科学基金团队合作流程模式对项目绩效的影响研究

The success of complex projects often depends on the ability to collaborate and solve problems. Scientific collaboration enables science teams to solve complex problems that individual researchers or disciplines cannot address, there‐by demonstrating stronger potential for technological innovation. Previous studies have identified collaboration patterns from a static structural or network perspective without emphasizing how to dynamically coordinate to improve team performance. In this study, dynamic evolutionary modeling of the scientific collaboration process was conducted to intuitively analyze a team's dependency relationships and coordination mechanisms as well as the different improvement effects of the scientific collaboration process on project performance. A scientific collaboration process pattern mining approach based on graph and sequence mining was developed, and the optimal team collaboration process pattern was identified. The conclusions follow: 1) most scientific collaboration process patterns have a positive impact on project performance; 2) the most efficient collaboration process pattern begins with knowledge expansion and ends with knowledge enhancement; and 3) conversely, when a team adopts knowledge expansion as its overall development strategy or as a priority during project execution and relies on internal knowledge enhancement in the middle and later stages of development, it is not conducive to enhancing project performance. These findings have significant practical value and provide guidance for project applicants, leading to scientific cooperation. They can provide targeted suggestions and new implementation ideas for optimizing team formation, improving collaborative environments, promoting collaborative behaviors, and evaluating project performance.