Understanding the relationships between motivators and effort in crowdsourcing marketplaces : A nonlinear analysis

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)267-276
Journal / PublicationInternational Journal of Information Management
Volume35
Issue number3
Publication statusPublished - Jun 2015
Externally publishedYes

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.

Research Area(s)

  • Crowdsourcing, Effort, Expectancy theory, Nonlinear analysis, Self efficacy, Trust

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