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Personality-based normative feedback intervention for energy conservation

Author

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  • Shen, Meng
  • Li, Xiang
  • Lu, Yujie
  • Cui, Qingbin
  • Wei, Yi-Ming

Abstract

Residential sector is considered as a key to energy conservation due to its significant share and fast growth. Normative feedback has been widely implemented in residential sector for its low cost and high effectivity. However, the potential of energy saving generated from the method has not been fully achieved, as the influence of personality traits and benchmark setting strategy on individual behavioral response has been overlooked. Therefore, this paper incorporates personality traits into the analysis of individual behavior patterns, and proposes a personality-based normative feedback mechanism which optimizes the benchmarks setting strategy in real time by optimal control algorithm. The agent-based modelling method is adopted to develop improved Deffuant-optimal control (DOC) model and to simulate the personality-driven energy conservation of residents under the proposed intervention mechanism. The study finds that intervention effect of the dynamic benchmark setting strategy is superior to normative feedback with fixed benchmarks in terms of energy savings and response agility, and individuals with different personality traits are significantly different in behavioral characteristics. Increase in openness promotes the residents to save energy quickly, and agreeableness has an inverted U-shaped relationship with residents' response agility. Open-minded and agreeable individuals perform well in energy saving while showing stronger boomerang effect. In addition, residents are classified according to their behavioral response patterns and personality traits, in order to analyze the time-dependent response characteristics and boomerang effect of different groups of individuals. The DOC model is evaluated by energy conservation experiments conducted in residential communities of Hangzhou, China. The proposed intervention mechanism improves the effectivity of normative feedback in both short-term and long-term, and provides an innovation approach for optimizing energy demand side management.

Suggested Citation

  • Shen, Meng & Li, Xiang & Lu, Yujie & Cui, Qingbin & Wei, Yi-Ming, 2021. "Personality-based normative feedback intervention for energy conservation," Energy Economics, Elsevier, vol. 104(C).
    • Handle: RePEc:eee:eneeco:v:104:y:2021:i:c:s0140988321005119
    DOI: 10.1016/j.eneco.2021.105654
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    References listed on IDEAS

    as
    1. Viggers, Helen & Keall, Michael & Wickens, Kristin & Howden-Chapman, Philippa, 2017. "Increased house size can cancel out the effect of improved insulation on overall heating energy requirements," Energy Policy, Elsevier, vol. 107(C), pages 248-257.
    2. Abanda, F.H. & Byers, L., 2016. "An investigation of the impact of building orientation on energy consumption in a domestic building using emerging BIM (Building Information Modelling)," Energy, Elsevier, vol. 97(C), pages 517-527.
    3. Rodrigo C. Carlson & Ioannis Papamichail & Markos Papageorgiou & Albert Messmer, 2010. "Optimal Motorway Traffic Flow Control Involving Variable Speed Limits and Ramp Metering," Transportation Science, INFORMS, vol. 44(2), pages 238-253, May.
    4. Aydin, Erdal & Brounen, Dirk & Kok, Nils, 2018. "Information provision and energy consumption: Evidence from a field experiment," Energy Economics, Elsevier, vol. 71(C), pages 403-410.
    5. Pablo-Romero, María del P. & Pozo-Barajas, Rafael & Yñiguez, Rocío, 2017. "Global changes in residential energy consumption," Energy Policy, Elsevier, vol. 101(C), pages 342-352.
    6. Hunt Allcott, 2011. "Consumers' Perceptions and Misperceptions of Energy Costs," American Economic Review, American Economic Association, vol. 101(3), pages 98-104, May.
    7. Belaïd, Fateh & Garcia, Thomas, 2016. "Understanding the spectrum of residential energy-saving behaviours: French evidence using disaggregated data," Energy Economics, Elsevier, vol. 57(C), pages 204-214.
    8. Ryu, Jun-Yeol & Kim, Dae-Wook & Kim, Man-Keun, 2021. "Household differentiation and residential electricity demand in Korea," Energy Economics, Elsevier, vol. 95(C).
    9. Busic-Sontic, Ante & Czap, Natalia V. & Fuerst, Franz, 2017. "The role of personality traits in green decision-making," Journal of Economic Psychology, Elsevier, vol. 62(C), pages 313-328.
    10. Enrica Cian & Ian Sue Wing, 2019. "Correction to: Global Energy Consumption in a Warming Climate," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(4), pages 1415-1415, August.
    11. Schultz, P. Wesley & Estrada, Mica & Schmitt, Joseph & Sokoloski, Rebecca & Silva-Send, Nilmini, 2015. "Using in-home displays to provide smart meter feedback about household electricity consumption: A randomized control trial comparing kilowatts, cost, and social norms," Energy, Elsevier, vol. 90(P1), pages 351-358.
    12. Ramea, Kalai & Bunch, David S. & Yang, Christopher & Yeh, Sonia & Ogden, Joan M., 2018. "Integration of behavioral effects from vehicle choice models into long-term energy systems optimization models," Energy Economics, Elsevier, vol. 74(C), pages 663-676.
    13. Silva, Petrônio C.L. & Batista, Paulo V.C. & Lima, Hélder S. & Alves, Marcos A. & Guimarães, Frederico G. & Silva, Rodrigo C.P., 2020. "COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    14. Anderson, Kyle & Song, Kwonsik & Lee, SangHyun & Krupka, Erin & Lee, Hyunsoo & Park, Moonseo, 2017. "Longitudinal analysis of normative energy use feedback on dormitory occupants," Applied Energy, Elsevier, vol. 189(C), pages 623-639.
    15. Boto-García, David & Bucciol, Alessandro, 2020. "Climate change: Personal responsibility and energy saving," Ecological Economics, Elsevier, vol. 169(C).
    16. Zhang, Jiangbo & Hong, Yiguang, 2013. "Opinion evolution analysis for short-range and long-range Deffuant–Weisbuch models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5289-5297.
    17. Stefano De Dominicis & Rebecca Sokoloski & Christine M. Jaeger & P. Wesley Schultz, 2019. "Making the smart meter social promotes long-term energy conservation," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-8, December.
    18. Weber, Sylvain & Puddu, Stefano & Pacheco, Diana, 2017. "Move it! How an electric contest motivates households to shift their load profile," Energy Economics, Elsevier, vol. 68(C), pages 255-270.
    19. Gao, Lan & Wang, Shanyong & Li, Jun & Li, Haidong, 2017. "Application of the extended theory of planned behavior to understand individual’s energy saving behavior in workplaces," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 107-113.
    20. Harold, Jason & Lyons, Seán & Cullinan, John, 2018. "Heterogeneity and persistence in the effect of demand side management stimuli on residential gas consumption," Energy Economics, Elsevier, vol. 73(C), pages 135-145.
    21. Du, Kerui & Yu, Ying & Wei, Chu, 2020. "Climatic impact on China's residential electricity consumption: Does the income level matter?," China Economic Review, Elsevier, vol. 63(C).
    22. Corinne Le Quéré & Robert B. Jackson & Matthew W. Jones & Adam J. P. Smith & Sam Abernethy & Robbie M. Andrew & Anthony J. De-Gol & David R. Willis & Yuli Shan & Josep G. Canadell & Pierre Friedlingst, 2020. "Temporary reduction in daily global CO2 emissions during the COVID-19 forced confinement," Nature Climate Change, Nature, vol. 10(7), pages 647-653, July.
    23. Enrica Cian & Ian Sue Wing, 2019. "Global Energy Consumption in a Warming Climate," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(2), pages 365-410, February.
    24. de la Rue du Can, Stephane & Leventis, Greg & Phadke, Amol & Gopal, Anand, 2014. "Design of incentive programs for accelerating penetration of energy-efficient appliances," Energy Policy, Elsevier, vol. 72(C), pages 56-66.
    25. Suresh P. Sethi, 2021. "Optimal Control Theory," Springer Texts in Business and Economics, Springer, edition 4, number 978-3-030-91745-6, June.
    26. Ramos, A. & Gago, A. & Labandeira, X. & Linares, P., 2015. "The role of information for energy efficiency in the residential sector," Energy Economics, Elsevier, vol. 52(S1), pages 17-29.
    27. Ornaghi, Carmine & Costanza, Enrico & Kittley-Davies, Jacob & Bourikas, Leonidas & Aragon, Victoria & James, Patrick A.B., 2018. "The effect of behavioural interventions on energy conservation in naturally ventilated offices," Energy Economics, Elsevier, vol. 74(C), pages 582-591.
    28. Song, Kwonsik & Anderson, Kyle & Lee, SangHyun, 2020. "An energy-cyber-physical system for personalized normative messaging interventions: Identification and classification of behavioral reference groups," Applied Energy, Elsevier, vol. 260(C).
    29. Shen, Meng & Young, Robert & Cui, Qingbin, 2016. "The normative feedback approach for energy conservation behavior in the military community," Energy Policy, Elsevier, vol. 98(C), pages 19-32.
    30. Aydin, Erdal & Brounen, Dirk, 2019. "The impact of policy on residential energy consumption," Energy, Elsevier, vol. 169(C), pages 115-129.
    31. Antonio Silva & Peter John, 2017. "Social norms don’t always work: An experiment to encourage more efficient fees collection for students," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-9, May.
    32. Bianchini, Gianni & Casini, Marco & Vicino, Antonio & Zarrilli, Donato, 2016. "Demand-response in building heating systems: A Model Predictive Control approach," Applied Energy, Elsevier, vol. 168(C), pages 159-170.
    33. Chen, Victor L. & Delmas, Magali A. & Locke, Stephen L. & Singh, Amarjeet, 2017. "Information strategies for energy conservation: A field experiment in India," Energy Economics, Elsevier, vol. 68(C), pages 215-227.
    34. Shen, Meng & Cui, Qingbin & Fu, Liping, 2015. "Personality traits and energy conservation," Energy Policy, Elsevier, vol. 85(C), pages 322-334.
    35. Quaglione, Davide & Cassetta, Ernesto & Crociata, Alessandro & Sarra, Alessandro, 2017. "Exploring additional determinants of energy-saving behaviour: The influence of individuals' participation in cultural activities," Energy Policy, Elsevier, vol. 108(C), pages 503-511.
    36. Peng Zhang & Xin Ma & Kun She, 2019. "A novel power-driven fractional accumulated grey model and its application in forecasting wind energy consumption of China," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-33, December.
    37. Guillaume Deffuant & David Neau & Frederic Amblard & Gérard Weisbuch, 2000. "Mixing beliefs among interacting agents," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 3(01n04), pages 87-98.
    38. Daiva Dumciuviene & Akvile Cibinskiene & Meda Andrijauskiene, 2019. "Determinants of Energy Saving: Evidence from a Vocational School in Greece," Energies, MDPI, vol. 12(19), pages 1-16, September.
    39. Carroll, James & Lyons, Seán & Denny, Eleanor, 2014. "Reducing household electricity demand through smart metering: The role of improved information about energy saving," Energy Economics, Elsevier, vol. 45(C), pages 234-243.
    40. Anderson, Kyle & Lee, SangHyun, 2016. "An empirically grounded model for simulating normative energy use feedback interventions," Applied Energy, Elsevier, vol. 173(C), pages 272-282.
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