A mixed-methods study on the determinants of solar home systems utilization in rural, off-grid Nigeria

Abstract

This study employs a mixed-methods research approach to scrutinize the varied determinants influencing the willingness of off-grid rural households in Kwara State, Nigeria, to adopt Solar Home Systems (SHS). Integrating quantitative survey data from 400 households, qualitative findings derived from semi-structured interviews, and secondary data, the research provides a robust empirical framework. Through the application of Interval Regression and Tobit models, the analysis pinpoints income and education as key positive drivers towards SHS adoption, yet reveals a contrasting gender divide. Interestingly, a high level of satisfaction with the current energy provision emerges as a stumbling block to SHS acceptance. The research further identifies a distinct trend: households located further away from the grid exhibit a heightened propensity to pay for SHS, signifying a higher value attribution to SHS in these off-grid areas. The findings underscore the need for targeted interventions that encapsulate the diverse characteristics of households to ensure successful SHS promotion. The comprehensive insights garnered from this study offer indispensable guidance for policymakers and energy providers, bolstering strategic efforts to enhance SHS uptake and ultimately contributing to Nigeria's shift towards a more sustainable energy future.

Analysis of the effect of climate-smart agricultural practices (CSAPs) on food security of maize production in Southeast, Nigeria

“…This procedure has been explored extensively by Kim, and Maddala (1992) [28] ; Gujarati (1980) [20] . The Tobit model uses a maximum likelihood estimation procedure to estimate the model parameters and can be used to extend the linear regression model to censored variables (Smithson, and Verkuilen, 2006; Audu et al, 2023) [46,9] . According to McDonald (2009) [32] , the Tobit model can also be used to estimate the effect of explanatory variables on truncated dependent variables.…”