Cold Chain Technology Adoption in Agriculture: Insights from the UTAUT Model on Vegetable Producers' Willingness

Josephine Joseph Mkunda

doi:10.4067/s0718-27242025000200079

Autores/as

Josephine Joseph Mkunda The Nelson Mandela African Institution of Science and Technology (NM-AIST), School of Business Studies and Humanities (BuSH), Department of Business Administration, Arusha, Tanzania.

DOI:

https://doi.org/10.4067/s0718-27242025000200079

Resumen

El modelo UTAUT ha sido aplicado extensamente en campos como la tecnología de la información y la educación, pero su aplicación en el sector agrícola, en lo que respecta a la adopción de la tecnología de cadena de frío entre los productores de hortalizas, sigue siendo escasa. A pesar de su potencial para reducir significativas pérdidas poscosecha y mejorar la seguridad alimentaria, la adopción de la CCT sigue siendo limitada en entornos agrícolas de bajos recursos. Utilizando datos recopilados de 87 productores de hortalizas y analizados mediante el Modelado de Ecuaciones Estructurales por Mínimos Cuadrados Parciales (PLS-SEM), el estudio examina la influencia de la expectativa de rendimiento, la expectativa de esfuerzo, la influencia social y las condiciones facilitadoras en la intención conductual. El modelo explicó el 58.9% de la varianza en la intención de adopción, siendo la expectativa de rendimiento (β = 0.491, p ≤ 0.000), la influencia social (β = 0.211, p ≤ 0.05) y las condiciones facilitadoras (β = 0.206, p ≤ 0.05) los predictores significativos. La expectativa de esfuerzo, aunque percibida positivamente, no mostró un efecto significativo, lo que sugiere que la facilidad de uso es secundaria a la utilidad percibida. Los hallazgos subrayan la importancia de los mensajes centrados en el rendimiento, la influencia de los pares y una infraestructura de apoyo para escalar las agrotecnologías. En conclusión, los productores de hortalizas indican una disposición a aceptar, adoptar y usar la tecnología; se recomienda tener en cuenta la capacitación sobre su operación. Esta investigación contribuye a la literatura sobre adopción de tecnología en la agricultura e informa políticas y prácticas destinadas a mejorar la resiliencia del sistema alimentario y alcanzar resultados de desarrollo sostenible.

Palabras clave:

Productores de hortalizas
Tecnología de cadena de frío
Teoría unificada de aceptación y uso de tecnología (UTAUT)
Intención de adopción
Tecnología modular de energía solar

Descargas

Los datos de descargas todavía no están disponibles.

Biografía del autor/a

Josephine Joseph Mkunda, The Nelson Mandela African Institution of Science and Technology (NM-AIST), School of Business Studies and Humanities (BuSH), Department of Business Administration, Arusha, Tanzania.

Josephine Joseph Mkunda is a Lecturer in the Department of Business Administration and Management in the School of Business Studies and Humanities (BuSH), at the Nelson Mandela African Institution of Science and Technology (NM-AIST) Arusha Tanzania. Dr. Mkunda’s main research interest covers areas of business strategies; business modelling, entrepreneurship and innovation management; international trade; analysis and management of agricultural value chains; Micro-and Macroeconomic analysis, Policies and Food Security as well as climate change and life cycle assessment in the agriculture sectors. With a multi-disciplinary academic background comprising BSc. in Food Science and Technology, Masters in Agricultural economics both from Sokoine University of Agriculture, Tanzania and PhD in International Marketing and Trade (Specialized in Business Modelling); Dr. Mkunda is highly interested in integrated research projects between science, technology, innovation (STI) and business management; climate change, and other issues that have an impact upon people at the grass roots level.

Citas

Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361–391. https://doi.org/10.1111/j.1540-5915.1999.tb01614.x

Bajunaied, K., Hussin, N., & Kamarudin, S. (2023). Behavioral intention to adopt FinTech services: An extension of unified theory of acceptance and use of technology. Journal of Open Innovation: Technology, Market, and Complexity, 9(1), 100010. https://doi.org/10.1016/j.joitmc.2023.100010

Becker, J. M., Klein, K., & Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: Guidelines for using reflective-formative type models. Long Range Planning, 45(5–6), 359–394. https://doi.org/10.1016/j.lrp.2012.10.001

Chikoye, D. M., Gupta, N. K., & Kandadi, K. R. (2018). Application of UTAUT in understanding the adoption of technologies for reducing post harvest maize losses in Zambia. International Journal of Agriculture and Environment Research, 4(3), 610-636. https://ijaer.in/2018files/ijaer_04__49.pdf

Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475-487. https://doi.org/10.1006/imms.1993.1022

de Sena Abrahão, R., Moriguchi, S. T., & Andrade, D. F. (2016). Intention of adoption of mobile payment: An analysis in the light of the Unified Theory of Acceptance and Use of Technology (UTAUT). RAI Revista de Administração e Inovação, 13(3), 221–230. https://doi.org/10.1016/j.rai.2016.06.003

Ekka, R., & Mjawa, B. (2020). Case study growth of Tanzania’s horticulture sector: Role of TAHA in reducing food loss. Climatelinks. Recuperado el 15 de abril de 2024, de https://www.climatelinks.org/resources/case-study-growth-tanzanias-horticulture-sector-role-taha-reducing-food-loss

Eweoya, I., Okuboyejo, S. R., Odetunmibi, O. A., & Odusote, B. O. (2021). An empirical investigation of acceptance, adoption and the use of E-agriculture in Nigeria. Heliyon, 7(6), e07588. https://doi.org/10.1016/j.heliyon.2021.e07588

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison-Wesley. Recuperado el 23 de enero de 2024, de https://people.umass.edu/aizen/f&a1975.html

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM) (3.ª ed.). SAGE Publications.

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1–2), 1–12. https://doi.org/10.1016/j.lrp.2013.01.001

Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115–135. https://doi.org/10.1007/s11747-014-0403-8

Henseler, J., Ringle, M. C., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. En Advances in International Marketing (pp. 277-319). Emerald JAI Press. http://dx.doi.org/10.1108/S1474-7979(2009)0000020014

Kline, R. B. (2011). Principles and practice of structural equation modeling (4.ª ed.). The Guilford Press.

Ky, S. S. (2025). Empowering Sub-Saharan farmers: The transformative effect of mobile money in agriculture. Journal of Rural Studies, 117, 103637. https://doi.org/10.1016/j.jrurstud.2025.103637

Lai, P. C. (2017). The literature review of technology adoption models and theories for the novelty technology. Journal of Information System and Technology Management, 14(1), 21-38. https://doi.org/10.4301/S1807-17752017000100002

Lescevica, M., Ginters, E., & Mazza, R. (2013). Unified Theory of Acceptance and Use of Technology for market analysis of FP7 CHOReOs products. Procedia Computer Science, 26, 51-68. https://doi.org/10.1016/j.procs.2013.12.007

Liu, C. H., Chen, Y. T., Kittikowit, S., Hongsuchon, T., & Chen, Y. J. (2022). Using Unified Theory of Acceptance and Use of Technology to evaluate the impact of a mobile payment app on the shopping intention and usage behavior of middle-aged customers. Frontiers in Psychology, 13, 830842. https://doi.org/10.3389/fpsyg.2022.830842

Makule, E., Dimoso, N., & Tassou, S. A. (2022). Precooling and cold storage methods for fruits and vegetables in Sub-Saharan Africa—A review. Horticulturae, 8(9), 776. https://doi.org/10.3390/horticulturae8090776

Match Maker Associates. (2017). Horticulture study: Mapping of production of fruits and vegetables in Tanzania. Embassy of the Kingdom of the Netherlands.

Mwalupaso, G., Baiyegunhi, L. J. S., & Zulu, M. C. (2021). Determinants of mobile money adoption among smallholder farmers using an extended UTAUT2 model. Cogent Business & Management, 8(1), 1892927. https://doi.org/10.1080/23311975.2021.1892927

Nkandu, P., & Phiri, J. (2022). Assessing the effect of ICTs on agriculture productivity based on the UTAUT model in developing countries. Case study of Southern Province in Zambia. Open Journal of Business and Management, 10, 3436-3454. https://doi.org/10.4236/ojbm.2022.106169

Ringle, C. M., Wende, S., & Becker, J. M. (2022). SmartPLS 4. SmartPLS GmbH. http://www.smartpls.com

Rogers, E. M. (1995). Diffusion of innovations (4.ª ed.). Free Press.

Salsabil, A. P., Pratama, A., & Wulansari, A. (2022). Behavior analysis on PLN mobile users using UTAUT method. Jurnal Riset Informatika, 5(1), 155-164. https://doi.org/10.34288/jri.v5i1.486

Saparudin, M., Rahayu, A., Hurriyati, R., Sultan, M. A., & Ramdan, A. M. (2020). Consumers’ continuance intention use of mobile banking in Jakarta: Extending UTAUT models with trust. Proceedings of 2020 International Conference on Information Management and Technology, ICIMTech 2020, 50–54. https://doi.org/10.1109/ICIMTECH50083.2020.9211188

Sharma, A., Mohan, A., Johri, A., & Mohammad, A. (2024). Determinants of fintech adoption in agrarian economy: Study of UTAUT extension model in reference to developing economies. Journal of Open Innovation: Technology, Market, and Complexity, 10(2), 100273. https://doi.org/10.1016/j.joitmc.2024.100273

United Republic of Tanzania. (2021). National sample census of agriculture 2019/20. National report. National Bureau of Statistics. https://www.nbs.go.tz/nbs/takwimu/Agric/Tanzania_Key_Findings_Report_2019-20_ASC.pdf

Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481. https://doi.org/10.1111/j.1540-5915.1996.tb01822.x

Venkatesh, V., & Davis, F. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. [suspicious link removed]

Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139. https://doi.org/10.2307/3250981

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

Venkatesh, V., Thong, J. Y. L., Chan, Y., Hu, P. J. H., & Brown, S. A. (2011). Extending the two-stage information systems continuance model: Incorporating UTAUT predictors and the role of context. Information Systems Journal, 21(6), 527-555. https://doi.org/10.1111/j.1365-2575.2011.00373.x

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412

Xie, Q., Zhu, Y., Liu, Y., & Wang, Y. (2022). Applying UTAUT model to understand farmers’ adoption of ecological agriculture technologies in China. Sustainability, 14(12), 7653. https://doi.org/10.3390/su14137653