Helping and Being Helped: Exploring the Motivations and Barriers to Upstream Reciprocity in Open-World Games

Abstract

In a game world, if you are having trouble, you may ask experienced players for help; after leveling up, you may help novice players avoid difficulties in turn. This phenomenon is called in-game “upstream reciprocity (UR)”. In this article, we studied the motivations for novice players seeking help and experienced players helping others through focus groups and tested the theoretical models of potential recipients (N = 232) and donors (N = 258), respectively. Our analyses showed that for both potential recipients and donors, higher degrees of extraversion and perceived value (utilitarian and hedonic values) increased in-game UR intention. Loneliness showed the opposite outcome in models that recipients with high loneliness degrees and donors with low loneliness degrees increased in-game UR intention. Besides, self-determination theory (autonomy, competence, and relatedness) was positively associated with UR intention in the donor model. Furthermore, we tested the discouraging factor hindering players from UR. Combining all the results, we suggested the keys for designers are to improve the function and gameplay of the multiplayer mode, encourage the sharing of in-game capital, and lower the rewards of social cooperation to increase autonomy.

Acknowledgements

The authors would like to gratefully acknowledge the reviewers’ comments. This work was supported jointly by the National Natural Science Foundation of China (Nos. 72271053, 71871056).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported jointly by the National Natural Science Foundation of China (Nos. 72271053, 71871056).

Notes on contributors

Yuhan Chen

Yuhan Chen is currently a PhD student in the Department of Industrial Design at Southeast University. Her scientific interests include online collaboration design, cognitive ergonomics, and human–computer interaction.

Chengqi Xue

Chengqi Xue is a full professor at Southeast University. His main research interests are neuro-design, industrial product modeling design, computer-aided industrial design, and human–computer interface design.