The potential of AI-enabled quality control facing high inspection standard in resilient cross-border operations

Baozhuang Niu, Jian Dong, Fengfeng XIE

Research output: Journal PublicationArticlepeer-review

Abstract

Technology Barriers to Trade (TBT) is commonly observed under which import inspection standards exceed international benchmarks. In such cases, traditional manual inspection may lead to significant supply uncertainty due to the compliance issues encountered during customs clearance, resulting in customers’ quality concerns. However, with the development of artificial intelligence (AI), AI-based quality control is an effective way to improve yield under high standards. To investigate whether a global manufacturer should adopt the AI-based quality control solution, we consider a global manufacturer with an overseas and a local manufacturing division, where the two manufacturing divisions sell products through their exclusive retailers. We find that AI inspection to meet TBT requirements will be preferred when the customs disposal cost is moderate and the AI cost is either low or high. Interestingly, we find that AI strategy may be better even when most overseas products have met the TBT requirements and customers’ quality concerns are faint. Global manufacturers are therefore advised to carefully assess market conditions and the co-opetition relationship between two manufacturing divisions. We highlight the substitutable relationship between tariff and TBT requirement as the barrier to import and recommend a lower tariff to harness the effectiveness of TBT.
Original languageEnglish
JournalInternational Journal of Production Research
DOIs
Publication statusPublished Online - 4 Sept 2024

Keywords

  • Responsible consumption and production
  • AI-based quality control
  • global operations
  • resilience improvement
  • co-opetition

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