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Interorganizational knowledge heterogeneity can fuel innovation but also create cognitive burdens – tensions that remain insufficiently understood in value chain contexts amid growing adoption of artificial intelligence (AI). We theorize an inverted U-shaped relationship between value chain knowledge heterogeneity – differences in technological knowledge between a focal firm and its key suppliers or customers – and the focal firm’s technological innovation, reflecting the competing forces of knowledge complementarity and cognitive burden. Using a patent-based knowledge-distance measure and panel data on Chinese listed firms from 2010 to 2020, we find evidence for this effect. We further show that a focal firm’s AI capabilities shifts the turning point rightwards in both supplier and customer contexts, thereby extending the range over which heterogeneity is beneficial; while it does not significantly alter the curvature in supplier contexts, it unexpectedly steepens the inverted U in customer contexts. Theoretical and practical implications are discussed.
Huang et al. (2025) studied this question.