Determinants influencing the adoption of the windy.com application among large-scale durian farmers’ groups in Rayong Province, Thailand

Main Article Content

Thonoi, A.
Thongkaew, E.
Suwanmaneepong, S.
Kerdsriserm, C.
Mankeb, P.

Abstract

The findings found that farmers who participated in training and utilised the Windy.com application, the majority of participants were male, aged between 51 and 60 years, with a bachelor’s degree and an average household size of 3–4 members. The farmers possessed 1–15 years’ experience in durian cultivation, with farm sizes ranging from 1 to 25 rai. The average durian yield was approximately 1,000–2,000 kilograms per rai, with an average market price of 91–120 Baht per kilogram. Participants demonstrated a high level of knowledge (µ = 81.20) and exhibited a positive attitude towards the Windy.com application (mean = 3.91), with the highest attitude score observed in the content dimension (µ = 4.08). Overall, the adoption of the application was rated as high (µ = 4.09), particularly concerning their intention to use it (µ = 4.23) and perceived usefulness (µ = 4.06). Multiple regression analysis reveals attitude to be the most significant predictor of adoption (β = 0.67, p < 0.01), suggesting that improved attitudes among farmers increased their adoption of the application. Conversely, factors such as farming experience and farm size  was significantly influenced adoption (p > 0.05). The results imply that promoting positive attitudes and providing effective training can significantly enhance farmers’ long-term adoption and utilisation of digital applications.

Article Details

How to Cite
Thonoi, A., Thongkaew, E., Suwanmaneepong, S., Kerdsriserm, C., & Mankeb, P. (2026). Determinants influencing the adoption of the windy.com application among large-scale durian farmers’ groups in Rayong Province, Thailand. International Journal of Agricultural Technology, 22(3), 1507–1520. retrieved from https://li04.tci-thaijo.org/index.php/IJAT/article/view/11739
Section
Original Study

References

Adesiji, G. B., Ogunlade, I. and Adekunle, O. (2024). Farmers’ perceived rating and usability attributes of mobile phone apps. Digital Agricultural Technologies, 3:45-58.

Abdullahi, H. O., Hassan, A. A., Mahmud, M. and Ali, A. F. (2021). Determinants of ICT adoption among small scale agribusiness enterprises in Somalia. International Journal of Engineering Trends and Technology, 69:68-76.

Agricultural Technology and Innovation Center, Bank for Agriculture and Agricultural Cooperatives (2023). Windy application: Weather forecasting for farmers. Retrieved from https://www.gosmartfarmer.com/innovation/22133

Amoussouhoui, R., Arouna, A., Ruzzante, S. and Banout, J. (2024). Adoption of ICT4D and its determinants: A systematic review and meta-analysis. Heliyon, 10:9.

Aung, N., Thein, Z. M. M. and Tun, Z. M. (2025). Investigating farmers’ adoption of mobile Agri-Tech: A TAM approach. Journal of Agricultural Informatics, 16:45-60.

Bloom, B. S. (1967). Evaluation of learning in secondary school. New York: McGraw–Hill Book Company Inc.

Boonchai, K. (2020). Agriculture and global food security in the era of climate change. ThaiPublica. Retrieved from https://thaipublica.org/2021/07/thai-climate-justice-for-all05/

Buathong, P. (2017). Factors affecting the decision of durian cultivation among farmers in Angkiri Sub-district, Makham District, Chanthaburi Province (Master Thesis). Burapha University, Thailand.

Charoenpituk, S., Suwanmaneepong, S., Llones, C. and Kerdsriserm, C. (2024). Community enterprise quality management of durian exports in Ban Khao Hin Thaen, Wang Chan District, Rayong Province, Thailand. International Journal of Agricultural Technology, 20:983-1000.

Chuang, J. H., Wang, J. H. and Liou, Y. C. (2020). Farmers’ knowledge, attitude, and adoption of smart agriculture technology in Taiwan. International Journal of Environmental Research and Public Health, 17:7236.

Department of Internal Trade, Ministry of Commerce (2024). Durian export report of Thailand. Bangkok, Thailand: Author.

Hennink, M. M. (2022). Sample sizes for saturation in qualitative research: A systematic review of empirical tests. Social Science & Medicine, 292:114523.

Kerdsriserm, C., Suwanmaneepong, S. and Praneetvatakul, S. (2024). Assessment of farmers’ acceptance, satisfaction, and utilization of mobile application for rice production cost and return in Chachoengsao Province, Thailand. International Journal of Agricultural Technology, 20:643-654.

Mankeb, P. (2016). The use of computers for agricultural analysis (2nd ed.). Bangkok, Thailand: Faculty of Agricultural Technology, King Mongkut’s University of Technology North Bangkok.

Mankeb P., Limunggura T., In-go A. and Chulilung P. (2014). Adoption of Good Agricultural Practices (GAP) by durian farmers in Koh Samui District, Surat Thani Province, Thailand. Kasetsart Journal of Social Sciences, 35:215-226.

Meehat, N., Suwanmaneepong, S. and Kerdsriserm, C. (2025). Factors affecting the sharing of information on quality durian production by farmers in Rayong Province, Thailand. International Journal of Agricultural Technology, 21:123-136.

Mishra, N., Bhandari, N., Maraseni, T., Devkota, N., Khanal, G., Bhusal, B., Basyal, D. K., Paudel, U. R. and Danuwar, R. K. (2024). Technology in farming: Unleashing farmers’ behavioral intention for the adoption of agriculture 5.0. PLOS ONE, 19:e0308883.

National Statistical Office of Thailand. (2023). Agricultural census 2023: GIS-based presentation of results. Retrieved from https://esurvey.nso.go.th/portal/apps/dashboards/83b24dd5011940689cd011e9d5259afa

Ntsoane, M. M., Ndoro, J. T. and Wayi-Mgwebi, N. (2025). Multivariate Probit Model Analysis of the Factors Influencing Smallholder Farmers’ Choice of ICT Tools: A Case Study of Mpumalanga, South Africa. Agriculture, 15:1817.

Okai, G. E. Y., Agangiba, W. A. and Agangiba, M. (2024). Assessment of farmers’ acceptance of intelligent agriculture system using Technology Acceptance Model. International Journal of Computer Applications, 186:16-22.

Okoroji, V., Lees, N. J. and Lucock, X. (2021). Factors affecting the adoption of mobile applications by farmers: An empirical investigation. African Journal of Agricultural Research, 17:19-29.

Prapruit, P., Wikraisakul, J. and Pomsakul, A. (2022). Knowledge and practice following Good Agricultural Practice (GAP) in durian cultivation along the border in Srisakorn district, Narathiwat Province. International Journal of Agricultural Technology, 18:1727-1738.

Seeda, W. (2024, November 10). Using weather information for precision durian farming [Interview by A. Thonoi]. In Innovation project for durian production and marketing management, Rayong Province.

Szabo, S., Rigg, J., and Ros, B. (2021). Agricultural productivity, aging farming workforce and rural transformation in Thailand. Frontiers in Sustainable Food Systems, 5:728120.

Thongpanchang, W. (2003). Durian: Cultivation handbook. Bangkok, Thailand: Kasetsart University, Community Agriculture Book Project.

Wanjohi, A. M. and Syokau, P. (2021). How to conduct Likert scale analysis. Kenya Projects Organization. Retrieved from https://kenpro.org/how-to-conduct-likert-scale-analysis/

Yeo, M. L. and Keske, C. M. (2024). From profitability to trust: Factors shaping digital agriculture adoption. Frontiers in Sustainable Food Systems.