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AI deployment for heterogeneous ports: Strategic choices between independent R&D and outsourcing

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  • Lu, Bo
  • Zhang, Guixian
  • Li, Yonggang

Abstract

Artificial intelligence (AI) technology is the key support for the intelligent transformation of ports. This study examines optimal AI technology deployment strategies for heterogeneous ports operating within co-opetition networks. We consider the ecological synergy characteristics, deployment effect uncertainty and port heterogeneity, construct a dual-market game-theoretic model to analyze the strategic choice between independent R&D and outsourcing. The results reveal that deployment decisions of port are shaped not only by cost-benefit considerations but also by the interplay of co-opetition structures, technological ecosystems, and AI technology risks. A cooperation paradox is identified, expansion of the cooperative market may reduce AI technology level when both ports pursue independent R&D, particularly under the expected effect of deployment is low. This outcome that underscores the technology investment motivational barriers in loosely coupled alliances. Conversely, when ports form a unified technology ecosystem, cooperative market growth positively correlates with the AI technology deployment level, driven by ecological synergy effects. If one port opts for independent R&D while the other outsources third-party AI technology, competitive advantage hinges on whether the former's AI deployment effect exceeds a critical threshold. The study delineates a multidimensional strategic space defined by cooperative market scale, competition intensity, AI technology deployment effect uncertainties and R&D costs, provide theoretical support for ports in choosing AI technology deployment strategy.

Suggested Citation

  • Lu, Bo & Zhang, Guixian & Li, Yonggang, 2026. "AI deployment for heterogeneous ports: Strategic choices between independent R&D and outsourcing," Transport Policy, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:trapol:v:178:y:2026:i:c:s0967070x25005207
    DOI: 10.1016/j.tranpol.2025.103977
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