Advertisement

Energy Efficiency

, Volume 7, Issue 6, pp 973–985 | Cite as

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

  • Fenna R. M. Leijten
  • Jan Willem Bolderdijk
  • Kees Keizer
  • Madelijne Gorsira
  • Ellen van der Werff
  • Linda StegEmail author
Original Article

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.

Keywords

Energy systems Consumer acceptance Conjoint analyses Autonomous Convenience 

References

  1. Abrahamse, W., & Steg, L. (2013). Social influence approaches to encourage resource conservation: a meta-analysis. Global Environmental Change, 23, 1773–1785.CrossRefGoogle Scholar
  2. 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.CrossRefGoogle Scholar
  3. 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.CrossRefGoogle Scholar
  4. Bolsen, T., & Cook, F. L. (2008). The polls—trends: public opinion on energy policy: 1974–2006. Public Opinion Quarterly, 72(2), 364–388.CrossRefGoogle Scholar
  5. 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.Google Scholar
  6. 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.CrossRefGoogle Scholar
  7. Clastres, C. (2011). Smart grids: another step towards competition, energy security and climate change objectives. Energy Policy, 39(9), 5399–5408.CrossRefGoogle Scholar
  8. 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.CrossRefGoogle Scholar
  9. Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum.CrossRefGoogle Scholar
  10. 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.CrossRefGoogle Scholar
  11. 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
  12. 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.CrossRefGoogle Scholar
  13. 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.CrossRefGoogle Scholar
  14. Grothe, O., & Schnieders, J. (2011). Spatial dependence in wind and optimal wind power allocation: a copula-based analysis. Energy Policy, 39(9), 4742–4754.CrossRefGoogle Scholar
  15. Hansla, A. (2011). Value orientation and framing as determinants of stated willingness to pay for eco-labeled electricity. Energy Efficiency, 4(2), 185–191.CrossRefGoogle Scholar
  16. 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.CrossRefGoogle Scholar
  17. 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.CrossRefGoogle Scholar
  18. 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.CrossRefGoogle Scholar
  19. Louviere, J. J. (1988). Analyzing decision making: metric conjoint analysis. Newsbury Park: Sage.Google Scholar
  20. Marcus, A., & Jean, J. (2009). Going green at home: the Green Machine. Information Design Journal, 17(3), 235–245.CrossRefGoogle Scholar
  21. Martins, F. R., & Pereira, E. B. (2011). Enhancing information for solar and wind energy technology deployment in Brazil. Energy Policy, 39(7), 4378–4390.CrossRefGoogle Scholar
  22. 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.CrossRefGoogle Scholar
  23. Niemeyer, S. (2010). Consumer voices: adoption of residential energy-efficient practices. International Journal of Consumer Studies, 34(2), 140–145.CrossRefGoogle Scholar
  24. 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.CrossRefGoogle Scholar
  25. Oldfield, E. (2011). Addressing energy poverty through smarter technology. Bulletin of Science, Technology and Society, 31(2), 113–122.CrossRefGoogle Scholar
  26. 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.CrossRefGoogle Scholar
  27. Pelham, B. W., & Blanton, H. (2012). Conducting research in psychology: measuring the weight of smoke. Belmont: Wadsworth.Google Scholar
  28. 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.CrossRefGoogle Scholar
  29. Samuelson, W., & Zeckhauser, R. (1988). Status quo bias in decision making. Journal of Risk Uncertainty, 1, 7–59.CrossRefGoogle Scholar
  30. 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.CrossRefGoogle Scholar
  31. 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
  32. 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.CrossRefGoogle Scholar
  33. 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
  34. 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.zbMATHGoogle Scholar
  35. 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.CrossRefGoogle Scholar
  36. 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.CrossRefGoogle Scholar
  37. Wood, G., & Newborough, M. (2003). Dynamic energy-consumption indicators for domestic appliances: environment, behaviour and design. Energy and Buildings, 35(8), 821–841.CrossRefGoogle Scholar
  38. 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.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Fenna R. M. Leijten
    • 1
  • Jan Willem Bolderdijk
    • 1
  • Kees Keizer
    • 1
  • Madelijne Gorsira
    • 1
  • Ellen van der Werff
    • 1
  • Linda Steg
    • 1
    Email author
  1. 1.Faculty of Behavioural and Social SciencesUniversity of GroningenGroningenThe Netherlands

Personalised recommendations