利用納許Q學習來探討汽車租賃公司與運輸網路公司之定價策略

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題名:	利用納許Q學習來探討汽車租賃公司與運輸網路公司之定價策略
作者:	傅晨哲;Fu, Chen-Che
貢獻者:	資訊管理學系
關鍵詞:	賽局理論;納許Q學習;定價策略
日期:	2022-07-25
上傳時間:	2022-10-04 12:01:42 (UTC+8)
出版者:	國立中央大學
摘要:	在國外，許多機場周圍都設有汽車租賃服務或是共享乘車服務，然而近兩年新冠肺炎的影響，許多機場的人流大量減少，讓汽車租賃公司與運輸網路公司也連帶受到衝擊，汽車租賃公司將閒置車輛出售以此來維持企業營運。隨著疫情逐漸趨緩，然而先前出售的汽車尚未購回，導致租車數量不足，但需求卻大幅增加，也就讓價格有所變化，因此我們認為租車數量會影響汽車租賃公司與運輸網路公司的定價策略，並且也會影響雙方的市場份額。本篇論文會藉由過去常被用來解決定價策略的賽局分析來去驗證，並且發現租車數量的變化確實會影響到雙方的定價策略與市場份額。除此之外，為了模擬現實世界代理們的運行，我們使用納許 Q 學習來模擬現實世界中，汽車租賃公司和運輸網路公司兩個代理的定價策略，而模擬結果和賽局分析的結果一致。;In foreign countries, many airports have car rental services and shared ride services. However, due to the impact of COVID-19 in the past two years, the flow of people in many airports has decreased significantly, which has also affected car rental companies and transportation network companies. Car rental companies sell their idle vehicles to maintain business operations. As the epidemic gradually eases, the previously sold cars have not been repurchased, resulting in a shortage of rental cars, but the demand has increased significantly, which has changed the price. Therefore, we believe that the number of rental cars will affect the pricing strategies of car rental companies and transportation network companies, and it will also affect the market share. In the literature, game theory model is often used to solve pricing strategy problems, so this thesis also uses game theory to solve pricing strategy problems, and we find that changes in the number of rental cars will indeed affect the pricing strategy and market share. Furthermore, in order to simulate the behavior of real-world agents, we use Nash Q-learning to simulate the pricing policies of two agents, the car rental company and the transportation network company, and the simulation results are consistent with the results of the game theory model.
顯示於類別:	[資訊管理研究所] 博碩士論文

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