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Raw and processed data from face-to-face interviews in women-owned enterprises: Productive use in 27 enterprises across multiple African countries

Authors: Gad, Djalila;

Raw and processed data from face-to-face interviews in women-owned enterprises: Productive use in 27 enterprises across multiple African countries

Abstract

The current body of research on the gender-energy nexus has largely concentrated on the effects of energy poverty within households, highlighting the impact on women in domestic settings. Nonetheless, women entrepreneurs involved in various productive activities are also crucial in adopting new energy technologies. This dataset presents raw and processed data obtained from 27 face-to-face interviews conducted across multiple African countries, focusing on micro and small-sized enterprises with at least one female owner. The data can be used to assess energy access among women entrepreneurs in Africa, focusing on the potential for renewable energy adoption. The data collection through semi-structured, face-to-face interviews occurred between February and September 2023. The semi-structured interviews were guided by a predetermined questionnaire featuring predominantly open-ended questions designed to collect quantitative and qualitative data. The main areas of data collection presented in this dataset span socio-economic factors related to the enterprise and entrepreneur, energy access characteristics including appliances, processes, and energy supply, and the potential for adopting renewable energy technologies, highlighting current barriers to and drivers for future energy access implementation. Key components of the dataset include the following: Socio-economic factors: Enterprise location, ISIC division and industry sector classification, main production goods, gender-based ownership structures, enterprise formality (based on registration), year of establishment or business start, enterprise size (number of employees), profit margins, and business challenges related to the owner's gender. Energy access characteristics: Type of energy carriers used, subapplication, grid blackout or fuel shortage, energy consumption levels, type, number and power rating of appliances used, temperature requirements, and energy expenditure. Potential for renewable energy adoption: Type and amount of process waste, perceived barriers and drivers for renewable energy adoption, willingness to invest in new technologies, and preferred financing methods for these new technologies. The dataset is valuable for researchers, policymakers, and practitioners aiming to understand the energy access landscape for women entrepreneurs in Africa. It provides a foundation for developing targeted interventions that promote gender equity in energy access and foster the adoption of renewable energy technologies. Researchers can use the data to perform analyses of the socio-economic and technical factors influencing energy use in micro- and small-sized enterprises. Policymakers can leverage the insights to design gender-sensitive energy policies and support mechanisms that address the specific needs of women entrepreneurs. Practitioners can develop innovative business models and financing solutions tailored to the unique challenges and opportunities identified in the dataset.

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Keywords

Productive Enterprise in Economic System, Sustainable Business, Sustainability, Africa, Energetics, Entrepreneurship, Social Sciences, Energy Engineering, Renewable Energy, Sustainable Development, Gender Equality, Cleaner Production

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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