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Eco-Labelling Of Green Energy Tariffs -Analysis Of The Influence Of Eco-Labels On Consumer Behavior

Lehmann, Nico 1; Beikirch, Philipp 1
1 Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Eco-labels, in the context of energy tariffs, are intended to ensure consumers a sustainable electricity generation. The main objective of this study is to investigate if available eco-labels have an influence on consumers’ choices in electricity tariffs. The study also examines the relative importance of other common attributes of electricity tariffs, namely the type of supplier, the electricity mix, the share of regional generation, and the price. Data was gathered using a two-part stated preference online survey in Germany, with 165 participants in total. In the first part, a Choice-Based Conjoint (CBC) survey was conducted. In the second part of the survey, participants were asked to complete choice tasks following the Maximum Difference Scaling (MaxDiff) methodology. Results using Hierarchical Bayesian (HB) analysis show substantial differences in the two survey parts. While sustainability is most important in the MaxDiff part, CBC results suggest that the price is the decisive factor when choosing an electricity tariff. Furthermore, eco-labels seem to have a big influence on the consumers’ choice behavior. On the contrary, analysis of the general awareness levels reveals that the certification criteria of the eco-labels are unknown to the majority of consumers, often even the labels themselves.

DOI: 10.1109/EEM49802.2020.9221970
Zitationen: 3
Zitationen: 1
Zugehörige Institution(en) am KIT Institut für Industriebetriebslehre und Industrielle Produktion (IIP)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 09.2020
Sprache Englisch
Identifikator ISBN: 978-1-72816-919-4
KITopen-ID: 1000124817
HGF-Programm 37.06.01 (POF III, LK 01) Networks and Storage Integration
Erschienen in 17th International Conference on the European Energy Market, EEM 2020, Stockholm, Sweden, 16 - 18 September 2020
Veranstaltung 17th International Conference on the European Energy Market (EEM 2020), Online, 16.09.2020 – 18.09.2020
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten Art.Nr. 9221970
Schlagwörter eco-labels, renewable energies, consumer behavior, choice-based conjoint,best-worst scaling, hierarchical bayesian estimation, attitude-behavior-gap
Nachgewiesen in Dimensions
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