現今的製造業並不僅是在品質出問題時才會面臨退貨問題，製造商間的退貨問題已從過往的品質異常退貨，演進成了未使用之剩餘庫存品退貨，原因在於備料需有前置時間，因此製造商普遍都會有安全庫存以防止斷料，然若終端顧客需求消失客戶急砍單時，則安全庫存就會形成庫存成本負擔，此時客戶為降低存貨成本通常都會要求退貨，而當面對這樣的半成品庫存退貨品時，如果接受了客戶的退貨，可說是會有立即性的外部損失，但如果不接受則又可能會惱怒客戶，最後客戶可能因此轉單他廠，影響層面可說是相當廣大，因此當面臨這樣的退貨問題時，該如何降低退貨損失又不失去競爭力就顯得格外重要。
本研究將利用賽局理論來進行製造業間退貨策略的探討，透過賽局樹的方式進行模擬尋求其均衡策略，或以斯塔克伯格模型結合回購契約並建立數學模型的方式，求解雙方的最佳訂購數量與回購價格並探討雙方利潤變化，最終透過實際案例與敏感度分析，藉此尋求出最佳之協同退貨策略。
分析結果顯示，不論是透過賽局樹來進行的退貨協商策略或是運用斯塔伯格模型來得到先行者有利的回購契約都能讓弱勢的一方得到更好的報酬，而尤其運用斯塔伯格模型所建構的數學模型，不僅能讓弱勢方得到先行者利益，更能透過降低風險的概念，讓彼此的獲利都得到提升，其研究的結果也顯示增加允收退貨率和設定允收退貨價格可有利於訂單的增長。此外，在實務面運用中需特別注意極端值問題，並非一概的否定或全盤的接受所求解出來的數據，應視產業別來調整成最適解，如此才能兼顧理論與實務而得到最佳的協同退貨策略。

Nowadays, manufactures industry face product return problem not only when there are quality problems, but also the unused left inventory return. The reason is that manufactures need to prepare materials before production, so manufactures often have safety inventory to prevent backlogging. However, if clients cancel the orders abruptly, safety inventory will become inventory cost burden. At this time, clients usually demand return to reduce inventory carrying cost. When facing work-in process inventory return, the manufacturers have immediate external failure costs if they accept the return. However, the manufacturers may annoy clients and the orders will be transferred to other factories if they don’t accept the return.
This paper will use game theory to study the returning strategies under two-echelon display optical film supply chain. Through game theory method, we do simulation and seek for its equilibrium. Specifically, we will use Stackelberg model along with buyback contract to implement the mathematical model to solve the best order quantity and buyback price for both parts. Finally, through real cases and sensitivity analysis to seek for the best returning strategies.

目錄
摘要 i
英文摘要 ii
致謝 x
表目錄 xiii
圖目錄 xiv
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 2
第三節 研究範圍與限制 3
第四節 研究流程 4
第五節 論文架構 6
第二章 文獻探討 7
第一節 光學膜產業鏈常見存貨系統 7
第二節 賽局理論 11
第三節 供應鏈協調 19
第四節 小結 25
第三章 問題定義與模型建立 26
第一節 問題定義 26
第二節 模式假設與符號參數定義 30
第三節 模式建構 33
第四節 模式求解 42
第五節 變數範圍探討 45
第六節 小結 46
第四章 個案分析與敏感度分析 47
第一節 個案概述 47
第二節 參數設定 49
第三節 各情境利潤分析說明 51
第四節 敏感度分析 54
第五節 賽局運用實務面探討 58
第六節 小結 62
第五章 結論與建議 64
第一節 研究結果 64
第二節 未來研究方向 65
參考文獻 67

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