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Understanding technology ownership to reveal adoption trends for energy efficiency measures in the Greek residential sector

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  • Spyridaki, Niki-Artemis
  • Stavrakas, Vassilis
  • Dendramis, Yiannis
  • Flamos, Alexandros

Abstract

This article explores technology ownership patterns to reveal adoption trends for energy efficiency measures (EEMs) in the Greek residential sector. To do so, we couple observational survey data with discrete choice modeling. Household preferences are revealed through EEMs owned by Greek householders, after having been questioned for a variety of end-use measures and details about their specification. Our results confirm prior evidence on traditional determinants οf technology adoption and extend those by validating that households familiar with information and communication technologies (ICTs) are more likely to own EEMs with smart features. We were also able to highlight the positive influence of participation in subsidy, as well as other support programmes for vulnerable consumers in households’ ownership of EEMs. Our results are then used to simulate the change in technology ownership rates, under no and full participation in a subsidy programme, for three income levels. Simulation outcomes suggest that, for almost all EEMs, the probability for technology ownership is greater for higher-income households benefitting from a subsidy. Nevertheless, the change in the probability of technology ownership due to the subsidy is larger for low- and medium-income households participating in the programme, further encouraging, thus, support for financial policies targeting lower-income households.

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  • Spyridaki, Niki-Artemis & Stavrakas, Vassilis & Dendramis, Yiannis & Flamos, Alexandros, 2020. "Understanding technology ownership to reveal adoption trends for energy efficiency measures in the Greek residential sector," Energy Policy, Elsevier, vol. 140(C).
  • Handle: RePEc:eee:enepol:v:140:y:2020:i:c:s030142152030166x
    DOI: 10.1016/j.enpol.2020.111413
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    2. Elissaios Sarmas & Vangelis Marinakis & Haris Doukas, 2022. "A data-driven multicriteria decision making tool for assessing investments in energy efficiency," Operational Research, Springer, vol. 22(5), pages 5597-5616, November.
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    4. Ahmad, Munir & Khan, Irfan & Shahzad Khan, Muhammad Qaiser & Jabeen, Gul & Jabeen, Hafiza Samra & Işık, Cem, 2023. "Households' perception-based factors influencing biogas adoption: Innovation diffusion framework," Energy, Elsevier, vol. 263(PE).
    5. Chappin, Emile J.L. & Schleich, Joachim & Guetlein, Marie-Charlotte & Faure, Corinne & Bouwmans, Ivo, 2022. "Linking of a multi-country discrete choice experiment and an agent-based model to simulate the diffusion of smart thermostats," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    6. Koasidis, Konstantinos & Marinakis, Vangelis & Nikas, Alexandros & Chira, Katerina & Flamos, Alexandros & Doukas, Haris, 2022. "Monetising behavioural change as a policy measure to support energy management in the residential sector: A case study in Greece," Energy Policy, Elsevier, vol. 161(C).
    7. Tzani, Dimitra & Stavrakas, Vassilis & Santini, Marion & Thomas, Samuel & Rosenow, Jan & Flamos, Alexandros, 2022. "Pioneering a performance-based future for energy efficiency: Lessons learnt from a comparative review analysis of pay-for-performance programmes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).

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