Abstract
Recent business and technological trends have transformed the structure and performance requirements for distribution channels in many industries. Higher service level expectations of retail customers, distribution outsourcing by manufacturers, and the proliferation of advanced information technologies drive these transformations, presenting new problems in supply chain management. Motivated by a project with a leading building-products manufacturer, this paper addresses some of these new issues. Over the past two decades, this manufacturer witnessed the migration of building-products sales from independent specialty retailers to largeretail chains, prompting it to create a new network of independent distributors to meet the service expectations of these ‘big-box’ retailers. This paper addresses three important challenges in managing the new distribution network. We first develop a fee-setting model to decide the manufacturer’s compensation scheme for the services provided by its in dependent distributors. Next, we address a tactical distribution planning problem, incorporating resource acquisition and deployment decisions, for scheduled deliveries when demand is highly variable. Lastly, we investigate possible mechanisms for limiting retail store-order variability, and analyze the system-wide cost benefits resulting from variability reduction. In addition to identifying new modeling opportunities and discussing their implications for the building-products manufacturer, this paper highlights new research opportunities resulting from the evolving dynamics of supply chain management.
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References
Baganha, M.P., and M.A. Cohen, 1998. “The Stabilizing Effect of Inventory in Supply Chains,” Operations Research, 46(Su 3), S72–S83.
Balakrishnan, A., H.P. Natarajan, and M.S. Pangburn, 2000 “Optimizing Delivery Feesfora Network of Distributors,” Manufacturing & Service Operations Management, 2(3), 297–316.
Bertsimas, D.J., and D. Simchi-Levi, 1996. “A New Generation of Vehicle Routing Research: Robust Algorithms, Addressing Uncertainty,” Operations Research, 44(2), 286–304.
Birge, J.R., and F. Louveaux, 1997. Introduction to Stochastic Programming, Springer, New York, NY.
Cachon, G.P., 1999. “Managing Supply Chain Demand Variability With Scheduled Ordering Policies,” Management Science, 45(6), 843–856.
Cachon, G.P., and P.H. Zipkin, 1999. “Competitive And Cooperative Inventory Policies In A Two-Stage Supply Chain,” Management Science, 45(7), 936–953.
Chen, F., 1999. “Decentralized Supply Chains Subjectto Information Delays,” Management Science, 45(8), 1076–1090.
Clark, A.J., and H. Scarf, 1960. “Optimal Policies for a Multi-Echelon Inventory Problem,” Management Science, 6, 475–490.
Gavirneni, S., R. Kapuscinski, and S. Tayur, 1999. “The Value Of Information In Capacitated Supply Chains,” Management Science, 45(1), 16–24.
Gendreau, M., G. Laporte, and R. Seguin, 1996. “A Tabu Search Heuristic For The Vehicle Routing Problem With Stochastic Demands And Customers,” Operations Research, 44(3), 469–477.
Gendreau, M., Laporte, G., and Seguin, R., 1996. “Stochastic Vehicle Routing,” European Journal of Operational Research, 88(1), 3–12.
Geunes, J., 1999. Models To Optimize Multi-Stage Linkages In Manufacturing And Distribution Operations, Ph.D. Thesis, Penn State University.
Goldberg, D.E., 1989. Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, MA.
Henig, M., Y. Gerchak, R. Ernst, and D.F. Pyke, 1997. “An Inventory Model Embeddedin Designing a Supply Contract,” Management Science, 43(2), 184–189.
Higle, J.L., and S. Sen, 1996. Stochastic Decomposition: A Statistical Method For Large Scale Stochastic Linear Programming, Kluwer, Boston, MA.
Lee, H.L., V. Padmanabhan, and S. Whang, 1997. “Information Distortion in a Supply Chain: The Bullwhip Effect,” Management Science, 43(4), 546–558.
Lee, H.L., K.C. So, and C.S. Tang, 2000. “The Value of Information Sharing in a Two-Level Supply Chain,” Management Science, 46(5), 626–643.
Lee, H.L., and S. Whang, 1999. “Decentralized Multi-Echelon Supply Chains: Incentives And Information,” Management Science, 45(5), 633–640.
Li, C., and P. Kouvelis, 1999. “Flexible and Risk-Sharing Supply Contracts Under Price Uncertainty,” Management Science, 45(10), 1378–1398.
Moinzadeh, K., and S. Nahmias, 2000. “Adjustment Strategies for a Fixed Delivery Contract,” Operations Research, 48(3).
Nahmias, S., 2000. Production and Operations Analysis, 4th ed., McGraw-Hill, Chicago, IL.
Porteus, E.L., 1990. “Stochastic Inventory Theory,” Ch. 12 in D.P. Heyman and M. Sobel (eds.), Handbooks in OR & MS, v2, North-Holland: Elsevier Publishers B.V., New York, NY.
Porteus, E.L., 2000. “Responsibility Tokens in Supply Chain Management,” Manufacturing & Service Operations Management, 2(2), 203–219.
Simchi-Levi, D., P. Kaminsky, and E. Simchi-Levi, 2000. Designing and Managing the Supply Chain, Irwin McGraw-Hill, Boston, MA.
Stewart, W.R., Golden, B.L., 1983. “Stochastic Vehicle Routing: A Comprehensive Approach,” European Journal of Operational Research, 14(4), 371–385.
Tsay, A., 1999 “The Quantity Flexibility Contract and Supplier-Customer Incentives,” Management Science, 45(10), 1339–1358.
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© 2002 Kluwer Academic Publishers
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Balakrishnan, A., Geunes, J., Pangburn, M.S. (2002). Coordinating the Distribution Chain: New Models for New Challenges. In: Geunes, J., Pardalos, P.M., Romeijn, H.E. (eds) Supply Chain Management: Models, Applications, and Research Directions. Applied Optimization, vol 62. Springer, Boston, MA. https://doi.org/10.1007/0-306-48172-3_9
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DOI: https://doi.org/10.1007/0-306-48172-3_9
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4020-0487-2
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