Does bonus motivate streamers to perform better? An analysis of compensation mechanisms for live streaming platforms

The authors consider a live streaming platform connecting streamers and users. Streamers perform for users in a virtual chat room on the platform. Users watch streamers’ performances and purchase virtual gifts for their favorite streamers. There are two types of streamers: non-contracted ones who stream independently and contracted ones who sign with and work for the platform. Based on observed industrial practice, the platform provides non-contracted streamers with a straight commission plan and contracted streamers with one of three alternative compensation plans, namely, the basic compensation plan (B-plan), salary-based incentive plan (SI-plan), and commission-based incentive plan (CI-plan). The platform first decides its compensation plans for two types of streamers, then the streamers decide their type and effort level. They explore and compare the streamers’ optimal decisions under different compensation plans. They interestingly find that the SI/CI bonus does not always motivate streamers to perform better. The SI bonus is only effective for the streamers whose ability is neither low nor high while the CI bonus can effectively motivate the majority of streamers except those having extremely low ability or some low-intermediate-ability streamers. In addition, the platform can screen out low-ability streamers and attract high-ability streamers to sign with it by properly designing its compensation plans. Finally, the authors examine managerial insights for the platform. They show that both SI-plan and CI-plan result in higher expected profits for the platform than the B-plan.

• Record URL:
  https://doi.org/10.1016/j.tre.2022.102758
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1366554522001491
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
• Supplemental Notes:
  • © 2022 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Yang, Xiaolin
  • Gou, Qinglong
  • Wang, Xin
  • Zhang, Juzhi
• Publication Date: 2022-8

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: 102758
• Serial:
  • Transportation Research Part E: Logistics and Transportation Review
  • Volume: 164
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1366-5545
  • Serial URL: http://www.sciencedirect.com/science/journal/13665545

Subject/Index Terms

• TRT Terms: Abilities; Data streaming; Employee compensation; Internet; Payment
• Identifier Terms: Mental effort
• Subject Areas: Data and Information Technology; Finance; Transportation (General);

Filing Info

• Accession Number: 01855707
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 24 2022 3:02PM