【作者】 王世明； 史泰龙；

【Author】 Wang Shiming;Shi Tailong;School of Business Administration, Liaoning Technical University;

【机构】 辽宁工程技术大学工商管理学院；

【摘要】 在人工智能战略驱动工程管理变革的背景下,AI技术对项目管理绩效的作用机制亟待厘清。本文基于社会认知理论和社会交换理论,探讨AI技术对项目管理绩效的路径效应,以342名建筑企业项目管理成员为调研对象,采用SEM与fsQCA混合方法,揭示其影响路径及边界条件。研究发现:(1)AI技术对项目管理绩效有显著正向影响,且通过显性知识共享与隐性知识共享发挥中介作用;(2)感知风险负向调节AI技术与知识共享(隐性)的关系;(3)fsQCA识别出三条高绩效路径,"AI技术+双维度知识共享+低感知风险"为最优组态。研究补充了工程管理领域技术赋能的知识传导机制与风险边界,为建筑企业利用AI技术提升项目管理绩效提供实践指引。更多还原

【Abstract】 Against the backdrop of engineering management transformation driven by artificial intelligence(AI) strategies, the mechanism through which AI technologies exert effects on project management performance urgently needs to be clarified. Based on social cognitive theory and social exchange theory, the path effects of AI technologies on project management performance are explored. A survey is conducted among 342 project management members from construction enterprises, and a mixed-method approach combining structural equation modeling(SEM) and fuzzy-set qualitative comparative analysis(fsQCA) is adopted to reveal the influencing paths and boundary conditions. The following findings are obtained. AI technologies are found to exert a significant positive impact on project management performance, and this impact is mediated by explicit knowledge sharing and tacit knowledge sharing. Perceived risk negatively moderates the relationship between AI technologies and tacit knowledge sharing. Three high-performance paths are identified via fsQCA, among which the configuration of "AI technologies plus dual-dimensional knowledge sharing + low perceived risk" is regarded as the optimal one. This research supplements the knowledge transmission mechanism and risk boundaries of technology empowerment in the field of engineering management, and provides practical guidelines for construction enterprises to improve project management performance by leveraging AI technologies.更多还原