Open AccessGamifying the gig: transitioning the dark side to bright side of online engagement
Author(s) -
Abhishek Behl,
Pratima Sheorey,
Kokil Jain,
Meena Chavan,
Isha Jajodia,
Zuopeng Zhang
Publication year - 2021
Publication title -
ajis. australasian journal of information systems/ajis. australian journal of information systems/australian journal of information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 18
eISSN - 1326-2238
pISSN - 1039-7841
DOI - 10.3127/ajis.v25i0.2979
Subject(s) - great rift , gig economy , workforce , social media , work engagement , popularity , computer assisted web interviewing , psychology , structural equation modeling , work (physics) , knowledge management , business , engineering , computer science , marketing , social psychology , world wide web , political science , mechanical engineering , physics , astronomy , machine learning , law
Gig work has transformed the work culture, globally. It’s sprawl, and popularity has also attracted excellent talent to join the gig workforce, most of which are online. While it has unfolded new avenues to showcase talent, its management irregularities have resulted in more significant dropouts. The study addresses a key research gap investigating the dropouts of gig workers on digital earning platforms by the moderating impact of gamified interventions on online platforms. We have based our arguments and derived our hypotheses based on social exchange theory and self-determination theory. A total of 367 responses were collected from white-collar gig workers who have completed tasks on one or more gig platforms in the past two years. We test our hypotheses using partial least square structural equation modelling (PLS-SEM). Results confirm that gamifying the online platform would enhance job satisfaction and productivity of gig employees, reducing the chances of quitting gig work. It is further observed that in the case of gig workers, high-performance work systems have a non-significant effect on the intentions to quit. The results contribute to the redesigning of online gig platforms with a layer of gamified artifacts to increase gig workers' retention.