臺灣博碩士論文加值系統

自美國在1978年解除對航空業管制後，航空公司便使用收益管理來獲得最大化收益。隨著航空業競爭日益激烈，收益管理被航空公司視為可以使企業成功的重要工具之一而逐漸獲得重視。
由於受到飛機座位容量之限制，航空公司必須對各艙等進行座位配置及訂定票價來最大化收益。過去研究通常將座位配置問題與訂價問題視為兩個獨立問題並分開討論。然而在實務上，各艙等需求數量是依票價高低來決定。故本研究以反需求函數建立需求與票價間之關係。並以兩種不同方法：期望邊際座位配置法與數學規劃法建立在不同情境下，可以同時決定追求最大化收益下之座位配置與票價模式。期望邊際座位收益法主要考量座位之邊際收益將隨著座位配置量的增加而下降，因此在計算各艙等的座位配置量時，是以各艙等座位配置量的期望邊際座位收益值為基礎。而數學規劃法可以在已知限制（如機位容量限制與票價限制）下進行座位配置與訂價，並求得最佳預期收益。
藉由模式測試結果可以發現透過數學規劃法所求得之最佳收益與期望邊際座位配置法相比，可以獲得較高之預期收益。另外，為了探討兩種方法在預期收益上之差異，本研究亦比較期望邊際座位配置法與數學規劃法所求之票價與座位配置量之差異。

After the 1978 US Airline Deregulation Act removed many of regulations over airlines, revenue management (RM) systems were introduced to the airlines for objectively maximizing their revenue. With the increased competition in the airline industry, RM has been recognized as an important tool for the business success in such industry and received a lot of attention. Due to the limited aircraft seats, airlines must determine the amount of seats to be allocated to each of all fare class seats and the fares of those seats to charge to maximize revenues. Previous researches related to RM in airlines generally considered pricing and seat allocation as two problems and studied them independently. However, in practice, the demand of each class seat depends on its fare. Therefore, we assume inverse demand function, the fare for each fare class seat depends upon the number of seats demanded by itself. This study used the methods of expected marginal seat revenue (EMSR) and mathematical programming to formulate seat allocation and pricing models to simultaneously determine the optimal fare and seat allocation multiple fare class seats, in such that the total expected revenue is maximized. The computational results on the test examples presented in this study demonstrated that the use of mathematical programming method can achieve optimal revenue, with the results that are better than those achieved with EMSR method. We also compared the difference between the solutions solved by mathematical programming method and EMSR method

目錄
第一章 緒論 1
1.1. 研究背景與動機 1
1.2. 研究問題、方法與目的 2
1.3. 研究流程 4
第二章 文獻回顧 6
2.1. 座位配置模式 6
2.1.1. 座位配置研究類型 8
2.1.2. 連續型需求變數之座位配置研究 10
2.1.3. 離散型需求變數之座位配置研究 15
2.2. 艙等價格座位需求與價格關係 18
2.3. 小結 20
第三章 模式建構 23
3.1. 票價反需求函數與模式假設 23
3.2. 單航段多艙等下之模式建構 26
3.2.1. 以數學規劃法在單航段多艙等下之模式建構 26
3.2.2. 以期望邊際座位收益法在單航段多艙等下之模式建構 29
3.2.3. 在單航段多艙等下兩種方法之比較 31
3.3. 多航段單艙等下之模式建構 35
3.3.1. 以數學規劃法在多航段單艙等下之模式建構 35
3.3.2. 以期望邊際座位收益法在多航段單艙等下之模式建構 39
3.3.3. 在多航段單艙等下兩種方法之比較 41
3.4. 多航段多艙等下之模式建構 46
3.4.1. 以數學規劃法在多航段多艙等下之模式建構 47
3.4.2. 以期望邊際座位收益法在多航段多艙等下之模式建構 56
3.4.3. 在多航段多艙等下兩種方法之比較 61
3.5. 小結 65
第四章 模式測試 67
4.1. 需求之機率分配 67
4.2. 反需求函數係數之設計 68
4.3. 單航段多艙等之座位配置 68
4.3.1. 數學規劃法之座位配置 69
4.3.2. 期望邊際座位收益法之座位配置 71
4.3.3. 單航段多艙等下之敏感度分析 73
4.4. 多航段單艙等之座位配置 78
4.4.1. 數學規劃法之座位配置 79
4.4.2. 期望邊際座位收益法之座位配置 82
4.4.3. 多航段單艙等下之敏感度分析 86
4.5. 多航段多艙等之座位配置 92
4.5.1. 數學規劃法之座位配置 92
4.5.2. 期望邊際座位收益法之座位配置 99
4.5.3. 多航段多艙等下之敏感度分析 108
4.6. 小結 118
第五章 研究結論與建議 119
參考文獻 121
一、中文部分 121
二、英文部分 121

一、中文部分
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