Technology Readiness and Generative AI Adoption in Logistics: Trust, Motivation, and Anthropomorphism

Abstract

This study examines how technology readiness shapes logistics professionals’ intention to adopt generative artificial intelligence (AI), with particular attention to the roles of trust, intrinsic motivation, and anthropomorphism. Drawing on the Technology Readiness Index and Self-Determination Theory, the study proposes that optimism, discomfort, insecurity, and service awareness influence adoption intention primarily through trust-based motivational and perceptual pathways. A cross-sectional survey was conducted among 203 logistics practitioners in Oman, Saudi Arabia, and Iraq, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM). The findings show that technology readiness dimensions do not directly predict generative AI adoption intention but significantly shape trust in AI. Trust emerged as a central mechanism, exerting a strong direct effect on adoption intention while also positively influencing intrinsic motivation and anthropomorphism. In turn, both intrinsic motivation and anthropomorphism significantly enhance intention to adopt generative AI. The indirect results further indicate that technology readiness operates mainly through trust-driven pathways rather than as a direct behavioral driver. The study extends AI adoption research by repositioning technology readiness as an upstream psychological resource and by highlighting the importance of trust, motivation, and perceptions of human-like AI in the logistics context.