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• Models asset specificity as an endogenous driver of General Purpose Technology (GPT) emergence. • Reveals a governance trade-off between static efficiency and dynamic innovation under uncertainty. • Shows that market governance can facilitate GPT emergence despite high asset specificity. • Introduces the “asset specificity dilemma” as a novel theoretical contribution to governance theory. • Reinterprets relational contracts as governance mechanisms supporting dynamic efficiency. Asset specificity critically determines governance structures under incomplete contracting. While transaction cost economics prescribes hierarchical governance to protect specific investments, this view overlooks their potential to drive technological change. This paper models how asset specificity evolves and facilitates the emergence of General Purpose Technologies (GPTs). We show that governance focused on static efficiency can suppress innovation, creating a trade-off between appropriation protection and innovation. Under uncertainty, firms choosing market governance despite high asset specificity enable systemic spillovers and technological generalization. The model integrates transaction cost economics, capabilities theory, and GPT literature, reinterpreting relational contracts as governance mechanisms for dynamic efficiency.
Tsutomu Harada (Fri,) studied this question.