Research on Data-Sharing Mechanisms and Value Chain Reconfiguration in the Macao--Hengqin Collaborative "Big Health" Industry

Shuang Diao and Yuting Zhang

Pinnacle Academic Press Proceedings Series, 2026, vol. 10, 205-213

Abstract: This paper examines how cross-border data-sharing between Macao and Hengqin ("Macao--Hengqin collaboration") can catalyze value chain reconfiguration in the Big Health industry spanning biomedicine, medical devices, digital health, wellness tourism, and elderly care. A governance-ready framework is proposed that aligns interoperable data infrastructure with clinical, industrial, and tourism-service workflows, integrating privacy-preserving technologies, trustable exchange rules, and outcome-oriented incentives. The study develops a five-layer architecture-data, features, analytics and forecasting, coordination and optimization, and risk-and-compliance-that links micro-level data flows to meso-level cluster synergies and macro-level productivity and competitiveness. Within this architecture, federated learning, tokenized data assets, and standardized interfaces are used to support secure cross-border collaboration in research and development, clinical trials, and service delivery. A semi-synthetic evaluation calibrated to Greater Bay Area statistics suggests that federated and tokenized data-sharing can shorten R&D cycles, increase cross-border patient recruitment efficiency, and elevate service export value while controlling privacy risk and regulatory exposure. The analysis further highlights institutional frictions, interoperability gaps, and governance challenges that may constrain implementation. In response, policy and operational strategies are proposed for platform design, standard harmonization, regulatory sandboxes, and public-private partnerships to realize sustained industrial upgrading, promote regional integration, and enhance the global competitiveness of the Macao-Hengqin Big Health cluster.

Keywords: health industry; data sharing; value chains; regional integration; governance; innovation policy (search for similar items in EconPapers)
Date: 2026
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