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Determinants of smallholder farmers’ willingness -to -pay for soyabean production inputs in northern Ghana

Author

Listed:
  • Adjei-Nsiah, Samuel
  • Gyan, Kwasi
  • Ahiakpa, John Kojo
  • Ampadu-Boakye T
  • Sedebo, DA

Abstract

Farmers in northern Ghana have been cultivating soyabean with very little or no agro-inputs due to cost and limited accessibility. Use of quality agro-inputs can significantly improve the productivity of soyabean. This study assesses farmers’ current use of soyabean production agro-inputs, identifies challenges faced by smallholder farmers in soyabean cultivation and assesses factors influencing farmers’ willingness-to-pay (WTP) for soyabean inputs (determinants) in northern Ghana. Four hundred (400) smallholder soyabean farmers were sampled using a multi-stage sampling method. In stage one, the study area was stratified into three regions, northern, upper east and upper west regions. Stage two encompassed purposive sampling of eight (8) districts across the three northern regions famed for soyabean production. Data was collected using a semi-structured questionnaire, key informant interviews and focus group discussions were conducted.. Descriptive statistics were performed and a contingency valuation method (CVM) was used to assess key determinants that influence farmers’ WTP for soyabean inputs. The results show that 74 % of the respondents were willing to pay for the soyabean inputs. However, 43, 47.3, 39.5 and 49.5 % of respondents were willing to pay at the bid price of 1.06/kg, 3.98/litre, 31.91/50kg bag and USD 5.32/100g sachet for certified seeds, herbicide (glyphosate), TSP fertiliser and inoculants, respectively. Age, household size, access to credit, participation and gains made from on-farm demonstrations significantly influenced farmers’ willingness to purchase certified soyabean seeds. Factors that significantly influenced farmers’ willingness to purchase glyphosate included household size, purpose and experience in soyabean production. In the case of triple superphosphaste fertiliser (TSP), access to extension services, participation and gains from farm demonstrations and distance to the nearest agro-input shop were identified as key determinants. Farmers’ willingness to purchase inoculants markedly correlated with age, credit, participation in on-field demonstrations, membership of farmer-based organisation and experience in soyabean production. The results of this study form a basis for making a business case for agro-input companies to invest in the distribution and sale of the newly introduced soyabean production inputs in northern Ghana. Development and promotion of early maturing and drought tolerant soyabean varieties by the National Agricultural Research Institutes are required to enable farmers to cope with the changing climatic conditions which pose a threat to soyabean production in northern Ghana.

Suggested Citation

  • Adjei-Nsiah, Samuel & Gyan, Kwasi & Ahiakpa, John Kojo & Ampadu-Boakye T & Sedebo, DA, 2022. "Determinants of smallholder farmers’ willingness -to -pay for soyabean production inputs in northern Ghana," African Journal of Food, Agriculture, Nutrition and Development (AJFAND), African Journal of Food, Agriculture, Nutrition and Development (AJFAND), vol. 22(08).
  • Handle: RePEc:ags:ajfand:334095
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    References listed on IDEAS

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    1. Pinuccia Calia & Elisabetta Strazzera, 2000. "Bias and efficiency of single versus double bound models for contingent valuation studies: a Monte Carlo analysis," Applied Economics, Taylor & Francis Journals, vol. 32(10), pages 1329-1336.
    2. W. Michael Hanemann, 1984. "Welfare Evaluations in Contingent Valuation Experiments with Discrete Responses," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(3), pages 332-341.
    3. Ariga, Joshua & Jayne, Thomas S., 2006. "Can the Market Deliver? Lessons from Kenya's Rising Use of Fertilizer Following Liberalization," Food Security Collaborative Policy Briefs 54646, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    4. Gockowski, James & Ndoumbe, Michel, 2004. "The adoption of intensive monocrop horticulture in southern Cameroon," Agricultural Economics, Blackwell, vol. 30(3), pages 195-202, May.
    5. Flett, Ross & Alpass, Fiona & Humphries, Steve & Massey, Claire & Morriss, Stuart & Long, Nigel, 2004. "The technology acceptance model and use of technology in New Zealand dairy farming," Agricultural Systems, Elsevier, vol. 80(2), pages 199-211, May.
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