Determinants of Digital Technologies Adoption in Manufacturing Companies: Empirical Research Based on Expanded UTAUT Model

Abstract

The main objective of this paper is to identify key determinants that impact the intention to adopt the most widely used digitalization and automation technologies in manufacturing companies—namely, the Internet of Things, Artificial Intelligence, and Big Data. An Expanded Unified Theory of Acceptance and Use of Technology (UTAUT) model was used, based on which tailored strategies for specific technology adoption can be defined. The data were collected through a survey conducted in manufacturing companies in the Republic of Serbia and analyzed using Structural Equation Modeling. The results show that the main drivers of intention to use these three technologies are performance expectancy, facilitating conditions, and the current level of digitalization and automation. All three determinants exhibit statistically significant and positive effects on adoption intentions. The main findings are valuable for decision makers and practitioners, offering insights into the factors that enable technology adoption and providing support for the development of effective implementation strategies based on the key determinants. Also, these results are relevant for other emerging and post-transitional economies in the Balkans and Eastern Europe, as they face similar infrastructural, institutional and digital challenges, as well as similar levels of industrialization and technological development.