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Digital transformation of energy allocation: From data transparency to socio-economic justice

Author

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  • Victor Zamlynskyi
  • Stanislav Gorodnichenko

Abstract

The relevance stems from the fact that, under the conditions of war and post-war recovery in Ukraine, the digital transformation of energy governance is becoming a key instrument for overcoming energy poverty, regional disparities, and a crisis of trust in energy policy. The organisation of digital energy allocation determines the social legitimacy of the energy transition and the recovery model. The purpose of the article was to substantiate the concept of digitally fair energy allocation and to develop a methodological framework for assessing the impact of digital tools on social justice and economic efficiency in distribution systems. The study systematised contemporary approaches to energy justice, analysed digital technologies in the energy sector, and applied comparative and systems analysis methods. On this basis, a conceptual “data-trust-justice” framework was developed, and a quasi-experimental design for evaluating digital allocation policies at the feeder level was formulated. The research established that the traditional centralised model of energy allocation, built on fragmented data and low transparency, reproduces regional disparities, energy poverty, and distrust towards regulatory decisions. Within the study, a new concept of “digitally fair energy allocation” was developed, combining economic efficiency and transparency with guaranteed access to basic energy services for vulnerable groups. The role of intelligent metering systems, big data analytics, artificial intelligence methods, and blockchain-based registries in forming an integrated “data-trust-justice” chain was analysed. A structure of digital allocation scenarios based on different principles of distributive justice was proposed, and measurable targets of implementation for distribution system operators were defined. The results showed that integrating justice criteria into digital allocation models helps to avoid socially regressive outcomes and strengthens the legitimacy of energy policy. The findings can be used by regulators, distribution system operators, central and local authorities, and energy and infrastructure project managers to design, monitor, and evaluate digital reforms in energy allocation, while considering principles of social equality and economic security

Suggested Citation

  • Victor Zamlynskyi & Stanislav Gorodnichenko, 2025. "Digital transformation of energy allocation: From data transparency to socio-economic justice," Innovation and Sustainability Articles, Innovation and Sustainability, vol. 5(4), pages 97-107, December.
  • Handle: RePEc:cve:innsjn:v:5:y:2025:i:4:p:97-107
    DOI: https://doi.org/10.31649/vis/4.2025.97
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