How to cite this paper
Jaroenwanit, P., Phuensane, P., Sekhari, A & Gay, C. (2023). Risk management in the adoption of smart farming technologies by rural farmers.Uncertain Supply Chain Management, 11(2), 533-546.
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Abd-Elaty, I., Kushwaha, N. L., Grismer, M. E., Elbeltagi, A., & Kuriqi, A. (2022). Cost-effective management measures for coastal aquifers affected by saltwater intrusion and climate change. Science of The Total Environment, 836, 155656.
Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS quarterly, 24(4), 665-694.
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Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information systems research, 9(2), 204-215.
Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies?. Decision sciences, 30(2), 361-391.
Allen, A. W., Cochran, F. L., Goldenbaum, G. C., & Liewer, P. C. (1977). Experimental and Numerical Studies of Magnetohydrodynamic Stability Properties of a Rectangular-Cross-Section Finite-β Toroidal Plasma. Physical Review Letters, 39(7), 404.
Amade, N., Oliveira, T., & Painho, M. (2020). Understanding the determinants of GIT post-adoption: perspectives from Mozambican institutions. Heliyon, 6(5), e03879.
Amoako-Gyampah, K., & Salam, A. F. (2004). An extension of the technology acceptance model in an ERP implementation environment. Information & management, 41(6), 731-745.
Amondo, E., & Simtowe, F. (2018). Technology Innovations, Productivity and Production Risk Effects of Adopting Drought Tolerant Maize varieties in Rural Zambia (No. 2058-2018-5357).
Aryal, J. P., Jat, M. L., Sapkota, T. B., Khatri-Chhetri, A., Kassie, M., & Maharjan, S. (2018). Adoption of multiple climate-smart agricultural practices in the Gangetic plains of Bihar, India. International Journal of Climate Change Strategies and Management, 10(3).
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Azam, M. S., & Shaheen, M. (2018). Decisional factors driving farmers to adopt organic farming in India: a cross-sectional study. International Journal of Social Economics, 46(4), 562-580.
Balafoutis, A. T., Evert, F. K. V., & Fountas, S. (2020). Smart farming technology trends: economic and environmental effects, labor impact, and adoption readiness. Agronomy, 10(5), 743.
Briggs, R. O., De Vreede, G. J., & Nunamaker Jr, J. F. (2003). Collaboration engineering with ThinkLets to pursue sustained success with group support systems. Journal of management information systems, 19(4), 31-64.
Caffaro, F., & Cavallo, E. (2019). The effects of individual variables, farming system characteristics and perceived barriers on actual use of smart farming technologies: Evidence from the Piedmont region, northwestern Italy. Agriculture, 9(5), 111.
Chau, P. Y. (1996). An empirical assessment of a modified technology acceptance model. Journal of management information systems, 13(2), 185-204.
Chau, P. Y. (1996). An empirical investigation on factors affecting the acceptance of CASE by systems developers. Information & Management, 30(6), 269-280.
Chau, P. Y., & Hu, P. J. H. (2002). Investigating healthcare professionals’ decisions to accept telemedicine technology: an empirical test of competing theories. Information & management, 39(4), 297-311.
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Clark, B., Panzone, L. A., Stewart, G. B., Kyriazakis, I., Niemi, J. K., Latvala, T., & Frewer, L. J. (2019). Consumer attitudes towards production diseases in intensive production systems. PloS one, 14(1), e0210432.
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Deng, X., Doll, W. J., Hendrickson, A. R., & Scazzero, J. A. (2005). A multi-group analysis of structural invariance: an illustration using the technology acceptance model. Information & Management, 42(5), 745-759.
Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task–technology fit constructs. Information & management, 36(1), 9-21.
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(7), e07588.
Filippini, R., Marescotti, M. E., Demartini, E., & Gaviglio, A. (2020). Social networks as drivers for technology adoption: a study from a rural mountain area in Italy. Sustainability, 12(22), 9392.
Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: an extended technology acceptance perspective. Information & management, 39(8), 705-719.
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Khandker, V., & Thakurata, I. (2018). Factors encouraging complete adoption of agricultural technologies: the case of hybrid rice cultivation in India. Journal of Agribusiness in Developing and Emerging Economies, 8(2), 270-287.
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Amoako-Gyampah, K., & Salam, A. F. (2004). An extension of the technology acceptance model in an ERP implementation environment. Information & management, 41(6), 731-745.
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Aryal, J. P., Jat, M. L., Sapkota, T. B., Khatri-Chhetri, A., Kassie, M., & Maharjan, S. (2018). Adoption of multiple climate-smart agricultural practices in the Gangetic plains of Bihar, India. International Journal of Climate Change Strategies and Management, 10(3).
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Azam, M. S., & Shaheen, M. (2018). Decisional factors driving farmers to adopt organic farming in India: a cross-sectional study. International Journal of Social Economics, 46(4), 562-580.
Balafoutis, A. T., Evert, F. K. V., & Fountas, S. (2020). Smart farming technology trends: economic and environmental effects, labor impact, and adoption readiness. Agronomy, 10(5), 743.
Briggs, R. O., De Vreede, G. J., & Nunamaker Jr, J. F. (2003). Collaboration engineering with ThinkLets to pursue sustained success with group support systems. Journal of management information systems, 19(4), 31-64.
Caffaro, F., & Cavallo, E. (2019). The effects of individual variables, farming system characteristics and perceived barriers on actual use of smart farming technologies: Evidence from the Piedmont region, northwestern Italy. Agriculture, 9(5), 111.
Chau, P. Y. (1996). An empirical assessment of a modified technology acceptance model. Journal of management information systems, 13(2), 185-204.
Chau, P. Y. (1996). An empirical investigation on factors affecting the acceptance of CASE by systems developers. Information & Management, 30(6), 269-280.
Chau, P. Y., & Hu, P. J. H. (2002). Investigating healthcare professionals’ decisions to accept telemedicine technology: an empirical test of competing theories. Information & management, 39(4), 297-311.
Chin, W. W., & Gopal, A. (1995). Adoption intention in GSS: Relative importance of beliefs. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 26(2-3), 42-64.
Clark, B., Panzone, L. A., Stewart, G. B., Kyriazakis, I., Niemi, J. K., Latvala, T., & Frewer, L. J. (2019). Consumer attitudes towards production diseases in intensive production systems. PloS one, 14(1), e0210432.
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation, Massachusetts Institute of Technology).
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3), 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.
Deng, X., Doll, W. J., Hendrickson, A. R., & Scazzero, J. A. (2005). A multi-group analysis of structural invariance: an illustration using the technology acceptance model. Information & Management, 42(5), 745-759.
Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task–technology fit constructs. Information & management, 36(1), 9-21.
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(7), e07588.
Filippini, R., Marescotti, M. E., Demartini, E., & Gaviglio, A. (2020). Social networks as drivers for technology adoption: a study from a rural mountain area in Italy. Sustainability, 12(22), 9392.
Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: an extended technology acceptance perspective. Information & management, 39(8), 705-719.
Godoe, P., & Johansen, T. (2012). Understanding adoption of new technologies: Technology readiness and technology acceptance as an integrated concept. Journal of European psychology students, 3(1).
Goodhue, D. L. (1995). Understanding user evaluations of information systems. Management science, 41(12), 1827-1844.
Goodhue, D. L. (1998). Development and measurement validity of a task‐technology fit instrument for user evaluations of information system. Decision sciences, 29(1), 105-138.
Gurkan, H., Shelia, V., Bayraktar, N., Yildirim, Y. E., Yesilekin, N., Gunduz, A., ... & Hoogenboom, G. (2020). Estimating the potential impact of climate change on sunflower yield in the Konya province of Turkey. The Journal of Agricultural Science, 158(10), 806-818.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multirative data analysis: A global perspective.
Hofstede, G. (1984). Culture's consequences: International differences in work-related values (Vol. 5). sage.
Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of management information systems, 16(2), 91-112.
Igbaria, M., Guimaraes, T., & Davis, G. B. (1995). Testing the determinants of microcomputer usage via a structural equation model. Journal of management information systems, 11(4), 87-114.
Igbaria, M., Parasuraman, S., & Baroudi, J. J. (1996). A motivational model of microcomputer usage. Journal of management information systems, 13(1), 127-143.
Joa, C. Y., & Magsamen-Conrad, K. (2022). Social influence and UTAUT in predicting digital immigrants’ technology use. Behaviour & Information Technology, 41(8), 1620-1638.
Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183–213.
Kernecker, M., Knierim, A., Wurbs, A., Kraus, T., & Borges, F. (2020). Experience versus expectation: Farmers’ perceptions of smart farming technologies for cropping systems across Europe. Precision Agriculture, 21(1), 34-50.
Khandker, V., & Thakurata, I. (2018). Factors encouraging complete adoption of agricultural technologies: the case of hybrid rice cultivation in India. Journal of Agribusiness in Developing and Emerging Economies, 8(2), 270-287.
King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & management, 43(6), 740-755.
Klerkx, L., Jakku, E., & Labarthe, P. (2019). A review of social science on digital agriculture, smart farming and agriculture 4.0: New contributions and a future research agenda. NJAS-Wageningen Journal of Life Sciences, 90, 100315.
Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information systems research, 13(2), 205-223.
Koutsos, T., & Menexes, G. (2019). Economic, agronomic, and environmental benefits from the adoption of precision agriculture technologies: a systematic review. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 10(1), 40-56.
Lee, J., Hong, N. L., & Ling, N. L. (2001). An analysis of students' preparation for the virtual learning environment. The internet and higher education, 4(3-4), 231-242.
Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & management, 40(3), 191-204.
Lewis, W., Agarwal, R., & Sambamurthy, V. (2003). Sources of influence on beliefs about information technology use: An empirical study of knowledge workers. MIS quarterly, 27(4), 657-678.
Lippert, S. K., & Michael Swiercz, P. (2005). Human resource information systems (HRIS) and technology trust. Journal of information science, 31(5), 340-353.
Mango, N., Makate, C., Tamene, L., Mponela, P., & Ndengu, G. (2018). Adoption of small-scale irrigation farming as a climate-smart agriculture practice and its influence on household income in the Chinyanja Triangle, Southern Africa. Land, 7(2), 49.
Mathieson, K. (1991). Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information systems research, 2(3), 173-191.
Michels, M., von Hobe, C. F., Weller von Ahlefeld, P. J., & Musshoff, O. (2021). The adoption of drones in German agriculture: a structural equation model. Precision Agriculture, 22(6), 1728-1748.
Molina-Maturano, J., Verhulst, N., Tur-Cardona, J., Güereña, D. T., Gardeazábal-Monsalve, A., Govaerts, B., & Speelman, S. (2021). Understanding smallholder farmers’ intention to adopt agricultural apps: the role of mastery approach and innovation hubs in Mexico. Agronomy, 11(2), 194.
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