Improving Team Winning Rate through Experiential and Observational Learning in E-Sports Games: A Multilevel Analysis

Despite participating in a growing number of tournaments, but can e-sports players continuously learn and improve? This question is deeply connected with experiential learning theory since players could acquire experience through repetitive participation but with increasingly smaller marginal returns. Observational learning is touted as a complementary learning mechanism by drawing on external sources of knowledge (or others) to accelerate learning progress. This study hence advances a dynamic and integrated research model that scrutinizes the moderating influence of peer- and rival-based observational learning on the relationship between experiential learning and team performance. Analyzing data gathered on 8,410 teams and 29,078 players in e-Sports games, we reveal that peer-based observational learning attenuates the negative effect of experiential learning on players’ incremental absorptive capacity, whereas rival-based observational learning reinforces the negative relationship between experiential learning and players’ incremental absorptive capacity. Players’ incremental absorptive capacity, in turn, enhances team performance.