Understanding the relationships between motivators and effort in crowdsourcing marketplaces: A nonlinear analysis
Yongqiang Sun,
Nan Wang,
Chunxiao Yin and
Jacky Xi Zhang
International Journal of Information Management, 2015, vol. 35, issue 3, 267-276
Abstract:
Crowdsourcing marketplace as a new platform to source ideas or works from the public has become popular in the contemporary world. However, the predictors of user effort in the crowdsourcing context is rarely investigated. In this study, based on the expectancy theory which suggests the effects of reward valence, trust and self efficacy, we develop a research model to study the factors influencing effort. Further, the non-linear relationship between self efficacy and effort and the moderating role of task complexity is proposed. A field survey with 205 subjects are performed to test the research model. The results show that: (1) reward valence and trust positively influence effort; and (2) when task complexity is high (low), there will be a convex (concave) relationship between self efficacy and effort. Implications for theory and practice are also discussed.
Keywords: Crowdsourcing; Expectancy theory; Trust; Self efficacy; Effort; Nonlinear analysis (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0268401215000109
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:35:y:2015:i:3:p:267-276
DOI: 10.1016/j.ijinfomgt.2015.01.009
Access Statistics for this article
International Journal of Information Management is currently edited by Yogesh K. Dwivedi
More articles in International Journal of Information Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().