Sustainability indices for energy utilization using a multi-criteria decision model

Abstract

Abstract Background Energy and water availability are considered vital for a country’s development. An exhaustive review of literature has been undertaken on indicators for sustainable energy development. In addition to energy and water, the resources of the country namely land availability, human capital, and nation’s wealth were also found to be vital for sustainable energy development of any country. These resources have to be optimally used for sustainable energy development which is measured in terms of technical, economic, social, environmental, and institutional indices. Methods In this research, a multi-criteria decision model was used to measure sustainable energy development efficiency. The natural resource of the country was considered as the input criteria, while the indices were used as the output criteria. This research is unique in finding if the country’s resources are being utilized in an efficient manner for sustainable development using the multi-criteria fuzzy-analytical hierarchical processing—data envelopment analysis model. Results From the fuzzy analytical hierarchical processing, it was found that experts were of the opinion that water availability and energy reserves were the most important parameters among the input resources, while environmental and social indices were opined to be the most important parameters among the output indices. Data envelopment analysis model was carried out using assurance region Charnes, Cooper, and Rhodes output-oriented method. The results revealed that Togo was the most efficient country with maximum sustainable energy development efficiency. Sensitivity analysis was also carried out to find which among the resources were sensitive with respect to energy sustainability for a specific country. Conclusion The analysis can help countries to benchmark themselves against the country lying in the efficient frontier and draft policies to improve their energy sustainability indices. Similar analysis and comparison can be done for other countries, since this research analysis was carried out only for 48 developing countries.