A Tripartite Evolutionary Game Analysis of Participant Decision-Making Behavior in Mobile Crowdsourcing
With the rapid development of the Internet of Things and the popularity of numerous sensing devices, Mobile crowdsourcing (MCS) has become a paradigm for collecting sensing data and solving problems. However, most early studies focused on schemes of incentive mechanisms, task allocation and data qua...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/5/1269 |
| _version_ | 1827752522652057600 |
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| author | Hanyun Hao Jian Yang Jie Wang |
| author_facet | Hanyun Hao Jian Yang Jie Wang |
| author_sort | Hanyun Hao |
| collection | DOAJ |
| description | With the rapid development of the Internet of Things and the popularity of numerous sensing devices, Mobile crowdsourcing (MCS) has become a paradigm for collecting sensing data and solving problems. However, most early studies focused on schemes of incentive mechanisms, task allocation and data quality control, which did not consider the influence and restriction of different behavioral strategies of stakeholders on the behaviors of other participants, and rarely applied dynamic system theory to analysis of participant behavior in mobile crowdsourcing. In this paper, we first propose a tripartite evolutionary game model of crowdsourcing workers, crowdsourcing platforms and task requesters. Secondly, we focus on the evolutionary stability strategies and evolutionary trends of different participants, as well as the influential factors, such as participants’ irrational personality, conflict of interest, punishment intensity, technical level and awareness of rights protection, to analyze the influence of different behavioral strategies on other participants. Thirdly, we verify the stability of the equilibrium point of the tripartite game system through simulation experiments. Finally, we summarize our work and provide related recommendations for governing agencies and different stakeholders to facilitate the continuous operation of the mobile crowdsourcing market and maximize social welfare. |
| first_indexed | 2024-03-11T07:17:38Z |
| format | Article |
| id | doaj.art-644d7da5d80541c4817885d7328a9517 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T07:17:38Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-644d7da5d80541c4817885d7328a95172023-11-17T08:10:32ZengMDPI AGMathematics2227-73902023-03-01115126910.3390/math11051269A Tripartite Evolutionary Game Analysis of Participant Decision-Making Behavior in Mobile CrowdsourcingHanyun Hao0Jian Yang1Jie Wang2School of Information, Shanxi University of Finance and Economics, Taiyuan 030006, ChinaSchool of Information, Shanxi University of Finance and Economics, Taiyuan 030006, ChinaSchool of Information, Shanxi University of Finance and Economics, Taiyuan 030006, ChinaWith the rapid development of the Internet of Things and the popularity of numerous sensing devices, Mobile crowdsourcing (MCS) has become a paradigm for collecting sensing data and solving problems. However, most early studies focused on schemes of incentive mechanisms, task allocation and data quality control, which did not consider the influence and restriction of different behavioral strategies of stakeholders on the behaviors of other participants, and rarely applied dynamic system theory to analysis of participant behavior in mobile crowdsourcing. In this paper, we first propose a tripartite evolutionary game model of crowdsourcing workers, crowdsourcing platforms and task requesters. Secondly, we focus on the evolutionary stability strategies and evolutionary trends of different participants, as well as the influential factors, such as participants’ irrational personality, conflict of interest, punishment intensity, technical level and awareness of rights protection, to analyze the influence of different behavioral strategies on other participants. Thirdly, we verify the stability of the equilibrium point of the tripartite game system through simulation experiments. Finally, we summarize our work and provide related recommendations for governing agencies and different stakeholders to facilitate the continuous operation of the mobile crowdsourcing market and maximize social welfare.https://www.mdpi.com/2227-7390/11/5/1269mobile crowdsourcingtripartite evolutionary gamestability analysis |
| spellingShingle | Hanyun Hao Jian Yang Jie Wang A Tripartite Evolutionary Game Analysis of Participant Decision-Making Behavior in Mobile Crowdsourcing Mathematics mobile crowdsourcing tripartite evolutionary game stability analysis |
| title | A Tripartite Evolutionary Game Analysis of Participant Decision-Making Behavior in Mobile Crowdsourcing |
| title_full | A Tripartite Evolutionary Game Analysis of Participant Decision-Making Behavior in Mobile Crowdsourcing |
| title_fullStr | A Tripartite Evolutionary Game Analysis of Participant Decision-Making Behavior in Mobile Crowdsourcing |
| title_full_unstemmed | A Tripartite Evolutionary Game Analysis of Participant Decision-Making Behavior in Mobile Crowdsourcing |
| title_short | A Tripartite Evolutionary Game Analysis of Participant Decision-Making Behavior in Mobile Crowdsourcing |
| title_sort | tripartite evolutionary game analysis of participant decision making behavior in mobile crowdsourcing |
| topic | mobile crowdsourcing tripartite evolutionary game stability analysis |
| url | https://www.mdpi.com/2227-7390/11/5/1269 |
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