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研究生: 戴昀潔
Dai, Yun-Jie
論文名稱: 再製造供應鏈中消費者預期後悔對定價策略及OEM採用區塊鏈策略之影響
The impact of consumers’ anticipated regret in remanufacturing supply chains on pricing strategies and OEM’s blockchain adoption strategy
指導教授: 謝中奇
Hsieh, Chung-Chi
學位類別: 碩士
Master
系所名稱: 管理學院 - 工業與資訊管理學系
Department of Industrial and Information Management
論文出版年: 2025
畢業學年度: 113
語文別: 中文
論文頁數: 86
中文關鍵詞: 再製造供應鏈消費者預期後悔區塊鏈技術
外文關鍵詞: Remanufacturing supply chain,, Consumers’ anticipated regret, Blockchain technology
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  • 近年來在永續性、達成淨零碳排的呼聲之下,再製造這種同時具有環境和經濟效益的生產方式逐漸受到關注。然而,一部分消費者對再製品品質存在疑慮,因而對其產生較低的感知品質、降低購買再製品的意願,也導致消費者無法正確判斷再製品估值、增加做出錯誤購買決策的風險,甚至出現購買後的後悔情緒。而區塊鏈的出現,使得供應鏈變得透明,可有效解決消費者對再製品品質不信任的問題,同時提升消費者對產品的感知價值。
    本研究將供應鏈問題設計成數學模型,考慮到再製造供應鏈中原始設備製造商 (Original Equipment Manufacturer, OEM)、第三方再製造商 (Third-Party Remanufacturer, TPR) 以及消費者之間的關係,探討消費者預期後悔 (Anticipated Regret, AR) 如何影響新品及再製品的價格、需求以及供應鏈成員的定價策略,同時關注OEM採用區塊鏈應對消費者預期後悔問題的動機與條件。
    本研究假設市場中存在一個OEM以及一個TPR,OEM將再製造授權給TPR進行,因此OEM僅向市場銷售新品,同時間TPR銷售再製品至市場與OEM競爭並支付單位授權費給OEM。OEM可以選擇是否導入區塊鏈揭露產品資訊,當導入區塊鏈時,會產生新品及再製品感知價值提升以及再製品品質不確定性緩解兩種效應。依據OEM採用區塊鏈的策略建構出兩模型,分別為模型N:OEM不採用區塊鏈,需考量消費者兩種AR心理、模型B:OEM採用區塊鏈,無需考量消費者AR心理,接著運用賽局理論找出供應鏈成員的均衡策略,最後對結果進行數值分析,檢視各參數對決策變數以及利潤的影響趨勢。
    研究發現,從OEM利潤的角度出發,在區塊鏈策略選擇上,市場上消費者對再製品具有高估值的機率越大OEM會更願意導入區塊鏈;而TPR在大多數的情況中皆受益於AR的存在,因此兩者之雙贏局面只存在於AR存在的前提下,並且隨著市場上消費者對再製品具有高估值的機率越大,達成雙贏的可能性越小;最後,若OEM採取向TPR收取授權費之策略可以影響TPR對再製品之定價策略、壓縮TPR之利潤空間並避免其透過過度壓低再製品價格來取得低價優勢,藉此維護新品在市場中的地位。

    In recent years, rising concerns over sustainability and net-zero emissions have drawn attention to remanufacturing, which offers both environmental and economic benefits. However, consumer skepticism about remanufactured product quality often leads to lower perceived value, reduced purchase intention, and inaccurate product evaluation, increasing the risk of poor purchase decisions and post-purchase regret.
    Blockchain technology enhances supply chain transparency, helping to rebuild trust in remanufactured products and improving their perceived value. While existing research has explored remanufacturing, blockchain in supply chains, and consumer anticipated regret separately, few studies integrate these aspects.
    To address this gap, this study develops a supply chain model involving an OEM and a third-party remanufacturer (TPR), focusing on the OEM’s blockchain adoption strategy. The equilibrium decisions and profits for both parties under different scenarios are derived. Results show that, depending on the costs and benefits, the OEM may adopt blockchain to mitigate consumer regret, but in some cases, it may allow regret to persist.

    摘要 i Extended Abstract iii 誌謝 vii 目 錄 viii 圖目錄 xi 表目錄 xiii 第一章、緒論 1 1.1 研究背景與動機 1 1.2 研究目的 4 1.3 研究流程 5 1.4 研究架構 6 第二章、文獻探討 7 2.1 再製造供應鏈 7 2.1.1 授權再製造 7 2.1.2 再製品之不確定估值 8 2.2 消費者預期後悔 9 2.3 區塊鏈技術於供應鏈之應用 10 2.4 小結 12 第三章、研究方法 15 3.1 情境描述 15 3.1.1 情境假設 16 3.1.2 符號定義 18 3.2 消費者效用函式 19 3.2.1 預期後悔之負效用式 19 3.2.2 模型N之消費者效用函式 22 3.2.3 模型B之消費者效用函式 24 3.3 模型建構 25 3.3.1 模型N 25 3.3.2 模型B 28 3.4 小結 33 第四章、數值分析 34 4.1 參數設定 34 4.1.1 模型求解 34 4.1.2 參數範圍 35 4.2 敏感度分析 36 4.2.1 消費者對再製品具有高估值的機率 λ 之敏感度分析 36 4.2.2 高估值型消費者購買再製品後對其真實估值 θH 之敏感度分析 40 4.2.3 新品相對於再製品的單位額外單位生產成本 c 之敏感度分析 43 4.2.4 參數變動影響之整理 47 4.3 區塊鏈策略分析 48 4.3.1 OEM是否導入區塊鏈 48 4.3.2 OEM與TPR之雙贏策略 49 4.4 授權費策略分析 50 4.4.1 消費者效用函式 50 4.4.2 模型建構 51 4.4.3 敏感度分析 52 第五章、結論與未來方向 55 5.1 結論 55 5.2 研究貢獻 56 5.3 未來研究方向 57 參考文獻 59 附錄A 64 模型N效用式建構 64 1. 情況一 pn-pr≤1-θHv 64 2. 情況二 pn-pr≥1-θLv 64 3. 情況三 1-θHv≤pn-pr≤1-θLv 65 命題1之證明 66 模型N求解過程 66 命題2之證明 69 模型B求解過程 69

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