Shadow economy and energy efficiency: utilising goal programming for sustainability assessment
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Date
2025-08-07
Open Access Location
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science+Business Media, LLC
Rights
(c) 2025 The Author/s
CC BY 4.0
CC BY 4.0
Abstract
This paper combined different methods of operations research, goal programming, and unsupervised machine learning into a single framework to examine energy efficiency across the globe. Using the latest data from 131 countries in 2017, our empirical findings reveal different patterns of energy efficiency among countries and country groups under both the meta-frontier and group-frontiers. We found an inequality in production technology for many countries, which made it difficult for them to improve their energy efficiency. Importantly, our analysis also reveals that the size of the shadow economy has a small but negative impact on energy efficiency. Consequently, we suggest that governments should (i) pay more attention to the shadow economy, (ii) increase investments in education and human capital, and (iii) strengthen their institutions.
Description
Keywords
Meta-frontier, Data envelopment analysis (DEA), Goal programming (GP), Euclidean common set of weights (ECSW), Sustainability, Machine learning (ML)
Citation
Alharbi SS, Boubaker S, Ngo T, Yuen MK. (2025). Shadow economy and energy efficiency: utilising goal programming for sustainability assessment. Annals of Operations Research. Latest Articles.