Key Drivers of Gig Economy Participation in Malaysia

Abstract

This study investigates the determinants of netizens’ participation in Malaysia’s gig economy, focusing on Foodpanda, Grab, and Airbnb. By employing advanced text analysis on social media comments, we identify key factors influencing attitudes, perceived control, and subjective norms towards gig work. A thematic analysis reveals distinct clusters within these constructs, which are then examined using partial least squares structural equation modelling (PLS-SEM) based on a modified Theory of Planned Behaviour. Our findings demonstrate that attitudes and perceived control significantly predict behavioural intentions to participate in the gig economy, while subjective norms exert no influence. These results underscore the importance of platform-related factors in shaping netizens’ decisions and highlight the potential of social media as a rich source of insights for understanding gig economy dynamics. Policymakers and platform providers can leverage these findings to develop strategies that enhance platform attractiveness, build trust, and foster a conducive environment for gig workers.