IMPACT OF ARTIFICIAL INTELLIGENCE (AI) ADOPTION ON LOGISTICS PERFORMANCE AND TRADE GROWTH IN ZANZIBAR'S AIR CARGO SECTOR

Abstract

This study examines the effect of Artificial Intelligence (AI) adoption on logistics performance and trade growth in Zanzibar’s air cargo sector. The analysis is guided by an Integrated Technology Performance Model (ITPM), drawing on the Technology Acceptance Model (TAM) to explain user acceptance, the Resource-Based View (RBV) to position AI as a strategic capability for efficiency, and Endogenous Growth Theory (EGT) to link improved logistics performance to increased trade outcomes. A mixed-methods approach was applied, using quantitative data from 154 respondents and qualitative insights from 20 logistics managers. The quantitative results show that AI adoption significantly improves logistics performance (β = 0.679, p < 0.05), and logistics performance positively contributes to trade growth (β = 0.621, p < 0.01). Mediation analysis confirms that logistics performance partially mediates the relationship between AI adoption and trade growth, indicating that efficiency gains are the primary channel through which AI supports trade expansion.