Determinants of solar technology adoption in rural households: The case of Belesa districts, Amhara region of Ethiopia

Ahmed, Yasin; Seid, Ebrahim; Ahmed, Mohammed

doi:10.1080/23322039.2022.2087644

Cited by 6 publications

(2 citation statements)

References 7 publications

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“…The marginal effect analysis indicates that for each additional member added to the household, the likelihood of adopting clean cooking fuel increases by 2.4% 32 . Previous studies suggest that larger households tend to adopt energy-efficient practices more than smaller ones, which is consistent with previous findings 50 , 51 . Similarly, larger households prefer more efficient cooking methods due to reduced cooking time and the preservation of wood resources 48 .…”

Section: Discussionsupporting

confidence: 92%

Determinants of household adoption of clean energy with its rural–urban disparities in Bangladesh

Haq,

Khan,

Chakma

et al. 2024

Sci Rep

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This study aims to investigate factors influencing the adoption of clean energy among households in Bangladesh, using Blinder-Oaxaca decomposition and extended probit regression model with data from the 2019 Bangladesh multiple indicator cluster survey. Small households, primarily Muslim and urban dwellers, who speak the Bengali language and are Internet and mobile users, were likelier to adopt cleaner fuels than their counterparts. On the contrary, households residing in the Barisal, Khulna, Rajshahi, and Rangpur divisions, belonging to poor and middle-class households, with household heads aged 15–64 and without formal education, were less likely to adopt cleaner fuels than their counterparts. The concentration curve revealed socioeconomic inequality in the adoption of clean energy, particularly favouring richer households in urban and rural areas. Further analysis using the Blinder-Oaxaca decomposition showed that urban residents showed a higher probability of adopting clean energy, with a significant difference of 0.508 compared to rural areas. Regarding the endowment effect, poor wealth quintile contributed the most, followed by the ownership of rented dwellings and the middle wealth quintile. The Bengali differential effect made the largest contribution to this aspect of the disparity, followed by the exposure of the Internet and the influence of the Dhaka and Chattogram divisions. The detailed analysis provides valuable insights for policymakers and practitioners on the issue of disparities in the adoption of clean energy between urban and rural areas in Bangladesh.

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Section: Discussionsupporting

confidence: 92%

Determinants of household adoption of clean energy with its rural–urban disparities in Bangladesh

Haq,

Khan,

Chakma

et al. 2024

Sci Rep

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show abstract

“…Previous studies [15]- [18] have reported that binary logistic and probit regression models fit in explaining the relationship between dependent and independent variables. However, [15] declared that the binary logistic regression model is much preferred by a researcher over the probit regression model since the binary model is easier to use and provides a more meaningful interpretation of the results than the other models. Binary logistic regression was employed in this study based on the advantages that it has over the probit model.…”

Section: Data Processing and Analysismentioning

confidence: 97%

Factors Influencing Rural Farmers' Access to Agricultural Extension Services Provided by Private Organizations in Kibondo District, Tanzania

Masanja,

Shausi,

Kalungwizi

2023

EJFOOD

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Agricultural extension plays a very important role in improving agricultural productivity in many countries, including Tanzania. Through agricultural extension services, farmers acquire useful information to minimize agricultural production challenges. Though farmers in many countries, including Tanzania, still rely on public extension services, the governments in many countries have started to open doors for non-governmental organizations (NGOs), farmer-based organizations, and private agribusiness firms to provide services to farmers. Regardless of their existence still access to extension services provided by private organizations has remained a main question. Studies have consistently pointed out that only a few farmers in rural areas get access to extension services provided by private organizations. Low access to extension services by rural farmers has contributed to low agricultural production in rural areas and has remained the main factor for persistent poverty. There are limited studies documenting the factors for low access to agricultural extension services provided by private organizations. This study aimed to determine factors influencing rural farmers’ access to agricultural extension services provided by private organizations in the Kibondo district. The study used a cross-sectional research design and data were collected by interviewing 120 farmers sampled from four villages. Data were analyzed using descriptive statistics and binary logistic regression model techniques. The study found that only 18.3% of farmers had access to extension services. Gender, marital status, education level, farmers’ income, and group membership had a positive and statistically significant association with access to extension services. The study concluded that only a small proportion of rural farmers in the study area had access to extension services. It is recommended that the provision of extension services by private organizations should consider the identified factors.

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Determinants of the sustained use of household clean fuels and technologies: Lessons from Vihiga county, Kenya

et al. 2023

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Determinants of solar technology adoption in rural households: The case of Belesa districts, Amhara region of Ethiopia

Cited by 6 publications

References 7 publications

Determinants of household adoption of clean energy with its rural–urban disparities in Bangladesh

Determinants of household adoption of clean energy with its rural–urban disparities in Bangladesh

Factors Influencing Rural Farmers' Access to Agricultural Extension Services Provided by Private Organizations in Kibondo District, Tanzania

Determinants of the sustained use of household clean fuels and technologies: Lessons from Vihiga county, Kenya

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