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Exploring the Interplay between Structural Factors, Environmental Concern, Personal Norm, and Household Electricity Consumption

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  • Habibi Asgarabad, Mojtaba

    (Norwegian University of Science and Technology)

  • Vesely, Stepan
  • Klöckner, Christian Andreas

    (Norwegian University of Science and Technology)

Abstract

Background and Aims: In the context of the ENCHANT project, we conducted a clustering analysis to categorize Norwegian participants in an electricity-saving program based on environmental concerns, personal norms, gender, educational level, social status, age, family size, and the ages of their children. Subsequently, we examined variations in Electricity Consumption per person normalized to seven days (EC), the access to Electricity Assets in the Household (EAH), Perceived Behavioral Control of electricity-saving tips (PBC), and Energy Poverty Risk (EPR) across different clusters. Participants: A sample of 1,135 Norwegians (508 females; mean age = 49.14, SD age = 12.86; age range = 23–86) participated in the study. Results: Two-step cluster analysis resulted in five distinct clusters: (i) multi-generational households with moderate concern, (ii) eco-ease in midlife, (iii) middle-aged females in medium-sized households, (iv) growing families with moderate concerns, and (v) moderate advocates with adolescents. Analysis of variance indicated significant variations in mean scores of EC, access to EAH, and PBC across clusters (p < .01), with no significant difference in terms of the REP among the clusters (p > .05). Discussion: Discernible pattern indicated that families with teenagers, characterized by a lower environmental concern, tend to exhibit higher electricity usage per person compared to their counterparts with moderate and high environmental concern, even in instances where there are old-aged parents present. This information can guide targeted strategies to promote electricity efficiency, especially for younger families and those with teenagers, who may face distinct challenges in adopting electricity-saving practices. Building on these findings, future research could delve deeper into the specific challenges that younger families and households with teenagers encounter in adopting electricity-saving practices. Key messages: 1. Our finding highlights the predominant influence of structural factors, such as household size and the number and age of children, on electricity consumption patterns. 2. Clusters with moderate environmental concern displayed variations in electricity use, challenging the assumption that higher environmental concern necessarily leads to lower energy consumption. 3. The identified clusters, each with distinct profiles and behaviors, suggest the need for tailored interventions.

Suggested Citation

  • Habibi Asgarabad, Mojtaba & Vesely, Stepan & Klöckner, Christian Andreas, 2024. "Exploring the Interplay between Structural Factors, Environmental Concern, Personal Norm, and Household Electricity Consumption," OSF Preprints gd5ra, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:gd5ra
    DOI: 10.31219/osf.io/gd5ra
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    References listed on IDEAS

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    1. Guomin Li & Wei Li & Zihan Jin & Zhihao Wang, 2019. "Influence of Environmental Concern and Knowledge on Households’ Willingness to Purchase Energy-Efficient Appliances: A Case Study in Shanxi, China," Sustainability, MDPI, vol. 11(4), pages 1-18, February.
    2. Sapci, Onur & Considine, Timothy, 2014. "The link between environmental attitudes and energy consumption behavior," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 52(C), pages 29-34.
    3. Heidi Bruderer Enzler & Andreas Diekmann, 2015. "Environmental Impact and Pro-Environmental Behavior: Correlations to Income and Environmental Concern," ETH Zurich Sociology Working Papers 9, ETH Zurich, Chair of Sociology.
    4. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
    5. Veronica Distefano & Maria Mannone & Irene Poli, 2023. "Exploring Heterogeneity with Category and Cluster Analyses for Mixed Data," Stats, MDPI, vol. 6(3), pages 1-16, July.
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