A Bibliometric Analysis of Using Technology Acceptance Model in The Agriculture Field
Öz
The Technology Acceptance Model (TAM), developed by Davis in 1989, has been used in over 10000 academic studies. This study aims to analyze research on TAM used for adopting new technologies in agriculture through bibliometric analysis. Using the Web of Science database, 117 studies were reviewed using “technology acceptance model” and “agriculture” as keywords. The analysis covers authorship, citations, sources, countries, institutions, key terms, co-occurrences, themes, and author relationships. The findings indicate that the journal with the highest number of publications is “Sustainability”, and the institution with the highest number of publications is Iowa State University. China is identified as the country with the most publications, while Germany is the country with the most citations. Additionally, the keyword “precision agriculture” stands out among the frequently used terms. As a result of bibliometric analysis, a general picture of the selected field was obtained..
Anahtar Kelimeler
Technology Acceptance Model (TAM), Bibliometric Analysis, Agriculture
Kaynakça
- Adnan, N., Nordin, S. M., Bahruddin, M. A., & Tareq, A. H. (2019). A state-of-the-art review on facilitating sustainable agriculture through green fertilizer technology adoption: Assessing farmers' behavior. Trends in Food Science & Technology, 86, 439-452.
- Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975.
- Cakirli Akyüz, N., & Theuvsen, L. (2020). The impact of behavioral drivers on adoption of sustainable agricultural practices: The case of organic farming in Turkey. Sustainability, 12(17), 6875.
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3), 397-415.
- https://english.news.cn/20230117/086a4980494b451baa0bea5c68dc562e/c.html, Erişim tarihi: 27.07.2024.
- https://www.usda.gov/media/press-releases/2023/04/06/usda-awards-innovations-climate-smart-agriculture-soil-health-and, Erişim tarihi: 27.07.2024.
- https://www.bbc.com/worklife/article/20240325-artificial-intelligence-ai-us-agriculture-farming, Erişim tarihi: 27.07.2024.
- Mulaudzi, A. I., Olorunfemi, O. D., & Agholor, A. I. (2024). Social media utilization level among South African smallholder farmers: A case study of Mopani District, Limpopo Province. Cogent Social Sciences, 10(1), 2356722.
- Ommani, A. R., Chizari, M., Salmanzadeh, C., & Hosaini, J. F. A. (2009). Predicting adoption behavior of farmers regarding on-farm sustainable water resources management (SWRM): Comparison of models. Journal of Sustainable Agriculture, 33(5), 595-616.
- Pierce, F. J., & Nowak, P. (1999). Aspects of precision agriculture. Advances in agronomy, 67, 1-85.