Research on the Adaptability of Smart Customs Clearance in the Guangdong-Hong Kong-Macao Greater Bay Area
Abstract
This study focuses on optimizing the facilitation of customs clearance models in the Guangdong-Hong Kong-Macao Greater Bay
Area (GBA). Addressing the inefficiencies and suboptimal user experiences inherent in the current two-stop, two-inspection and one-stop,
two-inspection models, we propose an innovative Cooperative Inspection, One-time Release model and construct an analytical framework
based on game theory. Through field investigations of cross-border clearance practices and the analysis of quantitative and qualitative data,
this research explores the impact of incentive mechanisms, information sharing, and other factors on clearance efficiency and collaborative
willingness. The methodology combines game-theoretic modeling and regression analysis to model key variables and validate the feasibility
of the new approach. Key findings demonstrate that the proposed model significantly enhances clearance efficiency, reduces processing time,
and optimizes resource allocation. However, its implementation hinges on data interoperability and policy coordination among stakeholders. Theoretically, this study extends the application of game theory to cross-border clearance systems, offering a novel analytical lens for
academia. Practically, it provides actionable recommendations for refining cross-border collaboration and customs policies, thereby advancing
regional integration and trade facilitation in the GBA. This work contributes empirical evidence and policy insights to the optimization of customs mechanisms in transnational regional cooperation contexts.
Area (GBA). Addressing the inefficiencies and suboptimal user experiences inherent in the current two-stop, two-inspection and one-stop,
two-inspection models, we propose an innovative Cooperative Inspection, One-time Release model and construct an analytical framework
based on game theory. Through field investigations of cross-border clearance practices and the analysis of quantitative and qualitative data,
this research explores the impact of incentive mechanisms, information sharing, and other factors on clearance efficiency and collaborative
willingness. The methodology combines game-theoretic modeling and regression analysis to model key variables and validate the feasibility
of the new approach. Key findings demonstrate that the proposed model significantly enhances clearance efficiency, reduces processing time,
and optimizes resource allocation. However, its implementation hinges on data interoperability and policy coordination among stakeholders. Theoretically, this study extends the application of game theory to cross-border clearance systems, offering a novel analytical lens for
academia. Practically, it provides actionable recommendations for refining cross-border collaboration and customs policies, thereby advancing
regional integration and trade facilitation in the GBA. This work contributes empirical evidence and policy insights to the optimization of customs mechanisms in transnational regional cooperation contexts.
Keywords
Trade Facilitation; Game Theory; Cross-border Collaboration
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PDFReferences
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DOI: http://dx.doi.org/10.70711/frim.v3i8.6927
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