Non-Exclusive Notifications for Ride-Hailing at Lyft II: Simulations and Marketplace Analysis
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866912978372132864 |
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| author | Ekbatani, Farbod Niazadeh, Rad Golari, Mehdi Camilleri, Romain Jehl, Titouan Sholley, Chris Leventi, Matthew Calderon, Theresa Lam, Angela Duclos, Paul Havard Holland, Tim Koch, James Reddy, Shreya |
| author_facet | Ekbatani, Farbod Niazadeh, Rad Golari, Mehdi Camilleri, Romain Jehl, Titouan Sholley, Chris Leventi, Matthew Calderon, Theresa Lam, Angela Duclos, Paul Havard Holland, Tim Koch, James Reddy, Shreya |
| contents | Ride-hailing platforms increasingly face uncertain driver acceptance, which makes traditional one-to-one 'exclusive dispatch (ED)' less efficient: rejections and timeouts force sequential retries and lengthen rider wait times, which in turn creates friction in the marketplace. 'Non-exclusive dispatch (NED)' mitigates this friction by broadcasting a request to multiple drivers in parallel. While NED can reduce latency, it introduces new design challenges -- most notably, how to choose notification sets and how to resolve driver contention (when multiple drivers accept the same ride).
In this paper -- the second in a two-part collaboration with Lyft -- we develop a theoretically grounded framework to evaluate the long-run performance and marketplace effects of transitioning from ED to NED. We bridge theory and practice by combining (i) an optimization model that formulates NED as a constrained welfare maximization problem with (ii) large-scale discrete-event simulations on proprietary Lyft traces and (iii) a stylized macroscopic equilibrium model. Across simulation and equilibrium analysis, we find that NED improves key fulfillment metrics relative to ED: it reduces match time (and hence rider reneging) while increasing both the number and the average quality of completed matches. We also quantify the speed--quality trade-off between two common contention resolution rules, 'First-Accept' and 'Best-Accept': First-Accept maximizes speed and throughput, whereas Best-Accept is required to maximize per-match quality. Finally, we show that slightly conservative notification heuristics can improve long-run efficiency by avoiding excessive locking of high-value drivers and preserving future availability. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2603_21531 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Non-Exclusive Notifications for Ride-Hailing at Lyft II: Simulations and Marketplace Analysis Ekbatani, Farbod Niazadeh, Rad Golari, Mehdi Camilleri, Romain Jehl, Titouan Sholley, Chris Leventi, Matthew Calderon, Theresa Lam, Angela Duclos, Paul Havard Holland, Tim Koch, James Reddy, Shreya Computer Science and Game Theory Ride-hailing platforms increasingly face uncertain driver acceptance, which makes traditional one-to-one 'exclusive dispatch (ED)' less efficient: rejections and timeouts force sequential retries and lengthen rider wait times, which in turn creates friction in the marketplace. 'Non-exclusive dispatch (NED)' mitigates this friction by broadcasting a request to multiple drivers in parallel. While NED can reduce latency, it introduces new design challenges -- most notably, how to choose notification sets and how to resolve driver contention (when multiple drivers accept the same ride). In this paper -- the second in a two-part collaboration with Lyft -- we develop a theoretically grounded framework to evaluate the long-run performance and marketplace effects of transitioning from ED to NED. We bridge theory and practice by combining (i) an optimization model that formulates NED as a constrained welfare maximization problem with (ii) large-scale discrete-event simulations on proprietary Lyft traces and (iii) a stylized macroscopic equilibrium model. Across simulation and equilibrium analysis, we find that NED improves key fulfillment metrics relative to ED: it reduces match time (and hence rider reneging) while increasing both the number and the average quality of completed matches. We also quantify the speed--quality trade-off between two common contention resolution rules, 'First-Accept' and 'Best-Accept': First-Accept maximizes speed and throughput, whereas Best-Accept is required to maximize per-match quality. Finally, we show that slightly conservative notification heuristics can improve long-run efficiency by avoiding excessive locking of high-value drivers and preserving future availability. |
| title | Non-Exclusive Notifications for Ride-Hailing at Lyft II: Simulations and Marketplace Analysis |
| topic | Computer Science and Game Theory |
| url | https://arxiv.org/abs/2603.21531 |