Journal article
The Dual Effects of Team Contest Design on On-Demand Service Work Schedules
Service science (Hanover, Md.), Vol.16(1), pp.22-41
03/01/2024
DOI: 10.1287/serv.2023.0320
Abstract
Emerging on-demand service platforms (OSPs) have recently embraced teamwork as a strategy for stimulating workers' productivity and mediating temporal supply and demand imbalances. This research investigates the team contest scheme design problem considering work schedules. Introducing teams on OSPs creates a hierarchical single leader multi-follower game. The leader (platform) establishes rewards and intrateam revenue-sharing rules for distributing workers' payoffs. Each follower (team) competes with others by coordinating the schedules of its team members to maximize the total expected utility. The concurrence of interteam competition and intrateam coordination causes dual effects, which are captured by an equilibrium analysis of the followers' game. To align the platform's interest with workers' heterogeneous working-time preferences, we propose a profit-maximizing contest scheme consisting of a winner's reward and time varying payments. A novel algorithm that combines Bayesian optimization, duality, and a penalty method solves the optimal scheme in the nonconvex equilibrium-constrained problem. Our results indicate that teamwork is a useful strategy with limitations. Under the proposed scheme, team contest always benefits workers. Intrateam coordination helps teams strategically mitigate the negative externalities caused by overcompetition among workers. For the platform, the optimal scheme can direct teams' schedules toward more profitable market equilibria when workers have inaccurate perceptions of the market.
Details
- Title: Subtitle
- The Dual Effects of Team Contest Design on On-Demand Service Work Schedules
- Creators
- Tingting Dong - Hong Kong University of Science and TechnologyXiaotong Sun - Hong Kong University of Science and TechnologyQi Luo - Clemson UniversityJian Wang - Heilongjiang Institute of TechnologyYafeng Yin - University of Michigan–Ann Arbor
- Resource Type
- Journal article
- Publication Details
- Service science (Hanover, Md.), Vol.16(1), pp.22-41
- Publisher
- Informs
- DOI
- 10.1287/serv.2023.0320
- ISSN
- 2164-3962
- eISSN
- 2164-3970
- Number of pages
- 21
- Grant note
- FW-HTF-P 2222806 / National Science Foundation; National Science Foundation (NSF)
- Language
- English
- Date published
- 03/01/2024
- Academic Unit
- Business Analytics
- Record Identifier
- 9984696568102771
Metrics
2 Record Views