Examining the Effects of Feedback-giving as a Gamification Mechanic in Crowd Rating Systems

ABSTRACT

Crowd rating derives a collective value based on massive homogeneous contributions from individual users, where using gamification design is a promising approach to encouraging users’ motivation and participation. Drawing upon self-determination theory and motivational affordances theory, this study investigates how different gamification objects, as building blocks for feedback-giving mechanics, affect users’ extrinsic and intrinsic motivation (i.e., compensation and enjoyment), which in turn affect their participation intention. We also examined the role of task complexity in moderating the gamified effects of feedback-giving mechanics. We conducted a four (gamification objects: leaderboards, progress, virtual characters, and plain) by two (task complexity: low and high) between-subject experiment with 402 subjects. The results suggested that feedback-giving as a critical gamification mechanic can motivate participants intrinsically or extrinsically. Specifically, leaderboards and progress positively influenced compensation, and leaderboards and virtual characters positively influenced enjoyment. Task complexity moderated the gamified effects of feedback-giving mechanics on compensation and enjoyment. With a higher task complexity, leaderboards even result in a higher level of enjoyment. This research contributes to the theoretical understanding of feedback-giving mechanics in crowd rating systems, and practically, suggests that the design of feedback-giving and task complexity should be effectively integrated to reach compensational and enjoyable motivation to encourage user engagement in crowd rating activities.

Disclosure of potential conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [71904215, 71774083, 72072194], the Ministry of Education, Humanities and Social Sciences Council in China [18YJCZH160], and the Social Science Fund Research Base Project of Beijing [19JDGLB029].

Notes on contributors

Jian Tang

Jian Tang is an Associate Professor at Central University of Finance and Economics, China. She received her PhD degree at Syracuse University. Her research areas include human-computer interaction, crowdsourcing, and social commerce. She is interested in topics about user experience, motivation, IT use and behaviors in various contexts.

Yuxiang (Chris) Zhao

Yuxiang (Chris) Zhao is a professor at Nanjing University of Science and Technology in China. His research areas include human-computer interaction, health informatics, crowdsourcing and crowdfunding, and digital humanities. Currently, Dr. Zhao is serving as the special issue guest editor of JASIST, IP&M, and Aslib Journal of Information Management.

Tianmei Wang

Tianmei Wang is a professor at the School of Information, Central University of Finance and Economics, China. She was a visiting scholar at the School of Management, Georgia Institute of Technology. She is a council member of China Information Economy Association. Her research interests include e-commerce, Internet economy, and e-government.

Zhiyuan Zeng

Zhiyuan Zeng was a student in the School of information at Central University of Finance and Economics. He received his master’s degree in Economics in 2017 and his bachelor’s degree in Management in 2015. He now works as a venture capital investor in Cicada Technology (Xi’an) Co, Ltd.