Details

Autor(en) / Beteiligte

• Häckel, Björn
• Pfosser, Stefan
• Tränkler, Timm

Titel

Explaining the energy efficiency gap - Expected Utility Theory versus Cumulative Prospect Theory

Ist Teil von

• Energy policy, 2017-12, Vol.111, p.414-426

Ort / Verlag

Kidlington: Elsevier Ltd

Erscheinungsjahr

2017

Quelle

PAIS Index

Beschreibungen/Notizen

• Energy efficiency is one of the key factors in mitigating the impact of climate change and preserving non-renewable resources. Although environmental and economic justifications for energy efficiency investments are compelling, there is a gap between the observable and some notion of optimized energy consumption - the so-called energy efficiency gap. Behavioral biases in individual decision making have been resonated by environmental research to explain this gap. To analyze the influence of behavioral biases on decisions upon energy efficiency investments quantitatively, we compare Expected Utility Theory with Cumulative Prospect Theory. On basis of a real-world example, we illustrate how the extent of the gap is influenced by behavioral biases such as loss aversion, probability weighting and framing. Our findings indicate that Cumulative Prospect Theory offers possible explanations for many barriers discussed in literature. For example, the size of the gap rises with increased risk and investment costs. Because behavioral biases are systematic and pervasive, our insights constitute a valuable quantitative basis for environmental policy measures, such as customer-focused and quantitatively backed public awareness campaigns, financial incentives or energy savings insurances. In this vein, this paper may contribute to an accelerated adaption of energy efficiency measures by the broader public. •Quantitative evaluation of energy efficiency investments under different theories.•Cumulative Prospect Theory provides an explanation for the energy efficiency gap.•The extent of the gap rises with risk and initial investment costs.•In Cumulative Prospect Theory, loss aversion is the main driver of the gap.•The analysis enables quantitatively backed behavioral policies.