{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T23:00:31Z","timestamp":1772060431351,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T00:00:00Z","timestamp":1738022400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72171102"],"award-info":[{"award-number":["72171102"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Improving the performance of the operations of ride-hailing platforms (RHPs) by adequately considering drivers\u2019 switching behaviors is becoming crucial for their profitability and sustainability. This study explores how to optimize the operations of RHPs by investigating the impact of commission rates on drivers\u2019 switching behaviors in a dynamic mobility market. Two queue-theory-based mathematical models have been developed to explore the relationship between commission rates, drivers\u2019 switching behaviors, and critical platform parameters in optimizing the operations of RHPs. Numerical examples are presented to demonstrate the applicability of such models in determining the best commission rate to optimize the operations of RHPs in duopoly and fully competitive market conditions. The findings suggest that understanding the intricate relationship between commission rates, drivers\u2019 switching behaviors, and critical platform parameters is significant for RHPs in formulating appropriate strategies and policies to ensure their sustainable operations.<\/jats:p>","DOI":"10.3390\/systems13020080","type":"journal-article","created":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T07:54:08Z","timestamp":1738050848000},"page":"80","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Improving Ride-Hailing Platform Operations in Dynamic Markets: A Drivers\u2019 Switching Perspective"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5639-3101","authenticated-orcid":false,"given":"Xingguang","family":"Chen","sequence":"first","affiliation":[{"name":"School of Business, Jianghan University, Wuhan 430056, China"},{"name":"Manufacturing Industry Development Research Center on Wuhan City Circle, Wuhan 430056, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1215-1650","authenticated-orcid":false,"given":"Hepu","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Business, Jianghan University, Wuhan 430056, China"},{"name":"School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, VIC 3000, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.cities.2018.01.012","article-title":"Ridesourcing, the sharing economy, and the future of cities","volume":"76","author":"Jin","year":"2018","journal-title":"Cities"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"104728","DOI":"10.1016\/j.trc.2024.104728","article-title":"Competition between autonomous and traditional ride-hailing platforms: Market equilibrium and technology transfer","volume":"165","author":"Wang","year":"2024","journal-title":"Transp. 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