Investigating the intention to use augmented reality technologies in agriculture: Will smart glasses be part of the digital farming revolution?

•Augmented reality and smart glasses adoption by future farmers is investigated.•The fundamental technology acceptance model is extended with three related factors.•Agricultural stakeholders perceive smart glasses positively for farm activities.•The relationships between the main constructs of the TAM are confirmed.•Intention to use is affected by attitude, compatibility, and perceived benefit. Agricultural revolutions have always been influenced by the historical context and driven by existing technologies. Currently, the world is pervaded by digital technologies that will represent a further step forward the evolution of the agricultural sector. Different digital technologies are being use by farmers to support the precise management of the farm. Smart glasses for augmented reality are promising digital technologies for the agricultural context, and their potential applications have been highlighted by several recent studies. These devices allow the real-time overlay of precise information on the elements of interest, providing farmers with specific data for supporting their activities. Although smart glasses and augmented reality are potentially valuable tools, it will be valuable to assess the actual willingness of farmers to use these devices in the context of the digital agricultural revolution. Therefore, this study aims to analyze the factors influencing farmers’ intentions to use smart glasses and augmented reality technologies. For this purpose, in the survey the extended version of technology acceptance model (TAM) was used. The original TAM was extended by adding relevant factors such as perceived benefit, compatibility, and self-efficacy. These factors were select based on a bibliography search for the study on the acceptance of smart farming technologies and augmented reality devices. The structural equation modeling technique was applied to analyze the questionnaire responses with a tow step approach. First, the measurement model was analyzed by performing a confirmatory factor analysis (CFA). Then, was evaluated the structural model by assessing the relationship between the factors to test the formulated hypothesis. All the factors considered were validate during the measurement model analysis, except for self-efficacy, which was removed to improve the model fit. The results show that attitude, perceived benefit, and compatibility directly influenced the agricultural stakeholders’ acceptance of smart glasses as a new and innovative tool to