{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T19:28:24Z","timestamp":1773775704065,"version":"3.50.1"},"reference-count":10,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2016,9,6]],"date-time":"2016-09-06T00:00:00Z","timestamp":1473120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGecom Exch."],"published-print":{"date-parts":[[2016,9,6]]},"abstract":"<jats:p>We study dynamic pricing policies for ridesharing platforms such as Lyft and Uber. On one hand these platforms are two-sided: this requires economic models that capture the incentives of both drivers and passengers. On the other hand, these platforms support high temporal-resolution for data collection and pricing: this requires stochastic models that capture the dynamics of drivers and passengers in the system.<\/jats:p>\n          <jats:p>We summarize our main results from [Banerjee et al. 2015], in which we study the role of dynamic pricing in ridesharing platforms using a queueing-theoretic economic model. We build a model of two-sided ridesharing platforms that captures both the stochastic dynamics of the marketplace and the strategic decisions of drivers, passengers and the platform. We show how our model can help explain the success of dynamic pricing in practice: in particular, we argue that the benefit of dynamic pricing over static pricing is not in the optimal performance, but rather, in the robustness of its performance to uncertainty in system parameters.<\/jats:p>","DOI":"10.1145\/2994501.2994505","type":"journal-article","created":{"date-parts":[[2016,9,6]],"date-time":"2016-09-06T12:48:51Z","timestamp":1473166131000},"page":"65-70","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":51,"title":["Dynamic pricing in ridesharing platforms"],"prefix":"10.1145","volume":"15","author":[{"given":"Siddhartha","family":"Banerjee","sequence":"first","affiliation":[{"name":"Cornell University"}]},{"given":"Ramesh","family":"Johari","sequence":"additional","affiliation":[{"name":"Stanford University"}]},{"given":"Carlos","family":"Riquelme","sequence":"additional","affiliation":[{"name":"Stanford University"}]}],"member":"320","published-online":{"date-parts":[[2016,9,6]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1287\/opre.1110.1027"},{"key":"e_1_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Banerjee S. Johari R. and Riquelme C. 2015. Pricing in ride-sharing platforms: A queueing-theoretic approach. Available at SSRN 2568258.  Banerjee S. Johari R. and Riquelme C. 2015. Pricing in ride-sharing platforms: A queueing-theoretic approach. Available at SSRN 2568258 .","DOI":"10.2139\/ssrn.2568258"},{"key":"e_1_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Gallego G. and van Ryzin G. 1994. Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Management science 40 8 999--1020.  Gallego G. and van Ryzin G. 1994. Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Management science 40 8 999--1020.","DOI":"10.1287\/mnsc.40.8.999"},{"key":"e_1_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Gurvich I. Lariviere M. and Moreno A. 2014. Staffing service systems when capacity has a mind of its own. Available at SSRN 2336514.  Gurvich I. Lariviere M. and Moreno A. 2014. Staffing service systems when capacity has a mind of its own. Available at SSRN 2336514 .","DOI":"10.2139\/ssrn.2336514"},{"key":"e_1_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Hassin R. and Haviv M. 2003. To queue or not to queue: Equilibrium behavior in queueing systems. Vol. 59. Springer Science & Business Media.  Hassin R. and Haviv M. 2003. To queue or not to queue: Equilibrium behavior in queueing systems . Vol. 59. Springer Science & Business Media.","DOI":"10.1007\/978-1-4615-0359-0"},{"key":"e_1_2_1_6_1","unstructured":"Kelly F. P. 1979. Reversibility and stochastic networks. Cambridge University Press.   Kelly F. P. 1979. Reversibility and stochastic networks . Cambridge University Press."},{"key":"e_1_2_1_7_1","doi-asserted-by":"crossref","unstructured":"Kojima F. and Pathak P. A. 2009. Incentives and stability in large two-sided matching markets. The American Economic Review 608--627.  Kojima F. and Pathak P. A. 2009. Incentives and stability in large two-sided matching markets. The American Economic Review 608--627.","DOI":"10.1257\/aer.99.3.608"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1162\/154247603322493212"},{"key":"e_1_2_1_9_1","unstructured":"Talluri K. T. and van Ryzin G. J. 2006. The theory and practice of revenue management. Vol. 68. Springer Science & Business Media.  Talluri K. T. and van Ryzin G. J. 2006. The theory and practice of revenue management . Vol. 68. Springer Science & Business Media."},{"key":"e_1_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Weyl E. G. 2010. A price theory of multi-sided platforms. The American Economic Review 1642--1672.  Weyl E. G. 2010. A price theory of multi-sided platforms. 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