Solvers’ participation in crowdsourcing platforms: Examining the impacts of trust, and benefit and cost factors

• Social exchange theory has been used to guide this study. • We identified contextual unique motivations for crowdsourcing participation. • We identified inhibitors for crowdsourcing participation. • We identified antecedents and consequence of trust in crowdsourcing. Organizations are increasingly crowdsourcing their tasks to unknown individual workers, i.e., solvers. Solvers' participation is critical to the success of crowdsourcing activities. However, challenges exist in attracting solvers to participate in crowdsourcing. In this regard, prior research has mainly investigated the influences of benefit factors on solvers’ intention to participate in crowdsourcing. Thus, there is a lack of understanding of the cost factors that influence actual participation behavior, in conjunction with the benefits. Additionally, the role of trust in the cost-benefit analysis remains to be explored. Motivated thus, based on social exchange theory and context-related literature, we develop a model to explain the impacts of benefit and cost factors as well as trust on solver participation behavior in crowdsourcing. The model was tested using survey and archival data from 156 solvers on a large crowdsourcing platform. As hypothesized, monetary reward, skill enhancement, work autonomy, enjoyment, and trust were found to positively affect solvers’ participation in crowdsourcing, while cognitive effort negatively affects their participation. In addition, it was found that monetary reward positively affects trust (trust partially mediates its effect on participation behavior), while loss of knowledge power negatively affects trust. The theoretical contributions and practical implications of the study are discussed.