Title: User participation behaviour in crowdsourcing initiatives: influencing factors, related theories and incentive strategies

Authors: Xu Zhang; Zhanglin Peng; Qiang Zhang; Xiaonong Lu; Hao Song

Addresses: School of Management, Hefei University of Technology, Hefei 230009, China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China ' School of Management, Hefei University of Technology, Hefei 230009, China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China ' School of Management, Hefei University of Technology, Hefei 230009, China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China ' School of Management, Hefei University of Technology, Hefei 230009, China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China ' School of Management, Hefei University of Technology, Hefei 230009, China; Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei 230009, China

Abstract: Crowdsourcing is a powerful paradigm that leverages collective intelligence to solve problems. Good performance in crowdsourcing initiatives depends on energetic user participation. This paper reviews and analyses the current existing research works that are related to user behaviour in crowdsourcing initiatives. Particular attention is paid to the following aspects. First, we summarise the influencing factors of user participation behaviour in crowdsourcing initiatives. Second, we review the related behaviour theories to further understand the relationship between these factors and user behaviour. Third, we generalise about incentive strategies from the perspective of requesters and crowdsourcing platforms. Finally, the research directions of user behaviour in crowdsourcing initiatives are discussed in this study.

Keywords: crowdsourcing; user participation; user behaviour; motivation; incentive strategies.

DOI: 10.1504/IJAHUC.2021.119084

International Journal of Ad Hoc and Ubiquitous Computing, 2021 Vol.38 No.1/2/3, pp.30 - 44

Received: 10 Aug 2020
Accepted: 09 Dec 2020
Published online: 22 Nov 2021 *

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