工业5.0背景下人机交互对项目韧性的作用机制研究——基于知识与能力视角

Research on the Mechanism Influences of Human-Robot Interaction on Project Resilience from the Knowledge and Capability Perspective in the Context of Industry 5.0

摘要:

在工业 5. 0 背景下,人工智能技术的嵌入对项目建造与运营的决策过程、资源配置方式、人机团队行为习惯和治理机制等产生重要影响,而项目场景中人机交互与项目韧性的作用机制鲜有研究。 基于资源编排理论、知识基础观和动态能力理论,以资源编排作为中介变量,以知识势差与人机信任为调节变量,从知识与能力视角构建了一个有调节的中介作用模型探究人机交互对项目韧性的影响机制。 369 份项目样本数据分析结果表明:人机交互对项目韧性具有显著正向影响,人机信任在上述关系中发挥调节作用;资源编排在人机交互和项目韧性之间具有中介作用,而知识势差正向调节资源编排在人机交互与项目韧性之间的中介效应。 研究结论有助于理解项目人机团队面对不确定环境时的行为交互和韧性反应,也为项目人机团队协同决策与项目韧性治理提供参考。 同时,丰富了项目场景中人机交互与韧性的研究体系,为工业 5. 0 背景下人工技术赋能项目韧性增强提供微观证据,为项目治理主体提供了实际的借鉴意义。

Abstract:

In the context of industry 5. 0, the integration of artificial intelligence technology has an impact on the decision-making processes, resource allocation methods, behavioral habits of human-robot teams, and governance mechanisms during the construction and operation of projects. However, existing research has overlooked the mechanism of human-robot Interaction and project resilience in the project scenario. Based on the resource orchestration theory, knowledge and dynamic capability theory, a moderated mediation model was constructed to explore the influence mechanism of human-machine interaction on project resilience in the context of industry 5. 0, which resource orchestration was set to the mediating variable, and knowledge potential difference and human-machine trust was set to the moderating variables. Data from 369 project samples were analyzed. The results indicate that human-machine interaction has a significant positive impact on project resilience, which human-machine trust plays a moderating role in this relationship. Resource orchestration serves as a mediator between human-machine interaction and project resilience, while knowledge potential difference positively moderates the mediating effect of resource orchestration in the relationship between human-machine interaction and project resilience. These findings contribute to understanding project teams’ behavioral interactions and resilience responses in uncertain environments, while also providing insights for collaborative decision-making and resilience governance in human-machine project teams. These results enrich the research system of human-machine interaction and resilience in project contexts, providing micro-level evidence for enhancing project resilience through human-in-the-loop technologies under the industrial 5. 0, while offering practical insights for project governance decision-makers.