Climate change poses great risks to poverty alleviation, food security and livelihoods sustainability in sub-Saharan Africa, declining crop yields and livestock productivity, especially in ASALs that suffer from fragile ecosystems characterized by frequent droughts and low rainfall. Climate-Smart Agriculture (CSA) objectives of improving productivity and incomes, adaptation, resilience to climate change and mitigation on GHGs emissions, are responses to these climate risks. CSA technologies, innovation and management practices (TIMPs) in general do exist, however they are concentrated in crop farming neglecting livestock production and especially in marginalized areas such as ASALs, which forms 85% of Kenyan land mass and is dominated by pastoral and nomadic livestock production. Most CSA practices are mainly at the production level and hardly extend to the entire value chain, and diffusion is slow due to several barriers. A mixed method approach was used to evaluate barriers to actors’ adoption of CSA in the pastoral Livestock red meat value chain starting from input suppliers, producers, to consumers (pasture to plate). This study used six broad perspectives to examine the barriers: 1) Knowledge and institutional; 2) Market and financial; 3) Policy and incentives; 4) Networks and engagement platforms; 5) Cultural and social; 6) Physical infrastructure barriers. These barriers can be surmounted with concerted efforts from the government, development partners, pastoral communities, value chain actors and public private partnership among others. Efforts such as modernization of the pastoral red meat value chains, integration of MSMEs into the livestock systems, access to affordable financing, availability of context based, affordable CSA TIMPs, incentives, policies and institutional support, which currently remains inadequate. Institutional barriers like lack of capacity, coupled with knowledge and behavioral barriers hinder adoption. Financial institutions and cooperative societies can be enablers, however, their reluctance to invest in the sector is a barrier too.
References
[1]
Abegunde, V. O., Sibanda, M., & Obi, A. (2020). Determinants of the Adoption of Climate-Smart Agricultural Practices by Small-Scale Farming Households in King Cetshwayo District Municipality, South Africa. Sustainability (Switzerland), 12, 195. https://doi.org/10.3390/su12010195
[2]
Aggarwal, P. K., Jarvis, A., Campbell, B. M., Zougmoré, R. B., Khatri-Chhetri, A., Vermeulen, S. J., Tan Yen, B. et al. (2018). The Climate-Smart Village Approach: Framework of an Integrative Strategy for Scaling Up Adaptation Options in Agriculture. Ecology and Society, 23, 14. https://doi.org/10.5751/ES-09844-230114
[3]
Alarcon, P., Dominguez-Salas, P., Häsler, B., Rushton, J., Alarcon, P., Fèvre, E. M., Ahmed, S. et al. (2017a). Mapping of Beef, Sheep and Goat Food Systems in Nairobi—A Framework for Policy Making and the Identification of Structural Vulnerabilities and Deficiencies. Agricultural Systems, 152, 1-17. https://doi.org/10.1016/j.agsy.2016.12.005
[4]
Alarcon, P., Fèvre, E. M., Muinde, P., Murungi, M. K., Kiambi, S., Akoko, J., & Rushton, J. (2017). Urban Livestock Keeping in the City of Nairobi: Diversity of Production Systems, Supply Chains, and Their Disease Management and Risks. Frontiers in Veterinary Science, 4, 171. https://doi.org/10.3389/fvets.2017.00171
[5]
Ali, D. A., Deininger, K., & Goldstein, M. (2014). Environmental and Gender Impacts of Land Tenure Regularization in Africa: Pilot Evidence from Rwanda. Journal of Development Economics, 110, 262-275. https://doi.org/10.1016/j.jdeveco.2013.12.009
[6]
Atela, J., Gannon, K. E., & Crick, F. (2018). Climate Change Adaptation among Female-Led Micro, Small and Medium Enterprises in Semi-Arid Areas: A Case Study from Kenya. https://doi.org/10.1007/978-3-319-71025-9_97-1
[7]
Baker, E. (2005). Institutional Barriers to Technology Diffusion in Rural Africa. 2005 Annual Meeting, Providence, 24-27 July 2005, 1-30.
[8]
Barro, R. J., & Sala-I-Martin, X. (1992). Convergence. Journal of Political Economy, 100, 223-251. https://doi.org/10.1086/261816
[9]
Bergevoet, R., & Van Engelen, A. (2014). The Kenyan Meat Sector; Opportunities for Dutch Agribusiness. Report No. 2014-032, LEI Wageningen UR. https://edepot.wur.nl/370228
[10]
Birch, I. (2018). Agricultural Productivity in Kenya: Barriers and Opportunities. https://opendocs.ids.ac.uk/opendocs/handle/20.500.12413/14211
[11]
Chandler, C. I. R. (2018). Knowledge, Attitudes, and Practice Surveys. In The International Encyclopedia of Anthropology (pp. 1-2). Wiley. https://doi.org/10.1002/9781118924396.wbiea1387
[12]
Cullen, K. L., Edwards, B. D., Casper, W. C., & Gue, K. R. (2014). Employees’ Adaptability and Perceptions of Change-Related Uncertainty: Implications for Perceived Organizational Support, Job Satisfaction, and Performance. Journal of Business and Psychology, 29, 269-280. https://doi.org/10.1007/s10869-013-9312-y
[13]
Dai, Z., Weisenstein, D. K., & Keith, D. W. (2018). Tailoring Meridional and Seasonal Radiative Forcing by Sulfate Aerosol Solar Geoengineering. Geophysical Research Letters, 45, 1030-1039. https://doi.org/10.1002/2017GL076472
[14]
Dearing, J. W. (2009). Applying Diffusion of Innovation Theory to Intervention Development. Research on Social Work Practice, 19, 503-518. https://doi.org/10.1177/1049731509335569
[15]
Dearing, J. W., & Cox, J. G. (2018). Diffusion of Innovations Theory, Principles, and Practice. Health Affairs, 37, 183-190. https://doi.org/10.1377/hlthaff.2017.1104
[16]
Descheemaeker, K., Oosting, S. J., Homann-Kee Tui, S., Masikati, P., Falconnier, G. N., & Giller, K. E. (2016). Climate Change Adaptation and Mitigation in Smallholder Crop-Livestock Systems in Sub-Saharan Africa: A Call for Integrated Impact Assessments. Regional Environmental Change, 16, 2331-2343. https://doi.org/10.1007/s10113-016-0957-8
[17]
Devaux, A., Torero, M., Donovan, J., & Horton, D. (2018). Agricultural Innovation and Inclusive Value-Chain Development: A Review. Journal of Agribusiness in Developing and Emerging Economies, 8, 99-123. https://doi.org/10.1108/JADEE-06-2017-0065
[18]
Dietz, M. (2011). Value Chain Governance that Benefits the Poor (pp. 1-15).
[19]
Energy Commission, C. (2011). Barriers to Climate Change Adaptation: A Diagnostic Framework.
[20]
Ericsson, E., & Lindberg, A. (2018). Development Opportunities in the Land Management Process in Rwanda.
[21]
Etwire, P. M., Buah, S., Ouédraogo, M., Zougmoré, R., Partey, S. T., Martey, E., Bayala, J., & Dayamba, S. D. (2017). An Assessment of Mobile Phone-Based Dissemination of Weather and Market Information in the Upper West Region of Ghana. Agriculture and Food Security, 6, 1-9. https://doi.org/10.1186/s40066-016-0088-y
[22]
Faber, A., & Hoppe, T. (2013). Co-Constructing a Sustainable Built Environment in the Netherlands-Dynamics and Opportunities in an Environmental Sectoral Innovation System. Energy Policy, 52, 628-638. https://doi.org/10.1016/j.enpol.2012.10.022
[23]
Fang, L. (2009). Entry Barriers, Competition, and Technology Adoption. https://doi.org/10.2139/ssrn.1433128
[24]
FAO (2003). Value Chain Analysis: A Case Study of Mangoes in Kenya (p. 11). Sugar and Beverages Group Raw Materials, Tropical and Horticultural Products Service Commodities and Trade Division Food and Agriculture Organization of the United Nations.
[25]
Fielding, K. S., & Hornsey, M. J. (2016). A Social Identity Analysis of Climate Change and Environmental Attitudes and Behaviors: Insights and Opportunities. Frontiers in Psychology, 7, Article No. 121. https://doi.org/10.3389/fpsyg.2016.00121
[26]
Gledhill, R., & Herweijer, C. (2012). Challenges and Opportunities for Scaling-Up Investment in CSA Prepared by PwC with Support from 22 Authors.
[27]
Godde, C. M., Mason-D’Croz, D., Mayberry, D. E., Thornton, P. K., & Herrero, M. (2021). Impacts of Climate Change on the Livestock Food Supply Chain; A Review of the Evidence. Global Food Security, 28, Article No. 100488. https://doi.org/10.1016/j.gfs.2020.100488
[28]
Gonzalez, C. (2005). Task Workload and Cognitive Abilities in Dynamic Decision Making. Human Factors, 47, 92-101. https://doi.org/10.1518/0018720053653767
[29]
Grossi, G., Goglio, P., Vitali, A., & Williams, A. G. (2019). Livestock and Climate Change: Impact of Livestock on Climate and Mitigation Strategies. Animal Frontiers, 9, 69-76. https://doi.org/10.1093/af/vfy034
[30]
Ishtiaq, M. (2019). Book Review Creswell, J. W. (2014). Research Design: Qualitative, Quantitative and Mixed Methods Approaches (4th Ed.). Thousand Oaks, CA: Sage. English Language Teaching, 12, 40-41. https://doi.org/10.5539/elt.v12n5p40
[31]
Jordaan, H., Grové, B., & Backeberg, G. R. (2014). Conceptual Framework for Value Chain Analysis for Poverty Alleviation among Smallholder Farmers. Agrekon, 53, 1-25. https://doi.org/10.1080/03031853.2014.887903
[32]
Khalifa, M., & Ning Shen, K. (2008). Explaining the Adoption of Transactional B2C Mobile Commerce. Journal of Enterprise Information Management, 21, 110-124. https://doi.org/10.1108/17410390810851372
[33]
Khatri-Chhetri, A., Pant, A., Aggarwal, P. K., Vasireddy, V. V., & Yadav, A. (2019). Stakeholders Prioritization of Climate-Smart Agriculture Interventions: Evaluation of a Framework. Agricultural Systems, 174, 23-31. https://doi.org/10.1016/j.agsy.2019.03.002
[34]
Kim, Y., & Crowston, K. (2011). Technology Adoption and Use Theory Review for Studying Scientists’ Continued Use of Cyber-Infrastructure. Proceedings of the American Society for Information Science and Technology, 48, 1-10. https://doi.org/10.1002/meet.2011.14504801197
[35]
Linnér, B. O., & Wibeck, V. (2020). Conceptualising Variations in Societal Transformations towards Sustainability. Environmental Science and Policy, 106, 221-227. https://doi.org/10.1016/j.envsci.2020.01.007
[36]
Maina, J., Wandiga, S., Gyampoh, B., & Charles, K.K.G. (2020). Assessment of Land Use and Land Cover Change Using GIS and Remote Sensing: A Case Study of Kieni, Central Kenya. Journal of Remote Sensing & GIS, 9, 1-5. https://www.longdom.org/open-access/assessment-of-land-use-and-land-cover-change-using-gis-and-remote-sensing-a-case-study-of-kieni-central-kenya-52802.html
[37]
Matsui, H., Hori, K., Yamada, E., & Kodama, K. (2020). Visualization and Punctuation of Psychological Counseling by Qualitative and Quantitative Methods. Psychology, 11, 796-821. https://doi.org/10.4236/psych.2020.115053
[38]
Ministry of Agriculture, Livestock Fisheries Irrigation (2018). Agricultural Sector Transformation and Growth Strategy: Towards Sustainable Agricultural Transformation and Food Security in Kenya (p. 46).
[39]
Moser, S. C., & Ekstrom, J. A. (2010). A Framework to Diagnose Barriers to Climate Change Adaptation. Proceedings of the National Academy of Sciences of the United States of America, 107, 22026-22031. https://doi.org/10.1073/pnas.1007887107
[40]
Mukanyandwi, V., Kurban, A., Hakorimana, E., Nahayo, L., Habiyaremye, G., Gasirabo, A., & Sindikubwabo, T. (2019). Seasonal Assessment of Drinking Water Sources in Rwanda Using GIS, Contamination Degree (Cd), and Metal Index (MI). Environmental Monitoring and Assessment, 191, 1-13. https://doi.org/10.1007/s10661-019-7757-9
[41]
Mukherjee, A., & Sarkar, S. (2018). Institutional Barriers to Technology Adoption: The Case of Silk Technology in Colonial India. SSRN Electronic Journal.
[42]
Mutisya, S. M., & Barker, M. (2011). Pupils’ Environmental Awareness and Knowledge: A Springboard for Action in Primary Schools in Kenya’s Rift Valley. Science Education International, 22, 55-71.
[43]
Mwongera, C., Nowak, A., Notenbaert, A. M. O., Grey, S., Osiemo, J., Kinyua, I., Girvetz, E. et al. (2019). Climate-Smart Agricultural Value Chains: Risks and Perspectives. In T. Rosenstock, A. Nowak, & E. Girvetz (Eds.), The Climate-Smart Agriculture Papers (pp. 235-245). Springer International Publishing. https://doi.org/10.1007/978-3-319-92798-5_20
[44]
Nkonya, E., Mirzabaev, A., & Von Braun, J. (2015). Economics of land degradation and improvement: An introduction and overview. In E. Nkonya, A. Mirzabaev, & J. von Braun (Eds.), Economics of Land Degradation and Improvement—A Global Assessment for Sustainable Development (pp. 1-14). Springer International Publishing. https://doi.org/10.1007/978-3-319-19168-3_1
[45]
Otieno, D. J., Hubbard, L., & Ruto, E. (2012). Determinants of Technical Efficiency in Beef Cattle Production in Kenya: Application of the Tobit Method. http://erepository.uonbi.ac.ke/handle/11295/31665
[46]
Pantano, E., & Di Pietro, L. (2012). Understanding Consumer’s Acceptance of Technology-Based Innovations in Retailing. Journal of Technology Management & Innovation, 7, 1-19. https://doi.org/10.4067/S0718-27242012000400001
[47]
Raciti, S. M., Groffman, P. M., Jenkins, J. C., Pouyat, R. V., Fahey, T. J., Pickett, S. T. A., & Cadenasso, M. L. (2011). Accumulation of Carbon and Nitrogen in Residential Soils with Different Land-Use Histories. Ecosystems, 14, 287-297. https://doi.org/10.1007/s10021-010-9409-3
[48]
Said, M. Y., Ogutu, J. O., Kifugo, S. C., Makui, O., Reid, R. S., & de Leeuw, J. (2016). Effects of Extreme Land Fragmentation on Wildlife and Livestock Population Abundance and Distribution. Journal for Nature Conservation, 34, 151-164. https://doi.org/10.1016/j.jnc.2016.10.005
[49]
Scott, R. (2004). Institutional Theory: Contributing to a Theoretical Research Program. In K. G. Smith, & M. A. Hitt (Eds.), Great Minds in Management: The Process of Theory Development (pp. 460-484). Oxford: Oxford University Press.
[50]
Scott, S., & Mcguire, J. (2017). Using Diffusion of Innovation Theory to Promote Universally Designed College Instruction. International Journal of Teaching, 29, 119-128.
[51]
Smith, R. A., Kim, Y., Zhu, X., Doudou, D. T., Sternberg, E. D., & Thomas, M. B. (2018). Integrating Models of Diffusion and Behavior to Predict Innovation Adoption, Maintenance, and Social Diffusion. Journal of Health Communication, 23, 264-271. https://doi.org/10.1080/10810730.2018.1434259
[52]
Sourcebook, S. (2013). Climate Smart Agriculture.
[53]
Stein, C., & Barron, J. (2017). Mapping Actors along Value Chains: Integrating Visual Network Research and Participatory Statistics into Value Chain Analysis. Colombo: International Water Management Institute (IWMI). https://doi.org/10.5337/2017.216
[54]
Tankha, S., Fernandes, D., & Narayanan, N. C. (2020). Overcoming Barriers to Climate Smart Agriculture in India. International Journal of Climate Change Strategies and Management, 12, 108-127. https://doi.org/10.1108/IJCCSM-10-2018-0072
[55]
Tasquier, G., Pongiglione, F., & Levrini, O. (2014). Climate Change: An Educational Proposal Integrating the Physical and Social Sciences. Procedia—Social and Behavioral Sciences, 116, 820-825. https://doi.org/10.1016/j.sbspro.2014.01.304
[56]
Thorlakson, T., & Neufeldt, H. (2012). Reducing Subsistence Farmers’ Vulnerability to Climate Change: Evaluating the Potential Contributions of Agroforestry in Western Kenya. Agriculture and Food Security, 1, Article No. 15. https://doi.org/10.1186/2048-7010-1-15
[57]
Thornton, P., Enahoro, D., Njiru, N., Wijk, M. van, Ashley, L., Cramer, L., Ericksen, P., & Graham, M. (2019). Program for Climate-Smart Livestock Systems. Country Stocktake: Ethiopia. https://cgspace.cgiar.org/handle/10568/106291
[58]
Torquebiau, E., Rosenzweig, C., Chatrchyan, A. M., Andrieu, N., & Khosla, R. (2018). Identifying Climate-Smart Agriculture Research Needs. Cahiers Agricultures, 27, 26001. https://doi.org/10.1051/cagri/2018010
[59]
UNEP (2010). Assessing Global Land Use: Balancing Consumption with Sustainable Supply.
[60]
United Nations (2019) Report of the Secretary-General On the 2019 Climate Action Summit the Way Forward in 2020. https://www.un.org/sites/un2.un.org/files/cas_report_11_dec_0.pdf
[61]
Vermeulen, S. J., Campbell, B. M., & Ingram, J. S. I. (2012). Climate Change and Food Systems. Annual Review of Environment and Resources, 37, 195-222. https://doi.org/10.1146/annurev-environ-020411-130608
[62]
Williamson, I., Enemark, S., Wallace, J., Rajabifard, A., Enemark, W., Rajabifard, W., & Press, E. (2010). Land Administration for Sustainable Development.
[63]
World Bank. (2019). Annual Report 2019: Ending Poverty, Investing in Opportunity. World Bank Group, 319. https://documents.worldbank.org/en/publication/documents-reports/documentdetail/156691570147766895/the-world-bank-annual-report-2019-ending-poverty-investing-in-opportunity
[64]
Zhang, X., Yu, P., Yan, J., Ton, A. M., & Spil, I. (2015). Using Diffusion of Innovation Theory to Understand the Factors Impacting Patient Acceptance and Use of Consumer E-Health Innovations: A Case Study in a Primary Care Clinic Healthcare Needs and Demand. BMC Health Services Research, 15, 71. https://doi.org/10.1186/s12913-015-0726-2
