Abstract
The rapid growth of cross-border e-commerce poses significant challenges to the labour-intensive customs clearance process. Physical inspection of contents remains a compulsory burden in the customs clearance process, even for modern customs clearance centres. This research aims to identify a sampling method for a global solution that satisfies stakeholders’ interests in cross-border e-commerce in terms of accuracy, promptness, and resilience. To accomplish this, operational data were collected from a customs clearance centre in southern China to perform a realistic simulation. Further, the performance of various sampling methods was simulated based on the current simple random sampling versus various two-stage sampling methods. Pallet handling utilises two-stage sampling methods to enhance efficiency in combination with an informative sample size. Thus, an appropriate two-stage sampling method ensures optimal performance, thereby overcoming the undesirable side effects of the sampling methods. The study found that TSS1 with a sampling probability proportional to pallet size was optimal in satisfying the contradictory interests of the stakeholders. This study provides a toolset to improve the efficiency of customs clearance by applying theoretical sampling techniques to the challenges encountered in customs clearance operations. Thus, it contributes to eliminating bottlenecks in customs clearance centres in countries worldwide, which can lead to the global success of cross-border e-commerce.
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Details
; Hwang, Beom-Seuk 2 1 Chung-Ang University, Department of International Logistics, Seoul, South Korea (GRID:grid.254224.7) (ISNI:0000 0001 0789 9563)
2 Chung-Ang University, Department of Applied Statistics, Seoul, South Korea (GRID:grid.254224.7) (ISNI:0000 0001 0789 9563)




