Energy consumption and savings: A survey-based study of Finnish households

Abstract

Energy has moved to the forefront in societal and economic development. Our homes and real estate are more and more dependent on electricity. In order to reach the full potential for new consumer-oriented market mechanisms and in order to fulfil climate policy targets we need more information on consumers’ behaviour and attitudes towards energy. This paper uses a survey to examine the attitudes and behaviour of households' energy-related issues. The analytical framework used is based on ordered choice and probability models. The objective is to identify households' characteristics that affect energy consumption and savings, attitudes towards climate change and conservation of natural resources, and the importance of municipal energy-related issues. According to the results, the importance of reduction in electricity consumption is positively correlated with attitudes towards mitigation of climate change and importance of renewable energy. Heating system of residence, income, and gender affect attitude and behaviour. Interestingly, the higher the income the less important is electricity reduction. Women have changed their behaviour in order to reduce electricity consumption more than men. Utilising this information it is possible for society to build efficient mechanisms, such as real-time pricing, through which we can affect consumers' energy-related behaviour and give incentives for energy savings and efficiency. One interesting result is also that over 80% of the respondents view municipalities' energy efficiency as very important.

Keywords:

• attitudes
• energy consumption
• households
• survey
• ordered probit

Notes

 1. Other possible approaches such as choice experiment method (see e.g. Bergman et al. 2008, Scarpa and Willis 2010, Juutinen et al. 2011) would have required more detailed data on households' willingness-to pay characteristics.

 2. This argument is based on the co-generation in heat and power, systematic energy audits and relatively large coverage of energy efficiency agreements.

 3. For the estimation of electricity demand function and analysis of electricity demand (see e.g. Dubin 1985, Flaig 1990, Filippini 1999).

 4. Personal domain includes individuals' basic values (Stern 1999, Stern et al. 1999).

 5. For broader definition of contextual domain see Stern 1999.

 6. See page http://www.ymparisto.fi/default.asp?node=22737&lan=en for more detailed description of the project.

 7. Especially those concerning housing, transportation and food.

 8. Answer to this category are from 4=very big threat to 1=not threat at all.

 9. Model specific intercepts values are excluded from the presentation of the model equations.

10. Before analysing question Ib we check the correlations between the answers of questions Ib and the actual behaviour of respondents. Actual behaviour was measured through the question “What actions you have done during the last year in order to reduce your electricity consumption”. We find clear correlation among the answer between these questions. Correlation value is (R) = 0.4894, p ≤ 8.366e–26.

11. Holland and Mansur (2008) argue that when coal provides the base load power and gas-fired stations are used in peak load periods, RTP is likely to increase greenhouse gases, but for those systems which rely less on coal, consumption smoothing as a result on RTP can potentially benefit the environment.