Logistics and Customs Digitalization Practices Assessment Using a Technology Acceptance Model

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Matiwos Ensermu Jaleta
Merid Nigussie Tulu


The importance of effective logistics services and customs operations is now recognized globally as a fundamental catalyst for development and is critical for national competitiveness. With the rapid advancement of digitalization, international trade actors around the world are increasingly adopting digital solutions to enable a digitally interconnected ecosystem and to exploit the potential of digitalization. This study applied quantitative approaches to evaluate and understand the status quo of digitalization practices of logistics services and customs operations using basic determinants from the technology acceptance model. A total of 622 responses were collected using subjective questionnaires from customs employees and logistics service providers. The main contribution is that although the determinants of the technology acceptance model are widely used tools, there is no coherent approach to use them to learn the digitalization practices of logistics services and customs operations. Therefore, this study seeks to better understand the trends in logistics and customs digitalization by analyzing the determinants of the technology acceptance model in terms of the simplicity of the technology to use, the importance of the usage, and the perception of user satisfaction. The study comprehensively analyzed and discussed factors of the acceptance model of technology and relevance. The result demonstrates that customs employees' technology usage practices are more positive than portfolios of logistics service providers perception. It serves to identify digitalization practices, enabling actors to determine and implement technologies that promote increased acceptance.

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Author Biographies

Matiwos Ensermu Jaleta, Addis Ababa University

Associate Professor of Logistics, School of Commerce

Merid Nigussie Tulu, Addis Ababa Science and Technology University

Artificial Intelligence and Robotics Center of Excellence