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University of Pennsylvania

Managing Self-Scheduling Capacity

Abstract

dc:description.abstract

Gig-economy platform like Uber, Lyft, Postmates, and Instacart have created markets in which independent service providers provide on-demand service to consumers. A hallmark of this arrangement is that providers decide for themselves when, where, and how much to work. In other words, the platform does not set its capacity's schedule; instead its capacity "self-schedules." This decentralization of decision making can create value for providers. The platform's challenge is then to devise a contract with its capacity that allows it to capture some of this value. I study the platform's contracting problem in three chapters. In the first, I show that the platform can benefit from allowing its providers to self-schedule. In the second, I study the platform's strategy when coordinating supply and demand across multiple states of the world. I show that the resulting dynamic pricing policy can be beneficial to consumers, despite widespread dislike of the real-world practice. I also show that, in many cases, the platform need not independently vary payments to providers to achieve near-optimal profit. Instead the platform may pay its providers a fixed percent commission on the price paid by consumers per completed service. In the final chapter, I argue that the findings above are distinct from the traditional two-sided markets literature. Though a classic two-sided market model experiences near-optimal performance of the fixed commission in many cases, the market conditions that produce poor fixed commission performance differ between the gig-economy model and the two-sided markets model. Because the two-sided market model does not accurately predict poor gig-economy fixed commission performance, it is important to study a model tailored the gig-economy to understand gig-economy specific applications.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Daniels, Kaitlin Marie
Advisor dc:contributor.advisor
  • Gerard P. Cachon

Rights

dc:rights
Statement dc:rights
  • Kaitlin Marie Daniels
Language dc:language
en

Identifiers

dc:identifier.*
Repository record dc:identifier.uri
https://repository.upenn.edu/handle/20.500.14332/30048
OAI identifier oai:identifier
oai:repository.upenn.edu:20.500.14332/30048

Chain of custody

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University of Pennsylvania
Base URL
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Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Daniels, Kaitlin Marie. Managing Self-Scheduling Capacity. 2017. https://repository.upenn.edu/handle/20.500.14332/30048