Capacity management in ridesharing operations
Guide(s)
Tripathi, Rajeev R
Department
Production and Operations Management
Area
Production and Operations Management
University
Indian Institute of Management Bangalore
Place
Bangalore
Publication Date
3-31-2021
Year Awarded
March 2021
Year Completed
March 2021
Year Registered
June 2014
Abstract
Many ridesharing platforms are struggling to become profitable. The answer to profitability partly depends on how well they manage their capacity. Specifically, how e↵ectively they deal with two major capacity-related challenges - (1) providing reliable service using independent service providers (self-scheduling capacity), and (2) improving utilisation levels of the existing capacity. Motivated by the two challenges, we develop stylised models to provide insights to platforms on e↵ective mechanisms for overcoming them. In chapter 2, we address the challenge of improving capacity utilisation in the context of shared rides. We propose a novel pricing mechanism that incentivises riders to join the largest-size pool instead of smaller ones. Riders joining large-size pools improves vehicle occupancy, which in-turn increases capacity utilisation. The incentive mechanism also ensures no rider benefits at the cost of others. Further, we provide insights on maximum acceptable detouring to passengers in shared rides. To deal with the challenge of providing reliable service, many platforms employ full-time service providers in addition to self-scheduling capacity. These service providers work exclusively for a platform and have limited flexibility, unlike selfscheduling service providers. For such situations, in chapter 3, we provide insights on how to deploy full-time capacity. We examine four operating models corresponding to four di↵erent ways a platform can deploy full-time capacity. Our findings show that asset-light platforms can achieve the same optimal profits using alternate operating models than what is currently being used by them. The presently used operating model risks being perceived discriminatory against self-scheduling service providers. The possibility of implementing alternate operating models can help platforms overcome this risk. While our focus in chapter 3 is on deploying full-time capacity, in chapter 4, we determine the optimal levels of both full-time and self-scheduling capacities.
Pagination
123p.
Copyright
Indian Institute of Management Bangalore
Document Type
Dissertation
DAC Chairperson
Tripathi, Rajeev R
DAC Members
Hazra, Jishnu; Jonnalagedda, Sreelata
Type of Degree
Ph.D.
Recommended Citation
Krishnaprasad, Srikanth, "Capacity management in ridesharing operations" (2021). Doctoral Dissertations. 57.
https://research.iimb.ac.in/doc_dissertations/57
Relation
DIS-IIMB-FPM-P21-08
