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Factors that influence consumers’ acceptance of future energy systems: the effects of adjustment type, production level, and price

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Abstract

To promote the successful introduction of sustainable energy systems, more insight is needed into factors influencing consumer’s acceptance of future energy systems. A questionnaire study among 139 Dutch citizens (aged 18–85) was conducted. Participants rated the acceptability of energy systems made up of four varying system attributes: type of energy (renewable or fossil), price (remains stable vs. 25 % increase), adjustments in use (convenience technology or consumers themselves decide on what to change), and production level (energy is produced at a central vs. community vs. household level). Conjoint analyses were conducted to determine the overall acceptability of future energy systems, the relative importance of the various attributes for acceptability, and preference for levels within each attribute. Interesting patterns were uncovered: participants preferred making adjustments in use themselves (autonomous), rather than relying on technology to make the changes for them. Consumers did not exhibit a clear preference for any of the presented production levels, indicating that they would be open to change in this energy system attribute. Because participants preferred energy systems in which adjustments in use are made autonomously and because adjustment type was very important for overall acceptability of energy systems, technological developers and policy makers should take this into consideration.

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Notes

  1. After discussion with various market parties (energy distribution companies), we decided that 25 % would constitute a plausible price increase.

References

  • Abrahamse, W., & Steg, L. (2013). Social influence approaches to encourage resource conservation: a meta-analysis. Global Environmental Change, 23, 1773–1785.

    Article  Google Scholar 

  • Abrahamse, W., Steg, L., Vlek, C., & Rothengatter, T. (2005). A review of intervention studies aimed at household energy conservation. Journal of Environmental Psychology, 25(3), 273–291.

    Article  Google Scholar 

  • Bolderdijk, J. W., Steg, L., Geller, E. S., Lehman, P. K., & Postmes, T. (2013). Comparing the effectiveness of monetary versus moral motives in environmental campaigning. Nature Climate Change, 3, 413–416.

    Article  Google Scholar 

  • Bolsen, T., & Cook, F. L. (2008). The polls—trends: public opinion on energy policy: 1974–2006. Public Opinion Quarterly, 72(2), 364–388.

    Article  Google Scholar 

  • Börjesson, M., Eliasson, J., Hugosson, M. B., & Brundell-Freij, K. (2012). The Stockholm congestion charges-5 years on. Effects, acceptability and lessons learnt. Transport Policy, 20, 1–12.

  • Burkhardt, J. J., III, Heath, G. A., & Turchi, C. S. (2011). Life cycle assessment of a parabolic trough concentrating solar power plant and the impacts of key design alternatives. Environmental Science and Technology, 45(6), 2457–2464.

    Article  Google Scholar 

  • Clastres, C. (2011). Smart grids: another step towards competition, energy security and climate change objectives. Energy Policy, 39(9), 5399–5408.

    Article  Google Scholar 

  • De Groot, J., & Steg, L. (2008). Value orientations to explain beliefs related to environmental significant behavior: how to measure egoistic, altruistic, and biospheric value orientations. Environment and Behavior, 40(3), 330–354.

    Article  Google Scholar 

  • Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum.

    Book  Google Scholar 

  • Faiers, A., Cook, M., & Neame, C. (2007). Towards a contemporary approach for understanding consumer behaviour in the context of domestic energy use. Energy Policy, 35(8), 4381–4390.

    Article  Google Scholar 

  • Gellings, C. W., & Samotyj. (2013). Smart Grid as advanced technology enabler of demand response. Energy Efficiency. doi:10.1007/s12053-013-9203-0.

    Google Scholar 

  • Gerpott, T. J., & Mahmudova, I. (2010). Determinants of green electricity adoption among residential customers in Germany. International Journal of Consumer Studies, 34(4), 464–473.

    Article  Google Scholar 

  • Green, P. E., & Srinivasan, V. (1990). Conjoint analysis in marketing: new developments with implications for research and practice. Journal of Marketing, 54(4), 3–19.

    Article  Google Scholar 

  • Grothe, O., & Schnieders, J. (2011). Spatial dependence in wind and optimal wind power allocation: a copula-based analysis. Energy Policy, 39(9), 4742–4754.

    Article  Google Scholar 

  • Hansla, A. (2011). Value orientation and framing as determinants of stated willingness to pay for eco-labeled electricity. Energy Efficiency, 4(2), 185–191.

    Article  Google Scholar 

  • Hanssen-Gram, K. (2013). Efficient technologies or user behavior, which is the more important when reducing households’ energy consumption. Energy Efficiency, 6(3), 447–457.

    Article  Google Scholar 

  • Jost, J. T., Banaji, M. R., & Nosek, B. A. (2004). A decade of system justification theory: accumulated evidence of conscious and unconscious bolstering of the status quo. Political Psychology, 25(6), 881–919.

    Article  Google Scholar 

  • Laroche, M., Bergeron, J., & Barbaro-Forleo, G. (2001). Targeting consumers who are willing to pay more for environmentally friendly products. Journal of Consumer Marketing, 18(6), 503–520.

    Article  Google Scholar 

  • Louviere, J. J. (1988). Analyzing decision making: metric conjoint analysis. Newsbury Park: Sage.

    Google Scholar 

  • Marcus, A., & Jean, J. (2009). Going green at home: the Green Machine. Information Design Journal, 17(3), 235–245.

    Article  Google Scholar 

  • Martins, F. R., & Pereira, E. B. (2011). Enhancing information for solar and wind energy technology deployment in Brazil. Energy Policy, 39(7), 4378–4390.

    Article  Google Scholar 

  • Mitchell, T. R., Thompson, L., Peterson, E., & Cronk, R. (1997). Temporal adjustments in the evaluation of events: The “Rosy View”. Journal of Experimental Social Psychology, 33(4), 421–448.

    Article  Google Scholar 

  • Niemeyer, S. (2010). Consumer voices: adoption of residential energy-efficient practices. International Journal of Consumer Studies, 34(2), 140–145.

    Article  Google Scholar 

  • Noppers, E., Keizer, K., Bolderdijk, J. W., & Steg, L. (2014). The adoption of sustainable innovations: driven by symbolic and environmental motives. Global Environmental Change, 25, 52–62.

    Article  Google Scholar 

  • Oldfield, E. (2011). Addressing energy poverty through smarter technology. Bulletin of Science, Technology and Society, 31(2), 113–122.

    Article  Google Scholar 

  • Palmer, K., Walls, M., Gordon, H., & Gerarden, T. (2013). Assessing the energy-efficiency information gap: results from a survey of home energy auditors. Energy Efficiency, 6(2), 271–292.

    Article  Google Scholar 

  • Pelham, B. W., & Blanton, H. (2012). Conducting research in psychology: measuring the weight of smoke. Belmont: Wadsworth.

    Google Scholar 

  • Press, M., & Arnould, E. J. (2009). Constraints on sustainable energy consumption: market system and public policy challenges and opportunities. Journal of Public Policy and Marketing, 28(1), 102–113.

    Article  Google Scholar 

  • Samuelson, W., & Zeckhauser, R. (1988). Status quo bias in decision making. Journal of Risk Uncertainty, 1, 7–59.

    Article  Google Scholar 

  • Sanders, D., Clarke, H. D., Stewart, M. C., & Whiteley, P. (2007). Does mode matter for modeling political choice? Evidence from the 2005 British Election Study. Political Analysis, 15, 257–285.

    Article  Google Scholar 

  • Schuitema, G., Steg, L., & Forward, S. (2010). Explaining differences in acceptability before and acceptance after the implementation of a congestion charge in Stockholm. Transportation Research-A: Policy and Practice, 44(2), 99–109.

    Google Scholar 

  • Schultz, P. W., Gouveia, V. V., Cameron, L. D., Tankha, G., Schmuck, P., & Franzek, M. (2005). Values and their relationship to environmental concern and conservation behavior. Journal of Cross-Cultural Psychology, 36, 457–475.

    Article  Google Scholar 

  • Steg, L., & Abrahamse, W. (2010). How to promote energy savings among households: Theoretical and practical approaches. In V. Corral-Verdugo, C. H. Garcia-Cadena, & M. Frias-Armenta (Eds.), Psychology approaches to sustainability: current trends in theory, research and applications (pp. 61–80). New York: Nova Science Publisher.

    Google Scholar 

  • Steg, L., Perlaviciute, G., Van der Werff, E., & Lurvink, J. (2012). The significance of hedonic values for environmentally-relevant attitudes, preferences and actions. Environment and Behavior. doi:10.1177/0013916512454730.

    MATH  Google Scholar 

  • van Boven, L., & Ashworth, L. (2007). Looking forward, looking back: anticipation is more evocative than retrospection. Journal of Experimental Psychology: General, 136(2), 289–300.

    Article  Google Scholar 

  • Whitehead, J. C., & Cherry, T. L. (2007). Willingness to pay for a Green Energy program: a comparison of ex-ante and ex-post hypothetical bias mitigation approaches. Resource and Energy Economics, 29(4), 247–261.

    Article  Google Scholar 

  • Wood, G., & Newborough, M. (2003). Dynamic energy-consumption indicators for domestic appliances: environment, behaviour and design. Energy and Buildings, 35(8), 821–841.

    Article  Google Scholar 

  • Yeager, D. S., Krosnick, J. A., Chang, L., Javitz, H. S., Levendusky, M. S., Simpser, A., et al. (2011). Comparing the accuracy of RDD telephone surveys and internet surveys conducted with probability and non-probability samples. Public Opinion Quarterly, 75, 709–747.

    Article  Google Scholar 

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Correspondence to Linda Steg.

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Leijten, F.R.M., Bolderdijk, J.W., Keizer, K. et al. Factors that influence consumers’ acceptance of future energy systems: the effects of adjustment type, production level, and price. Energy Efficiency 7, 973–985 (2014). https://doi.org/10.1007/s12053-014-9271-9

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  • DOI: https://doi.org/10.1007/s12053-014-9271-9

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