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This research examines the ethical and social dimensions of optimization in energy applications, emphasizing their interpretive nature.

June 12, 2026Open Access

From models to meaning - an autoethnographic path toward a reflexive framework for interpreting human and ethical dimensions in energy system optimization

Key Points

This research examines the ethical and social dimensions of optimization in energy applications, emphasizing their interpretive nature.
Utilized an autoethnographic approach based on ten years of interdisciplinary experience in academia, industry, and education.
Investigated energy-related optimization applications including electric vehicle charging and sustainable logistics.
Developed a reflexive framework to analyze how model outputs are negotiated and interpreted.
Optimization models are shown to be interpretive, gaining meaning through stakeholder interactions and narratives.
Found ethical tensions like efficiency versus social responsibility in modeling practices are central to decision-making processes.
Proposed a framework that promotes more context-aware and ethically informed decision-support approaches.

Abstract

Abstract This study explores the ethical, social and interpretive aspects underlying the application of optimization to real-world decision-making, with special emphasis on energy-related applications. Based on ten years of interdisciplinary experience across academia, industry, and education, this research investigates how abstract optimization models gain meaning in practice within energy informatics applications such as electric vehicle charging, battery systems, energy system planning, and sustainable logistics. In this work, an autoethnographic approach is used to show that modeling is not only a technical activity, but also a highly interpretive process shaped by values such as efficiency, fairness, and accountability, as well as by the need to balance formal simplicity with complex stakeholder realities. Building on these insights the study proposes a reflexive framework that conceptualizes optimization as a meaning-making practice, with the objective of capturing how model outputs are constructed, interpreted, and negotiated across different contexts. The findings show that optimization models do not generate purely objective solutions. At the same time their outputs acquire meaning and authority through processes of framing, storytelling, and interaction with stakeholders. Ethical tensions, such as those between technical elegance and social responsibility, or between abstraction and contextual complexity, emerge as central features of modeling practice and are often managed through informal negotiation and compromise. This paper advances the understanding of optimization as a socially embedded practice, by introducing a structured framework grounded in empirical and reflexive analysis. It contributes to ongoing discussions in operations research and energy informatics by providing a conceptual lens for interpreting the human dimensions of modeling, and by supporting more reflective, context-aware, and ethically informed approaches to decision support.

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