COID-19, Armed Conflict and ICTs Adoption Decisions. Insights from Cameroonian Farmers

Authors

  • Roland Azibo Balgah College of Technology, Department of Agribusiness technology University of Bamenda, Cameroon
  • Dorothy Nyiang Bwifon College of Technology, Department of Agribusiness technology University of Bamenda, Cameroon
  • Peter Ngek Shillie College of Technology, Department of Agribusiness technology University of Bamenda, Cameroon

DOI:

https://doi.org/10.14738/assrj.98.12763

Keywords:

ICTs adoption, Farmers, determinants, COVID 19, armed conflict, Cameroon

Abstract

It is common knowledge that adopting information and communication technologies -ICTs can significantly enhance agricultural performance. However, their adoption and usage in African agriculture remains disappointing. This study assesses ICTs adoption rates and adoption determinants among Cameroonian farmers. A structured questionnaire was used to collect data from a random sample of 120 farmers in two selected sites highly hit by COVID 19 and an on-going armed conflict in Cameroon’s North West region. Data collected and analysed using SPSS, version 25.0 revealed an overall ICTs adoption rate of 87.5%: 3 times higher than the national average. Experience with ICTs was the lone variable that significantly influenced ICTs adoption at 95% confidence interval (β=0.414, p=0.034). However, the age of the farmer (β=0.122, P=0.073), ICTs usage in last six months (β=-4, 316, p=0.072), farm size (β=1.132, p=0.06), and farmers income (β=-5.22, p=0.072) significantly influenced ICTs adoption only at the 10 percent level. Based on these results we conclude that high ICT adoption rates by farmers in the study is most likely an adaptation strategy to the combined negative lockdown and ghost town effects of COVID 19 and the on-going armed conflict respectively; which create incentives for ICTs adoption. We recommend ICT awareness campaigns, experience-sharing and capacity building as key activities to sustain ICT adoption and eventually stem future dis-adoption rates. Research thrust on the positive impacts of perceived negative events like COVID 19 and armed conflicts especially in Africa is encouraged.

References

Ajzen I, Fishbein, M, Atomic I (1980) Agency E, Federal T, Commission T. Theory of Reasoned Action/Theory of Planned Behavior. Handb Theor Soc Psychol 2007: 67-98.

Ajzen I (1991) The theory of planned behaviour. Organizational Behav Hum Deci Proc 50: 179-211.

Awzi NP, Quandt A (2021) Livelihood resilience to environmental changes in areas of Kenya and Cameroon: A comparative analysis. Clim Chang 165 (33): 1-27. https://doi.org/10.1007/sl0584-021-0307-5

Ayim C, Kassahun A, Addison C, Tekinerdogan B (2022) Adoption of ICT innovations in the agriculture sector in Africa: a review of the literature. Agri Food Secur 11(22.) https://doi.org/10.1186/s40066-022-00364-7

Bagchi K. Udo G (2007) Empirically testing factors that drive ICT adoption in Africa and OECD set of nations. Issues Info Systs 8(2): 45-52.

Bakehe NP, Fambeu AH, Piaptie GBT (2017) Internet Adoption and Use in Cameroon. AERC Res Paper No. 336. Nairobi: African Economic Research Consortium.

Balgah R.A, Kimengsi JN, Antonia FK (2016). Farmer’s knowledge and perception to climate change variability in North West Cameroon. World J Soc Sci (3): 261-273.

Balgah, R.A and Fonteh, A.A. (2019) Applying Relativity in Understanding Poverty and Promoting Economic Development in Rural Africa. African Journal of Economic Review 7(1): 219-237. DOI: 10.22004/ag.econ.285008

Bamenda III Council (2020) climate. DATA.org. https://en.climate-data.org˲northwest. Accessed 25 Feb 2021.

Bang HN, Balgah RA (2022). The ramification of Cameroon’s Anglophone crisis: conceptual analysis of a looming “Complex Disaster Emergency”. J Int Hum Action 7(6). https://doi.org/10.1186/s41018-022-00114-1

Bartholomew A, Wainwright D, Green G (2009) Policy Issues of e-Commerce Technology Diffusion in Southeast Nigeria the Case of Small-Scale Agribusiness. Interdiscip Stud Built Virtual Env 2 (1): 39-48. 29

Bisson L, Hambleton T (2020) COVID-19 Impact on West African value Chains. Clingadael: The Netherlands Institute of International Relations.

Bogdan RC, Biklen SK (1998) Qualitative Research for Education. An Introduction to Theories and Models. Allyn and Bacon, Needham Heights MA.

Buchenrieder G, Brandl J, Balgah R (2021) The Perception of Flood Risks: A Case Study of Babessi in Rural Cameroon. Int J Disast Risk Sci 12: 1-12. https://doi.org/10.1007/s13753-021-00345-7.

Chunrong A, Norton EC (2003) Interaction terms in Logit and Probit models. University of Florida, Gainesville.

Davis FD (1989) Perceived Usefulness, Perceived Ease of Use and User Acceptance of Technology. MIS Quart 13(3): 319-940.

Davis, FD, Bogozzi RP, Warshaw, PR (1989) User acceptance of computer technology: A comparison of two theoretical models. Manag Sci 35(1): 982-1003.

Deloitte Consulting (2012). E-Transform Africa. Agriculture Sector Study: Sector Assessment and Opportunities for ICT. Report by Deloitte Consulting.

Dholakia RR, Kshetri N (2004) Factors Impacting the Adoption of the Internet among SMEs. Small Busin Econ 23:311-322. https://doi.org/10.1023/B:SBEJ.0000032036.90353.1f

Donner J (2007) Customer Acquisition Among Small and Informal Businesses in Urban India: Comparing Face-to-Face and Mediated Channels. The Elect J Info Systs Dev Countries 32(3): 2-14. https://doi.org/10.1002/j.1681-4835.2007.tb00222.x

El Bilali, H, Allahyari MS (2018) Transition towards sustainability in agriculture and food systems: Role of information and communication technologies. Info Process Agri 5(4): 456-464. https://doi.org/10.1016/j.inpa.2018.06.006

Fambeu AH (2021). Adoption of information and Communications Technology (ICT) in Industrial Firms in Cameroon. AERC Research Paper No. 470, Nairobi: African Economic Research Consortium.

Farrell G (2007) infoDev survey of ICT and Education in Africa; Uganda country report. www.infodev.org. Accessed on 26 Nov 2010.

Feder G, Umali DL (1993) The Adoption of Agricultural Innovations: A Review. Technol Forecast Soc Chang 43: 215-239. https://doi.org/10.1016/0040-1625(93)90053-A.

Ferris S, Engoru P, Kaganzi, E (2008) Making Market Information Services Work Better for the Poor in Uganda. Report of Research Workshop on Collective Action and Market Access for Smallholders. Cali, Colombia. Food and Agriculture Organization (FAO) (2017) Information and Communication Technology (ICT) in Agriculture: A Report to the G20 Agricultural Deputies.

Fountas S, Pedersen SM, Blackmore S (2007) ICT in Precision Agriculture – diffusion of Technology, University of Thessaly, Greece; available from http://www.departments.agri.huji.ac.il/economics/gelb-pedersen-5.pdf. Accessed on 17 April 2022.

Galloway L, Mochrie R (2005) The use of ICT in rural firms: a policy-orientated literature review. info 7(3):33-46.Ihttps://doi.org/10.1108/14636690510596784

Gwaka LT (2017) Digital Technologies and Sustainable Livestock Systems in Rural Communities. Electr J Info Systs Dev Countries 81(6): 1-24. https://doi.org/10.1002/j.1681-4835.2017.tb00598.x

Hanifer PE, Mahendra F, Mahir P (2022). The moderating effect of social media use in impulsive buying of personal protective equipments during the COVID 19 Pandemic. Congent Soc Sci 8(1). https://doi.org/10.1080/23311886.2022.2062094

Hill R., Davies PB, Williams MD (2008) Older people and internet engagement: Acknowledging social moderators of internet adoption, access and use. Info

Jacobs SJ, Herselman, ME (2006) Information Access for Development: a Case Study at a Rural Community Centre in South Africa Issues in Informing Science and Information Technology.

Jordan AH, College D, Zitek EM (2012) Marital bias in perception of employees. Basic Appli Soc psychol 34: 474-481.

Kim,Y, Crowston K (2011) Technology Adoption and Use Theory Review for Studying Scientists Continued Use of Cyber-infrastructure. Available at: http://crowston.syr.edu/system/files/ASIST2011.pdf. Accessed on 20 June

Kimengsi JN, Mukong AK, Balagh RA (2020) Livelihood Diversification and Household Well-Being: Insights and Policy Implication for Forest –Based communities in Cameroon. Society Nat Res 33(7): 896-895. DOI 10.1080/08941920.2020. 1769243.

Lazar M. (2019). Afro Barometer: Cameroon’s linguistic divide deepens to rift on questions of democracy, trust, national identity. https://www.afrobarometer.org/publications/ad283-cameroons-linguistic-divide-deepensriftquestions-democracy-trust-national-identity. Accessed 23 Nov 2021.

Madalla G (1983) Limited Dependent and Qualitative Variables in Econometrics, Cambridge University Press, Cambridge.

Manfre C, Nordehn C (2013) Exploring the Promise of Information and Communication Technologies for Women Farmers in Kenya. Cultural Practice, LLC. MEAS Case Study No. 4. August 2013.

Msoffe G. Ngulube P (2017) Information sources preference of poultry farmers in selected rural areas of Tanzania. Librar Info Sci 38(3): 265–271.

Msuya CP, Duvel, GH, Rwambali EG (2014) The Influence of Independent and Intervening Variables on Adoption of Recommended Maize Varieties in Tanzania. Tanzania J Agri Sci 13(1): 26-40.

Ngochembo GG, Balgah, RA, Fonteh MF (2022) The effects of adopting technological innovations on value chain actors in Cameroon. Asian J Agri Exten, Econ Sociol 40(5):103-114. DOI: 10.9734/AJAEES/2022/v40i53089

Nji PM, Engwali DF (2019) Farmer organisation in the northwest region of Cameroon: Actual state of affairs. Int J Agri Exten Rur Dev Stud 6(2):13-26.

Nyanda DS (2015) Factors Influencing Adoption of Improved Cassava Production Technologies in Mkuranga District, Tanzania, A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of Masters of Science in Agricultural Education and Extension, Sokoine University of Agriculture, Morogoro, Tanzania.

OCHA (2022) CAMEROON: North-West and South-West. Situation Report No. 40.

Sitrep_nwsw_february2022_fv.pdf. Accessed on 14 April 2022.

Oladele OI (2011) Effect of Information Communication Technology on Agricultural Information Access among Researchers, Extension Agents, and Farmers in South Western Nigeria. J Agri Food Info 12(2): 167-176.

Olayemi SS, Conway JS, Sennuga MA (2020) Impact of information and communication technologies (ICTs) on agricultural productivity among smallholder farmers: Evidence from sub-Saharan Communities. Int J Ag Exten and Rur Dev 7(1),27-43.

Opara, UN (2008). Agricultural Information Sources used by Farmers in Imo State, Nigeria. Info Dev 24(4): 289 -295.

Osei SK, Folitse BY, Dzandu LP, Obeng-Koranteng G (2016). Sources of information for urban vegetable farmers in Accra, Ghana. Info Dev. DOI: 10.1177/ 0266666916638712.

Peansupap V, Walker D (2005) Factors affecting ICT diffusion: A case study of three large Australian construction contractors. Eng, Construct Archit Manag 12(1): 27-33. DOI: https://doi.org/10.1108/09699980510576871

Pimentel P, Francisco S (2009) Initiatives for Development of Agricultural Information Management to Policy Makers: A Case Study from Mozambique. In: Opening Access to Agricultural Information and Knowledge: sharing the experience of the NARS. 12-17 July, 2009, Ghana, Accra.

Rao SS (2004) Role of ICTs in India's rural community information systems. Info 6(4): 261-269. http://dx.doi.org/10.1108/14636690410555663

Rathgeber EM, Adera EO (Eds) (2000) Gender and the Information revolution in Africa. International Development Research Centre (IDRC), Ottawa.

Saloner G, Shepard A (1995) Adoption of technologies with network effects: an empirical examination of adoption of automated machines. RAND J Econs 26(3): 479-501.

Shillie PN, Bime M-JE, Balgah RA, Wiysherinyuy ML (2022) Access to and repayment of Agricultural Credit in the face of COVID 19: A Gender Analysis in Selected Microfinance Institutions in Cameroon. Fin Econs Rev 4(1): 1-10.

Simeunović D, Russo NL (2010), Prerequisite for Growth: ICT Usage in Secondary Education in Bosnia and Herzegovina. INFOTECH-Jahorina 7(9):1023-1030.

SPAU (2020) Articulating the Pathways of the Socio-Economic Impact of the Coronavirus (COVID-19) Pandemic on the Kenyan Economy. Nairobi: The Strategic Policy Advisory Unit (SPAU), UNDP Kenya Country Office.

Stan, M, Totally S, Hallu M, Addom, BK (2019). The Digitalization of African Agriculture report 2018-2019 the Netherlands CTA, Wageningen.

Tambi NE, Mukhebi WA, Maina WO (1999) A probit Analysis of livestock producers’ demand for private veterinary services in high potential areas of Kenya, Agri systs 59: 163-176.

Voogt J, Knezek G (2008) International Handbook of Information Technology in Primary and Secondary Education. Springer. https://link.springer.com/book/10.1007/978-0-387-73315-9

Windrum P, Berranger P, (2002) The Adoption of e-business technologies by SMEs MERIT-Infonomics Research Memorandum series’: No. 2002-023 http://www.mmu.ac.uk.

Wolcott P, Kamal M, Qureshi S (2008) Meeting the challenges of ICT adoption by micro-enterprises. J Enterprise Info Manag 21(6): 620-628. http://dx.doi.org/10.1108/17410390810911212

World Bank (2013) Cameroon Socio-economic Statistic http://www.stwr.org/ globalization/world- bankpoverty-figures-what-do-they-mean.html. Accessed on 5 March 2022.

World Bank (2007) World Development Report 2008: Agriculture for Development. Washington, DC, The World Bank.

Wuepper, D, Zilberman D, Sauer, J (2020) Non-cognitive skills and climate change adaptation: Empirical evidence from Ghana’s pineapple farmers. Climat Dev 12(2): 151–162. https://doi.org/10.1080/17565529.2019.1607240

Yang KCC (2005) Exploring factors affecting the adoption of mobile commerce in Singapore. Telemat Informat 22: 257-277. https://doi.org/10.1016/j.tele.2004.11.003

Zemach LL (2018) Determinant Factors and their Coping Strategies of Cassava Production of Farm Households: The Case of Amaroworeda in Southern Nations, Nationalities and Peoples Regional State of Ethiopia. Int J Innov and Res in Edu 5(4): 367-376.

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Published

2022-08-10

How to Cite

Balgah, R. A., Bwifon, D. N., & Shillie, P. N. (2022). COID-19, Armed Conflict and ICTs Adoption Decisions. Insights from Cameroonian Farmers. Advances in Social Sciences Research Journal, 9(8), 12–32. https://doi.org/10.14738/assrj.98.12763