本文探討具有損耗性的商品在單一批發商對多個零售商的配銷通路之中，決策制定協調對其利潤之影響。我們設定在單一批發商及多個零售商的結構下，當零售端面對價格及存貨水準相依的需求環境時，研究四種不同的配銷通路策略，分別為單店個別補貨策略、多店協同補貨策略、多店VMI協同補貨策略和多店VMI協同補貨加寄售策略。
探討在四個策略中，配銷通路成員會採取不同的補貨週期及零售價決策來最大化利潤，在單店個別補貨策略，零售商制定對自己最佳的補貨週期及零售價；在多店協同補貨策略，零售端會提出共同補貨週期及協調零售價，使零售端利潤最大化；在多店VMI協同補貨策略，由於批發商代為管理存貨，以通路單位時間利潤最大化訂定補貨週期，零售端再依此補貨週期訂定共同零售價；在多店VMI協同補貨加寄售策略，批發商同時決定補貨週期及零售價格，對通路單位時間利潤最大化，訂定補貨週期及零售價格。
本文的目的分析當配銷系統採用上述不同策略且產品具有損耗性特質時，決策制定之協調、供應商管理存貨所產生的價值，並且檢視配銷系統中因決策制定協調產生之價值是如何分配在成員之間，我們利用數值分析來輔助了解可能的情形為何，並透過敏感度分析來了解在參數變動下，對各整合策略通路單位時間利潤的影響。

This study is to discuss the impact of vender managed inventory and decision-making coordination for perishable items in a distribution system consisting of multiple retailers and upstream wholesaler . We consisting of four varying-level strategies for integrating a distribution system—including “single retailer coordinated replenishment and pricing”, “multiple retailers coordinated replenishment and pricing”, and “vendor managed inventory ” ,” vendor managed inventory with coordinated pricing”.
Depending on the four strategies, members of a distribution system tend to adopt different replenishment model to maximize their profit. We assume that the downstream retailers face a continuous time-varying and price- varying demand and generate his own optimal replenishment interval to trigger the upstream wholesaler replenishment under decentralized decision making. On the other hand, we develop a system coordination replenishment model with the objective of maximizing whole system profit to generate the common replenishment interval under centralized decision making.
Our objective is to quantify and analyze value generated from a system of vendor managed inventory and decision coordination for perishable items in a whole distribution system according to aforementioned four different strategies, and then, to observe how the value is distributed among members of the system. In the study, data simulation analysis is used to investigate all possible situations, and sensitivity analysis to find out effects of variable parameters on each strategy.

1. 鄒易宏(2007), Information Sharing and Decision Coordination for Perishable Items in a Supply Chain 損耗性商品在配銷系統中之資訊分享和決策制定之協調,國立中央大學工業管理研究所碩士論文。
2. Abdul-Jalbar, B., & Gutiérrez, J., & Puerto, J., & Sicilia, J.,(2003). Policies for inventory/distribution systems: The effrct of centralization vs. Decentralization. International Journal of Production Economics 81-82 (1), 281-293.
3. Achabal, D.D., & Mcintyre, S.H., & Smith, S.A., & Kalyanam, K.,(2000) A Decision Support System for Vendor Managed Inventory. Journal of Retailing, Volume 76(4) pp. 430–454,
4. Axsäter, S., & Zhang, W.F., (1999). A joint replenishment policy for multi-echelon inventory control. International Journal of Production Economics 59 (1-3), 243-250.
5. Banerjee, A., (1986). A joint economic-lot-size model for purchaser and vendor. Decision sciences 17 (3), 292-311.
6. Banerjee, A., & Kim, S., (1995). An integrated JIT inventory model. International Journal of Operations & Production Management 15 (9), 237-244.
7. Banerjee, A.,& Banerjee, S., (1992). Coordinated, orderless inventory replenishment for a single supplier and multiple buyers through electronic data interchange. International Journal of Technology Management 7 (4/5), 328-336.
8. Boyd, E.A.,& Bilegan, I.C., (2003). Revenue management and e-commerce. Management Science 49, 1363-1386.
9. Cachon, P.T., & M.A.Lariviere (2005),Supply chain coordination with revenue-sharing contracts: strengths and limitations, Management Science 50, 30-44.
10. Chan, C.K., & Cheung, B.K.-S., & Langevin, A., (2003). Solving the multi-buyer joint replenishment problem with a modified genetic algorithm. Transportation Research Part B: Methodological 37 (3), 291-299.
11. Chen, J.M.,& Chen, T.H.,(2005), Effects of joint replenishment and channel coordination. Journal of the Operational Research Society (2005) 56, 1224–1234
12. Chen, T.H.,& Chen, J.M.,(2005),Optimizing supply chain collaboration based on joint replenishment and channel coordination distribution channel. Transportation Research Part E 41 (2005) 261–285
13. Chen, J.M.,& Chen, T.H.,(2007)The profit-maximization model for a multi-item distribution channel. Transportation Research Part E 43 (2007) 338–354
14. Corbett, C.J., & D. Zhou., & C.S Tang,.,(2004),Designing supply contract: contract type and information asymmetry, Management Science 50, 550-559.
15. Covert, R.P., & Philip, G.C., (1973). An EOQ model for items with Weibull distribution deterioration. AIIE Trans 5: 323-326.
16. Dave, U. & Patel, L.K. (1981). (T, Si) Policy inventory model for deteriorating items with time proportional demand. Journal of the Operational Research Society 32: 137-142.
17. Federgruen, A., & Tzur, M., (1994). The joint replenishment problem with time-varying costs and demands: efficient, asymptotic and Є–optimal solutions. Operations Research 42 (6), 1067-1086.
18. Federgruen, A., & Zheng, Y.S., (1992). The joint replenishment problem with general joint cost structures. Operations Research 40 (2), 384-403.
19. Ford, W. H.,(1913) HOW MANY PARTS TO MAKE AT ONCE. The Magazine of Management, Volume 10, Number 2, February 19 13, pp. 135-136, 152
20. Frenk, J.B.G., & Kleijn, M.J., & Dekker, R., (1999). An efficient algorithm for a generalized joint replenishment problem. European Journal of Operational Research 118 (2), 413-428.
21. Frohlich, M.T.,& Westbrook, R., (2002). Demand chain management in manufacturing and services: web-based integration, drivers and performance. Journal of Operations Management 20, 729–745.
22. Fung, R.Y.K., & Ma, X., (2001). A new method for joint replenishment problems. Journal of the Operacional Research Society 52 (3), 358-362.
23. Ghare, P.M. & Schrader, G..F. (1963), A model for exponentially decaying inventories, Journal of Industrial Engineering, Vol.14, 238-243.
24. Hollier, R.H., & Mak, K.L., & Lai, K.K., (2002). Computing optimal (s,S) policies for inventory systems with a cut-off transaction size and the option of joint replenishment. International Journal of Production Research 40 (14), 3375-3389.
25. Ingene, C.A., & M.E. Parry(1995), Channel coordination when retailer compete, Marketing Science 14,360-377.
26. Iyer, G.,(1998), Coordinating channels under price and nonprice competition, Marketing Science 17,338-355.
27. Jackson, P., & Maxwell, W., & Muckstadt, J., (1985). The joint replenishment problem with a power-of-two restriction. IIE Transactions 17 (1), 25-32.
28. Joneja, D., (1990). The joint replenishment problem: New heuristics and worst case performance bounds. Operations Research 38 (4), 711-723.
29. Kao, E.P.C., (1979). A multi-product dynamic lot-size model with individual and joint set-up costs. Operations Research 27 (2), 279-289.
30. Kaspi, M., & Rosenblatt, M.J., (1985). The effectiveness of heuristic algorithms for multi-item inventory systems with joint replenishment costs. International Journal of Production Research 23 (1), 109-116.
31. Khouja, M., (2003). Optimizing inventory decisions in a multi-stage multi-customer supply chain. Transportation Research Part E: Logistics and Transportation Review 39 (3), 193-208.
32. Khouja, M., & S. Goyal.,(2008), A review of the joint replenishment problem literature:1989–2005, European Journal of Operational Research 186 (2008) 1–16.
33. Krishnan, H., & R. Kapuscinski, & Butz, D.A.,(2004), Coordinating contracts for decentralized supplychains with retailer promotional effort, Management Science 50,48-63.
34. Lee, F.C., & Yao, M.J., (2003). A global optimum search algorithm for the joint replenishment problem under power-of-two policy. Computers and Operations Research 30 (9), 1319-1333.
35. Lee, H.L,& Whang, S., (2001). Demand chain excellence. Supply Chain Management Review March-April, 40-46.
36. Lee, W., (2005). A joint economic lot size model for raw material ordering, manufacturing setup, and finished goods delivering. Omega 33 (2), 163-174.
37. Lu, L., (1995). A one-vendor multi-buyer integrated inventory model. European Journal of Operational Research 81 (2), 312-323.
38. Miranda, P.A.,& Garrido, R.A., (2004). Incorporating inventory control decisions into a strategic distribution network design model with stochastic demand. Transportation Research Part E: Logistics and Transportation Review 40 (3), 183-207.
39. Moon, I. & Lee, S. (2000). The effects of inflation and time-value of money on an economic order quantity model with a random product life cycle. European Journal of Operational Research 125: 588-601.
40. Nahmias, S. (1978), Perishable inventory theory: A review, Operations Research, Vol.30, No.4, 680-708.
41. Nielsen, C., &Larsen, C.,(2005). An analytical study of the Q(s, S) policy applied to the joint replenishment problem. European Journal of Operational Research 163 (3), 721-732.
42. Netessine, S. and N. Rudi.,(2006), Supply chain choice on the internet, Management Science 52,844-864.
43. Raju, J. and Z.J. Zhang.,(2005), Channel coordination in the presence of a dominant retailer, Marketing Science 24,254-262.
44. Philip, G.C. (1974). A generalized EOQ model for items with Weibull distribution. AIIE Trans 6: 159-162.
45. Sachan, R.S. (1984). On (T, Si) Policy inventory model for deteriorating items with time proportional demand. Journal of the Operational Research Society 35: 1013-1019.
46. Sahin, F. & Robinson, E.P. (2002), Flow coordination and information sharing in supply chains: review, implications, and directions for future research, Decision Sciences, Vol.35, No.4, 505-536.
47. Silver, E.A., (1976). A simple method of determining order quantities in jointly replenishments under deterministic demand. Management Science 22 (12), 1351-1361.
48. Spiegel, M.R., (1960). Applied differential equations. Englewood Cliffs, NJ: Prentice-Hall.
49. Sodhi, M.S.,& Sodhi, N.C., (2005). Six sigma pricing. Harvard Business Review 82 (5), 135-142.
50. Sucky, E., (2004). Coordinated order and production policies in supply chains. OR Spectrum 26, 493-520.
51. Tadikamalla, P.R. (1978). An EOQ inventory model for items with gamma distributed deterioration. AIIE Trans 10: 78.
52. van Eijs, M.J.G., Heuts, R.M.J., Kleijnen, J.P.C., (1992). Analysis and comparison of two strategies for multi-item inventory systems with joint replenishment costs. European Journal of Operational Research 59, 405–412.
53. Viswanathan, S.,& Piplani, R., (2001). Coordinating supply chain inventories through common replenishment epochs. European Journal of Operational Research 129 (2), 277-286.
54. Wang,Y.,& Gerchak,Y.,(2002),Supply chain contracting and coordination with shelf space dependent demand, Supply Chain Management: Models, Applications, and Research Directions, 137—162.