Understanding Solvers' Continuance Intention in Crowdsourcing Contest Platform: An Extension of Expectation-Confirmation Model

The great potential of crowdsourcing contest is bringing the issue of how to sustain solvers’ participation intention to be a hot topic in research and practice. This study uses the framework of Expectation-confirmation model to explain solvers’ continuance intention. Due to the uncertainties inherent in crowdsourcing contest, trust, a salient psychological belief, should be taken into account with the Expectation-confirmation model framework to predict solvers’ continuance intention. In addition, the intensive demand of intelligence and competition indicate interaction and fairness as two crucial factors for solvers to achieve expectation, thus suggesting that they may have influence on the confirmation level. Corresponding to these challenges, this study integrates platform trust, interaction, and perceived fairness into an extended Expectation-confirmation model to examine solvers’ continuance intention. Using a sample of 306 solvers, empirical results show that satisfaction, perceived benefits, and platform trust, which are positively associated with confirmation, are three significant antecedents of solvers’ continuance intention. Confirmation is further found to be significantly determined by interaction and perceived fairness. These findings provide some implications in both theory and practice for understanding the process of triggering sustained intention with an Expectation-confirmation model framework in crowdsourcing contest.