有鑒於過往品牌商與通路商間議價與通路資源分配過程中，多仰賴過去銷售紀錄與議價人員本身之經驗，較缺乏量化客觀的決策支援系統。本研究以個案公司的冷鏈產品為例，設計一供應鏈系統模擬，找出最適的議價價格與通路資源分配策略。
本研究先探討品牌商與通路商之間的一對一關係，進而針對一家品牌商對多家通路商進行探討。藉由模擬品牌商與通路商在不同議價力情境的議價過程，同時考量在資源有限下不同型態通路間之各式訂單分配規則，評估品牌商及各通路的期望效益，提供實務上品牌商議價與通路資源分配決策的參考。
根據事先設定的議價價位上下限，分為十個價格區間(1-10進貨價格依序由高到低)，透過在模擬10,000的結果。當面對議價力強的通路商，本研究建議品牌商必須把握8-9的價位區間，而面對議價力弱的通路商則可運用6-7價位區間進行最終議價。
在供應鏈通路資源模擬系統中，本研究探討三種資源分配規則。品牌商的績效指標為所有通路的總銷售量、總顧客滿足率以及平均DC庫存持有成本；通路商的績效指標為該通路的銷售量、顧客滿足率以及平均通路庫存持有成本。由於實務上習慣把資源投注在市占率最大或銷售率最高的通路，但長期下來會使中小通路的資源被大通路吞食。另一方面當供應商僅能依靠大通路時，就會使通路的議價力過大失去談判的籌碼。筆者認為在後續研究可以深入探討以總顧客滿足率變異數為指標設計新的資源分配規則，追求效益同時兼顧多通路間資源分配的公平性。

This study based on Taiwan market mainly discussed about international famous brand ice cream supplier negotiate annual sales price and corresponding quantity allocation with multiple channel firm. Especially on perishable product, its property makes challenges on this study.
In general, the process of negotiations and resource allocations between the supplier and channel are mostly depend on the past records and bargaining staff’s experiences. Probably we need a quantized and objective decision-making mechanisms based on simulation results.
There are two parts: Simulation of Negotiation and Simulation Inventory Management. In simulation of negotiation, channel’s bargain power will divide into 5 degrees. On the other side, in simulation of inventory management, we considered three types of allocation rules under four resource scenarios. These results of simulation could offer the brand supplier a practical reference of decision-making.
We suggest that in the future research, we can find out a new resource allocation rules based on the variation of customer satisfaction to purse both the fairness and the efficiency of resource allocation.

第一章 緒論 1
第二章 文獻回顧 11
第三章 研究內容 29
第四章 實驗結果與分析 47
第五章 結論與建議 71
參考文獻 73
附錄 77

1.陳慧娟 (2011)。冷鏈品質協同管理模式與國際趨勢的因應，台灣工業技術研究院。
2.台灣經濟研究院 (2016)。專案計畫執行成果期末報告：通路業者對市場價格掌控能力之研究，經濟部商業司。
3.張銀益、陳慧玲、吳元發、蔡聰源、胡俊之（2009）。多重指標模式在易腐性商品日供應量預測上的應用研究－以S超級市場為例。Journal of Data Analysis，4，1-24。
4.郭幸民 (2012)。系統模擬與Arena應用，滄海書局。
5.曾渙釗 (2008)。採購議價與談判技巧，管理拾穗NO.451。
6.黃允成、呂坤霖（2009）。從間隔時間之觀測到易腐性商品最佳訂購策略之研究。管理研究學報，9，93-113。
7.Bernstein, F.& Federgruen, A. (2003), Pricing and Replenishment Strategies in a Distribution System with Competing Retailers, Operations Research. 51, 3, 409-426.
8.Blackburn, J. & Scudder, G. (2009), Supply Chain Strategies for Perishable Products: The Case of Fresh Produce. Production and Operations Management, 18, 129-137.
9.Cachon, G.P. & Lariviere, M.A.(1999) An equilibrium analysis of linear, proportional and uniform allocation of scarce capacity. IIE Transactions ,31, 835.
10.Çakır, M.& Balagtas, J.V. (2014). Consumer Response to Package Downsizing: Evidence from the Chicago Ice Cream Market, Journal of Retailing, 90, 1, 1-12.
11.Chew, E.P., Lee, C., & Liu, R.. (2009) Joint inventory allocation and pricing decisions for perishable products. International Journal of Production Economics, 120, 1, 139-150.
12.Cormier, G. & Rezg, N., (2011) On coordinating maintenance, production and subcontracting: insights from simulation models, Journal of Quality in Maintenance Engineering, 17, 3, 268-280.
13.Cui, T.H., Raju, J.S., & Zhang, Z.J. (2007). Fairness and Channel. Coordination Management Science ,53,8, 1303-1314.
14.Cui, T.P. & Zhang, Y.. (2018) Cognitive Hierarchy in Capacity Allocation. Management Science ,64, 3, 1250-1270
15.Dai, Y., Chao, S., Fang, S.C, & Nuttle, H.L.W.(2006). Capacity Allocation and Inventory Policy in A Distribution System. Asia-Pacific Journal of Operational Research. 23, 04, 543-571
16.Dragović, B., Tzannatos, E. & Park, N. (2019). Simulation modelling in ports and container terminals: literature overview and analysis by research field, application area and tool. Flexible Services and Manufacturing Journal, 29, 1,4-34
17.Fisher, R.(1984). The Pros and Cons of "Getting to YES". Journal of Legal Education; Durham, N.C., 34, 1, 120.
18.Hall, N.G. & Liu, Z. (2008). Cooperative and Noncooperative Games for Capacity Planning and Scheduling. State-of-the-Art Decision-Making Tools in the Information-Intensive Age. 9, 108-129.
19.Hu, B. , Chao, M., Dong X. &Young, J.S. (2018) Supply chain coordination under vendor managed inventory-consignment stocking contracts with wholesale price constraint and fairness, International Journal of Production Economics, 202, 21-31.
20.Huang, W. & Swaminathan, J.M. (2009). Introduction of a second channel: Implications for pricing and profits. European Journal of Operational Research, 194, 1, 258-279,
21.Ingene, C.A. & Parry, M.E. (1995). Channel Coordination When Retailers Compete. Marketing Science ,14, 360–377.
22.Ingene, C.A. & Parry, M.E.(1998). Manufacturer-Optimal Wholesale Pricing When Retailers Compete. Marketing Letters , 9, 1, 65–77.
23.Jack, G.A.J. van der Vorst, Tromp, S.O. & Durk, J. van der Zee (2009) Simulation modelling for food supply chain redesign; integrated decision making on product quality sustainability and logistics, International Journal of Production Research, 47, 23, 6611-6631
24.Kosalka, T. M. (2006). Decision making through the simulation of centralized and decentralized distribution storage systems. ProQuest Dissertations Publishing.
25.Kumar, N. (1996). The power of trust in manufacturer-retailer relationships. Harvard Business Review. 74, 6, 92-106.
26.Li, D. (2019). Pricing Power of Agricultural Products under the Background of Small Peasant Management and Information Asymmetry. Asian Agricultural Research ,8, 3,12-16.
27.Liu, Z. (2012). Equilibrium analysis of capacity allocation with demand competition. Naval Research Logistics, 59, 254-265.
28.Lo, C.P., (2010) Perishability as a determinant of vertical coordination: The case of the US egg, poultry, and pork industries, China Agricultural Economic Review, 2, 1,49-62.
29.Lusiantoro, L., Yates, N., Mena, C. & Varga, L. (2018). A refined framework of information sharing in perishable product supply chains, International Journal of Physical Distribution & Logistics Management, 48, 3, 254-283
30.Poundstone, W. (2010) The Myth of Fair Value (and How to Take Advantage of It) Farrar, Straus and Giroux.
31.Rijpkema, W.A., Rossi, R., Jack G.A.J. van der Vorst, (2014). Effective sourcing strategies for perishable product supply chains, International Journal of Physical Distribution & Logistics Management, 44 , 6, 494-510
32.Routroy, S. & Bhausaheb, N.A. (2010). Evaluation of Inventory Performance for Perishable Products Through Simulation. IUP Journal of Operations Management, 9, 1/2, 71–80
33.Routroy, S. & Prashanth, T. (2010). Evaluation of Inventory Performance for Perishable Products in a Dynamic Pricing Environment, IUP Journal of Operations Management, 9, 3, 6–15.
34.Salem, R.W. & Haouari, M. (2016). A simulation-optimisation approach for supply chain network design under supply and demand uncertainties, International Journal of Production Research, 55, 7, 1845-1861.
35.Shakoor, M., Nasra, M.AI, Jadayil, W.A., Jaber, N. & Jadayil, S.A. | Duc Pham (Reviewing Editor) (2017). Evaluation of provided services at MRI department in a public hospital using discrete event simulation technique: A case study, Cogent Engineering, 4, 1.
36.Shukla, M. & Jharkharia, S. (2013). Agri‐fresh produce supply chain management: a state‐of‐the‐art literature review, International Journal of Operations & Production Management, 33, 2, 114-158,
37.Suraj, B.V.S. , Sharma, S.K. & Routroy, S. (2016). Positioning of inventory in supply chain using simulation modeling. IUP Journal of Supply Chain Management, 13, 2, 20-32.
38. Weiss, L.B. (2012) Ice Cream: A Global History, Reaktion Books
39.Yang, Y.& Tan, H. (2014). Study on pricing strategy of hybrid distribution channels of Cruise Companies. International Conference on Logistics Engineering, Management and Computer Science, 1951-6851.