EAPSI: Team Assembly and Performance in a Large Sample of Chinese Online Gamers

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Traditional teams are well-established, clearly delineated groups of two or more people working together to achieve a common goal. However, due to the advent of the Internet, individuals are now able to assemble into teams with increasing flexibility and fluidity. For instance, geographically dispersed individuals from a diverse array of backgrounds can temporarily join forces to complete a unique project, and then subsequently disband. This study will use a very large sample of Chinese online gaming teams in attempts to resolve the yet unanswered questions of how people go about choosing teammates when engaging in this type of ephemeral teamwork and whether some methods of teammate selection result in better performance than others. This research will be conducted at Fudan University in Shanghai, China under the guidance of Dr. Yunjie Xu. Dr. Xu is a foremost expert in quantitative methodology, and has unprecedented access to some of China's largest and most popular online gaming communities.This project will utilize a dataset that is largely comprised of digital trace data, which is a type of big data that stems from the automatic recording of information based on user activity within the context of a virtual system. One primary benefit of using digital trace data is the unobtrusive nature of its acquisition; the current data were all collected within the context of a virtual online game, allowing for inconspicuous tracking of teaming patterns. Furthermore, the proposed hypotheses will be tested using a specific network analytic method known as exponential random graph modeling (ERGM). In this method, an observed network of relationships (i.e., team assembly ties) is modeled by estimating parameters based on individual differences, relational configurations present in the observed network, and even other relational independent variables. This NSF EAPSI award is funded in collaboration with the Chinese Ministry of Science and Technology.