EAGER: Collaborative Research: Some Assembly Required: Understanding the Emergence of Teams and Ecosystems of Teams

EAGER：协作研究：需要一些组装：了解团队和团队生态系统的出现

• 批准号: 1248269
• 负责人: Jaideep Srivastava
• 金额: $ 12.38万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1248269&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Research; Some; Assembly

This research project will develop a theoretical and computational framework to understand and enable the socio-technical dynamics shaping the assembly of teams in distributed global contexts. The main barrier to understanding and explaining the role of human centered computing in team assembly is finding a suitable research environment where (1) geographically distributed individuals from potentially different cultures are assembling in teams of varying sizes to accomplish a variety of tasks over varying durations; (2) their actions, interactions and transactions are captured with precise time-stamps; and (3) their outcomes would be recorded with well-defined metrics. Massively multiplayer online role-playing games offer a research environment that meets all of these requirements. EVE Online, a massively multiplayer online role-playing game, offers a potentially suitable research opportunity to study the assembly of teams and ecosystems of teams. It is notable for allowing as many as tens of thousands of people to interact simultaneously on a single server cluster, from around the world, through a well-developed economic system and serious long-term coalitions, in a more flexible action framework than many other popular games possess. This high-risk high-payoff project will explore the feasibility of using data from EVE Online to identify the socio-technical and cultural mechanisms that explain the assembly of teams more generally. If successful, the study will serve as a model for larger scale studies that, in addition to identifying the assembly mechanisms also assess the impact of these mechanisms on the performance of global teams. The most important and complex decisions in society are made in teams. And yet, assembling effective teams is a daunting task. While there is an awareness of how team collaborations can spearhead socio-economic change, we still have sparse sociotechnical knowledge of how globally distributed cross-cultural teams and systems of teams are assembled. This project seeks to address this limitation. First, the proposed research offers the promise to launch a new generation of theorizing and research on the assembly mechanisms of teams and ecosystem of teams. The empirical data that will be used to develop and test these theories will be a high risk effort but with potential for unprecedented scale, size, and completeness. Second, the research will arguably be the first effort in the field of social networks to develop hypergraph techniques to study assembly of teams and ecosystems of teams. The knowledge and tools developed in this research will allow practitioners to cultivate more effectively the emergence and performance of ad hoc teams in business, science and gaming. It will also provide other scientific disciplines with new computational statistical modeling methodologies and tools to model hypergraphs.

这一研究项目将制定一个理论和计算框架，以了解和支持在分散的全球背景下塑造团队集合的社会技术动态。理解和解释以人为中心的计算在团队组建中的作用的主要障碍是找到一个合适的研究环境，在这个环境中，(1)来自潜在不同文化的地理分布的个人聚集在不同规模的团队中，以在不同的持续时间内完成各种任务；(2)他们的行动、交互和交易被用准确的时间戳捕获；(3)他们的结果将用定义良好的度量来记录。大型多人在线角色扮演游戏提供了一个满足所有这些要求的研究环境。Eve Online是一款大型多人在线角色扮演游戏，它提供了一个潜在的合适的研究机会来研究团队的集合和团队的生态系统。值得注意的是，它允许来自世界各地的多达数万人在一个服务器集群上同时互动，通过发达的经济系统和严肃的长期联盟，在比许多其他流行游戏更灵活的动作框架中。这个高风险、高回报的项目将探索使用EVE Online的数据来确定更普遍地解释团队集合的社会-技术和文化机制的可行性。如果成功，这项研究将成为更大规模研究的模型，除了确定组装机制外，还评估这些机制对全球团队绩效的影响。社会上最重要和最复杂的决定是在团队中做出的。然而，组建有效的团队是一项艰巨的任务。虽然人们已经意识到团队合作可以如何引领社会经济变革，但我们仍然缺乏关于全球分布的跨文化团队和团队系统是如何组装的社会技术知识。该项目试图解决这一限制。首先，拟议的研究提供了启动新一代关于团队组装机制和团队生态系统的理论和研究的承诺。将用于开发和测试这些理论的经验数据将是一项高风险的工作，但具有前所未有的规模、规模和完整性的潜力。其次，这项研究可以说是社交网络领域开发超图技术来研究团队组装和团队生态系统的第一次努力。这项研究中开发的知识和工具将使从业者能够更有效地培养商业、科学和游戏领域的临时团队的出现和表现。它还将为其他科学学科提供新的计算统计建模方法和工具，以模拟超图。