Data-Driven Disintermediation in Green Technology Supply-Demand Matching: Mechanisms and Evidence
DOI:
https://doi.org/10.65514/cpjpb006Keywords:
Green Technology Transfer; Data Elements; Functional DisintermediationAbstract
Despite the surge in green innovation, technology transfer remains constrained by high search frictions and trust deficits that traditional human-centric intermediation struggles to resolve. Grounded in Transaction Cost Theory, this study conducts an exploratory dual-case study of the "Zhizhe" Model and "Anxinwu" Platform in China to investigate how data elements reconstruct this mechanism. The findings reveal a "Dual-Drive Mechanism" where AI-enabled semantic alignment reduces ex-ante search costs, while blockchain-based evidence chains mitigate ex-post trust costs by substituting bureaucratic endorsement. We conclude that digitization leads to "Functional Disintermediation"—decoupling routine matching and verification from human agents—contingent upon "Techno-Institutional Co-evolution".
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