A gender-differentiated analysis of climate-smart agriculture adoption by smallholder farmers: application of the extended technology acceptance model

References

• Ainembabazi, J. H., & Mugisha, J. (2014). The role of farming experience on the adoption of agricultural technologies: Evidence from smallholder farmers in Uganda. The Journal of Development Studies, 50(5), 666–679. https://doi.org/10.1080/00220388.2013.874556
   Web of Science ®Google Scholar
• Alkhaldi, A., & Al-Sa’di, A. (2016). Guidelines integrating cultural theories with technology acceptance theories: A review. New Zealand Journal of Computer-Human Interaction, 1(2).  https://www.researchgate.net/profile/Ayman_Alkhaldi/publication/325012884
   Google Scholar
• Al-Mamary, Y. H., Al-Nashmi, M., Hassan, Y. A. G., & Shamsuddin, A. (2016). A critical review of models and theories in field of individual acceptance of technology. International Journal of Hybrid Information Technology, 9(6), 143–158. https://doi.org/10.14257/ijhit.2016.9.6.13
   Google Scholar
• Andersson, J. A., & D’Souza, S. (2014). From adoption claims to understanding farmers and contexts: A literature review of Conservation Agriculture (CA) adoption among smallholder farmers in southern Africa. Agriculture, Ecosystems & Environment, 187, 116–132.
   Web of Science ®Google Scholar
• Arslan, A., Asfaw, S., Cavatassi, R., Lipper, L., McCarthy, N., Kokwe, M., & Phiri, G. (2018). Diversification as part of a CSA strategy: The cases of Zambia and Malawi. In L. Lipper, N. McCarthy, D. Zilberman, S. Asfaw, & G. Branca (Eds.), Climate smart agriculture: Building resilience to climate change (pp. 527–562). Springer.
   Google Scholar
• Belay, A., Recha, J. W., Woldeamanuel, T., & Morton, J. F. (2017). Smallholder farmers’ adaptation to climate change and determinants of their adaptation decisions in the Central Rift Valley of Ethiopia. Agriculture & Food Security, 6(1), 1–13. https://doi.org/10.1186/s40066-017-0100-1
   Google Scholar
• Burton, R. J. F. (2004). Reconceptualising the ‘behavioural approach’ in agricultural studies: A socio-psychological perspective. Journal of Rural Studies, 20(3), 359–371. https://doi.org/10.1016/j.jrurstud.2003.12.001
   Web of Science ®Google Scholar
• Chismar, W. G., Wiley-Patton, S. (2003). Does the extended technology acceptance model apply to physicians. Paper Presented at the System Sciences, 2003. Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS’03). IEEE Computer Society.
   Google Scholar
• Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155
   PubMed Web of Science ®Google Scholar
• Creswell, W. J., & Plano Clark, L. V. (2011). Designing and conducting mixed methods research (2nd ed.). SAGE.
   Google Scholar
• DasGupta, R., & Shaw, R. (2017). Disaster risk reduction: A critical approach. In J. M. a. J. G. Ilan Kelman (Ed.), The Routledge handbook of disaster risk reduction including climate change adaptation. Routledge.
   Google Scholar
• Doss, C. R. (2001). Designing agricultural technology for African women farmers: Lessons from 25 years of experience. World Development, 29(12), 2075–2092. https://doi.org/10.1016/S0305-750X(01)00088-2
   Web of Science ®Google Scholar
• Dutot, V. (2015). Factors influencing near field communication (NFC) adoption: An extended TAM approach. The Journal of High Technology Management Research, 26(1), 45–57. https://doi.org/10.1016/j.hitech.2015.04.005
   Google Scholar
• Richard Eiser, J., Bostrom, A., Burton, I., Johnston, D. M., McClure, J., Paton, D., van der Pligt, J., & White, M. P. (2012). Risk interpretation and action: A conceptual framework for responses to natural hazards. International Journal of Disaster Risk Reduction, 1, 5–16. https://doi.org/10.1016/j.ijdrr.2012.05.002
   Web of Science ®Google Scholar
• FAO. (2010). Climate-smart’agriculture: Policies, practices and financing for food security, adaptation and mitigation. FAO.
   Google Scholar
• Gebrehiwot, T., & Van Der Veen, A. (2015). Farmers prone to drought risk: Why some farmers undertake farm-level risk-reduction measures while others not? Environmental Management, 55(3), 588–602. https://doi.org/10.1007/s00267-014-0415-7
   PubMed Web of Science ®Google Scholar
• Glover, D., Sumberg, J., & Andersson, J. A. (2016). The adoption problem; or why we still understand so little about technological change in African agriculture. Outlook on Agriculture, 45(1), 3–6. https://doi.org/10.5367/oa.2016.0235
   Web of Science ®Google Scholar
• Glover, D., Sumberg, J., Ton, G., Andersson, J., & Badstue, L. (2019). Rethinking technological change in smallholder agriculture. Outlook on Agriculture, 48(3), 169–180. https://doi.org/10.1177/0030727019864978
   Web of Science ®Google Scholar
• Gupta, N., Fischer, A. R., & Frewer, L. J. (2012). Socio-psychological determinants of public acceptance of technologies: A review. Public Understanding of Science, 21(7), 782–795. https://doi.org/10.1177/0963662510392485
   PubMed Web of Science ®Google Scholar
• Jamovi, T. P. (2019). jamovi (Version 1.0.7.0). https://www.jamovi.org
   Google Scholar
• Kelman, I., Gaillard, J. C., & Mercer, J. (2015). Climate change’s role in disaster risk reduction’s future: Beyond vulnerability and resilience. International Journal of Disaster Risk Science, 6(1), 21–27. https://doi.org/10.1007/s13753-015-0038-5
   Web of Science ®Google Scholar
• Khoza, S., Van Niekerk, D., & Nemakonde, L. D. (2019). Understanding gender dimensions of climate-smart agriculture adoption in disaster-prone smallholder farming communities in Malawi and Zambia. Disaster Prevention and Management: An International Journal, 28(5), 530–547. https://doi.org/10.1108/DPM-10-2018-0347
   Web of Science ®Google Scholar
• Lai, P. (2017). The literature review of technology adoption models and theories for the novelty technology. Journal of Information Systems and Technology Management, 14(1), 21–38. https://doi.org/10.4301/S1807-17752017000100002
   Google Scholar
• Lalani, B., Dorward, P., Holloway, G., & Wauters, E. (2016). Smallholder farmers’ motivations for using conservation agriculture and the roles of yield, labour and soil fertility in decision making. Agricultural Systems, 146, 80–90. https://doi.org/10.1016/j.agsy.2016.04.002
   Web of Science ®Google Scholar
• Martínez-García, C. G., Dorward, P., & Rehman, T. (2013). Factors influencing adoption of improved grassland management by small-scale dairy farmers in central Mexico and the implications for future research on smallholder adoption in developing countries. Livestock Science, 152(2–3), 228–238. https://doi.org/10.1016/j.livsci.2012.10.007
   Web of Science ®Google Scholar
• Meijer, S. S., Catacutan, D., Ajayi, O. C., Sileshi, G. W., & Nieuwenhuis, M. (2015). The role of knowledge, attitudes and perceptions in the uptake of agricultural and agroforestry innovations among smallholder farmers in sub-Saharan Africa. International Journal of Agricultural Sustainability, 13(1), 40–54. https://doi.org/10.1080/14735903.2014.912493
   Web of Science ®Google Scholar
• Murray, U., Gebremedhin, Z., Brychkova, G., & Spillane, C. (2016). Smallholder farmers and climate smart agriculture: Technology and labor-productivity constraints amongst women smallholders in Malawi. Gender, Technology and Development, 20(2), 117–148. https://doi.org/10.1177/0971852416640639
   PubMed Web of Science ®Google Scholar
• Ngigi, M. W., Müller, U., & Birner, R. (2018). Farmers’ intrinsic values for adopting climate-smart practices in Kenya: Empirical evidence from a means-end chain analysis. Climate and Development, 10(7), 614–624. https://doi.org/10.1080/17565529.2018.1442786
   Web of Science ®Google Scholar
• Price, J. C., & Leviston, Z. (2014). Predicting pro-environmental agricultural practices: The social, psychological and contextual influences on land management. Journal of Rural Studies, 34, 65–78. https://doi.org/10.1016/j.jrurstud.2013.10.001
   Web of Science ®Google Scholar
• Stokstad, E. (2017). New crop pest takes Africa at lightning speed. Science, 356(6337), 473–474. https://doi.org/10.1126/science.356.6337.473
   Web of Science ®Google Scholar
• Tarhini, A., Hone, K., & Liu, X. (2014). Measuring the moderating effect of gender and age on e-learning acceptance in England: A structural equation modeling approach for an extended technology acceptance model. Journal of Educational Computing Research, 51(2), 163–184. https://doi.org/10.2190/EC.51.2.b
   Web of Science ®Google Scholar
• Tashakkori, A., & Teddlie, C. (2010). Sage handbook of mixed methods in social & behavioral research. Sage.
   Google Scholar
• Teddlie, C., & Tashakkori, A. (2009). Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences. Sage.
   Google Scholar
• Van Hulst, F. J., & Posthumus, H. (2016). Understanding (non-) adoption of conservation agriculture in Kenya using the reasoned action approach. Land Use Policy, 56, 303–314. https://doi.org/10.1016/j.landusepol.2016.03.002
   Web of Science ®Google Scholar
• Wauters, E., Bielders, C., Poesen, J., Govers, G., & Mathijs, E. (2010). Adoption of soil conservation practices in Belgium: An examination of the theory of planned behaviour in the agri-environmental domain. Land Use Policy, 27(1), 86–94. https://doi.org/10.1016/j.landusepol.2009.02.009
   Web of Science ®Google Scholar
• Yazdanpanah, M., Hayati, D., Hochrainer-Stigler, S., & Zamani, G. H. (2014). Understanding farmers’ intention and behavior regarding water conservation in the Middle-East and North Africa: A case study in Iran. Journal of Environmental Management, 135, 63–72. https://doi.org/10.1016/j.jenvman.2014.01.016
   PubMed Web of Science ®Google Scholar
• Zeweld, W., Van Huylenbroeck, G., Tesfay, G., & Speelman, S. (2017). Smallholder farmers' behavioural intentions towards sustainable agricultural practices. Journal of Environmental Management, 187, 71–81. https://doi.org/10.1016/j.jenvman.2016.11.014
   PubMed Web of Science ®Google Scholar