. Production and Operations Management, 19, 261–278.
Chen, F. (2003). Information sharing and supply chain coordination. In S. Graves & T. Kok, Chapter 7, Handbooks in operations research and managment science: Supply chain management. New York: North-Holland publishers.
Eppen, G. D., & Iyer A. V. (1997). Backup agreements in fashion buying—the value of upstream flexibility. Management Science, 43(11), 1469–1484.
Eppen, G. D., & Martin, R. K. (1988). Determining safety stock in the presence of stochastic lead time and demand. Management Science, 34(11), 1380–1390.
Feng, Y. Y., & Xiao, B. C. (2008). A combined risk and revenue analysis for managing perishable products. Operations Research, 56(5), 1305–1311.
Goyal, S. K, & Giri, B. C. (2001). Recent trends in modeling of deteriorating inventory. European Journal of Operational Research, 134, 1–16.
Hagen, J. W., Minami, D., Mason, B., & Dunton, W. (1999). California’s produce trucking industry: characteristics and important issues. California Agricultural Technology Institute, http://cab.cati.csufresno.edu/research_publications/99/990301/.
Karaesmen, I. Z., Scheller-Wolf, A., & Deniz, B. (2011). Managing perishable and aging inventories: review and future research directions. In K. G. Kempf, P. Keskinocak, & R. Uzsoy (Eds.), Planning production and inventories in the extended enterprise (pp. 393–436). USA: Springer.
Kasmire, R. F. (1999). Fresh produce and perishability, RBCS Handbook, http://www.thepacker.com/rbcs/handbookarticles/properis.htm
Krishan, H., Kapuscinski, R., & Butz, D. (2004). Coordinating contracts for decentralized supply chains with retailer promotional effort. Management Science, 50(1), 48–63.
Lal, R., Little, J. D. C., & Villas-Boas, J. M. (1996). A theory of forward buying, merchandising, and trade deals. Marketing Science, 15(1), 21–37.
Lodree Jr., E. J., & Uzochukwu, B. M. (2008). Production planning for a deteriorating item with stochastic demand and consumer choice. International Journal of Production Economics, 116, 219–232.
Lau, H. S., & Zhao, L. G. (1993). Optimal ordering policies with two suppliers when lead times and demands are all stochastic. European Journal of Operational Research, 68, 120–133.
Nahmias, S. (1982). Perishable inventory theory: a review. Operations Research, 30(4), 680–708.
Nawrocki, D. (1999). A brief history of downside risk measures. Journal of Investing, 8(3), 9–26.
Organisation for Economic Co-operation and Development (2005). OECD in Figure-2005 edition, http://www.oecd.org/document/.
Parlar, M., & Wang, Q. (1994). Discounting decisions in a supplier-buyer relationship under a linear buyer’s demand. IIE Transactions, 26, 34–41.
Pasternack, B. (1985). Optimal pricing and returns for perishable commodities. Marketing Science, 4(2), 166–176.
Petruzzi, N. C., & Dada, M. (1999). Pricing and the newsvendor problem: a review. Operations Research, 47(2), 183–194.
Plambeck, E., & Zenios, S. (2000). Performance-based incentives in a dynamic principal-agent model. Manufacturing and Service Operations Management, 2, 240–263.
Raafat, F. (1991). Survey of literature on continuously deteriorating inventory models. Journal of the Operational Research Society, 42, 27–37.
Rajan, A., Steinberg, R., & Steinberg, R. (1992). Dynamic pricing and ordering decisions by a monopolist. Management Science, 38(2), 240–262.
Ray, S., Li, S. L., & Song, Y. Y. (2005). Tailored supply chain decision making under price-sensitive stochastic demand and delivery uncertainty. Management Science, 51(12), 1873–1891.
Sanchez, J., & Kipe, S. (2004). U.S. Horticulture Exports to Asia 2004, Foreign Agricultural Service, Horticultural and Tropical Products Division, United States Department of Agriculture.
Shen, D., Lai, K. K., Leung, S. C. H., & Liang, L. (2010). Modelling and analysis of inventory replenishment for perishable agricultural products with buyer-seller collaboration. International Journal of Systems Science, 10, 1–11.
Song, X. P., Cai, X., & Chen, J. (2005). Studies on interaction and coordination in supply chains with perishable products: a review. In C. K. Chan & H. W. J. Lee (Eds.), Successful strategies in supply chain management, Chapter X (pp. 222–248), Idea Group PA: Inc.
Taylor, T. (2000). Coordination under Channel Rebates with Sales Effort Effect. Working Paper, Stanford University, Stanford.
Tsay, A. (1999). The quantity flexibility contract and supplier-customer incentives. Management Science, 45(10), 1339–1358.
Tsay, A., S. Nahmias, & Agrawal, N. (1999). Modeling supply chain contracts: a review. In S. Tayur, R. Ganeshan, & M. Magazine (Eds.), Chapter 10, Quantitative Models for Supply Chain Management. Boston: Kluwer Academic.
Wang, Q. N. (2001). Coordinating independent buyers in a distribution system to increase a supplier’s profits. Manufacturing & Service Operation Management, 3, 337–348.
Wang, Y. (2004). Joint Pricing-production Decisions in Supply Chains of Complementary Products with Uncertain Demand. Working Paper, Weatherhead School of Management, Case Western Reserve University.
Wang, Y., Jiang, L., & Shen, Z. (2004). Channel performance Under consignment contract with revenue sharing. Management Science, 50(1), 34–47.
Weng, Z. K. (1995). Channel coordination and quantity discounts. Management Science, 41, 1509–1522.
Weng, Z. K. (1999). The power of coordinated decisions for short-life-cycle products in a manufacturing and distribution supply chain. IIE Transactions, 31, 1037–1049.
Whitin, T. M. (1957). Theory of inventory management. NJ: Princeton University Press.
Acknowledgements
We gratefully acknowledge the support of (i) Research Grants Council of Hong Kong, GRF No. CUHK410509 and Direct Grant No. 2050415, for X. Q. Cai; (ii) National Natural Science Foundation of China, Research Fund No. 70890082 and 70621061, and the MOE, P.R. China, through the Project of the Key Research Institute of Humanities and Social Sciences in Universities, under Grant No. 08JJD630001, for J. Chen; (iii) National Natural Science Foundation of China, Research Fund No. 70601017 and 71071083 for Y. B. Xiao, and (iv) National Natural Science Foundation of China, Research Fund No. 70801035 and 71171105, for X. L. Xu.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media New York
About this chapter
Cite this chapter
Cai, X., Chen, J., Xiao, Y., Xu, X., Yu, G. (2012). Optimal Decisions of the Manufacturer and Distributor in a Fresh Product Supply Chain Involving Long-Distance Transportation. In: Choi, TM. (eds) Handbook of Newsvendor Problems. International Series in Operations Research & Management Science, vol 176. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3600-3_14
Download citation
DOI: https://doi.org/10.1007/978-1-4614-3600-3_14
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-3599-0
Online ISBN: 978-1-4614-3600-3
eBook Packages: Business and EconomicsBusiness and Management (R0)