Analysis of IoT Adoption Intention Among Horticulture Farmers: an Integration of the UTAUT Model and Trust in Technology

Authors

DOI:

https://doi.org/10.32493/jiup.v11i2.58183

Keywords:

Internet of Things (IoT), UTAUT, Perceived Trust in Technology, Behavioral Intention, Horticulture Farmers

Abstract

IoT-based tools can support more precise decisions in horticulture, but their use among Indonesian farmers is still limited. We investigated adoption intention and use behavior among 100 horticulture farmers in Bogor City using an extended UTAUT model that combines Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, and Perceived Trust in Technology. Survey responses were analyzed with PLS-SEM in SmartPLS 4. Effort Expectancy was the only significant predictor of Behavioral Intention (β = 0.371), and Behavioral Intention was significantly associated with Use Behavior (β = 0.515). Performance Expectancy, Social Influence, Facilitating Conditions, and Perceived Trust in Technology had no significant direct effects. The model accounted for 18.7% of the variance in Behavioral Intention and 26.2% in Use Behavior. For farmers at this early stage of IoT exposure, ease of use appears to matter more than expected performance gains or available support. Programs intended to broaden adoption should therefore emphasize simple interfaces, practical demonstrations, repeated training, and opportunities for farmers to learn by using the technology.

References

[1] H. Z. Sinaga and A. A. Waskita, “Optimisasi Desain Jaringan IoT untuk Pelacakan Produk di Rantai Pasok Pertanian: Tinjauan Literatur Sistematis,” PROKASDADIK: Prosiding Kecerdasan Artifisial, Sains Data, dan Pendidikan Masa Depan, vol. 3, no. 1, pp. 13–21, 2025.

[2] N. Larasati, A. A. Putri, A. S. Soemodinoto, N. Alyssa, and O. S. Shoofiyani, “Unified theory of acceptance and use of technology model to understand farmer’s readiness: Implementation of precision agriculture based on digital IoT monitoring apps in West Java, Indonesia,” Asian Journal of Agriculture and Rural Development, vol. 14, no. 4, pp. 176–183, Oct. 2024, doi: https://doi.org/10.55493/5005.v14i4.5258.

[3] K. Sharma and S. K. Shivandu, “Integrating artificial intelligence and Internet of Things (IoT) for enhanced crop monitoring and management in precision agriculture,” Sensors International, vol. 5, 2024, doi: https://doi.org/10.1016/j.sintl.2024.100292.

[4] S. N. Chang, C. B. Chu, S. Wang, C. Hsu, and T. Y. Lee, “Construction of Intelligent Large and Small Scale Demonstration Irrigation Field and Information System Platform,” Taiwan Water Conservancy, vol. 72, no. 4, pp. 1–19, 2024, doi: https://doi.org/10.6937/TWC.202412_72(4).0001.

[5] J. S. Liu, C. C. Tung, F. L. Ko, and P. H. Wang, “Investigations on the Application of Upgrading Irrigation Management with Internet of Things Technology,” Taiwan Water Conservancy, vol. 70, no. 3, pp. 40–52, 2022, doi: https://doi.org/10.6937/TWC.202209_70(3).0004.

[6] M. K. R. Villalta, M. C. Chirinos, and R. R. S. Torres, “Development of an IoT System Based on LoRaWAN to Monitor the Distribution and Quality of Irrigation Water in Rural Areas of Arequipa, Peru,” SSRG International Journal of Electrical and Electronics Engineering, vol. 11, no. 10, pp. 223–230, 2024, doi: https://doi.org/10.14445/23488379/IJEEE-V11I10P123.

[7] L. Sun et al., “Intelligent agriculture technology based on internet of things,” Intelligent Automation and Soft Computing, vol. 32, no. 1, pp. 429–439, 2022, doi: https://doi.org/10.32604/iasc.2022.021526.

[8] K. M. Hosny, W. M. El-Hady, and F. M. Samy, “Technologies, Protocols, and applications of Internet of Things in greenhouse Farming: A survey of recent advances,” Information Processing in Agriculture, vol. 12, no. 1, pp. 91–111, Mar. 2025, doi: https://doi.org/10.1016/j.inpa.2024.04.002.

[9] S. Mansoor, S. Iqbal, S. M. Popescu, S. L. Kim, Y. S. Chung, and J. H. Baek, “Integration of smart sensors and IOT in precision agriculture: trends, challenges and future prospectives,” Frontiers in Plant Science, vol. 16, no. May, pp. 1–21, 2025, doi: https://doi.org/10.3389/fpls.2025.1587869.

[10] M. N. Mowla, N. Mowla, A. F. M. S. Shah, K. M. Rabie, and T. Shongwe, “Internet of Things and Wireless Sensor Networks for Smart Agriculture Applications: A Survey,” IEEE Access, vol. 11, no. 12, pp. 145813–145852, 2023, doi: https://doi.org/10.1109/ACCESS.2023.3346299.

[11] L. Bao et al., “Intelligent drip fertigation increases water and nutrient use efficiency of watermelon in greenhouse without compromising the yield,” Agricultural Water Management, vol. 282, 2023, doi: https://doi.org/10.1016/j.agwat.2023.108278.

[12] J. Liu, H. A. O. Wu, and I. Riaz, “Advanced Technologies for Smart Fertilizer Management in Agriculture : A Review,” IEEE Access, vol. 13, no. August, pp. 139766–139790, 2025, doi: https://doi.org/10.1109/ACCESS.2025.3594361.

[13] Z. Xu, A. E. Adeyemi, E. Catalan, S. Ma, A. Kogut, and C. Guzman, “A scoping review on technology applications in agricultural extension,” PLOS ONE, vol. 18, no. 11, 2023, doi: https://doi.org/10.1371/journal.pone.0292877.

[14] Badan Pusat Statistik Jawa Barat, Buklet Hasil Pencacahan Lengkap Sensus Pertanian 2023. 2023.

[15] L. Li, X. Min, J. Guo, and F. Wu, “The influence mechanism analysis on the farmers’ intention to adopt Internet of Things based on UTAUT-TOE model,” Scientific Reports, vol. 14, no. 1, Dec. 2024, doi: https://doi.org/10.1038/s41598-024-65415-4.

[16] Y. Shi, A. B. Siddik, M. Masukujjaman, G. Zheng, M. Hamayun, and A. M. Ibrahim, “The Antecedents of Willingness to Adopt and Pay for the IoT in the Agricultural Industry: An Application of the UTAUT 2 Theory,” Sustainability, vol. 14, no. 11, Jun. 2022, doi: https://doi.org/10.3390/su14116640.

[17] R. G. Asir and H. L. Manohar, “Variations on Internet of Things adoption factors between India and the USA,” South African Journal of Business Management, vol. 54, no. 1, pp. 1–13, 2023, doi: https://doi.org/10.4102/sajbm.v54i1.3810.

[18] C. Indrayanto, Farikhin, and T. Prahasto, “A Combination Model Of Utaut, Hot, And Contextual Variables For Analyzing Farmers’ Behavior Towards Internet Of Things (IoT)-Based Agricultural Technology,” in ICSINTESA 2024 - 2024 4th International Conference of Science and Information Technology in Smart Administration: The Collaboration of Smart Technology and Good Governance for Sustainable Development Goals, Institute of Electrical and Electronics Engineers Inc., 2024, pp. 77–82. doi: https://doi.org/10.1109/ICSINTESA62455.2024.10748166.

[19] G. Scur, A. V. D. da Silva, C. A. Mattos, and R. F. Gonçalves, “Analysis of IoT adoption for vegetable crop cultivation: Multiple case studies,” Technological Forecasting and Social Change, vol. 191, Jun. 2023, doi: https://doi.org/10.1016/j.techfore.2023.122452.

[20] A. M. A. Zamil, H. M. U. Javed, and S. Ali, “Internet of things platforms adoption in agriculture: comparative theoretical models,” International Journal of Retail and Distribution Management, vol. 52, no. 9, pp. 965–981, Nov. 2024, doi: https://doi.org/10.1108/IJRDM-10-2022-0420.

[21] A. Piancharoenwong and Y. F. Badir, “IoT smart farming adoption intention under climate change: The gain and loss perspective,” Technological Forecasting and Social Change, vol. 200, Mar. 2024, doi: https://doi.org/10.1016/j.techfore.2023.123192.

[22] L. Kuen, D. Westmattelmann, M. Bruckes, and G. Schewe, “Who earns trust in online environments? A meta-analysis of trust in technology and trust in provider for technology acceptance,” Electronic Markets, vol. 33, no. 1, Dec. 2023, doi: https://doi.org/10.1007/s12525-023-00672-1.

[23] M. L. Yeo and C. M. Keske, “From profitability to trust: factors shaping digital agriculture adoption,” Frontiers in Sustainable Food Systems, vol. 8, 2024, doi: https://doi.org/10.3389/fsufs.2024.1456991.

[24] D. C. Toader, C. M. Rădulescu, and C. Toader, “Investigating the Adoption of Blockchain Technology in Agri-Food Supply Chains: Analysis of an Extended UTAUT Model,” Agriculture, vol. 14, no. 4, Apr. 2024, doi: https://doi.org/10.3390/agriculture14040614.

[25] T. Pienwisetkaew, S. Wongsaichia, B. Pinyosap, S. Prasertsil, K. Poonsakpaisarn, and C. Ketkaew, “The Behavioral Intention to Adopt Circular Economy-Based Digital Technology for Agricultural Waste Valorization,” Foods, vol. 12, no. 12, Jun. 2023, doi: https://doi.org/10.3390/foods12122341.

[26] S. Banluesapy, M. Ketcham, and M. Rattanasiriwongwut, “Integrating Theories into a Model for the Acceptance of Internet of Things Technology for Developing Smart Farm Platforms: A Study of Readiness in the Agricultural Industry,” Global Journal of Flexible Systems Management. Springer, 2026. doi: https://doi.org/10.1007/s40171-025-00479-3.

[27] M. A. B. Rodzoan and A. Shah, “Smart Farming: Integrating IoT and UAV Technologies for Precision Agriculture through the Lens of Technology Acceptance and the UTAUT2 Model,” Pakistan Journal of Life and Social Sciences, vol. 22, no. 2. Elite Scientific Publications, pp. 6218–6233, 2024. doi: https://doi.org/10.57239/PJLSS-2024-22.2.00468.

[28] J. E. Kennedy, “Planning Falsifiable Confirmatory Research,” Psychological Methods, vol. 31, no. 4, pp. 627–642, 2026, doi: https://doi.org/10.1037/met0000639.

[29] Badan Pusat Statistik Kota Bogor, Kota Bogor Dalam Angka 2025, vol. 25. 2025.

[30] J. F. Hair, G. T. M. Hult, C. M. Ringle, and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Third Edition, 3rd ed. SAGE Publications, 2022, doi: https://doi.org/10.1007/978-3-030-80519-7

[31] J. F. Hair and A. Alamer, “Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example,” Research Methods in Applied Linguistics, vol. 1, no. 3, Dec. 2022, doi: https://doi.org/10.1016/j.rmal.2022.100027.

Downloads

Published

2025-06-30