Social network indices as performance predictors in a virtual organization

Measuring an individual´s potential to accomplish a goal has key implications in organizational studies, behavioral analysis, business and management among other areas. This relative potential, which is dependent on a myriad of factors, e.g., experience, resource management, cooperation, etc., could shape the individual´s performance, motivation, leadership, and likely success. The increasing prevalence of virtual organizations provides unique challenges and opportunities to study complex research questions via convenient data collection. In this NSF-funded research, we introduce a multi-factor dynamic model to estimate the potential of an individual to accomplish a goal in a virtual organization. We analyze data from a Massive Multi-player Online Role-Playing Game (MMORPG), Travian, collected in a controlled environment for over 3.5 months. The data contains activities of 7,406 players, including, players´ profiles, daily snapshots of individual and alliance attributes, amount of gold, military strength, trades and cooperation, diplomacy status as well as a 2.3 million-message graph. We model players´ potential to survive as a multi-factor function derived from the data attributes, including SNA-based network measures from the message graph. The model predicts a player´s potential to win the game or to achieve a specified goal. The target is to identify the influence of network behavior for the player, and how network statistics for each player influence the accuracy of the prediction.