博碩士論文 109423049 詳細資訊




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姓名 傅晨哲(Chen-Che Fu)  查詢紙本館藏   畢業系所 資訊管理學系
論文名稱 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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檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 (2027-9-1以後開放)
摘要(中) 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。
摘要(英) 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.
關鍵字(中) ★ 賽局理論
★ 納許Q學習
★ 定價策略
關鍵字(英)
論文目次 中文摘要 ............................................................................................................................. I 英文摘要 ............................................................................................................................ II 誌謝 ...................................................................................................................................III 目錄 ...................................................................................................................................IV 圖目錄 ...............................................................................................................................VI 表目錄 ..............................................................................................................................VII 一、 緒論 ...........................................................................................................................1
1-1 研究動機 ............................................................................................................1
1-2 研究目的 ............................................................................................................1
二、 文獻回顧 ...................................................................................................................3
2-1 賽局模型 ............................................................................................................3
2-2 多代理系統 ........................................................................................................4
三、 賽局模型 ...................................................................................................................8
3-1 賽局模型設置 .................................................................................................... 8
3-2 條件 .................................................................................................................. 14
3-3 命題 .................................................................................................................. 15
四、 納許 Q 學習實作.....................................................................................................17 五、 結果分析 .................................................................................................................19
5-1 賽局模型模擬結果 ..........................................................................................19 iv
5-2 納許Q學習模擬結果 ......................................................................................21 六、 結論 .........................................................................................................................25 參考文獻 ..........................................................................................................................26 附錄 ..................................................................................................................................29
情境一的證明 ..............................................................................................................29 情境二的證明 ..............................................................................................................29 情境四的證明 ..............................................................................................................29 情境三的證明 ..............................................................................................................30
參考文獻 [1] Sharma, A. and J.L. Nicolau, An open market valuation of the effects of COVID-19 on the travel and tourism industry. Annals of Tourism Research, 2020. 83: p. 102990.
[2] Nhamo, G., K. Dube, and D. Chikodzi, Impact of COVID-19 on the Global Network of Airports, in Counting the Cost of COVID-19 on the Global Tourism Industry. 2020, Springer. p. 109-133.
[3] Nhamo, G., K. Dube, and D. Chikodzi, Impact of COVID-19 on global car rental industry and ride and share transport services, in Counting the cost of COVID-19 on the global tourism industry. 2020, Springer. p. 159-181.
[4] Hossain, M., The effect of the Covid-19 on sharing economy activities. Journal of Cleaner Production, 2021. 280: p. 124782.
[5] Yang, Y., W. Jin, and X. Hao. Car rental logistics problem: A review of literature. in 2008 IEEE International Conference on Service Operations and Logistics, and Informatics. 2008. IEEE.
[6] Korstanje, M.E., The Impact of COVID-19 on the Rent-a-Car Industry: An Study Case With Focus in Argentina, in Socio-Economic Effects and Recovery Efforts for the Rental Industry: Post-COVID-19 Strategies. 2021, IGI Global. p. 111-133.
[7] Ciuffini, F., S. Tengattini, and A.Y. Bigazzi, Mitigating Increased Driving after the COVID-19 Pandemic: An Analysis on Mode Share, Travel Demand, and Public Transport Capacity. Transportation Research Record, 2021: p. 03611981211037884.
[8] Lin, M., S. Li, and A.B. Whinston, Innovation and price competition in a two-sided market. Journal of Management Information Systems, 2011. 28(2): p. 171-202.
[9] Gerding, E., et al., Two-sided online markets for electric vehicle charging. 2013.
[10] Hagiu, A., Two‐sided platforms: Product variety and pricing structures. Journal of
Economics & Management Strategy, 2009. 18(4): p. 1011-1043.
[11] Waltman, L. and U. Kaymak, Q-learning agents in a Cournot oligopoly model. Journal
of Economic Dynamics and Control, 2008. 32(10): p. 3275-3293.
[12] Nakov, A. and G. Nuño, Learning from experience in the stock market. Journal of
Economic Dynamics and Control, 2015. 52: p. 224-239.
[13] Hu, J. and M.P. Wellman, Nash Q-learning for general-sum stochastic games. Journal of
machine learning research, 2003. 4(Nov): p. 1039-1069.
[14] Hotelling, H., Stability in competition, in The collected economics articles of Harold
Hotelling. 1990, Springer. p. 50-63.
[15] Wang, S., H. Chen, and D. Wu, Regulating platform competition in two-sided markets under the O2O era. International Journal of Production Economics, 2019. 215: p. 131- 143.
[16] Belleflamme, P. and M. Peitz, Managing competition on a two‐sided platform. Journal of Economics & Management Strategy, 2019. 28(1): p. 5-22.
[17] Armstrong, M., Competition in two‐sided markets. The RAND journal of economics, 2006. 37(3): p. 668-691.
[18] Chakravorti, S. and R. Roson, Platform competition in two-sided markets: The case of payment networks. Review of Network Economics, 2006. 5(1).
[19] Bowling, M. and M. Veloso, An analysis of stochastic game theory for multiagent reinforcement learning. 2000, Carnegie-Mellon Univ Pittsburgh Pa School of Computer Science.
[20] Nurhidayah, F. and F. Alkarim, Domination of transportation network companies (TNCs) in Indonesia: an Indonesian case. International Journal of Business, Economics and Law, 2017. 12(3): p. 11-20.
[21] Suranovic, S., Surge Pricing and Price Gouging: Public Misunderstanding as a Market Imperfection. Institute for International Economic Policy Working Paper Series, Elliott School of International Affairs, George Washington University, IIEP-WP-2015-20, 2015.
[22] Wang, A., The economic impact of transportation network companies on the taxi industry. 2015.
[23] Bernstein, F., G.A. DeCroix, and N.B. Keskin, Competition between two-sided platforms under demand and supply congestion effects. Manufacturing & Service Operations Management, 2021. 23(5): p. 1043-1061.
[24] Nikzad, A., Thickness and competition in ride-sharing markets. Available at SSRN 3065672, 2017.
[25] Ainscough, T.L., P.J. Trocchia, and J.R. Gum, Consumer rental car choice: Price, agent, and brand effects. Journal of Business & Economics Research (JBER), 2009. 7(7).
[26] Lin, X., et al., Should ride-sharing platforms cooperate with car-rental companies? Implications for consumer surplus and driver surplus. Omega, 2021. 102: p. 102309.
[27] Zhang, C., J. Chen, and S. Raghunathan, When sharing economy meets traditional business: Coopetition between ride-sharing platforms and car-rental. Available at SSRN 3659380, 2020.
[28] Sutton, R.S. and A.G. Barto, Reinforcement learning: An introduction. Robotica, 1999. 17(2): p. 229-235.
[29] Watkins, C.J.C.H., Learning from delayed rewards. 1989.
[30] Kaelbling, L.P., M.L. Littman, and A.W. Moore, Reinforcement learning: A survey.
Journal of artificial intelligence research, 1996. 4: p. 237-285.
[31] Tesauro, G. and J.O. Kephart, Pricing in agent economies using multi-agent Q-learning.
Autonomous agents and multi-agent systems, 2002. 5(3): p. 289-304.
[32] Nowé, A., P. Vrancx, and Y.-M.D. Hauwere, Game theory and multi-agent reinforcement
learning, in Reinforcement Learning. 2012, Springer. p. 441-470.
[33] Kaisers, M. and K. Tuyls. Frequency adjusted multi-agent Q-learning. in Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1-Volume 1. 2010.
[34] Kastius, A. and R. Schlosser, Dynamic pricing under competition using reinforcement learning. Journal of Revenue and Pricing Management, 2022. 21(1): p. 50-63.
[35] Vainer, J. and J. Kukacka, Nash Q-learning agents in Hotelling’s model: Reestablishing equilibrium. Communications in Nonlinear Science and Numerical Simulation, 2021. 99: p. 105805.
指導教授 張李治華 審核日期 2022-7-25
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