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What do people ‘learn by looking’ at direct feedback on their energy consumption? Results of a field study in Southern France

Author

Listed:
  • Adnane Kendel
  • Nathalie Lazaric
  • Kevin Maréchal

Abstract

The abundant literature on consumer feedback shows that it is an efficient instrument for reducing household energy consumption. However, the reported reductions are strongly dependent on contextual factors and on the type of feedback provided. Given the importance of learning to this respect, this dimension constitutes the core focus of the present study which reports the findings of the TICELEC (i.e. French acronym for information technologies for responsible electricity consumption) project in France. The experiment included a control group (G1: the self-monitoring group) and one equipped group (G2). All participants reduced their consumption and learnt either directly from feedback or indirectly through self-monitoring. The amount of energy savings, which is larger than in similar experiments, can be explained by two factors. First, the specificity of our sample (i.e. high income, high consumption) which allows for potentially large energy savings. Second, high involvement of participants and the building of trust. The quantitative and qualitative dimensions of learning are then discussed. Additionally, we focus on peak-load shifting in G2 with 2 subgroups (G21 and G22). The higher proportion of shifters in G22 and the higher ‘quality’ of their shifting suggest a higher level of learning enabled by the more sophisticated feedback. Although this translated into only a moderately higher rate of energy savings, the higher degree of absorbed knowledge (i.e. through ‘learning by looking through connecting’) might lead to a qualitatively distinctive type of energy saving.

Suggested Citation

  • Adnane Kendel & Nathalie Lazaric & Kevin Maréchal, 2017. "What do people ‘learn by looking’ at direct feedback on their energy consumption? Results of a field study in Southern France," ULB Institutional Repository 2013/261826, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:ulb:ulbeco:2013/261826
    Note: SCOPUS: ar.j
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    Cited by:

    1. Morgane Innocent & Agnès François-Lecompte & Nolwenn Roudaut, 2020. "Comparison of human versus technological support to reduce domestic electricity consumption in France," Post-Print hal-02450849, HAL.
    2. Crago, Christine L. & Spraggon, John M. & Hunter, Elizabeth, 2020. "Motivating non-ratepaying households with feedback and social nudges: A cautionary tale," Energy Policy, Elsevier, vol. 145(C).
    3. Lazaric, Nathalie & Toumi, Mira, 2022. "Reducing consumption of electricity: A field experiment in Monaco with boosts and goal setting," Ecological Economics, Elsevier, vol. 191(C).
    4. Belaïd, Fateh & Youssef, Adel Ben & Lazaric, Nathalie, 2020. "Scrutinizing the direct rebound effect for French households using quantile regression and data from an original survey," Ecological Economics, Elsevier, vol. 176(C).
    5. Batalla-Bejerano, Joan & Trujillo-Baute, Elisa & Villa-Arrieta, Manuel, 2020. "Smart meters and consumer behaviour: Insights from the empirical literature," Energy Policy, Elsevier, vol. 144(C).
    6. Belaïd, Fateh & Ranjbar, Zeinab & Massié, Camille, 2021. "Exploring the cost-effectiveness of energy efficiency implementation measures in the residential sector," Energy Policy, Elsevier, vol. 150(C).
    7. Innocent, Morgane & Francois-Lecompte, Agnès, 2018. "The values of electricity saving for consumers," Energy Policy, Elsevier, vol. 123(C), pages 136-146.
    8. Amel Attour & Marco Baudino & Jackie Krafft & Nathalie Lazaric, 2020. "Determinants of smart energy tracking application use at the city level: Evidence from France," Post-Print hal-02942483, HAL.
    9. Gautier, Axel & Hoet, Brieuc & Jacqmin, Julien & Van Driessche, Sarah, 2019. "Self-consumption choice of residential PV owners under net-metering," Energy Policy, Elsevier, vol. 128(C), pages 648-653.
    10. Fouad, M.M. & Kanarachos, Stratis & Allam, Mahmoud, 2022. "Perceptions of consumers towards smart and sustainable energy market services: The role of early adopters," Renewable Energy, Elsevier, vol. 187(C), pages 14-33.
    11. Christophe Charlier, Gilles Guerassimoff, Ankinée Kirakozian, and Sandrine Selosse, 2021. "Under Pressure! Nudging Electricity Consumption within Firms. Feedback from a Field Experiment," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 129-154.
    12. Innocent, Morgane & Francois-Lecompte, Agnes & Roudaut, Nolwenn, 2020. "Comparison of human versus technological support to reduce domestic electricity consumption in France," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    13. Nathalie Lazaric & Mira Toumi, 2021. "Boosting Citizens Towards Reduced Energy Consumption: A Field Experiment in the Principality of Monaco," GREDEG Working Papers 2021-17, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    14. Belaïd, Fateh, 2022. "Mapping and understanding the drivers of fuel poverty in emerging economies: The case of Egypt and Jordan," Energy Policy, Elsevier, vol. 162(C).
    15. Attour, Amel & Baudino, Marco & Krafft, Jackie & Lazaric, Nathalie, 2020. "Determinants of energy tracking application use at the city level: Evidence from France," Energy Policy, Elsevier, vol. 147(C).
    16. Aladejare, Samson Adeniyi, 2025. "The role of natural resource wealth and national-level economic forces in energy poverty intensity in African economies," Resources Policy, Elsevier, vol. 106(C).
    17. Paolo Zangheri & Tiago Serrenho & Paolo Bertoldi, 2019. "Energy Savings from Feedback Systems: A Meta-Studies’ Review," Energies, MDPI, vol. 12(19), pages 1-18, October.
    18. Bernadeta Gołębiowska & Anna Bartczak & Wiktor Budziński, 2019. "Impact of social comparison on DSM in Poland," Working Papers 2019-10, Faculty of Economic Sciences, University of Warsaw.
    19. Jorge Antunes & Rangan Gupta & Zinnia Mukherjee & Peter Wanke, 2022. "Information entropy, continuous improvement, and US energy performance: a novel stochastic-entropic analysis for ideal solutions (SEA-IS)," Annals of Operations Research, Springer, vol. 313(1), pages 289-318, June.

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    Keywords

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    JEL classification:

    • D10 - Microeconomics - - Household Behavior - - - General
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D13 - Microeconomics - - Household Behavior - - - Household Production and Intrahouse Allocation
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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