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研究生: 魏鴻儒
Wei, Hung-Ju
論文名稱: 考量顧客差異性及超賣政策之航空業者動態定價策略
Dynamic Pricing Strategies for Airlines Considering Customer Heterogeneity and Overbooking Policies
指導教授: 莊雅棠
Chuang, Ya-Tang
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: 73
中文關鍵詞: 顧客差異動態規劃超賣政策
外文關鍵詞: Customer Heterogeneity, Dynamic Programming, Overbooking
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  • 航空公司在制定機票定價策略時,面臨乘客需求差異、座位有限以及乘客未登機現象(No-show)等挑戰。為了有效應對這些問題,本研究建立了一個有限期的動態規劃模型,旨在最大化航空業者的收益。基於乘客需求的異質性,本研究選用了混合多項羅吉特模型(Mixed Multinomial Logit Model, MMNL)來區分不同乘客群體對於票價的選擇行為。相比於多項羅吉特模型(Multinomial Logit Model, MNL),MMNL模型能夠更精確地捕捉乘客偏好中的隨機性,適用於反映商務乘客和休閒乘客等不同群體的需求差異。模型同時考量了超賣政策與乘客未登機現象對收益的潛在影響,並透過動態調整每個銷售期的票價,找出最佳的定價策略。

    When designing ticket pricing strategies, airlines face multiple challenges such as heterogeneous customer demand, limited seat capacity, and passenger no-shows. To address these issues effectively, this study develops a finite-horizon dynamic programming model aimed at maximizing airline revenue. Considering the heterogeneity of passenger preferences, the Mixed Multinomial Logit (MMNL) model is adopted to distinguish the ticket choice behavior of different customer segments. Compared to the traditional Multinomial Logit (MNL) model, the MMNL model better captures the randomness in individual preferences, making it suitable for representing the varying sensitivities of business and leisure travelers. The proposed model also incorporates the impact of overbooking policies and no-show behavior on expected revenue, and dynamically adjusts ticket prices across multiple selling periods to determine the optimal pricing strategy.

    摘要 i 英文延伸摘要 ii 目錄 vii 表目錄 ix 圖目錄 x 第一章 緒論 1 1.1 研究動機 1 1.2 研究目標 5 1.3 論文架構 5 第二章 文獻回顧 7 2.1 顧客差異性 7 2.2 馬可夫決策過程 8 2.3 艙等差異 9 2.4 多項羅吉特模型 10 2.5 混合多項羅吉特模型 12 2.6 超賣政策 13 第三章 模型建構 15 3.1 問題描述 15 3.2 情境假設 18 3.3 顧客購買行為 19 3.3.1 效用函數設計 19 3.3.2 選擇機率的推導 19 3.4 定價模型 20 第四章 模型求解 25 4.1 模型求解流程 25 4.1.1 MMNL模型計算步驟 25 4.1.2 動態規劃 27 4.2 參數設定 30 4.3 結果與分析 31 4.3.1 銷售期數 32 4.3.2 剩餘座位數 36 4.3.3 客群比例 45 4.3.4 超賣政策 49 第五章 結論與未來研究方向 54 5.1 結論 54 5.2 未來研究建議 55 5.2.1 納入退票 55 5.2.2 針對多艙等進行超賣 55 5.2.3 超賣懲罰為非線性成長 56 5.2.4 考慮團體乘客 56 參考文獻 58

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