Assessing The Capacities of Rural Youth to Adopt Smart Agriculture Technologies: A Case Study of Kanakantapa Farming Block in Chongwe District, Zambia
Authors
Master’s Student at Mulungushi University, School of Social Sciences, Department of Social Development Studies, Kabwe (Zambia)
Mulungushi University, School of Social Sciences, Department of Social Development Studies, Kabwe (Zambia)
Article Information
DOI: 10.47772/IJRISS.2026.100600913
Subject Category: Sociology
Volume/Issue: 10/6 | Page No: 12996-13016
Publication Timeline
Submitted: 2026-06-18
Accepted: 2026-06-24
Published: 2026-07-08
Abstract
Background: The adoption of smart agriculture technologies has increasingly emerged as a critical strategy for enhancing agricultural productivity, climate resilience, and rural livelihoods among young farmers in Zambia. However, despite growing policy attention, the capacities of rural youth to effectively adopt these technologies remain inadequately understood, particularly in farming blocks characterised by limited institutional support and socio-economic constraints.
Aim: To assess the capacities of rural youth to adopt smart agriculture technologies in Kanakantapa Farming Block of Chongwe District, Zambia.
Methods: Guided by Human Capital Theory, Diffusion of Innovations Theory, Social Capital Theory, and Agricultural Innovation Systems Theory, the study employed a case study research design, informed by the concurrent mixed-method approach. The study employed simple random sampling technique to select 120 youth farmers aged between 18 and 35 years from Kanakantapa Farming Block while the purposive non-random sampling method was used to select the five (5) key informants drawn from agricultural extension services and farmer cooperative leaders. Quantitative data were collected using structured questionnaires while qualitative data were collected through key informant interviews. Quantitative data was analysed using descriptive statistics, Chi-square tests, Pearson correlation analysis, and binary logistic regression in SPSS version 27, while qualitative data from key informants were analysed thematically.
Findings: The study established that 67.5% of respondents were aware of smart agriculture technologies, while 80.8% had access to ICT and digital agricultural platforms. However, major institutional and socio-economic barriers constrained adoption. Approximately 61.7% had not received formal training in smart agriculture, 57.5% lacked extension support, and 61% lacked access to agricultural finance. Inferential analysis indicated statistically significant relationships between smart agriculture adoption and educational attainment (χ2 = 14.82, p < 0.01), extension access (r = 0.61, p < 0.001), ICT access (r = 0.54, p < 0.001), and agricultural training (OR =3.71, p < 0.001). The study further established that adopters of smart agriculture technologies reported increased crop yields, improved income levels, and greater livelihood diversification. Nevertheless, structural barriers including financial exclusion, high input costs, weak extension systems, poor ICT infrastructure, and gender inequalities continued to undermine wider adoption among rural youth.
Conclusion: The study concludes that although rural youth in Kanakantapa possess considerable potential to participate in smart agriculture technologies, their capacities are undermined by inadequate institutional support, limited financing opportunities, insufficient training, and restricted access to modern agricultural inputs. The study recommends strengthening youth-targeted agricultural financing schemes, expanding extension and training services, improving ICT infrastructure, and enhancing policy implementation frameworks to support inclusive and sustainable smart agriculture adoption among rural youth in Zambia.
Keywords
Downloads
References
1. African Development Bank [AfDB] (2022). African Economic Outlook 2022: Supporting Climate Resilience and a Just Energy Transition in Africa. Abidjan: African Development Bank. [Google Scholar] [Crossref]
2. Aker, J.C., Ghosh, I. and Burrell, J. (2023). ‘The promise of digital agriculture in developing countries’. World Development, 165, pp. 1-15. [Google Scholar] [Crossref]
3. Arslan, A., Belotti, F., and Lipper, L. (2022). ‘Climate-smart agriculture: Assessing the adaptation implications in Zambia’. Journal of Agricultural Economics, 73(1), pp. 201-223. [Google Scholar] [Crossref]
4. Becker, G.S. (1964) Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education. New York: Columbia University Press. [Google Scholar] [Crossref]
5. Best, J. W. and Kahn, J. V. (2003). Research in Education. Boston: Library of Congress Cataloguing-in-Publication data. [Google Scholar] [Crossref]
6. Birks, M. and Mills, J. (2011). Grounded theory: A practical guide. London: Sage. [Google Scholar] [Crossref]
7. Braun, V. and Clarke, V. (2006). Using Thematic Analysis in Psychology. Qualitative Research in Psychology, 3, pp. 77-101. [Google Scholar] [Crossref]
8. Bryman, A. (2012). Social Research Methods, 4th edition. Oxford: Oxford University Press. [Google Scholar] [Crossref]
9. Bryman, A. (2016). Social Research Methods, 5th edition. Oxford: Oxford University Press. [Google Scholar] [Crossref]
10. Chamberlin, J., Sitko, N. J., and Hichaambwa, M. (2023). ‘Youth employment and rural transformation in Zambia’s agricultural sector’. World Development Perspectives, 31, pp. 100512. [Google Scholar] [Crossref]
11. Consultative Group on International Agricultural Research [CGIAR] (2023). Climate-Smart Agriculture in Africa: Scaling Resilient Agricultural Systems. Montpellier: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). [Google Scholar] [Crossref]
12. Creswell, J.W. and Plano Clark, V.L. (2018). Designing and conducting mixed methods research, 3rd edition. Thousand Oaks, CA: SAGE. [Google Scholar] [Crossref]
13. Food and Agriculture Organization [FAO] (2021). Youth Engagement in Climate-Smart Agriculture in Malawi. Rome: FAO. [Google Scholar] [Crossref]
14. Food and Agriculture Organization [FAO] (2022). The Future of Food and Agriculture: Drivers and Triggers for Transformation. Rome: FAO. [Google Scholar] [Crossref]
15. Food and Agriculture Organization [FAO] (2023). The State of Food and Agriculture 2023: Revealing the True Cost of Food to Transform Agrifood Systems. Rome: FAO. [Google Scholar] [Crossref]
16. Geza, W., Ngidi, M., Ojo, T. and Mabhaudhi, T. (2021). ‘The dynamics of youth participation in agriculture in Sub-Saharan Africa’. Sustainability, 13(18), 9879. [Google Scholar] [Crossref]
17. Guest, G., Namey, E. and Mitchell, M. (2020). Collecting qualitative data: A field manual for applied research. Thousand Oaks, CA: Sage. [Google Scholar] [Crossref]
18. International Fund for Agricultural Development [IFAD] (2022). Rural Development Report 2022: Transforming Food Systems for Rural Prosperity. Rome: IFAD. [Google Scholar] [Crossref]
19. International Fund for Agricultural Development [IFAD] (2023). Creating Opportunities for Rural Youth through Digital Agriculture. Rome: IFAD. [Google Scholar] [Crossref]
20. Israel, M., and Hay, I. (2006). Research Ethics for Social Scientists: Between Ethical Conduct and Regulatory Compliance. London: Sage. [Google Scholar] [Crossref]
21. Klerkx, L., Jakku, E. and Labarthe, P. (2022). ‘A review of social science on digital agriculture’. Agricultural Systems, 190, 103-118. [Google Scholar] [Crossref]
22. Koomson, I., Villano, R.A. and Hadley, D. (2020). ‘Access to credit and farm technology adoption in rural Africa’. Journal of Rural Studies, 76, pp. 1-13. [Google Scholar] [Crossref]
23. Kothari, C.R. (2020). Research methodology: Methods and techniques, 4th edition. New Delhi: New Age International. [Google Scholar] [Crossref]
24. Makokha, S., Kibwika, P. and Okry, F. (2020). ‘Youth engagement in climate-smart agriculture in East Africa’. African Journal of Rural Development, 5(2), pp. 213-229. [Google Scholar] [Crossref]
25. Mhlanga, B., Ndhlovu, K. and Moyo, S. (2021) ‘Land tenure systems and youth participation in agriculture in Southern Africa’, Land Use Policy, 109, 105635. [Google Scholar] [Crossref]
26. Morse, J. M. (1991). “Strategies for sampling.” In Qualitative Nursing Research: A Contemporary Dialogue (JM Morse, Ed.) Newbury Park, CA: Sage, pp. 127-145. [Google Scholar] [Crossref]
27. Mutambara, J., Crick, F. and Hove, L. (2020). ‘Agricultural commercialisation and rural incomes in developing economies’. Development Southern Africa, 37(6), pp. 1021-1038. [Google Scholar] [Crossref]
28. Mutengwa, C.S., Mhlanga, N. and Ngwenya, B. (2023). ‘Financial barriers affecting adoption of climate-smart agriculture among smallholder farmers’. Climate and Development, 15(3), pp. 244-256. [Google Scholar] [Crossref]
29. Ngoma, H., Mulenga, B. P., and Jayne, T. S. (2021) ‘Climate-smart agriculture practices and productivity outcomes among smallholder farmers in Zambia’, Food Security, 13(4), pp. 987-1002. [Google Scholar] [Crossref]
30. Ojo, T.O., Baiyegunhi, L.J.S. and Salami, A.O. (2020). ‘Impact of extension services on climate-smart agriculture adoption’. Technology in Society, 63, 101-112. [Google Scholar] [Crossref]
31. Putnam, R. D. (1993). Making Democracy Work: Civic Traditions in Modern Italy. Princeton, NJ: Princeton University Press. [Google Scholar] [Crossref]
32. Rogers, E. M. (2003). Diffusion of Innovations, 5th edition. New York: Free Press. [Google Scholar] [Crossref]
33. Rose, D.C., Wheeler, R., Winter, M. and Lobley, M. (2021). ‘Improving the uptake of digital technologies in agriculture’. Journal of Rural Studies, 85, pp. 115-128. [Google Scholar] [Crossref]
34. Rosenstock, T. S., Lamanna, C., Chesterman, S., Bell, P., Arslan, A., and Richards, M. (2021) ‘When less is more: Innovations for tracking progress toward global adaptation goals’. Global Environmental Change, 67, p. 102231. [Google Scholar] [Crossref]
35. Sitko, N. J. and Jayne, T. S. (2021). ‘Structural transformation and rural youth employment in Zambia’. Agricultural Economics, 52(5), pp. 761-776. [Google Scholar] [Crossref]
36. Sitko, N.J. and Jayne, T.S. (2021). ‘Structural transformation and youth employment challenges in African agriculture’. Development Policy Review, 39(4), pp. 602-621. [Google Scholar] [Crossref]
37. Smith, J. A., Flower, P., and Larkin, M. (2009). Interpretative phenomenological analysis: theory, method and research. USA: Sage. [Google Scholar] [Crossref]
38. Spielman, D. J. and Birner, R. (2008) How Innovative is Your Agriculture? Using Innovation Indicators and Benchmarks to Strengthen National Agricultural Innovation Systems. World Bank Agriculture and Rural Development Discussion Paper No. 41. Washington, DC: World Bank. [Google Scholar] [Crossref]
39. Spielman, D.J. and Birner, R. (2008). ‘How innovative is your agriculture? Using innovation indicators and benchmarks to strengthen national agricultural innovation systems’. World Bank Agricultural and Rural Development Discussion Paper, 41(6), pp. 1-34. [Google Scholar] [Crossref]
40. United Nations (2023). World Youth Report 2023: Youth Social Entrepreneurship and the 2030 Agenda. New York: United Nations. [Google Scholar] [Crossref]
41. World Bank (2023). Zambia Economic Brief: Enhancing Agricultural Resilience and Productivity. Washington, DC: World Bank. [Google Scholar] [Crossref]
42. Yamane, T. (1967). Statistics: An Introductory Analysis, 2nd edition. New York: Harper and Row. [Google Scholar] [Crossref]
43. Yeboah, F.K. and Jayne, T.S. (2023). ‘Africa’s evolving youth employment challenge and the role of agriculture’. African Journal of Agricultural and Resource Economics, 18(1), pp. 1-19. [Google Scholar] [Crossref]
44. Zambia Statistical Agency (2023). Zambia Labour Force Survey Report 2023. Lusaka: Zambia Statistics Agency. [Google Scholar] [Crossref]
45. Zougmoré, R., Partey, S., Ouédraogo, M., Torquebiau, E., and Campbell, B. M. (2023) ‘Climate-smart agriculture and sustainable food systems in Sub-Saharan Africa’. Sustainability Science, 18(2), pp. 541-556. [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- The Dynamic of Religious Pluralism and Cultural Identity in Rongmei Naga (Kabui) Society
- Effects of Social-Economic Empowerment of Teenage Mothers and Nurture Care. A Case of Kimbilio Hope Centre, Machakos, Kenya
- Gendering Caste and Casteing Gender: A Study of Social Sickness in Uma Chakravarti’s Gendering Caste: Through a Feminist Lens
- Counselling as Social Work for Women Empowerment in Akwa Ibom State: A Case Study of Ibiono Ibom Local Government Area. Implications for Counsellors
- Motherhood: Inclusion and Containment, A Case Study