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Digital Demand-Side Management and Energy Justice: Understanding Engagement Profiles and Responses to Automation

Quantitative
Narratives
Survey Research
Technology
Empirical
Energy
Selin Yilmaz
Université de Lausanne
Selin Yilmaz
Université de Lausanne

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Abstract

Energy transitions are increasingly governed through digitally enabled instruments such as automated demand-side management (DSM), which rely on narratives of flexibility, participation, and collective benefit to enrol households in managing their household energy demand via the smart technologies they own. Yet these narratives often presume an “ideal” energy subject, rational, technologically competent, and able to adapt everyday practices through automation, raising critical questions of whose capacities and values are recognised in the energy transition projects. This paper investigates how individuals respond to demand-side management (DSM) narratives that emphasise community benefit, local grid support, and national energy crisis, with a particular focus on digitally enabled and automated solutions with data sharing. Using a profiling approach and empirical evidence from a survey, it identifies distinct engagement profiles that differ in their acceptance to change everyday energy practices through digital tools such as smart devices, automation, and data-driven control, as well as in their levels of socio-technical capacities that varied strongly across different social groups. Early results show that automated and digitalized forms of DSM are not perceived uniformly: while some profiles view automation as enabling flexibility and collective contribution, others experience it as constraining, opaque, or exclusionary. This paper contributes to debates on recognition justice by demonstrating how governance narratives and technological designs actively constitute who is seen as a legitimate participant in the energy transition. Building on these findings, the paper develops considerations about the justice and legitimacy implications of digital DSM programs, highlighting how automation can be designed and governed in ways that are inclusive, transparent, and responsive to diverse capacities and preferences.