Raw data to paper "Productive use of energy of women-owned micro-, small-, and medium-sized enterprises: Insights from food and textile businesses in selected African countries"
Description
This study investigates to what extent the gender of the enterprise owner impacts the productive use of energy. Specifically, it explores how women and men differ in their productive use within micro, small, and medium-sized enterprises (MSME). Data collection methodology: - Period: January 2023 to January 2024. - Sampling Approach: Deliberate and convenience sampling. - Data Collection Tool: Structured questionnaire distributed via a web-based platform. Description of data: The dataset offers a gender-focused analysis of productive energy use, assessing 65 women-owned food and textile businesses across seven African countries: Egypt, Ghana, Kenya, Malawi, Nigeria, Tanzania, and Tunisia. These data complement the research article by providing in-depth insights into energy use patterns and business profiles. Structure of the dataset: - Sheet 1: This sheet contains the cleaned initial responses from participants, with basic assumptions added for calculation clarity and transparency. - Sheet 2: This sheet contains analysed data and calculations as presented in the accompanying research paper. It covers business profiles, legal statuses of women-owned enterprises, energy use patterns (demand levels, types of energy carriers, access type), and energy expenditure. Notable findings: 1. Energy carriers: Female-owned businesses typically rely on one or two energy carriers, whereas female-male co-owned enterprises use multiple energy carriers. 2. Fuel use: A variance in fuel use among different ownership structures is observed, with diesel, biomass, and liquefied petroleum gas being notable choices. 3. Awareness and demand levels: Increasing ownership diversity correlates with greater awareness of energy metrics and higher monthly demand for electric and mechanical power. A similar trend - with some variance - is observed for thermal energy. 4. Energy expenditure: Enterprises with diverse ownership structures tend to have lower energy expenditure per kilogram of production output (USD/kg/month). Some sole female-owned enterprises have energy expenditures exceeding 100 USD/kg/month, female-female partnerships may reach 100 USD/kg/month while female-male co-owned enterprises stay below 10 USD/kg/month. Conclusions and recommendations: This research highlights the importance of understanding gendered productive energy practices and the need for gender mainstreaming in energy access and use interventions. It underscores the necessity for renewable energy solutions and capacity-building programs to address the efficiency and accessibility challenges women entrepreneurs face. Additionally, it recommends further research to enhance the efficiency and sustainability of energy use in women-owned enterprises. Use of data: Researchers, policymakers, and practitioners can use this data to develop targeted energy access interventions for women-owned MSME, and design renewable energy solutions tailored to the specific needs of female entrepreneurs.
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Steps to reproduce
The data was gathered using a structured web-based questionnaire and analysed using Microsoft Excel for a descriptive study. Key steps included: 1. Data cleaning: Each response was cross-checked against predetermined criteria and indicators ensuring accuracy and relevance. 2. Inclusion criteria: Only enterprises with at least one female owner, categorised as a micro, small, or medium-sized enterprise (based on employee numbers), and engaged in productive use activities in the food or textile sectors (as per ISIC) were included. Duplicated responses were removed. 3. Segregation and classification: Responses were segregated by country, industry sector and gender-based ownership structure. Enterprises were classified into three categories: (i) sole female-owner, (ii) female-female partnerships, and (iii) female-male co-owned enterprises. 4. Energy demand estimation: Monthly electrical, mechanical, and thermal demands were estimated based on the business activity, production value chain, final production output, and energy carriers used. Energy demand levels were standardised to kilowatt-hours equivalent (kWheq) per month, and production outputs were converted to kilograms (kg) per month. Financial data was converted to USD using average conversion rates for 2022. 5. On-grid vs. off-grid classification: Enterprises not using grid electricity were classified as off-grid. Locations were cross-checked with Africa Grid data to verify potential grid access. For more details, kindly refer to the full research article titled "Productive use of energy of women-owned micro-, small-, and medium-sized enterprises: Insights from food and textile businesses in selected African countries".