Solvers' participation in crowdsourcing initiatives for social innovation: Exploring interactions among motivational forces

We know that solvers self-selecting in social innovation challenges come from diverse backgrounds including, among others, scientists, engineers, entrepreneurs, researchers, and professionals from various industries. However, we are not aware of what motives actually bring such solvers to self-select to address these challenges. This study aims at understanding how different kinds of motivations intervene and interact with the solvers' intention to participate considering the specific context of crowdsourcing for social innovation. Drawing on the self-determination theory, we built a theoretical framework that hypothesizes how intrinsic, extrinsic, and prosocial motivations interact with one another and affect solvers' self-selection process in social innovation initiatives. Empirically, to investigate the theoretical framework, a survey research design involving the use of questionnaires was adopted to obtain primary data from solvers engaged in crowdsourcing initiatives for social innovation to solve Covid-19-related problems in the HeroX platform. We found that prosocial motivations positively affect the solvers' self-selection process. Moreover, our results highlight that intrinsic and extrinsic motivations differently moderate the relationship between prosocial motivations and intention to participate. The results of this study offer relevant contributions to previous crowdsourcing and organizational psychology literature and provide critical implications for managers designing and organizing crowdsourcing for social innovation challenges.