Three-Party Evolutionary Game Model of Stakeholders in Mobile Crowdsourcing
Bibliographic Data
| ID | 22108180 |
|---|---|
| Authors | Fuxing Li (0000-0003-1673-2567, Yantai University), Yingjie Wang (0000-0003-0920-9305, Yantai University), Yang Gao (0009-0000-7351-748X, Yantai University), Xiangrong Tong (0000-0003-4855-3723, Yantai University), Nan Jiang (0009-0009-0058-3481, East China Jiaotong University), Zhipeng Cai (0000-0001-6017-975X, Georgia State University) |
| Year | 2022 |
| Volume | 9 |
| Issue | 4 |
| Pages | 974-985 |
| Publication date | 2022-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | IEEE Transactions on Computational Social Systems (JOURNAL) |
| Journal identifiers | ISSN: 2329-924X • E-ISSN: 2373-7476 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/tcss.2021.3135427 |
| OpenAlex | W4206180948 |
| Language | EN |
| Citations received | 10 |
| References cited | 40 |
As a new paradigm to solve problems by gathering the intelligence of crowds, mobile crowdsourcing has become one of the hot spots in academic and industrial fields. Task requester, platform, and crowd workers are stakeholders in mobile crowdsourcing, which inevitably leads to conflicts of interest. In order to solve this problem, this article constructs a three-party evolutionary game model among task requester, platform, and crowd workers. This model also considers the collusion between crowd workers and the platform to make it more realistic. Then, the replication dynamics method is utilized to analyze the evolutionary stability strategy. The strategies of rewards and penalties are given to avoid free-riding and false-reporting problems. Finally, the stability of the equilibrium point in the three-party game system is verified through simulation experiments, and the effective methods to motivate each player to choose a trusted strategy are given
Business · Collusion · Computer security · Crowds · Crowdsourcing · Game theory · Machine learning · World Wide Web · Auction Theory and Applications · Computer Science · Data Stream Mining Techniques · Engineering · Mobile Crowdsensing and Crowdsourcing
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| Unique citing works | 10 |
|---|---|
| Citations per year | 5 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 10 |