The hidden power of emotions: How psychological factors influence skill development in smart technology adoption

Gerli, Paolo; Clement, Jessica; Esposito, Giovanni; Mora, Luca; Crutzen, Nathalie

Abstract

Working within the theoretical framework set by the Technology Acceptance Model (TAM) literature, this paper clarifies how psychological factors (emotions, attitudes, beliefs, and information-seeking) affect skill development in the context of smart farming technologies. Interviews with multiple stakeholders from the agriculture sectors of three European countries (Belgium, Italy, and the United Kingdom) were used to develop a new conceptual model that attempts to generalize the complex interplay existing between skills and psychological factors in the context of smart technology adoption. This conceptualization provides a systematic view of the correlation between skills and psychological factors, complements the TAM by introducing the new concept of attitude to learning, and clarifies how the interplay between cognitive and emotional components influences the decisions to adopt and use smart technologies. In addition to these theoretical contributions, the paper emphasizes the importance of designing policy initiatives that tackle both cognitive and emotional barriers to the adoption of smart technologies, urging decision makers to move away from the simplistic assumption that increasing the digital skills of potential users automatically leads to growth in the adoption and implementation of smart technologies.

Citation

Gerli, P., Clement, J., Esposito, G., Mora, L., & Crutzen, N. (2022). The hidden power of emotions: How psychological factors influence skill development in smart technology adoption. Technological Forecasting and Social Change, 180, Article 121721. https://doi.org/10.1016/j.techfore.2022.121721

• Journal Article Type: Article
• Acceptance Date: Apr 22, 2022
• Online Publication Date: Apr 29, 2022
• Publication Date: 2022-07
• Deposit Date: May 5, 2022
• Publicly Available Date: May 5, 2022
• Journal: Technological Forecasting and Social Change
• Print ISSN: 0040-1625
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 180
• Article Number: 121721
• DOI: https://doi.org/10.1016/j.techfore.2022.121721
• Keywords: Smart technology, Smart agriculture, Technology acceptance, Digital skills, Psychological factors, Attitude to learning
• Public URL: http://researchrepository.napier.ac.uk/Output/2866906