• Shimon ELBAZ
  • Adriana ZAIŢ




electricity demand, energy efficiency, behavioral economics, neoclassical economics, consumer behavior


Purpose: The present study investigated the main literature on the subject of methods and policies for reducing the electricity demand of domestic consumers, in order to identify the place of behavioral tools.Methodology: We used secondary sources, performing a literature review, together with analysis and synthesis. Findings: Policy makers prefer to use tools offered by neoclassical economics, such as various forms of taxation, fines and financial incentives in order to make domestic electricity consumers save electricity, on the assumption that consumers will make rational decisions while maximizing their personal benefit. However, studies conducted in recent years in the field of behavioral economics, which are based on the assumption that consumers’ decisions are not rational and are affected by cognitive biases, showed that the use of behavioral tools, such as detailed online information (feedback),social comparison information, information on varying rates (dynamic pricing) and general information (advertising campaign), are tools that are not less appropriate than the ones the neoclassical economics offers, mainly because electricity is an invisible product and consumers are unable to assess it by normal cognitive measures. Using an interdisciplinary combination of behavioral tools that come from a variety of approaches taken from a wide variety of different academic fields, it is possible to receive efficient results in the endeavor of reducing electricity demand. Implications: Although the neoclassical economics still remains the fundamental theory used by policymakers, it is recommended to consider behavioral economics as a complementary approach to the neoclassical economics, and combine behavioral tools in the policymakers’ toolbox, especially when those tools do not require a significant financial investment, thus efficiently maximizing the reduction of electricity demand among domestic consumers. These theoretical results will be used for designing future empirical researches on the efficiency of behavioral tools in changing the pattern of electricity consumers’ behavior.

JEL Codes - Q40, M21, M38, H41


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(3), 273-291. doi: http://dx.doi.org/10.1016/j.jenvp.2005.08.002

Allcott, H., 2011. Social norms and energy conservation. Journal of Public Economics, 95(9-10), 1082-1095. doi: http://dx.doi.org/10.1016/j.jpubeco.2011.03.003

Allcott, H., and Mullainathan, S., 2010. Behavior and Energy Policy. Science, 327(5970), 1204-1220. doi: http://dx.doi.org/10.1126/science.1180775

Andrey, E., and Morelli, J., 2010. Design of a smart meter techno-economic model for electric utilities in Ontario. Paper presented at the Electric Power and Energy Conference (EPEC), Halifax, NS, Canada.

Ariely, D., 2008. Predictably Irrational: The Hidden Forces that Shape Our Decisions. New York, USA: HarperCollins.

Benders, R. M. J., Kok, R., Moll, H. C., Wiersma, G., and Noorman, K. J., 2006. New approaches for household energy conservation—In search of personal household energy budgets and energy reduction options. Energy Policy, 34(18), 3612-3622. doi: http://dx.doi.org/10.1016/j.enpol.2005.08.005

Boyce, J. K., and Riddle, M., 2007. Cap and Dividend: How to Curb Global Warming While Protecting the Incomes Of American Families. PERI Working Papers, 150(november), 28.

Carlsson, F., and Johansson-Stenman, O., 2012. Behavioral economics and environmental policy. Annual Review of Resource Economics, 4(1), 75-99. doi: http://dx.doi.org/10.1146/annurev-resource-110811-114547

Chatterton, T., and Department of Energy and Climate Change, 2011. An introduction to thinking about ’energy behaviour’: A multi-model approach. Other, (december). http://eprints.uwe.ac.uk/17873.

Chetty, R., 2015. Behavioral Economics and Public Policy: A Pragmatic Perspective. American Economic Review, 105(5), 1-33. doi: http://dx.doi.org/10.1257/aer.p20151108

Cialdini, R. B., Kallgren, C. A., and Reno, R. R., 1991. A focus theory of normative conduct. Advances in Experimental Social Psychology, 24, 201-234. doi: http://dx.doi.org/10.1016/


Cialdini, R. B., Reno, R. R., and Kallgren, C. A., 1990. A focus theory of normative conduct: Recycling the concept of norms to reduce littering in public places. Journal of Personality and Social Psychology, 58(6), 1015-1026. doi: http://dx.doi.org/10.1037/0022-3514.58.6.1015

Creyts, J., Derkach, A., Farese, P., Nyquist, S., and Ostrowski, K., 2009. Unlocking energy efficiency in the US economy. United Kingdom: McKinsey Global Energy and Materials.

Darby, S., 2006. The Effectiveness of Feedback on Energy Consumption - A Review for Defra of the Literature on Metering, Billing and Direct Displays. United Kingdom: Environmental Change Institute, Oxford University.

Darby, S., 2010. Literature reviews for the Energy Demand Research Project. London, UK: Ofgem.

De Martino, B., Kumaran, D., Seymour, B., and Dolan, R. J., 2006. Frames, biases, and rational decision- making in the human brain. Science, 313(5787), 684-687. doi: http://dx.doi.org/10.1126/science.1128356

DellaVigna, S., 2009. Psychology and Economics: Evidence from the Field. Journal of Economic Literature, 47(2), 315-372. doi: http://dx.doi.org/10.1257/jel.47.2.315

Dulleck, U., and Kaufmann, S., 2004. Do customer information programs reduce household electricity demand? The Irish program. Energy Policy, 32(8), 1025-1032. doi: http://dx.doi.org/10.1016/S0301-4215(03)00060-0

Ehrhardt-Martinez, K., Donnelly, K. A., and Laitner, J. A., 2010. Advanced metering initiatives and residential feedback programs: a meta-review for household electricity-saving opportunities. Washington, USA: American Council for an Energy-Efficient Economy.

European Environment Agency, 2012. Final electricity consumption by sector - ENER 018. Data and maps. from http://www.eea.europa.eu

Fan, S., and Hyndman, R., 2011. The Price Elasticity of Electricity Demand in South Australia. Energy Policy, 39(6), 3709-3719. doi: http://dx.doi.org/10.1016/j.enpol.2011.03.080

Faruqui, A., and Palmer, J., 2011. Dynamic Pricing of Electricity and its Discontents. San Francisco, USA: The Brattle Group.

Festinger, L., 1954. A theory of social comparison processes. Human Relations, 7, 117-140. doi: http://dx.doi.org/10.1177/001872675400700202

Fischer, C., 2008. Feedback on household electricity consumption: a tool for saving energy? Energy Efficiency, 1(1), 79-104. doi: http://dx.doi.org/10.1007/s12053-008-9009-7

Gardner, G. T., and Stern, P. C., 2002. Environmental problems and human behavior (2nd ed. ed.). Boston, MA: Pearson Custom Publishing.

Geller, E. S., 2002. The challenge of increasing proenvironmental behavior. In R. B. Bechtel and A. Churchman (Eds.), Handbook of environmental psychology (pp. 525-540). New York: Wiley.

Geva, A., 1994. Consumer behavior, purchasing decisions. Tel-Aviv, Israel: The Open University.

Gilbert, D. T., Pinel, E. C., Wilson, T. D., Blumberg, S. J., and Wheatley, T. P., 1998. Immune neglect: a source of durability bias in affective forecasting. Journal of Personality and Social Psychology, 75(3), 617-638.

Goldman, C. A., Barbose, G. L., and Eto, J. H., 2002. California Customer Load Reductions during the Electricity Crisis: Did They Help to Keep the Lights On? Journal of Industry, Competition and Trade, 2(1), 113-142. doi: http://dx.doi.org/10.1023/a:1020883005951

Hirshleifer, D., and Shumway, T., 2003. Good day sunshine: Stock returns and the weather. The Journal of Finance, 58(3), 1009-1032. doi: http://dx.doi.org/10.1111/1540-6261.00556

International Energy Agency, 2011. Technology Roadmap: Smart Grid: OECD/IEA.

Israeli Smart Energy Association - ISEA, 2013. Road Map for Smart Grid Implementation in Israel. http://www.isea.org.il/sg-road-map-homepage.

Jensen, O. M., 2003. Visualisation turns down energy demand. Paper presented at the ECEEE 2003 Summer Study (published in the proceedings), Saint-Raphaël, France.

Kahneman, D., 2005. Rationality, Fairness, Happiness: Selected Writings. Hebrew: Haifa University Press and Keter Publishing.

Kahneman, D., 2013. Thinking, fast and slow. New York, USA: Farrar, Straus and Giroux.

Kahneman, D., and Tversky, A., 1979. Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. doi: http://dx.doi.org/10.2307/1914185

King, C. S., and Chatterjee, S., 2003. Predicting California Demand Response. Public Utilities Fortnightly, 141, 27-32.

King, P., 2009. ThalerRichard H. and SunsteinCass R. (2008), Nudge: Improving Decisions about Health, Wealth and Happiness. London: Yale. £18, pp. 293, hbk. Journal of Social Policy, 38(4), 726-727. doi: http://dx.doi.org/10.1017/S0047279409990158

Labandeira, X., Labeaga, J. M., and Lopez-Otero, X., 2012. Estimation of elasticity price of electricity with incomplete information. Energy Economics, 34(3), 627-633. doi: http://dx.doi.org/10.1016/j.eneco.2011.03.008

Lee, L., Amir, O., and Ariely, D., 2009. In search of homo economicus: Cognitive noise and the role of emotion in preference consistency. The Journal of Consumer Research, 36(2), 173-187. doi: http://dx.doi.org/10.1086/597160

Logenthiran, T., Srinivasan, D., and Shun, T. Z., 2012. Demand side management in smart grid using heuristic optimization. IEEE Transactions on Smart Grid, 3(3), 1244-1252. doi: https://doi.org/10.1109/TSG.2012.2195686

Lucey, B. M., and Dowling, M., 2005. The Role of Feelings in Investor Decision- Making. Journal of Economic Surveys, 19(2), 211-237. doi: http://dx.doi.org/10.1111/j.0950-0804.2005.00245.x

Lusardi, A., Keller, P. A., and Keller, A. M., 2009. New ways to make people save: a social marketing approach. In A. Lusardi (Ed.), Overcoming the saving slump: how to improve the effectiveness of financial education and saving programs. Chicago: University of Chicago Press. doi:http://dx.doi.org/10.7208/chicago/9780226497105.003.0008

Lutzenhiser, L., Gossard, M. H., and Bender, S., 2002. Crisis in Paradise: Understanding Household Conservation Response to California's 2001 Energy Crisis. Paper presented at the ACEEE Summer Study on Energy Efficiency in Buildings (published in Proceedings).

Mack, B., and Hallmann, S., 2004. Strom sparen in Lummerlund--eine Interventionsstudie in einer Passiv- und Niedrigenergiehaussiedlung. [Conserving electricity in Lummerlund. An intervention study in a passive and low energy house residential area]. Umweltpsychologie, 8(1), 12-29.

MacLellan, D., 2008. NSTAR Power Cost Monitor Pilot. Paper presented at the Behavior, Energy & Climate Change Conference, Sacramento.

Ministry of national infrastructures. energy and water resources, 2010. National energy efficiency program. from http://energy.gov.il/GxmsMniPublications/energy.pdf

Ministry of national infrastructures. energy and water resources, 2012. Press conference on electricity saving from http://energy.gov.il/AboutTheOffice/SpeakerMessages/Pages/GxmsMniSpokesmanElectricityBazoret12.aspx

Mizobuchi, K., and Takeuchi, K., 2012. The Influences of Economic and Psychological Factors on Energy- Saving Behavior: A Field Experiment in Matsuyama, Japan http://www.econ.kobe-u.ac.jp/RePEc/koe/wpaper/2012/1206.pdf.

Mohsenian-Rad, A. H., Wong, V. W., Jatskevich, J., Schober, R., and Leon-Garcia, A., 2010. Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. Smart Grid. IEEE Transactions on Smart Grid, 1(3), 320-331.

Moshari, A., Yousefi, G. R., Ebrahimi, A., and Haghbin, S., 2010. Demand-side behavior in the smart grid environment. Paper presented at the Innovative Smart Grid Technologies Conference, Chalmers Lindholmen Gothenburg, Sweden.

Mountain, D., 2006. The Impact of Real-Time Feedback on Residential Electricity Consumption: The Hydro One Pilot. Ontario: Mountain Economic Consulting and Associates, Inc.

Newell, R. G., and Siikamaki, J., 2013. Nudging Energy Efficiency Behavior: The Role of Information Labels. NBER Working Paper Series, 19224(july), 41. doi: http://dx.doi.org/10.3386/w19224

Pollitt, M. G., and Shaorshadze, I., 2011. The role of behavioural economics in energy and climate policy. EPRG Working Paper, 1130, 1-29. doi: https://doi.org/10.17863/CAM.5237

Poortinga, W., Steg, L., and Vlek, C., 2004. Values, Environmental Concern, and Environmental BehaviorA Study into Household Energy Use. Environment and Behavior, 36(1), 70-93. doi: http://dx.doi.org/10.1177/0013916503251466

Ratner, R. K., Soman, D., Zauberman, G., Ariely, D., Carmon, Z., Keller, P. A., and Kim, B. K., 2008. How behavioral decision research can enhance consumer welfare: From freedom of choice to paternalistic intervention. Marketing Letters, 19(3-4), 383-397. doi: http://dx.doi.org/10.1007/s11002-008-9044-3

Schultz, P. W., Nolan, J. M., Cialdini, R. B., Goldstein, N. J., and Griskevicius, V., 2007. The constructive, destructive, and reconstructive power of social norms. Psychological Science, 18(5), 429-434. doi: http://dx.doi.org/10.1111/j.1467-9280.2007.01917.x

Smart Grid Consumer Collaborative - SGCC, 2011. State of the Consumer Report (pp. 38).

Soman, D., 2007. Behavioural economics in the field: improving prudence through field experiments. Toronto: Rotman School of Management, University of Toronto.

Steg, L., 2008. Promoting household energy conservation. Energy Policy, 36(12), 4449-4453. doi: http://dx.doi.org/10.1016/j.enpol.2008.09.027

Strbac, G., 2008. Demand side management: Benefits and challenges. Energy Policy, 36(12), 4419-4426. doi: http://dx.doi.org/10.1016/j.enpol.2008.09.030

Sverdlov, A., and Dolev, S., 2009. Handling peak demand for electricity in Israel: Analysis of the problem and offer solutions to policy. Tel Aviv, Israel: Israel Energy Forum.

Tabori, L., 2012. The Israeli electricity sector, an optimization through the diversion of demand. Hebrew: Radiant organization. Milken Institute.

Thaler, R. H., 2005. Advances in Behavioral Finance, Volume II. Princeton, UK: Princeton University Press.

Triandis, H., 1977. Interpersonal behaviour. Monterey, CA: Brookds /Cole Pub. Co.

Tversky, A., and Kahneman, D., 1974. Judgment under Uncertainty: Heuristics and Biases. Science, 185(4157), 1124-1131. doi: http://dx.doi.org/10.1126/science.185.4157.1124

U.S. Department of Energy [DOE], 2006. Benefits of Demand Response in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005. from https://energy.gov/oe/downloads/benefits-demand-response-electricity-markets-and-recommendations-achieving-them-report

Van Dam, S. S., Bakker, C. A., and Van Hal, J. D. M., 2010. Home energy monitors: Impact over the medium-term. Building Research and Information, 38(5), 458-469. doi: http://dx.doi.org/10.1080/09613218.2010.494832

Watson, A., Viney, H., and Schomaker, P., 2002. Consumer attitudes to utility products: a consumer behaviour perspective. Marketing Intelligence & Planning, 20(7), 394-404. doi: http://dx.doi.org/10.1108/02634500210450837

Winett, R. A., Love, S. Q., and Kidd, C., 1982. The Effectiveness of An Energy Specialist and Extension Agents in Promoting Summer Energy Conservation by Home Visits. Journal of Environmental Systems, 12(1), 61-70. doi: http://dx.doi.org/10.2190/B4DN-N9H8-A57Y-2JDG




How to Cite

ELBAZ, S., & ZAIŢ, A. (2017). EFFICIENT USE OF BEHAVIORAL TOOLS TO REDUCE ELECTRICITY DEMAND OF DOMESTIC CONSUMERS. Scientific Annals of Economics and Business, 63(SI), 89–107. https://doi.org/10.1515/saeb-2016-0137