EAGER: Social Dynamics of Organizational Behavior in Temporary Virtual Teams

本研究利用在线电子竞技（e-sports）记录的大规模，详细，国际化和不引人注目的数据来了解临时虚拟团队的组织行为。 团队合作和协作是现代组织取得成功的关键，随着团队变得越来越分散，虚拟，自我组装，跨职能和临时性，需要修改现有的支持有效团队合作的框架。多人在线电子竞技是开发新的和更有效的技术中介团队合作框架的模型：明确和一致的性能指标，用于定量分析的详细和公开的行为数据，大型和国际用户群，以及广泛的随机化，重复观察和匹配，以进行强有力的因果推理。从高节奏、自然主义决策的详细行为记录中得出的推论可以扩展到许多其他环境，如灾难响应或突发新闻。这项研究的结果可以为识别嘈杂的社会系统中未充分利用的专业知识，优化团队组装算法以提高性能，改善临时虚拟团队的决策以及使用在线电子竞技作为现有团队的诊断工具提供经验基础。该项目的研究结果还将为电子竞技的设计和管理提供信息，电子竞技已经吸引了全球数千万用户。该项目追求两个倡议，以了解如何提高临时虚拟团队的性能。第一个倡议研究如何在高节奏的情况下，团队大会决策影响团队绩效。第二项计划研究软件和数据库补丁如何破坏心智模型和决策。这项研究将在（1）现有的组织理论和团队流程结构之间进行三角分析，（2）数据挖掘，机器学习和计量经济学的定量方法，用于分析有关用户行为的非侵入性观察数据，以及（3）几种流行的电子竞技的独特启示，以检查在自然环境中影响团队绩效的变量和机制。 本研究项目的结果将（1）提供比较经验的见解到一个快速增长的文化和经济现象;（2）开发框架和模型，以增加在社会技术系统的参与;和（3）为提高临时虚拟团队的性能提供可推广的建议。该项目将创建免费的软件库、数据库、支持教程和文档，使其他研究人员能够使用电子竞技数据开发和评估组织理论。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This research leverages the large-scale, detailed, international, and unobtrusive data logged by online electronic sports (e-sports) to understand the organizational behavior of temporary virtual teams. Teamwork and collaboration are essential for success in contemporary organizations, and as teams become increasingly distributed, virtual, self-assembled, cross-functional, and temporary, existing frameworks for supporting effective teamwork need to be revised. Multiplayer online e-sports are models for developing new and more effective frameworks for technologically-mediated teamwork: clear and consistent performance metrics, detailed and public behavioral data for quantitative analysis, a large and international user base, and extensive randomization, repeated observations, and matching for making strong causal inferences. The inferences made from detailed behavioral records of high-tempo, naturalistic decision making can be extended to many other settings such as disaster response or breaking news. The findings from this research could provide the empirical basis for identifying under-utilized expertise in noisy social systems, optimizing team assembly algorithms to improve performance, improving decision making in temporary virtual teams, and using online e-sports as diagnostic tools for existing teams. The findings from this project will also inform the design and governance of e-sports that already attract tens of millions of users around the world. The project pursues two initiatives to understand how to improve the performance of temporary virtual teams. The first initiative examines how team assembly decision-making in high-tempo contexts influences team performance. The second initiative examines how software and database patches disrupt mental models and decision-making. This research will triangulate between (1) existing organizational theories and constructs about team processes, (2) quantitative methods from data mining, machine learning, and econometrics for analyzing unobtrusive observational data about user behavior, and (3) the unique affordances of several popular e-sports to examine the variables and mechanisms that influence team performance in a naturalistic setting. The results of this research project will (1) provide comparative empirical insights into a rapidly growing cultural and economic phenomenon; (2) develop frameworks and models to increase engagement in sociotechnical systems; and (3) provide generalizable recommendations for improving the performance of temporary virtual teams. This project will create free software libraries, data collections, and supporting tutorials and documentation enabling other researchers to develop and evaluate organizational theories using data drawn from e-sports.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.