Gamifying the gig: transitioning the dark side to bright side of online engagement

Abhishek Behl*, Pratima Sheorey, Kokil Jain, Meena Chavan, Isha Jajodia, Zuopeng (Justin) Zhang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)
51 Downloads (Pure)


Gig work has transformed the work culture, globally; its spread and popularity has attracted excellent talent, most of it online. While the gig sector has opened new avenues to showcase talent, lack of consistent engagement of gig workers have resulted in significant dropouts. The study addresses a key research gap by investigating digital platform gig work dropouts through the moderating impact of gamified interventions on online platforms. We have based our arguments and derived hypotheses on the basis of the social exchange theory and the self-determination theory. A total of 367 responses were collected from white-collar gig workers who had 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, thereby reducing their 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.

Original languageEnglish
Pages (from-to)1-34
Number of pages34
JournalAustralasian Journal of Information Systems
Publication statusPublished - 22 Jun 2021

Bibliographical note

Copyright © 2021. authors. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


  • Dark side
  • Engagement
  • Gamification
  • Gig Work
  • Intention to Quit


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