Abstract
A field study of 50 households in a collective community in Israel provides initial support for the hypotheses about the relations between actors’ agency, capacity and electricity demand reduction. ‘Agency’ refers to actors’ willingness and ability to make their own free choices and ‘capacity’ refers to actors’ ability to perform the choices they made. According to the hypotheses, change is more likely to happen when actors’ levels of agency and capacity are high; unlikely to happen when the levels are low and uncertain when there is a mismatch between levels of agency and capacity (one is high and the other low). In the research, levels of agency and capacity regarding 11 energy saving actions were self-reported and electricity consumption was metered before and during energy saving campaign. Findings show that levels of agency were lower than those of capacity for no-cost actions which require high engagement, while levels of capacity were lower than those of agency for high-cost action which require low engagement. In addition, households with high agency and high capacity reduced their electricity consumption by 9.39 % (on average); those with low agency and low capacity increased their consumption by 6.67 %; and those with a mismatch between agency and capacity reduced their consumption by 1.91 %.
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Notes
Degree-day figures quantify how hot or cold the weather has been as a single index number for the region and period of time (month or week). This allows us to account for the effect of weather on electricity consumption.
References
Abrahamse, W., Steg, L., et al. (2005). A review of intervention studies aimed at household energy conservation. Journal of Environmental Psychology , 25(3), 273–291.
Darby, S. (2006). The effectiveness of feedback on energy consumption, A Review for DEFRA of the Literature on Metering, Billing and direct Displays. Oxford: Environmental Change Institute.
Davies, M., & Oreszczyn, T. (2012). The unintended consequences of decarbonising the built environment: a UK case study. Energy and Buildings , 46(0), 80–85.
Druckman, A., & Jackson, T. (2008). Household energy consumption in the UK: a highly geographically and socio-economically disaggregated model. Energy Policy , 36(8), 3177–3192.
ECF (2010). European Climate Foundation. Decarbonization roadmaps for the EU-27, ECF.
Ellenberg, J. H. (1994). Selection bias in observational and experimental studies. Statistics in Medicine , 13(5–7), 557–567.
European Commission (2011). Energy Roadmap 2050 Brussles. European: Commission.
Eyre, N. (2012). Decentralisation of governance in the low carbon transition. The Handbook of Energy and Climate Change. R. Fouquet, Edward Elgar.
Faiers, A., Cook, M., et al. (2007). Towards a contemporary approach for understanding consumer behaviour in the context of domestic energy use. Energy Policy , 35(8), 4381–4390.
Frederiks, E. R., Stenner, K., et al. (2015). Household energy use: applying behavioural economics to understand consumer decision-making and behaviour. Renewable and Sustainable Energy Reviews , 41(0), 1385–1394.
Gram-Hanssen, K. (2010). Residential heat comfort practices: understanding users. Building Research and Information , 38(2), 175–186.
Hamilton, J., Mayne, R., et al. (2014). Scaling up local carbon action: the role of partnerships, networks and policy. Carbon Management , 5(4), 463–476.
Janda, K. B., & Parag, Y. (2011). A middle-out approach for improving energy efficiency in existing buildings, ECEEE Summer Study, Belambra Presqu'île de Giens. France: European Council for an Energy-Efficient Economy.
Janda, K. B., & Parag, Y. (2013). A middle-out approach for improving energy performance in buildings. Building Research and Information , 41(1), 39–50.
Loorbach, D., & Verbong, G. (Eds.) (2010). Governing the energy transition. Routledge: New York.
Lopes, M., Antunes, C., et al. (2012). Energy behaviours as promoters of energy efficiency: a twenty-first century review. Renewable and Sustainable Energy Reviews , 16(6), 4095–4104.
Lutzenhiser, L., K. Janda, et al. (2002). Understanding the response of commercial and institutional organizations to the California energy crisis. A report to the California Energy Commission - Sylvia Bender, Project Manager.
Madden, T. J., Ellen, P. S., et al. (1992). A comparison of the theory of planned behavior and the theory of reasoned action. Personality and Social Psychology Bulletin , 18(1), 3–9.
McMakin, A. H., Malone, E. L., et al. (2002). Motivating residents to conserve energy without financial incentives. Environment and Behavior , 34, 848.
McMillan, D. W., & Chavis, D. M. (1986). Sense of community: a definition and theory. Journal of Community Psychology , 14(1), 6–23.
Parag, Y. (2014). From energy security to the security of energy services: shortcomings of traditional supply-oriented approaches and the contribution of a socio-technical and user-oriented perspectives. Science & Technology Studies , 27(1), 97–108.
Parag, Y. (2015). Beyond energy efficiency: a ‘prosumer market’ as an integrated platform for consumer engagement with the energy system, ECEEE 2015 Summer Study on Energy Efficiency (pp. 15–23). ECEEE: France.
Parag, Y., & Janda, K. B. (2010). A middle-out approach to agency, capacity and societal change, The 8th British Institute of Energy Economics (BIEE) Academic Conference. Oxford, UK: BIEE.
Parag, Y., & Janda, K. (2014). More than filler: middle actors and socio-technical change in the energy system from the “middle-out”. Energy Research & Social Science , 3, 102–112.
Parag, Y., & Sovacool, B. K. (2016). Electricity market design for the prosumer era. Nature Energy , 1, 16032.
Parag, Y., Hamilton, J., et al. (2013). Network approach for local and community governance of energy: the case of Oxfordshire. Energy Policy , 62, 1064–1077.
Poortinga, W., Steg, L., et al. (2004). Values, environmental concern, and environmental behavior: a study into household energy use. Environment and Behavior , 36(1), 70–93.
Randall, D. M., & Fernandes, M. F. (1991). The social desirability response bias in ethics research. Journal of Business Ethics , 10(11), 805–817.
Schultz, P. W., Nolan, J. M., et al. (2007). The constructive, destructive, and reconstructive power of social norms. Psychological Science , 18(5), 429–434.
Seyfang, G. (2010). Community action for sustainable housing: building a low-carbon future. Energy Policy , 38(12), 7624–7633.
Shove, E. (2003). Users, technologies and expectations of comfort, cleanliness and convenience. Innovation: The European Journal of Social Science Research , 16(2), 193–206.
Skea, J., Ekins, P., et al. (Eds.) (2010). Energy 2050: making the transition to a secure low-carbon energy system. UKERC: London.
Smith, A. (2012). Civil society in sustainable energy transitions, Governing the energy transition. New York, Routledge: D. Loorbach and G. Verbong.
Smith, A., Voß, J.-P., et al. (2010). Innovation studies and sustainability transitions: the allure of the multi-level perspective and its challenges. Research Policy , 39(4), 435–448.
Sorrell, S. (2015). Reducing energy demand: a review of issues, challenges and approaches. Renewable and Sustainable Energy Reviews , 47(0), 74–82.
Stern, P. C. (2000). Toward a coherent theory of environmentally significant behavior. Journal of Social Issues , 56(3), 407–424.
van der Werff, E., & Steg, L. (2015). One model to predict them all: predicting energy behaviours with the norm activation model. Energy Research & Social Science , 6(0), 8–14.
Van Raaij, W. F., & Verhallen, T. M. M. (1983). A behavioral model of residential energy use. Journal of Economic Psychology , 3(1), 39–63.
Verbong, G. P., & Geels, F. W. (2010). Exploring sustainability transitions in the electricity sector with socio-technical pathways. Technological Forecasting and Social Change , 77(8), 1214–1221.
Walker, G., & Devine-Wright, P. (2008). Community renewable energy: what should it mean. Energy Policy , 36(2), 497–500.
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The EU FP7 Marie Curie CIG grant no. 303443, ‘STESS: Socio-technical approach to energy services security’ supported the writing of this paper. The authors wish to thank Dr. Tamar Trop, from Haifa University.
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Annex 1: The middle-out framework for energy transition
Annex 1: The middle-out framework for energy transition
The middle-out is a new and evolving framework for analyzing socio-techno-economic transitions, developed by Yael Parag and Kathryn B. Janda. Janda and Parag (2011, 2013) and Parag and Janda (2014) argue that despite the complex nature of the energy system, policy makers tend to simplistically divide it into energy suppliers and consumers. As a result, governments try to promote the transition to a low-carbon society by regulating energy suppliers in a top-down manner, while encouraging (economically and morally) end-users to reduce their energy consumption and support the transition from the bottom-up. However, at present, there seems to be a mismatch between many of the energy and climate change policy objectives (for example, 80 % emission reduction by 2050 in the UK) and the capability of top and bottom actors to deliver them within the existing frameworks of top-down and bottom-up actions. In this context, the middle-out framework (Janda and Parag 2011; Janda and Parag 2013; Parag and Janda, 2014) focuses on middle actors as agents of change. Middle actors in the case of energy are neither the regulator, the energy supplier or the consumer, but rather actors who influence various aspects of the ways energy is produced, delivered or consumed. This group includes actors such as community-based organizations and intermediaries that provide platforms and space for collective action (Hamilton, Mayne et al. 2014), religious leaders who influence behavioral norms including consumption norms, values and behavior (Parag and Janda, 2014), as well as building and planning professionals and associations who plan and construct buildings’ infrastructures and thus influence both the efficiency of the infrastructure and the energy-related interfaces with occupants (Janda and Parag 2011; Janda and Parag 2013).
Due to their position in-between top and bottom actors, to their own levels of agency and capacity, and to their unique characteristics and interactions with other actors in the field, middle actors are in a good position to meaningfully mediate between top and bottom actors, facilitate the interactions between them, enhance their levels of agency and capacity – and encourage and promote action. As such, they often serve as agents of change and exert their influence in three directions: downstream (e.g., on energy end users), upstream (e.g., on decision-makers) and sideways (e.g., on other middle actors) (Parag and Janda, 2014). Hence the name ‘middle-out’.
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Parag, Y., Zur, S. & Raz, N. Levels of consumers’ agency and capacity as predictors for electricity demand reduction in the residential sector. Energy Efficiency 10, 597–611 (2017). https://doi.org/10.1007/s12053-016-9471-6
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DOI: https://doi.org/10.1007/s12053-016-9471-6