Determinants of actual and potential adoption of improved indigenous chicken under asymmetrical exposure conditions in rural Kenya

Mwololo, Henry; Nzuma, Jonathan M.; Ritho, Cecilia; Ogutu, Sylvester Ochieng; Kabunga, Nassul

doi:10.1080/20421338.2019.1636489

Cited by 7 publications

(3 citation statements)

References 29 publications

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“…This finding disagreed with those of the previous studies in India, where 85% of the pig farmers were landless [35]. Furthermore, although this study indicated that only 14.0% of the respondents owned <1 acre or no land, the previous findings confirmed that land ownership positively affected the probability of a farmer accepting or adopting an innovation [40]. Notably, pigs can be reared on a small piece of land because they are not grazers and are regarded as the most ideal to rear on given the space requirement [41].…”

Section: Gender Issuescontrasting

confidence: 99%

Attitudes and preferences of traditional farmers toward reproductive biotechnology application for improved indigenous pig production in Zambia

et al. 2022

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Background and Aim: Pig production remains crucial to the livelihood of farmers in Zambia. However, low production continues to undermine efforts to reduce animal protein deficit; hence, the need emerges to improve production through biotechnology. To contribute to the prediction of their acceptance, this study assessed the attitudes and preferences of traditional farmers toward reproductive biotechnologies by exploring the socio-demographic characteristics of farmers. Materials and Methods: The study conducted a cross-sectional descriptive survey that employed a mixed-methods design with a qualitative-quantitative methodological triangulation. Quantitative data were obtained from 622 respondents using a questionnaire, whereas seven focus group discussions (FGDs) were conducted to obtain qualitative data. Descriptive statistics and thematic analysis were used to analyze quantitative and qualitative data, respectively. Results: The majority (65.1%) of the respondents were low-income earners who mainly (64.8%) attained primary education. In addition, pig farming was dominated by middle-aged (43.7%) and elderly (40.7%) individuals. Moreover, most of the respondents owned (51.3% and 78.0%) more than 2 acres and six pigs, respectively. Furthermore, the respondents expressed a positive attitude (3.84±0.42) toward reproductive biotechnology application. However, despite supportive opinions (4.17±0.54) and favorable behavioral intentions (4.09±0.51), their feelings were generally neutral (3.10±0.89). In addition, the study observed various contrasting attitudes across socio-demographic factors. The respondents mainly preferred artificial insemination (AI; 66.2%). The results of the FGDs supported the survey findings. Nevertheless, the lack of information, knowledge and practical exposure, absence of peer influence, perceived beliefs and risks, poverty situations, and gender issues were pinpointed as the identified barriers to the biotechnology acceptance of the participants. Conclusion: The respondents generally supported reproductive biotechnology application and its contribution to improved production. However, further promotion of the favorable attitudes of the farmers will be required. In this case, interventions sensitive to their socio-demographic characteristics, perceived barriers, and identified contributing factors to favorable attitudes will be crucial. In addition, despite the overwhelming preference for AI, efforts to promote AI-supporting reproductive technologies are required because they contribute to AI success rate.

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Section: Gender Issuescontrasting

confidence: 99%

Attitudes and preferences of traditional farmers toward reproductive biotechnology application for improved indigenous pig production in Zambia

et al. 2022

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“…It further suggests that farmers who know about rural bank credit programs have about 3% higher likelihood of accessing credit from the rural banks than a randomly selected farmer from the general population (Table 3). The estimated PSB confirms the positive impact of awareness on the adoption of rural bank credit programs among smallholder farmers in Ghana and is consistent with Mwololo et al (2020), who found that exposure is significant in the uptake of improved indigenous chicken in Kenya.…”

Section: Resultssupporting

confidence: 85%

Adoption of rural bank credit programs among smallholder farmers in Ghana: an average treatment effect estimation of rates of exposure and adoption and their determinants

Missiame

Irungu

Nyikal

et al. 2021

AFR

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PurposeThe study aims to estimate the rates of exposure to, and adoption of, rural bank credit programs by smallholder farmers in rural Ghana and the factors responsible for those rates.Design/methodology/approachThe study used a random sample of 300 smallholder farmers in the Fanteakwa District of Ghana, obtained through the multistage sampling technique. The study also employed the average treatment effects approach to estimate the average treatment effect of farmers’ exposure to rural bank credit programs, on their adoption of such programs.FindingsThe actual adoption rate is approximately 41%, and the potential, conditional on the whole population being aware of rural bank credit programs, is approximately 61%. Accordingly, there is a gap of about 20% in the adoption of rural bank credit programs, and is due to the incomplete exposure of smallholder farmers to the rural bank credit programs. Age of the household head, access to extension services, membership in farmer-based organizations and active savings accounts with a rural bank are the major contributors to smallholder farmer exposure to and the adoption of rural bank credit programs.Originality/valueThe current study is the first of its kind to be conducted in Ghana on rural bank credit programs. It takes into account the extent to which smallholder farmers are exposed to such credit programs and how it influences their decisions to access or adopt.

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“…Advancing age of household heads significantly increased adoption contradicts the work of Rogers (2003), Bokusheva et al (2012), andAshraf et al (2015), who stated that older people are more reserved regarding the introduction and acceptance of innovations due to declining cognitive and learning abilities; but here we may be considering capital intensive technologies which may not be pocket friendly to younger farmers. Exposure to extension services positively influenced adoption agreeing with Lwelamira and Mzarai (2010), Akpan et al (2012), andMwololo et al, (2019), Information sources, especially multiple sources increased the probability of adoption of certain technologies, and this is supported by Degaga and Alamerie (2020). Also, having adequate sources of farm labour has been shown to positively influence the adoption and the intensity of the adoption of PHLRT.…”

Section: Discussionsupporting

confidence: 52%

Assessment of factors influencing adoption of tomato post-harvest loss-reduction technologies in Kaduna state, Nigeria

Korie

Njeru

Mburu

et al. 2023

EAJSTI

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The Nigerian government's policy on agriculture supports productivity enhancements, yet tomato production is constrained by post-harvest losses of up to over 45%. 420 tomato farmers were selected for study in Kaduna State, Nigeria. Multinomial Logit Model was used to determine factors influencing losses while factors influencing adoption and intensity were modelled using Tobit. The results showed the adoption rate of (new technologies) RP was 3.57%, CS = 0.47%, RT = 0.71%, MD =0.71%, CD = 100%. Adoption rate of (traditional method) raffia basket was 100%. For farmers, the highest source of losses was those in storage (70.5%), followed by farm level (14.5%). Results on factors influencing PHL showed that in transit, Modern Technology accentuated losses (p<0.10), while Car/truck ownership mitigated losses (p<0.01) In storage, Modern Technology (p<0.05), Farm Distance (p<0.05), Farm Size (p<0.10), and Own Car/truck ownership (p<0.10) mitigated losses, while only Multiple Cropping (p<0.05) accentuated losses. In marketing, education (p<0.05), modern technology (p<0.10), multiple cropping (P<0.10), and credit access (P<0.10) accentuated losses while age of farmer (p<0.10), years of technology adoption (p<0.10), farm size (p<0.10), and wealth status of farmer (p<0.05) mitigated losses. The results factors influencing adoption and adoption intensity of PHL-reducing technology show that Education (p<0.05), Age (p<0.10), Extension (p<0.10), CS_Information_Sources (p<0.01), RT_Information_Sources (p<0.01), MD_Information_Sources (p<0.05), Labour_sourcesT (p<0.01), Credit_sourcesT (p<0.10), and Farm_Size (p<0.01) were positive and had a significant influence. Education had a quadratic (Education2) negative influence on adoption of PHL reducing technologies. In conclusion, extension services exposure, large farm holding, and multiple information sources positively influenced adoption of post-harvest loss reduction technologies. The field survey also showed a 100% willingness of the farmers to adopt improved/modern technologies. The study recommended using PPP model to make these modern technologies and farm practices within the financial reach of farmers to mitigate post-harvest losses.

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Determinants of actual and potential adoption of improved indigenous chicken under asymmetrical exposure conditions in rural Kenya

Cited by 7 publications

References 29 publications

Attitudes and preferences of traditional farmers toward reproductive biotechnology application for improved indigenous pig production in Zambia

Attitudes and preferences of traditional farmers toward reproductive biotechnology application for improved indigenous pig production in Zambia

Adoption of rural bank credit programs among smallholder farmers in Ghana: an average treatment effect estimation of rates of exposure and adoption and their determinants

Assessment of factors influencing adoption of tomato post-harvest loss-reduction technologies in Kaduna state, Nigeria

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