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Abstract
The research examined the factors affecting farmers’ behavior in the coffee production on geographical indication in Lam Dong province from a psycho-behavioral perspective. The research integrated the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) as its conceptual framework. The data were collected through direct interviews with 604 coffee farmers and processed through Smart-PLS 4.0 software. The results of the study showed that the factors in the model explained 64.6% of the change in behavioral intention and 71% of the change in the performance behavior of farmers in coffee production according to GI. The performance behavior of farmers is directly influenced by the factors of behavioral intentions, attitudes, conditions for participation, and indirectly through the factors of behavioral intentions, including attitudes, awareness of the efficacy of GI organizations, recognition of utility, and conditions for participation. Consequently, to enhance the behavioral implementation of farmers in coffee production aligned with the GI, it is imperative to elevate awareness regarding the economic, social, and environmental advantages of the model, alongside fostering the community's involvement in the development of regional brands.
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How to Cite
Tran Hoai Nam, Nguyen Thuy Dung, Nguyen Minh Ton, Duong Thi Thu Thinh, Tran Thi Minh Nuong, & Nguyen Xuan Thanh. (2026). Analysis of factors affecting farmers’ behavior in geographical indication the coffee production in Lam Dong province. E-Journal of Agricultural Science and Technology, 10(2), 5613–5623. https://doi.org/10.46826/huaf-jasat.v10n2y2026.1353
Section
AGRICULTURAL EXTENSION - RURAL DEVELOPMENT
Copyright @ 2017-2026 by E-Journal of Agricultural Science and Technology
References
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Ajzen, I. (2002). Constructing a TPB questionnaire: Conceptual and methodological considerations.
Arfini, F., Cozzi, E., Mancini, M. C., Ferrer-Perez, H., & Gil, J. M. (2019). Are geographical indication products fostering public goods? Some evidence from Europe. Sustainability, 11(1), 272.
Becker, T. C. (2009). European food quality policy: the importance of geographical indications, organic certification and food quality assurance schemes in European countries. Estey Journal of International Law and Trade Policy, 10(1), 111-130.
Correa, C. M. (2005). The TRIPS agreement and developing countries. In The World Trade Organization: Legal, Economic and Political Analysis (pp. 2010–2046).
Cristina, V. P. (2021). The long-term fortunes of territories as a route for agri food policies: evidence from Geographical Indications. Bio base Appl. Econ. 10(2), 89.
Dong, H., Wang, H., & Han, J. (2022). Understanding ecological agricultural technology adoption in China using an integrated Technology Acceptance Model—Theory of Planned Behavior. Frontiers in Environmental Science, 10, 927668.
Dammert, A. C., & Mohan, S. (2015). A survey of the economics of fair trade. Journal of Economic Surveys, 29(5), 855-868.
Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach. Psychology Press.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling. Sage.
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Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based SEM. Journal of the Academy of Marketing Science, 43(1), 115–135.
Laksono, P., Irham, Mulyo, J. H., & Suryantini, A. (2022). Farmers' willingness to adopt geographical indication practice in Indonesia. Heliyon, 8(8), e10178.
Menapace, L., Moschini, G. (2012). Quality certification by geographical indications, trademarks and firm reputation, European Review of Agricultural Economics, 39 (4),539-566. DOI: https://doi.org/10.1093/erae/jbr053
Mishra, N., et al. (2024). Technology in farming: Unleashing farmers' behavioral intention for adoption of agriculture 5.0. PLoS One, 19(8), e0308883.
Nguyen, T. P. L., Doan, X. H., Nguyen, T. T., & Nguyen, T. M. (2021). Factors affecting Vietnamese farmers' intention toward organic production. International Journal of Social Economics, 48(8), 1213–1228.
Oliveira, T., Faria, M., Thomas, M. A., & Popovič, A. (2014). Extending the understanding of mobile banking adoption. International Journal of Information Management, 34(5), 689–703.
Phung, Q. A., & Dao, N. (2024). Farmers' perceptions of sustainable agriculture in the Red River Delta, Vietnam. Heliyon, 10(7), e28576.
Santana, G. d. S. R. D. B., Lense, G. H. E., Brizolari, G. R., et al. (2023). Modeling soil losses by water erosion in a coffee growing area in Southeastern Brazil. Revista Brasileira de Geografia Física, 16(4), 2031–2046.
Todd, P. A., & Benbasat, I. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.
Tohidyan Far, S., Rezaei-Moghaddam, K., & Shokri Koochak, S. (2025). An integrated model for analyzing farmers' behavioral intention towards environmental technologies. Discover Environment, 3(1).
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model. Management Science, 46(2), 186–204.
Vu, T. K. L. (2024). An analysis of coffee grower households in response to the global coffee crisis in Lam Dong Province, Vietnam. Journal of Southeast Asian Studies, 29(1), 46–67.
Wijayanil, A., Ardhanariswari, K. A., Prayudi, & Probosari, N. (2022). Protection of geographic indications to maintain the quality of robusta coffee on the slopes of Mt. Arjuna, Welirang, and Bromo. IOP Conference Series: Earth and Environmental Science, 1018(1).
Wu, S., Xiao, Y., Pacala, A., Badulescu, A., & Khan, S. (2024). Understanding Chinese farmers’ behavioral intentions to use alternative fuel machinery. Sustainability, 16(24), 11059.
Wulandari, S., & Ferry, Y. (2021). Strategies on technology management for coffee smallholder to promote smart farming. IOP Conference Series: Earth and Environmental Science, 759(1), 012057.
Xiang, P., & Guo, J. (2023). Understanding farmers’ intentions to adopt pest and disease green control techniques. Sustainability, 15(14), 10822.
Raykov, T. (2008). An introduction to applied multivariate analysis. Routledge.
Vennin, S. (2025). Opportunities and obstacles: How to ensure Vietnamese smallholder coffee farmers are ready for the EUDR. Sustainable Rural Development.
Vicofa. (26/10/2024). Xuất khẩu cà phê niên vụ 2023 - 2024 lập kỷ lục 5,43 tỷ USD. Khai thác từ https://vicofa.org.vn/xuat-khau-ca-phe-nien-vu-2023-2024-lap-ky-luc-543-ty-usd-bid2570.html
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
Ajzen, I. (2002). Constructing a TPB questionnaire: Conceptual and methodological considerations.
Arfini, F., Cozzi, E., Mancini, M. C., Ferrer-Perez, H., & Gil, J. M. (2019). Are geographical indication products fostering public goods? Some evidence from Europe. Sustainability, 11(1), 272.
Becker, T. C. (2009). European food quality policy: the importance of geographical indications, organic certification and food quality assurance schemes in European countries. Estey Journal of International Law and Trade Policy, 10(1), 111-130.
Correa, C. M. (2005). The TRIPS agreement and developing countries. In The World Trade Organization: Legal, Economic and Political Analysis (pp. 2010–2046).
Cristina, V. P. (2021). The long-term fortunes of territories as a route for agri food policies: evidence from Geographical Indications. Bio base Appl. Econ. 10(2), 89.
Dong, H., Wang, H., & Han, J. (2022). Understanding ecological agricultural technology adoption in China using an integrated Technology Acceptance Model—Theory of Planned Behavior. Frontiers in Environmental Science, 10, 927668.
Dammert, A. C., & Mohan, S. (2015). A survey of the economics of fair trade. Journal of Economic Surveys, 29(5), 855-868.
Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior: The reasoned action approach. Psychology Press.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling. Sage.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling. Springer.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based SEM. Journal of the Academy of Marketing Science, 43(1), 115–135.
Laksono, P., Irham, Mulyo, J. H., & Suryantini, A. (2022). Farmers' willingness to adopt geographical indication practice in Indonesia. Heliyon, 8(8), e10178.
Menapace, L., Moschini, G. (2012). Quality certification by geographical indications, trademarks and firm reputation, European Review of Agricultural Economics, 39 (4),539-566. DOI: https://doi.org/10.1093/erae/jbr053
Mishra, N., et al. (2024). Technology in farming: Unleashing farmers' behavioral intention for adoption of agriculture 5.0. PLoS One, 19(8), e0308883.
Nguyen, T. P. L., Doan, X. H., Nguyen, T. T., & Nguyen, T. M. (2021). Factors affecting Vietnamese farmers' intention toward organic production. International Journal of Social Economics, 48(8), 1213–1228.
Oliveira, T., Faria, M., Thomas, M. A., & Popovič, A. (2014). Extending the understanding of mobile banking adoption. International Journal of Information Management, 34(5), 689–703.
Phung, Q. A., & Dao, N. (2024). Farmers' perceptions of sustainable agriculture in the Red River Delta, Vietnam. Heliyon, 10(7), e28576.
Santana, G. d. S. R. D. B., Lense, G. H. E., Brizolari, G. R., et al. (2023). Modeling soil losses by water erosion in a coffee growing area in Southeastern Brazil. Revista Brasileira de Geografia Física, 16(4), 2031–2046.
Todd, P. A., & Benbasat, I. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.
Tohidyan Far, S., Rezaei-Moghaddam, K., & Shokri Koochak, S. (2025). An integrated model for analyzing farmers' behavioral intention towards environmental technologies. Discover Environment, 3(1).
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model. Management Science, 46(2), 186–204.
Vu, T. K. L. (2024). An analysis of coffee grower households in response to the global coffee crisis in Lam Dong Province, Vietnam. Journal of Southeast Asian Studies, 29(1), 46–67.
Wijayanil, A., Ardhanariswari, K. A., Prayudi, & Probosari, N. (2022). Protection of geographic indications to maintain the quality of robusta coffee on the slopes of Mt. Arjuna, Welirang, and Bromo. IOP Conference Series: Earth and Environmental Science, 1018(1).
Wu, S., Xiao, Y., Pacala, A., Badulescu, A., & Khan, S. (2024). Understanding Chinese farmers’ behavioral intentions to use alternative fuel machinery. Sustainability, 16(24), 11059.
Wulandari, S., & Ferry, Y. (2021). Strategies on technology management for coffee smallholder to promote smart farming. IOP Conference Series: Earth and Environmental Science, 759(1), 012057.
Xiang, P., & Guo, J. (2023). Understanding farmers’ intentions to adopt pest and disease green control techniques. Sustainability, 15(14), 10822.
Raykov, T. (2008). An introduction to applied multivariate analysis. Routledge.
Vennin, S. (2025). Opportunities and obstacles: How to ensure Vietnamese smallholder coffee farmers are ready for the EUDR. Sustainable Rural Development.