Exploring the determinants of university students’ contribution intention on crowdsourcing platforms: a value maximization perspective

Abstract

ABSTRACT Crowdsourcing is an emerging web-enabled method to gain external expertise and ideas on tasks or projects. Mass contributions from the crowd are the key to the success and effectiveness of crowdsourcing. University students are important potential users and promising sources of contributions in the crowdsourcing context. However, little is known about the factors that shape university students’ intention to participate in this new web frontier. Thus, the current study investigates the determinants of university students’ contribution intention on crowdsourcing platforms. Based on the value-based adoption model (VAM) and crowdsourcing characteristics, this study develops a model to understand the determinants of university students’ intention to contribute ideas and solutions on crowdsourcing platforms. Data collected from 135 university students in Taiwan were tested against the research model using the partial least squares (PLS) method. The results indicate that perceived value and perceived behavioral control are key determinants of university students’ contribution intention on crowdsourcing platforms, and that reputation, perceived enjoyment, task autonomy, and trust are significant factors affecting perceived value. This study contributes to extend the knowledge regarding how to better promote crowdsourcing contributions, as well as how to foster and encourage university students to participate in crowdsourcing activities.