網際網路交易之動態價格模式｜國立清華大學博碩士論文庫

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研究生：	陳彥翔 Yen-Hsiang Chen
論文名稱：	網際網路交易之動態價格模式 Dynamic Pricing Model on the Internet Market
指導教授：	溫于平 Ue-Pyng Wen
口試委員:
學位類別：	碩士 Master
系所名稱：	工學院 - 工業工程與工程管理學系 Department of Industrial Engineering and Engineering Management
論文出版年：	2004
畢業學年度：	92
語文別：	英文
論文頁數：	45
中文關鍵詞：	動態價格、有時限的商品、收益管理、網際網路市場
外文關鍵詞：	Dynamic Pricing, Perishable Products, Revenue Management, Internet Market
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很多企業的業者都有機會透過動態價格來增加收益，尤其是針對像是飛機票、旅館房間和流行性商品等有時限的商品，這些商品在一特定期間內若沒售完就會變得沒有價值，因此如何利用顧客不同的購買時間和剩下的商品數，動態地調整有時限商品的價格使業者收益最大，即成為一個重要的議題。由於網際網路的發達，使得賣方對於市場變化能夠作即時的反應，以及網路上較低的價格更新成本，於是動態價格在網際網路交易的應用顯得更有價值。
本研究建構了網際網路交易中之動態價格模式，其中交易的商品為有時限的商品。根據模式，可以計算出所有最佳的時間序列，然後藉著這些轉換價格的時間點，可以動態地調整價格使業者獲得最大收益。此外，本篇提出了幾個定理說明模式中期望收益和時間序列的特性，接著並以一售票系統為例，證實如何應用本研究提出的模式，計算出時間序列來動態地調整商品的售價。最後亦探討了幾個很實際的延伸問題，包括業者能額外訂貨以及允許顧客退還商品。

In many industries, sellers have the opportunity to enhance their revenues through the dynamic pricing of their perishable products such as flight seats, hotel rooms, and seasonal fashion goods that become worthless if they are not sold by a specific time. Therefore, how to dynamically adjust the prices of perishable products through differentiating the purchased time and the amount of unsold items to maximize the revenue is an important issue. Due to the immediate response and lower menu cost on the Internet, the application of the dynamic pricing to the Internet market is especially valuable.
In this thesis, we construct a dynamic pricing model for selling a given stock of identical perishable products over a finite time horizon on the Internet. By the model, we can compute all optimal switching time. Then according to the calculated time thresholds, we can dynamically adjust prices on the Internet to maximize the total profit. In addition, we propose some lemmas to demonstrate the properties of the expected revenue and the time thresholds in the model. Furthermore, we illustrate a numerical example to show the procedure and the results. Finally, we examine several extensions where overbooking, re-supply, and cancellations are allowed.

Table of Content
Abstract……………………………………………………………...……i
Acknowledgement……………………………………………………….iii
Table of Content………………...……………………………………… iv
List of Figures…………………………………………………………vi
List of Tables…………………………………………….……………vii
Chapter 1  Introduction………………………………………………….1
1.1    Background and Motivation………………………………………………….1
1.2    Research Aims and Scope……………………………………………………4
1.3    Framework of this Thesis…………………………………………………….5
Chapter 2  Literature Review……………………………………………7
2.1 Revenue Management………………………………………………………..7
2.2 Seat Inventory Control……………………………………………………….8
2.3 Dynamic Pricing Policy……………………………………………………...9
2.4 Overbooking…………………………………………………………...……11
2.5 Dynamic Pricing on the Internet……………………………………………12
Chapter 3  Model Construction………………………………………..14
3.1 Problem Statement………………………………………………………….14
3.1.1 Problem Assumptions and Restrictions………………….……………...…..14
3.1.2 Notations…..……………………………………………….………...……..15
3.2 Model Framework…………………………………………………………..16
3.2.1 Model Description ………………………………………….………...…….16
3.2.2 Model Formulation………………………………………….………...…….16
3.3 Structure of the Time Thresholds…………………………………………...24
Chapter 4  Numerical Examples………………………….…………...27
4.1 Ticket Pricing Example……………………………………………………..27
4.2 Character of the Time Thresholds…………………………………………..31
Chapter 5  Extensions………………………………….……………...35
5.1 Re-supply…………………………………………………………………...35
5.2 Cancellations……………………………………………………………….37
Chapter 6  Conclusion…………………………………………………41
Reference………………………………………………………………..43

List of Figures
Figure 1.1 Procedure of the study……………………………………………………..6
Figure 2.1 Framework of revenue management……………………………………….7
Figure 4.1 All time thresholds in the entire period…………………………………...30
Figure 4.2 Time thresholds with last 5 tickets left…………………………………...31
Figure 4.3 Comparisons in high demand and low demand…………………………..32
Figure 4.4 Time thresholds in time period 8 to 12…………………………………...33
Figure 4.5 Time thresholds in time period 23 to 26………………………………….34
Figure 5.1 Comparisons in three different probability of the cancellations………….40
Figure 6.1 Time thresholds with last 20 tickets left………………………………….42

List of Tables
Table 4.1 Data in Example 1…………………………………………………………27
Table 4.2 Demand and revenue in Example 1………………………………………..28
Table 4.3 Optimal time thresholds   in high demand (Example 1)……………….28
Table 4.4 Optimal time thresholds   in low demand (Example 1)………………..29
Table 4.5 Optimal time thresholds   in medium demand (Example 1)…………...29
Table 5.1 The expected revenue   in Example 2……………………………..36
Table 5.2 The expected revenue   at t = 28.5…………………………………37
Table 5.3 Time thresholds   in three cases in Example 3…………………………39

                                

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