Objective measurement of energy behavior in theory of Planned Behavior Research: A scoping review

Halkos, George and Gkargkavouzi, Anastasia (2026): Objective measurement of energy behavior in theory of Planned Behavior Research: A scoping review.

Abstract

The Theory of Planned Behavior (TPB) is the dominant psychological framework for explaining individual energy behavior, yet its predictive validity in this domain rests almost entirely on intentions or self-reported behavior, which correlate only modestly with objective measures. This exploratory scoping review, informed by the PRISMA extension for scoping reviews (PRISMA-ScR), maps how behaviour has been measured in quantitative TPB research on energy use, saving, and curtailment, and detects the specific studies that measured behavior objectively, through meters, sensors, billing or consumption records, monitored devices, or direct observation. Searches of Scopus and Web of Science identified 773 records, 467 unique records remained after deduplication and full-text assessment confirmed four eligible studies. Studies measuring energy behaviour through objective outcomes are therefore rare in the TPB literature, and where they exist, they rely either on consumption traces (records, meters, or sensors) or on coding by trained observers. A common design weakness is the inconsistency between constructs measured at the individual level and outcomes measured at the household, dormitory, or office level. Across the eligible studies, TPB constructs show weak and varying associations with objectively measured energy behavior; intention is often non-significant, while prediction improves when behavior is verified in real time against consumption traces. These findings are preliminary, as screening of the records whose abstracts did not state the measurement method is ongoing. Testing whether the theory explains energy behavior rather than self-reports, requires designs that pair person-attributable objective outcomes with full TPB measurement.

• Item Type: MPRA Paper
• Language: English
• Keywords: Theory of planned behaviour; energy behaviour; objective measurement; measurement practice; intention-behaviour Gap; Scoping Review.
• Subjects: C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C80 - General; C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C83 - Survey Methods ; Sampling Methods; D - Microeconomics > D9 - Intertemporal Choice > D90 - General; D - Microeconomics > D9 - Intertemporal Choice > D91 - Intertemporal Household Choice ; Life Cycle Models and Saving; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q41 - Demand and Supply ; Prices; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q48 - Government Policy; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q50 - General; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q56 - Environment and Development ; Environment and Trade ; Sustainability ; Environmental Accounts and Accounting ; Environmental Equity ; Population Growth

References

Abrahamse, W., & Steg, L. (2009). How do socio-demographic and psychological factors relate to households’ direct and indirect energy use and savings? Journal of Economic Psychology, 30(5), 711–720. https://doi.org/10.1016/J.JOEP.2009.05.006

Abrahamse, W., & Steg, L. (2011). Factors Related to Household Energy Use and Intention to Reduce It: The Role of Psychological and Socio-Demographic Variables. Human Ecology Review, 18(1), 30–40. http://www.jstor.org/stable/24707684

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. https://doi.org/10.1016/j.jenvp. 2005.08.002

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T

Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314-324. https://doi.org/10.1002/hbe2.195

Armitage, C. J., & Conner, M. (2001). Efficacy of the theory of planned behaviour: A meta-analytic review. British Journal of Social Psychology, 40(4), 471-499. https://doi.org/10.1348/014466601164939

Bampatsou, C, Halkos, G. and Dimou A. (2017) Determining economic productivity under environmental and resource pressures: an empirical application. Journal of Economic Structures 6(1), 12 https://link.springer.com/ article/10.1186/s40008-017-0071-1

Benders, R. M. J., Kok, R., Moll, H. C., Wiersma, G., & 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. https://doi.org/10.1016/j.enpol.2005.08.005

Gkargkavouzi, A., Halkos, G., & Matsiori, S. (2019). Environmental behavior in a private-sphere context: Integrating theories of planned behavior and value belief norm, self-identity and habit. Resources, Conservation and Recycling, 148, 145–156. https://doi.org/10.1016/J.RESCONREC.2019.01.039

Gkargkavouzi A. and Halkos GE (2026). Psychological Resilience to Climate Change: The Role of Self‐Efficacy, Mindfulness, Perceived Nature Restorativeness, and Subjective Well‐Being. Sustainable Development 34, 1435-1457 https://onlinelibrary.wiley.com/doi/full/10.1002/sd.70401

Bosnjak, M., Ajzen, I., & Schmidt, P. (2020). The theory of planned behavior: Selected recent advances and applications. Europe’s Journal of Psychology, 16(3), 352-356. https://doi.org/10.5964/ejop.v16i3.3107

Campbell, M., McKenzie, J. E., Sowden, A., Katikireddi, S. V., Brennan, S. E., Ellis, S., … Thomson, H. (2020). Synthesis without meta-analysis (SWiM) in systematic reviews: Reporting guideline. BMJ, 368, l6890. https://doi.org/10.1136/bmj.l6890

Canova, L., & Manganelli, A. M. (2020). Energy-saving behaviours in workplaces: Application of an extended model of the theory of planned behaviour. Europe’s Journal of Psychology, 16(3), 384-400. https://doi.org/10.5964/ejop.v16i3.1893

Chen, M.-F. (2016). Extending the theory of planned behavior model to explain people's energy savings and carbon reduction behavioral intentions to mitigate climate change in Taiwan: Moral obligation matters. Journal of Cleaner Production, 112, 1746-1753. https://doi.org/10.1016/j.jclepro.2015. 07.043

Chen, Y., Sumiyoshi, D., Morita, Y., Ishibashi, S., Wang, X., Yamamoto, T., Ueno, T., & Oh, J. (2025). BI-Tech: An IoT-Based Behavioral Intervention System for User-Driven Energy Optimization in Commercial Spaces. IEEE Access, 13, 166853–166872. https://doi.org/10.1109/ACCESS.2025.3607329

Cooke, A., Smith, D., & Booth, A. (2012). Beyond PICO: The SPIDER tool for qualitative evidence synthesis. Qualitative Health Research, 22(10), 1435-1443. https://doi.org/10.1177/1049732312452938

Creutzig, F., Niamir, L., Bai, X., Callaghan, M., Cullen, J., Díaz-José, J., … Ürge-Vorsatz, D. (2022). Demand-side solutions to climate change mitigation consistent with high levels of well-being. Nature Climate Change, 12, 36-46. https://doi.org/10.1038/s41558-021-01219-y

Dietz, T., Gardner, G. T., Gilligan, J., Stern, P. C., & Vandenbergh, M. P. (2009). Household actions can provide a behavioral wedge to rapidly reduce US carbon emissions. Proceedings of the National Academy of Sciences, 106(44), 18452-18456. https://doi.org/10.1073/pnas.0908738106

Fang, H., Wang, Y., & Xiao, H. (2021). A new mining framework for discovering the association between household characteristics and residential electricity consumption patterns. Applied Energy, 298, 117226. https://doi.org/10.1016/j.apenergy.2021.117226

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison-Wesley.

Frederiks, E. R., Stenner, K., &Hobman, E. V. (2015). Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour. Renewable and Sustainable Energy Reviews, 41, 1385-1394. https://doi.org/10.1016/j.rser.2014.09.026

Gao, L., Wang, S., Li, J., & Li, H. (2017). Application of the extended theory of planned behavior to understand individual's energy saving behavior in workplaces. Resources, Conservation and Recycling, 127, 107-113. https://doi.org/10.1016/j.resconrec.2017.08.030

González-Torres, M., Pérez-Lombard, L., Coronel, J. F., Maestre, I. R., & Yan, D. (2022). A review on buildings energy information: Trends, end-uses, fuels and drivers. Energy Reports, 8, 626-637. https://doi.org/10.1016/j.egyr. 2021.11.280

Halkos G. (2023) The drivers of sustainability in transitional and emerging economies. Economic Change and Restructuring 56 (5), 3217-3221 https://link.springer.com/article/10.1007/s10644-023-09549-x

Halkos, G. (2024). Modeling Energy-Environment-Economy Interrelations. Energies, 17(24), 6343. https://doi.org/10.3390/en17246343

Halkos, G. (2025). Economic Analysis and Policies in the Energy Sector. Energies, 18(16), 4214. https://doi.org/10.3390/en18164214

Halkos G. and Petrou KN (2019). Analysing the energy efficiency of EU member states: The potential of energy recovery from waste in the circular economy. Energies 12 (19), 3718. https://www.mdpi.com/1996-1073/12/19/3718

Halkos G. and Zisiadou A. (2020). Is investors’ psychology affected due to a potential unexpected environmental disaster?. Journal of Risk and Financial Management 13 (7), 151. https://www.mdpi.com/1911-8074/13/7/151

Halkos GE, Aslanidis PSC (2024). Monitoring sustainable waste management in OECD countries: A Malmquist productivity approach. Waste Management 190, 623-631 DOI: 10.1016/j.wasman.2024.10.035

International Energy Agency(2025). Energy efficiency 2025. Market Report, IEA. Available at: https://iea.blob.core.windows.net/assets/23a80bb2-6985-4507-ab99-c1d700f6548b/EnergyEfficiency2025.pdf

Karlin, B., Davis, N., Sanguinetti, A., Gamble, K., Kirkby, D., & Stokols, D. (2014). Dimensions of conservation: Exploring differences among energy behaviors. Environment and Behavior, 46(4), 423-452. https://doi.org/10.1177/0013916512467532

Karlin, B., Zinger, J. F., & Ford, R. (2015). The effects of feedback on energy conservation: A meta-analysis. Psychological Bulletin, 141(6), 1205-1227. https://doi.org/10.1037/a0039650

Klöckner, C. A. (2013). A comprehensive model of the psychology of environmental behaviour: A meta-analysis. Global Environmental Change, 23(5), 1028-1038. https://doi.org/10.1016/j.gloenvcha.2013.05.014

Kormos, C., & Gifford, R. (2014). The validity of self-report measures of proenvironmental behavior: A meta-analytic review. Journal of Environmental Psychology, 40, 359-371. https://doi.org/10.1016/j.jenvp.2014.09.003

Kriek, J., Stols, G., &Bukula, T. (2013). Can behavioral intentions predict domestic electricity consumers' actual behavior towards energy efficiency? Energy Education Science and Technology Part B: Social and Educational Studies, 5(1), 189-206. Retrieved from https://repository.up.ac.za/server/api/core/bitstreams/c493584e-6da2-404f-8ac0-79b28faaa078/content

Lange, F., & Dewitte, S. (2019). Measuring pro-environmental behavior: Review and recommendations. Journal of Environmental Psychology, 63, 92-100. https://doi.org/10.1016/j.jenvp.2019.04.009

Liu, N., Luo, X., Liu, X., & Xing, M. (2025). Impacts of normative information on college students' energy-saving intentions and behaviors in the dormitory. Energy and Built Environment, 6(2), 347-361. https://doi.org/10.1016/j.enbenv.2023.12.001

Mi, L., Xu, T., Sun, Y., Yang, H., Wang, B., Gan, X., & Qiao, L. (2021). Promoting differentiated energy savings: Analysis of the psychological motivation of households with different energy consumption levels. Energy, 218, 119563. https://doi.org/10.1016/j.energy.2020.119563

Munn, Z., Peters, M. D. J., Stern, C., Tufanaru, C., McArthur, A., &Aromataris, E. (2018). Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Medical Research Methodology, 18, 143. https://doi.org/10.1186/s12874-018-0611-x

Ouzzani, M., Hammady, H., Fedorowicz, Z., &Elmagarmid, A. (2016). Rayyan - a web and mobile app for systematic reviews. Systematic Reviews, 5, 210. https://doi.org/10.1186/s13643-016-0384-4

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71

Sheeran, P., & Webb, T. L. (2016). The intention-behavior gap. Social and Personality Psychology Compass, 10(9), 503-518. https://doi.org/10.1111/ spc3.12265

Tiefenbeck, V., Goette, L., Degen, K., Tasic, V., Fleisch, E., Lalive, R., & Staake, T. (2018). Overcoming salience bias: How real-time feedback fosters resource conservation. Management Science, 64(3), 1458-1476. https://doi.org/10.1287/mnsc.2016.2646

Tricco, A. C., Lillie, E., Zarin, W., O'Brien, K. K., Colquhoun, H., Levac, D., … Straus, S. E. (2018). PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Annals of Internal Medicine, 169(7), 467-473. https://doi.org/10.7326/M18-0850

Wilson, C. (2014). Evaluating communication to optimise consumer-directed energy efficiency interventions. Energy Policy, 74(C), 300–310. https://doi.org/10.1016/J.ENPOL.2014.08.025

Yilmaz, S. E. (2025). From perceptions to practice: Examining organizational predictors of energy-saving behavior through mixed methods. Energy Efficiency, 18, 62. https://doi.org/10.1007/s12053-025-10356-8

Yuriev, A., Dahmen, M., Paillé, P., Boiral, O., &Guillaumie, L. (2020). Pro-environmental behaviors through the lens of the theory of planned behavior: A scoping review. Resources, Conservation and Recycling, 155, 104660. https://doi.org/10.1016/j.resconrec.2019.104660

Zhang, Y., Wang, Z., & Zhou, G. (2013). Antecedents of employee electricity saving behavior in organizations: An empirical study based on norm activation model. Energy Policy, 62, 1120-1127. https://doi.org/10.1016/j.enpol.2013. 07.036