Human, organizational and technological factors influencing harmonized system code misclassification in express customs clearance

Harmonized System (HS) classification is a core function of customs administration, underpinning tariff assessment, regulatory controls, and trade statistics. In express customs clearance environments, however, HS classification must be performed under time-critical conditions characterized by high shipment volumes, limited documentation quality, strict service-level requirements, and increasing reliance on digital declaration systems. Despite standardized nomenclature and the growing use of automated and technology-assisted classification tools, HS misclassification remains a persistent issue with significant compliance, fiscal, and operational implications. Existing research has predominantly emphasized legal interpretation, enforcement outcomes, or technical system design, while giving comparatively limited attention to the human, organizational, and socio-technical conditions under which classification decisions are made in practice. This study examines the human, organizational, and technology-related factors contributing to HS misclassification in express customs clearance operations using a qualitative research design. Data was collected through semi-structured interviews with six practitioners directly involved in HS classification, supervisory oversight, and operational support roles. deductive thematic analysis reveals that HS misclassification is not solely attributable to technical complexity or individual error. Instead, it emerges from the interaction between uneven depth of HS knowledge (particularly at subheading and national-digit levels), informal onboarding and buddy-session learning, high workload intensity, time pressure driven by cleared-on-arrival (COA) performance targets, constrained opportunities for verification, and organizational practices that prioritize processing speed over analytical depth. The findings further show that technology and system-based classification tools play a dual role. While automated HS suggestions and digital workflows support processing efficiency, they may also reinforce historical classification patterns and reduce critical verification when corrective feedback mechanisms, system governance, and structured learning loops are limited. These socio-technical dynamics amplify misclassification risk, particularly when documentation quality is poor and operational pressure is high. By conceptualizing HS misclassification as a socio-technical and organizational phenomenon rather than a purely legal or technical problem, this study contributes empirical insight into express customs clearance practice and highlights the importance of strengthening competency assurance, workload and process design, verification controls, information quality, and governance of technology-assisted classification to support sustainable compliance alongside trade facilitation objectives.