Document Type : Research Paper

Authors

1 Researcher in Department of Management Social Sciences, Niroo Research Institute (NRI), Tehran, Iran

2 Ph.D. Student in Public Administration, Faculty of Public Administration and Organizational Sciences, College of Management, University of Tehran, Tehran, Iran

Abstract

 The household sector, accounting for 28 percent of global energy consumption and 32 percent of greenhouse gas emissions, is a central focus of energy policy. While traditional policies have primarily emphasized technological interventions, evidence shows that reliance on such measures alone, without attention to behavioral and social dimensions, cannot ensure sustainable effectiveness. This study aims to develop a localized framework for behavioral policymaking in Iran’s residential energy sector, employing a mixed-method approach in two stages. First, a meta-synthesis of global experiences was conducted to identify patterns of behavioral interventions. Second, a survey of 594 Tehran residents aged 18 and above was carried out, with data analyzed using multivariate regression techniques. The meta-synthesis revealed that information framing, feedback, and social norms were the most widely applied behavioral tools internationally. At the national level, however, lifestyle emerged as the strongest predictor of household energy consumption, while ethical-religious values and material culture also played a significant role. Integrating these two strands of evidence resulted in the development of a four-layered framework: (1) socio-cultural foundations; (2) behavioral operational interventions; (3) institutional and technological support  and (4) policy capacity-building.This framework offers policymakers a practical roadmap for designing and implementing interventions that are both culturally resonant and technically sound, contributing to the sustainable management of residential energy consumption in Iran.
Introduction
The household sector is one of the largest consumers of energy worldwide, accounting for nearly 28% of global energy use and 32% of greenhouse gas emissions associated with energy consumption.


 This situation underscores the urgency of designing effective policies to promote energy conservation and efficiency. Traditional approaches have largely relied on technological and infrastructural solutions such as smart meters, energy-efficient appliances, and insulation improvements. While these interventions remain essential, recent decades have highlighted the limitations of “hard” measures when implemented in isolation. A growing body of research in behavioral sciences has revealed that human decisions regarding energy use are shaped not only by structural or economic constraints but also by psychological, cultural, and social factors. Behavioral public policy, therefore, has emerged as a complementary approach, drawing on insights from behavioral economics, cognitive psychology, and social sciences to design interventions that are cost-effective, context-sensitive, and ethically grounded. However, the geographical spread and heterogeneity of behavioral interventions in the energy sector have made it difficult to achieve a coherent understanding of their applicability, especially in developing countries such as Iran.This study addresses this gap by developing a context-specific framework for behavioral policymaking in household energy consumption in Iran. By employing a dual-method approach—meta-synthesis of international behavioral policy experiences and a national survey among Iranian households—this research integrates global evidence with local insights. The goal is to develop a multi-layered framework that policymakers can use to design behavioral interventions tailored to Iran’s socio-cultural and institutional context.
 
Methods and Materials
A mixed-method design was employed to ensure comprehensive insights.
Phase I – Meta-Synthesis:
The first phase involved a meta-synthesis of 23 documented behavioral policy interventions implemented in different countries between 2000 and 2023. Behavioral policy interventions were identified using systematic searches of international databases and institutional reports, employing keywords such as “behavioral public policy” and “energy.” The interventions were analyzed along six dimensions:

Temporal and geographical scope
Target population
Operationalization strategies
Behavioral levers applied (e.g., nudges, feedback, framing)
Data collection methods
Tools of intervention (e.g., smart meters, gamification, mobile applications).

Phase II – National Survey:
The second phase employed a large-scale survey among Iranian households to capture context-specific drivers of energy consumption behavior. The survey targeted residents of Tehran aged 18 and above, using random sampling. A total of 594 valid responses were collected. The questionnaire measured awareness, attitudes, values, lifestyle, material culture, and demographic characteristics.


 Validity was ensured through expert reviews and pilot testing, while reliability was tested using Cronbach’s alpha across pre-test and final samples. Data were analyzed using SPSS through descriptive statistics, correlation tests, and multiple regression analysis to identify key behavioral determinants.
Results and Discussion
Meta-Synthesis Findings
The international evidence indicated a growing prevalence of behavioral interventions, particularly in Europe (56) and Asia (35), with rapid acceleration since 2018. The most frequently employed levers included:

Information framing(14 instances),
Feedback mechanisms(11 instances),
Social norms and comparative feedback(11 instances).

Technological tools such as smart meters, IoT-enabled devices, and gamification-based applications were widely utilized to enhance feedback mechanisms. Interventions relying on framing showed that the way information is presented significantly influences consumer behavior, although their effects tended to diminish over time unless reinforced by reminders or gradual learning processes. Similarly, social norm-based interventions, such as providing households with comparative energy consumption reports, proved effective in shifting behaviors through peer influence.
Survey Findings in Iran
The survey results revealed several context-specific determinants of household energy consumption behavior:

Lifestylewas the strongest predictor of behavior (β = 0.234), highlighting the formative role of family and early socialization.
Moral and religious values(β = 0.224) were also significant, with many respondents perceiving energy saving as an ethical and even religious duty.
Material culture(β = 0.103), such as housing infrastructure and appliances, had a measurable impact.
Age(β = 0.135) was positively correlated, while income (β = –0.138) and gender (β = –0.112) showed negative correlations with energy-saving behaviors.

Notably, awareness (ρ = 0.064) had no significant relationship with actual behavior, indicating that education and information provision alone are insufficient to change practices. Furthermore, while international evidence emphasized cost-based feedback, Iranian respondents identified intrinsic values of energy saving—rather than cost concerns—as their primary motivation, a finding that reflects the distorting effects of low tariffs and subsidies.
Integration and Framework Development
By synthesizing both sets of findings, the study proposes a four-layered framework for behavioral policymaking in Iran’s household energy sector:

Cultural-Social Foundations:Redesigning communication strategies to emphasize energy saving as a moral and religious value; empowering families as behavioral units; and promoting community-based role models.
Operational Behavioral Interventions:Combining global tools such as comparative smart bills and mobile notifications with locally resonant framings (e.g., responsibility toward future generations).
Institutional and Technological Support:Accelerating smart meter deployment, creating interactive digital platforms, and designing incentive schemes based on behavioral improvement rather than absolute consumption.
Institutional Capacity-Building:Establishing behavioral insights teams, experimental policy labs, and legal frameworks to institutionalize behavioral policymaking.

Conclusion
This study demonstrated the necessity of integrating behavioral insights into energy policy in Iran. While international evidence highlights the efficacy of nudges such as framing, feedback, and social norm mechanisms, the national survey underscores the decisive role of lifestyle, moral-religious values, and family orientation in shaping Iranian household energy behavior.
The findings emphasize that awareness alone cannot drive behavioral change, and reliance on cost-based incentives is ineffective in contexts with heavily subsidized energy. Instead, interventions must align with cultural and moral values to trigger intrinsic motivations. By combining global experiences with localized insights, the proposed framework offers policymakers a practical roadmap for designing sustainable and context-sensitive behavioral interventions.
The contribution of this research lies in demonstrating that effective energy policymaking requires a multi-layered approach that bridges technological solutions with behavioral levers while embedding them in institutional and cultural contexts. Such a strategy not only enhances the effectiveness of energy conservation policies but also contributes to broader goals of sustainable development and climate change mitigation.

Keywords

داودی، پرویز، سالم، علی اصغر . (1385). اثر تغییر قیمت بنزین بر رفـاه خانـوارها در دهک‌های مختلف درآمدی. فصلنامه پژوهشنامه اقتصادی، 6(23), 15-48.
کیقبادی، مریم، اکبرنیا، الهه سادات، پیرمراد، حمیدرضا، پسندیده، اشرف السادات . (1403). بررسی نقش پایگاه اقتصادی خانوار در رفتار مصرف انرژی برق با استفاده از پیمایش. فصلنامه پژوهشنامه اقتصادی، 24(92)، 99-136. doi: 10.22054/joer.2025.78344.1202.
 Afif, Z., Islan, W. W., Calvo-Gonzalez, O., & Dalton, A. G. (2018). Behavioral Science Around the World: Profiles of 10 Countries. In eMBeD brief. Washington, D.C.: World Bank Group.
Agarwal, S., Sing, T. F., & Sultana, M. (2022). Public media campaign and energy conservation: A natural experiment in Singapore. Energy Economics, 114. https://doi.org/10.1016/j.eneco.2022.106281
Allcott, H., & Rogers, T. (2014). The short-run and long-run effects of behavioral interventions: Experimental evidence from energy conservation. American Economic Review, 104(10), 3003–3037. https://doi.org/10.1257/aer.104.10.3003
AlSkaif, T., Lampropoulos, I., van den Broek, M., & van Sark, W. (2018). Gamification-based framework for engagement of residential customers in energy applications. Energy Research and Social Science, 44 (May), 187–195. https://doi.org/10.1016/j.erss.2018.04.043
Ayres, I., Raseman, S., & Shih, A. (2013). Evidence from two large field experiments that peer comparison feedback can reduce residential energy usage. The Journal of Law, Economics, & Organization, 29 (5), 992-1022.
Banerjee, S., & John, P. (2021). Nudge plus: incorporating reflection into behavioral public policy. Behavioural Public Policy, 1–16. https://doi.org/10.1017/bpp.2021.6
Beck, C. T. (2002). Mothering multiples: A meta-synthesis of qualitative research. MCN The American Journal of Maternal Child Nursing, 27 (4), 214–221. https://doi.org/10.1097/00005721-200207000-00004
Beegy, W. N., & Spring-stof, E. V. (2022). Report on pilot results : interim report Delivery date : 28 October 2022 Authors : Marta Gabriel (INEGI), Stratos Keranidis , Dimitris Voulgarakis Lucija Nad , Erica Svetec (ZEZ), Peter Conradie , Stephanie Van Hove ( IMEC ), Merkouris Karaliopoulos (. 957012, 1–82.
Belaïd, F., & Joumni, H. (2022). Behavioral attitudes towards energy saving : Empirical evidence from France To cite this version : HAL Id : hal-03052065 Behavioral Attitudes towards Energy Saving : Empirical Evidence from France.
Belaïd, F., & Massié, C. (2022). What are the salient factors determining the usage of heating energy sources in France? Evidence from a discrete choice model. Energy and Buildings, 273, 1–40. https://doi.org/10.1016/j.enbuild.2022.112386
Bélaïd, F., Rault, C., & Massié, C. (2021). A Life-Cycle Theory Analysis of French Household Electricity Demand. SSRN Electronic Journal, January. https://doi.org/10.2139/ssrn.3762880
Belaid, F., Youssef, A. Ben, & Omrani, N. (2020). Investigating the factors shaping residential energy consumption patterns in France: Evidence form quantile regression. European Journal of Comparative Economics, 17 (1), 127–151. https://doi.org/10.25428/1824-2979/202001-127-151
Benartzi, S., Beshears, J., Milkman, K. L., Sunstein, C. R., Thaler, R. H., Shankar, M., Tucker-ray, W., Congdon, W. J., & Galing, S. (2017). Should Governments Invest More in Nudging ? Psychological Science, 28 (8), 1041–1055. https://doi.org/10.1177/0956797617702501
Bender, S. L., Moezzi, M., Gossard, M. H., & Lutzenhiser, L. (2002). Using Mass Media to Influence Energy Consumption Behavior : California ’ s 2001 Flex Your Power Campaign as a Case Study Public Information Campaigns as Policy Tools. Proceedings of the 2002 ACEEE Summer Study, 8, 1–14.
Bollinger, B., & Gillingham, K. (2012). Peer Effects in the Diffusion of Solar Photovoltaic Panels ∗. 1–40.
Davoudi, P., & Salem, A. A. (2007). The impact of gasoline price changes on household welfare across different income deciles. Journal of Economic Research, 6(23), 15–48. [In Persian]
Dimitropoulos, A. & et al. (2017). Tackling Environmental Problems with the Help of Behavioural Insights. Tackling Environmental Problems with the Help of Behavioural Insights (Issue June). https://doi.org/10.1787/9789264273887-en
Economidou, M., Todeschi, V., Bertoldi, P., D’Agostino, D., Zangheri, P., & Castellazzi, L. (2020). Review of 50 years of EU energy efficiency policies for buildings. Energy and Buildings, 225, 110322. https://doi.org/10.1016/j.enbuild.2020.110322
Efficiency, F. E. (2020). Fostering Energy Efficiency and BehAvioural Change through ICT . Get involved in smart energy efficiency through. 768935.
Energie, B. für W. und. (2014). Behavioural Economics and Energy Conservation - Final Report. 727642.
European Environment Agency. (2013). Achieving energy efficiency through behaviour change: what does it take? In Luxembourg: Publications Office of the European Union, 2013 (Issue 5). http://www.engerati.com/sites/default/files/Day2-1440-AncaDianaBarbu-EUW2013.pdf
Fanghella, V., & Della Valle, N. (2021). A Behavioral Model for In-Home Displays Usage in Social Housing Districts. In Green Energy and Technology. Springer International Publishing. https://doi.org/10.1007/978-3-030-57332-4_36
Final Report Peak Time Rebate Program Process Evaluation. (2013). Freire-gonzález, J. (2015). Energy Efficiency Policies and the Jevons Paradox. 5 (1), 69–79.
Hernandez, M., Bhagavatula, K., Cibi, S., K, R., Krishnan, S., Malaviya, S., & Jairaj, B. (2022). Shifting Household Energy Use in Bangalore, India: Using Behaviorally Informed Energy Reports. World Resources Institute, February, 1–32. https://doi.org/10.46830/wriwp.20.00046
IEC. (2018). China: Energy efficiency report, 2018. http://www05.abb.com/global/scot/scot316.nsf/veritydisplay/0a9c91a9a97f3bbdc12579d0004ef177/$file/China Energy efficiency Report.pdf
Kendel, A., Lazaric, N., & Maréchal, K. (2017). What do people ‘learn by looking’ at direct feedback on their energy consumption? Results of a field study in Southern France. Energy Policy, 108, 593–605. https://doi.org/10.1016/j.enpol.2017.06.020
Keyghobadi, M., Akbarnia, E. S., Pirmorad, H. R., & Pasandideh, A. S. (2024). Examining the role of households’ economic status in electricity energy consumption behavior using a survey approach. Journal of Economic Research, 24(92), 99–136. https://doi.org/10.22054/joer.2025.78344.1202 [In Persian]
Krarti, M., Aldubyan, M., & Williams, E. (2020). Residential building stock model for evaluating energy retrofit programs in Saudi Arabia. Energy, 195, 116980. https://doi.org/10.1016/j.energy.2020.116980
Lazaric, N., & Toumi, M. (2022). Reducing consumption of electricity: A field experiment in Monaco with boosts and goal setting. Ecological Economics, 191, 1–41. https://doi.org/10.1016/j.ecolecon.2021.107231
Lepenies, R., & Małecka, M. (2019). The ethics of behavioural public policy. The Routledge Handbook of Ethics and Public Policy, 513–525. https://doi.org/10.4324/9781315461731-41
Makris, P., Efthymiopoulos, N., Vergados, D. J., Varvarigos, E., Nikolopoulos, V., Papagiannis, J., Pomazanskyi, A., Irmscher, B., Stefanov, K., Pancheva, K., & Georgiev, A. (2018). SOCIALENERGY: A gaming and social network platform for evolving energy markets’ operation and educating virtual energy communities. IEEE International Energy Conference, ENERGYCON 2018, 1–6. https://doi.org/10.1109/ENERGYCON.2018.8398797
Motherway, B., Klimovich, K., Mooney, E., & & Gelis, C. (2022). Empowering people to act: How awareness and behaviour campaigns can enable citizens to save energy during and beyond today’s energy crisis. Proceedings - 2022 IEEE Future Networks World Forum, FNWF 2022. https://doi.org/10.1109/FNWF55208.2022.00137
Naoko DOI, and OGAWA, A. (2021). CERT Thematic Discussions : The role of ʻbehavioural aspectsʼ for reaching net zero emissions by 2050 Impact of “ Setsuden ” - data survey on the potential for Japan ’ s electricity savings by behavioural change What is “ Setsuden ” ? To cope with the rol.
OECD. (2017). Behavioural Insights and Public Policy. In Behavioural Insights and Public Policy. https://doi.org/10.1787/9789264270480-en
Pasquier, S., Heffner, G., & Unit, E. (2011). SAVING ELECTRICITY IN A HURRY Update 2011. Data and Analyses. http://www.ourenergypolicy.org/wpcontent/uploads/2013/05/az2463.pdf#page=15
SANDERS, M., SNIJDERS, V., & HALLSWORTH, M. (2018). Behavioural science and policy: where are we now and where are we going? Behavioural Public Policy, 2 (2), 144–167. https://doi.org/10.1017/bpp.2018.17
Sanin, M. E., Trillas, F., Mejdalani, A. N., López, D., & Carvalho Metanias Hallack, M. (2019). Using Behavioral Economics in The Design of Energy Policies. Idb. http://dx.doi.org/10.18235/0002262%0Ahttp://dx.doi.org/10.18235/0002262
Sudarmaji, E., Ambarwati, S., & Munira, M. (2022). Measurement of the Rebound Effect on Urban Household Energy Consumption Savings. International Journal of Energy Economics and Policy, 12 (5), 88–100. https://doi.org/10.32479/ijeep.13426
Team, B. I. (2012). Behaviour Change and Energy Use.
Thaler, R. H., & Sunstein, C. R. (2009). Nudge: Improving Decisions About Health, Wealth, and Happiness. Penguin Books.
Thapar, S. (2020). Energy consumption behavior: A data-based analysis of urban Indian households. Energy Policy, 143 (February), 111571. https://doi.org/10.1016/j.enpol.2020.111571
Users TCP and IEA. (2020). Behavioural insights for demand-side energy policy and programmes: An environment scan, User-Centred Energy Systems Technology Collaboration Programme. December. https://doi.org/10.47568/6OR105
Walsh, D., & Downe, S. (2005). METHODOLOGICAL ISSUES IN NURSING RESEARCH Meta-synthesis method for qualitative research: a literature review. Journal of Advanced Nursing, 50 (2), 204–211. https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2648.2005.03380.x
Wang, B., Deng, N., Liu, X., Sun, Q., & Wang, Z. (2021). Effect of energy efficiency labels on household appliance choice in China: Sustainable consumption or irrational intertemporal choice? Resources, Conservation and Recycling, 169 (September 2020), 105458. https://doi.org/10.1016/j.resconrec.2021.105458
Yu, B., Yang, X., Zhao, Q., & Tan, J. (2020). Causal Effect of Time-Use Behavior on Residential Energy Consumption in China. Ecological Economics, 175 (5), 106706.
https://doi.org/10.1016/j.ecolecon.2020.106706