Collaborative Research: Mapping the High Performance Design Team "Genome"

协作研究：绘制高性能设计团队“基因组”图谱

• 批准号: 1635386
• 负责人: Larry Leifer
• 金额: $ 15万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1635386&HistoricalAwards=false
• 关键词: Collaborative; Research; Mapping; Performance; Design

Engineering design is a social-technical activity commonly practiced in teams. Understanding how engineers interact and work in teams is central to the understanding of technical innovation, and consequently, to industry efforts to improve the quality of technical innovation in the U.S. In this research, engineering design teams from industry will be directly observed in order to develop a new integrated model of High Performance Design Teams (HPDTs). The behavioral interactions and individual cognitive characteristics of the team members will be assessed, along with the products of the team sessions. The individual characteristics of the team members and their behavioral interactions will be mapped in relation to their performance in terms of innovative design to identify the behavioral building blocks of design teams that produce high performance outcomes. Identification of these behavioral building blocks will have a broad impact on current design practice and future research by providing the basis for developing scientific models of and new tools for improving engineering design teams in complex industry environments. Positive impact on engineering education will occur through transferring to students an explicit understanding of what accounts for high performance design and how one behaves in order to achieve it. This project will develop a new model of the building blocks that characterize High Performance Design Teams (HPDTs) based on their behavioral interactions and individual characteristics. Engineering design teams from industry, that will be recruited on a performance gradient from high to low performance, will be observed. Team behaviors will be analyzed using the Interaction Dynamics Notation (IDN), while individual characteristics will be assessed through the Kirton Adaption-Innovation inventory (KAI) and the Engineering ABAKAS (Assessment of Behaviors, Attributes, Knowledge, Attitudes, and Skills). These data will be synthesized with performance data from each team to create a descriptive model of the essential building blocks of High Performance Design Teams (HPDTs). This project will be the first to combine in application the IDN to model team behavioral interactions, the KAI to measure individual cognitive style, and the Engineering ABAKAS to assess engineering innovativeness. The new descriptive model of HPDTs resulting from this novel combination of approaches will have the potential to transform the way engineering design teams in industry are selected, trained, and managed in the search for high quality innovative products and services. The research methods applied will enable engineering and design researchers and practitioners to understand how highly effective teams operate at a granular level based on who they are, how they behave, and what they produce.

工程设计是一种社会技术活动，通常在团队中进行。了解工程师如何互动和团队工作是核心的技术创新的理解，因此，行业努力提高技术创新的质量在美国在这项研究中，工程设计团队从行业将直接观察，以开发一个新的综合模型的高性能设计团队（HPDT）。团队成员的行为互动和个人认知特征将被评估，沿着团队会议的产品。团队成员的个人特征和他们的行为互动将映射到他们的创新设计方面的表现，以确定产生高性能成果的设计团队的行为构建模块。这些行为的构建块的识别将有广泛的影响，目前的设计实践和未来的研究提供了基础，开发科学的模型和新的工具，以改善工程设计团队在复杂的行业环境。通过向学生传递高性能设计的原因以及如何实现高性能设计的明确理解，将对工程教育产生积极影响。本项目将开发一种新的构建模块模型，该模型基于高性能设计团队（HPDT）的行为互动和个人特征。将观察来自工业界的工程设计团队，他们将按照从高到低的绩效梯度招聘。团队行为将使用互动动力学符号（IDN）进行分析，而个人特征将通过柯顿适应创新清单（KAI）和工程ABAKAS（行为，属性，知识，态度和技能的评估）进行评估。这些数据将与每个团队的绩效数据进行综合，以创建高绩效设计团队（HPDT）基本构建块的描述性模型。这个项目将是第一个联合收割机在应用中结合IDN来模拟团队行为互动，KAI来衡量个人的认知风格，和工程ABAKAS来评估工程创新。HPDT的新的描述性模型，从这种新颖的组合方法将有可能改变的方式，在工业工程设计团队的选择，培训和管理，在寻找高质量的创新产品和服务。所应用的研究方法将使工程和设计研究人员和从业人员能够根据他们是谁，他们的行为方式以及他们的产品来了解高效团队如何在粒度级别上运作。