Integrating UTAUT and social exchange theory to decipher knowledge-sharing in crowdsourcing

Microtask crowdsourcing platforms enable rapid, large-scale completion of simple tasks by a globally distributed workforce. This study investigates the factors influencing knowledge-sharing behaviours among crowdworkers, integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) with Social Exchange Theory (SET) to provide a comprehensive understanding of these dynamics. Using Structural Equation Modelling (SEM) to analyse survey data from 413 crowdworkers, the study identifies key drivers such as Performance Expectancy (PE), Effort Expectancy (EE), and Rewards, which significantly impact both Knowledge-sharing Intention (KSI) and Behaviour (KSB). Our findings highlight the importance of user-friendly and accessible digital tools in promoting active knowledge-sharing within online communities. Effort Expectancy directly influences Knowledge-sharing Behaviour, highlighting the importance of usability in sustaining platform adoption. This research confirms the robustness of the UTAUT model and extends it with social exchange elements to offer new insights into human aspects of information systems.