Generative AI on innovation performance of construction enterprises: the role of knowledge-based dynamic capabilities and enterprise AI capabilities

Purpose The aim of this study was to investigate the associations among generative artificial intelligence (AI), knowledge-based dynamic capabilities, enterprise AI capabilities (EAIC) and innovation performance of the construction enterprises. Design/methodology/approach The structural equation model was used in this study. First, the hypothesis of the relationship between generative AI, knowledge-based dynamic capabilities, EAIC and innovation performance was proposed based on the previous relevant literature; then, the research data were collected by 310 questionnaires; finally, these hypotheses were tested through data analysis. Findings Generative AI positively influenced knowledge-based dynamic capabilities and innovation performance of the construction enterprises; knowledge-based dynamic capabilities had a mediating effect on the influence of generative AI on innovation performance of the construction enterprises; EAIC had a positive moderating effect on the influence of generative AI on innovation performance of the construction enterprises. Originality/value In this study, knowledge-based dynamic capability and EAIC are introduced into the relationship model between generative AI and innovation performance of the construction enterprises, and an integrated model is proposed about the relationship between these factors. This study enriches the research content of AI application, dynamic capability and innovation management. The research results are conducive to generative AI in the innovation process and the formulation of innovation strategies.