<p>The digitalisation of energy systems presents both opportunities and sustainability challenges. While digital innovations can improve efficiency and resilience, they often entail hidden environmental and social costs, complicated by uncertainty and data opacity. This study examines how Multi-Criteria Decision Analysis (MCDA) can guide responsible digitalisation choices in the energy sector. It proposes a framework tailored to contexts characterised by high uncertainty, limited data availability, and diverse stakeholder perspectives. By structuring trade-offs and prioritising sustainable outcomes, the framework supports decision-makers in selecting digital strategies that maximise net societal benefits while minimising negative spill-overs. Empirical applications illustrate its practical relevance, highlighting how uncertainty integration and method selection can be operationalised to strengthen decision support. This study also contributes by integrating stochastic modelling into MCDA frameworks, providing a structured method to manage uncertainty in sustainability-oriented digital energy decisions. This research advances the field of energy decision analysis by demonstrating the value of MCDA in navigating complex, uncertain digitalisation pathways and by offering actionable insights for practitioners committed to sustainable energy transitions.</p>

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A stochastic multi-criteria decision analysis framework for responsible energy digitalisation

  • Aiste Rugeviciute,
  • Davide La Torre,
  • Vincent Courboulay

摘要

The digitalisation of energy systems presents both opportunities and sustainability challenges. While digital innovations can improve efficiency and resilience, they often entail hidden environmental and social costs, complicated by uncertainty and data opacity. This study examines how Multi-Criteria Decision Analysis (MCDA) can guide responsible digitalisation choices in the energy sector. It proposes a framework tailored to contexts characterised by high uncertainty, limited data availability, and diverse stakeholder perspectives. By structuring trade-offs and prioritising sustainable outcomes, the framework supports decision-makers in selecting digital strategies that maximise net societal benefits while minimising negative spill-overs. Empirical applications illustrate its practical relevance, highlighting how uncertainty integration and method selection can be operationalised to strengthen decision support. This study also contributes by integrating stochastic modelling into MCDA frameworks, providing a structured method to manage uncertainty in sustainability-oriented digital energy decisions. This research advances the field of energy decision analysis by demonstrating the value of MCDA in navigating complex, uncertain digitalisation pathways and by offering actionable insights for practitioners committed to sustainable energy transitions.