EXPLORING THE FORMATION MECHANISM OF TECHNOLOGY STANDARD COMPETITIVENESS IN ARTIFICIAL INTELLIGENCE INDUSTRY: A FUZZY-SET QUALITATIVE COMPARATIVE ANALYSIS

Abstract

This study aims to reveal the complex mechanism influencing technology standard competitiveness (TSC) in the artificial intelligence industry. Compared with research using traditional linear models, this research adopts the fuzzy-set qualitative comparative analysis (fsQCA) method to obtain the multiple equivalent paths for different factors that jointly produce TSC. The sample of this study involves 32 countries, and the research framework is constructed from the technological, organizational, and environmental aspects of the phenomenon. The fsQCA method was used to demonstrate the asymmetric relationship between cause and effect. The results indicate four configuration paths but no necessary conditions leading to TSC. Academic research intensity and market size play vital roles in developing TSC. Some logically complementary relationships exist between organizational participation, technological innovation ability, and international competitive pressure. These findings are helpful for policymakers in their formulation of artificial intelligence– related strategies.