Goal setting & defaults

We shed light on the question of whether, and to what extent, defaults can help to improve the effectiveness of energy efficiency campaigns.

Working group

Claire-Michelle Loock, Jan Landwehr (Center for Customer Insight, University of St. Gallen), Thorsten Staake

Description

In our study we investigate the role of IT in the stimulation of energy-efficient behavior in private households. The practical motivation for our research is the fact that domestic energy consumption in Western countries has a significant and still-increasing contribution of 20% to 30% to the total world energy use (EEA 2001; EIA 2009), excluding the energy used for transportation, which accounts for an additional share of 29% (EIA 2009). Changing consumption behavior in private households might therefore be an effective lever for increasing energy efficiency on a large scale. However, energy consumption is highly dependent on consumer’s choices and habits (Dimitropoulos 2007). How much effort consumers expend to save electricity, whether they invest in better insulation or more efficient heating and cooling systems, the car they buy and how they drive it, among others, is – within the wide spectrum of effective laws and regulations – ultimately left up to individuals. It is thus crucial to find ways to motivate users to adopt efficient technologies by either influencing the context in which decisions are being made (e.g., by providing incentives) or by targeting an individual’s perceptions, preferences, and abilities (Abrahamse et al. 2005; Allcott & Mullainathan 2010).

For this purpose, we consider defaults as an instrument to nudge consumers towards desirable behavior. Defaults are a well known concept from marketing research that has been examined in the context of one-time purchasing decisions and series of one-time decisions (cf. Park et al. 2000; Choi et al. 2005, Goldstein et al. 2008). A web information portal for electricity customers operated by an Austrian utility company is the technological platform used for our study. In a field study with 1,839 customers, we investigate whether defaults apply for repeated behavior, that is, whether the higher default goals, which require the continuous commitment of the energy consumers, will translate to higher savings.

We found that customers who set a saving goal save 2.85% more electricity than the control group. These results underline the incremental effect of goal setting over feedback and prove the concept’s powerful influence on energy consumption in general. Furthermore, we found that defaults are successful in nudging energy consumers towards higher saving goals. Specifically, our results suggest that when customers are faced with a medium- or high-default goal, they set higher saving goals than those in the low-default-goal condition. However, low- or medium-default levels do not appear to significantly increase the saving goal compared to the no-default condition. Interestingly, although customers in the medium-default condition set on average as high saving goals as those customers in the no-default condition, the former customers are the only ones who save significantly more electricity than the control group. Although we found a significant effect of default level on savings in electricity consumption, only customers in the medium-default condition saved significantly more electricity than the control group.

The findings are highly relevant for the design of efficiency programs and the design of the emerging IT-enabled smart grid infrastructures.

Links

www.vkw.at/velix

 

Contact

Claire-Michelle Loock

References

  • Abrahamse, W., Steg, L., Vlek, C., and Rothengatter, T. 2005. “A review of intervention studies aimed at household energy conservation,” Journal of Environmental Psychology (25), pp. 273-91.
  • Allcott, H. 2010. “Social Norms and Energy Conservation,” Science (327:5970), pp. 1204-1205.
  • Choi, J., Laibson, D., Madrian, C.B., and Metrick, A. 2005. “Optimal defaults and active decisions,” National Bureau of Economic Research, NBER working paper 11074.
  • Dimitropoulos, J. 2007. “Energy productivity improvements and the rebound effect: An overview of the state of knowledge,” Energy Policy (35), pp. 6354–563.
  • EEA. 2001. Indicator Fact Sheet Signals 2001 – Chapter Households, European Environment Agency, Copenhagen, http://www.eea.europa.eu/data-and-maps/indicators/household-energy-consumption/household-energy-consumption
  • EIA. 2009. Annual Energy Review 2009, U.S. Energy Information Administration, Washington, DC, http://www.eia.doe.gov/aer/pdf/aer.pdf
  • Goldstein, D.G., Johnson, E.J., Herrmann, A., and Heitmann, M. 2008. “Nudge your customers toward better choices,” Harvard Business Review (86:12), pp. 99-105.
  • Park, C. W., Jun, S.Y., and MacInnis, D.J. 2000. “Choosing what I want versus rejecting what I do not want: An application of decision framing to product choice options,” Journal of Marketing Research (37:2), pp. 187-202.