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Antecedents and outcomes of participation in local energy communities: A mixed-methods longitudinal study
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Resumo(s)
Local energy communities (LECs) have gained substantial momentum across Europe and worldwide due to their integration of sustainable technologies that enable decentralised renewable energy production and foster collaboration among community actors. Despite this rapid growth, a holistic examination of both the antecedents and outcomes of participation in LECs remains limited. To address this gap, this thesis adopts a mixed-methods approach comprising three complementary studies. Study 1 employs a qualitative design, based on interviews with community members to identify key outcomes of participation in LECs. Study 2 uses a longitudinal quantitative approach to develop and test a Belief-Action-Outcome (BAO) model through partial least squares structural equation modelling (PLS-SEM), drawing on data collected across two time periods (2023 for antecedents; 2025 for outcomes) from individuals in five European countries. Study 3 provides a corroborative qualitative analysis that triangulates findings from the first two studies, enabling an assessment of convergence and divergence from the two previous studies. The results reveal that empowerment and frequency of sustainable technology use significantly promote participation in LECs, and that this participation, in turn, positively influences community environmental performance, perceived well-being, and energy poverty alleviation. A cross-country analysis shows that while the main findings hold across different cultural contexts, Türkiye exhibits a distinct positive cultural effect on energy poverty alleviation. Taken together, the corroborative qualitative findings show strong overall convergence with the quantitative results, while also explaining context-dependent differences, particularly regarding diversity of use. This research offers theoretical contributions to the understanding of digital and community-based sustainability transitions and provides actionable implications for policymakers and LEC practitioners.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
Palavras-chave
Local energy communities longitudinal study PLS-SEM antecedents outcomes mixed-methods