How AI Enables Platform Enterprises to Build Competitive Advantages: A Configurational Analysis from the Perspective of Situated AI Theory

While existing research analyzes AI’s impact on platform enterprises’ competitive advantages from technological or organizational perspectives, it fails to adequately account for how multiple factors combined shape competitive advantages. From the perspective of situated AI theory, this study examines how the combinations among AI application characteristics, situated AI activities, platform enterprise attributes, and environmental characteristics collaboratively build platform enterprises’ competitive advantages. Drawing on panel data from Chinese listed platform enterprises and employing fuzzy-set Qualitative Comparative Analysis (fsQCA), this study reveals that (1) AI technology innovation and recasting AI are necessary conditions for platform enterprises to establish competitive advantages; (2) AI-enabled competitive advantages emerge from three types of configurations, the situated AI dominance type, the situated AI subsidiary type, or the collaborative drive type; (3) the AI-enabled combinations result in competitive advantages by three paths, AI internalization, AI leverage, and AI collaboration; and (4) the AI-enabled competitive advantages are more likely to be achieved by innovation platforms than by transaction platforms. These research findings fill the knowledge gap in AI-enabled competitive strategy, enrich the literature on situated AI theory, and offer practical guidance for platform enterprises’ AI applications.