Project #Economy, Policy Paper §9: Behavioural economy approach towards tackling energy poverty through positive energy districts

Project #Economy, Policy Paper §9: Behavioural economy approach towards tackling energy poverty through positive energy districts

Teodor Kalpakchiev,
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The review into behaviour and decision-making literature revealed predominance of social practice and social identity theories, which embed actions into social and collective norms, as well as theory of planned behaviour and social network theory[1], which investigate resp. the constraints of deployed policy, as well as the ability of homogenous actor constellations to instigate innovation. Besides from their community and background, viewed from a complexity science perspective, potential prosumers are influenced from the socio-technical surroundings[2]. An interesting approach stemming from the capabilities perspective of Amartya Sen, which emphasizes the ability to engage in meaningful social relations and participate in society[3].

Feedback (e.g. peer-to-peer comparison, digital realtime nudging, negative framing, provision of foregone repetitive payoffs) has proven to be an important element in experiments and especially if framed negatively, improves social learning due to loss aversion[4]. The inefficiency of overt frequency overload (e.g. of electronic feedback) can be circumvented through locally isolated micro-relations of social belonging as feedback mechanism[5]. Similarly, feedback can be combined with an education component in a mobile application such as Apolis Planeta[6]. When it comes to social context, it is noteworthy that in prosperous households, self-reporting if upgrades are present bears no significant results[7] and that generally income, education (together with agreeableness, openness, conscientiousness)[8] bear positive results in energy behaviour. Due to its restrictive context (context specific practices and cognitive bias) [9], the question of inducing any reduction of the rebound effect in social housing obliterates direct transposition of such lessons and points towards a more systemic approach to practice alteration.

Energy poverty’s billing perspective[10] would be less applicable in the research than the widely adopted services, e.g. unsatisfied needs for energy services, such as mobility, washing, heating, cooking, cooling and lighting[11], as well as the poor building energy performance (Bulgaria exhibits worst performance, least efforts and highest Gini coefficient)[12] perspectives.

Social housing dwellers are diversified (elderly, youth, students, immigrants, temporary workers), fragmented (in Italy due to possible sales L.560/93) and potentially segregated low income population, who fail to meet housing needs on market[13]. In the Casanova district in northern Italy, inhabitants have exhibited 167% greater consumption of heating than planned, proportionate to the complexity of technology, causal relationship with technical management and (reluctant) user behaviour[14].

Nevertheless, it provides an economy of scale in implementation of physical enhancements, provision of incentives, as well as financial costs[15]. The visibility of deployed technical modernization and pre-existing attitudes, overcoming fear and uncertainty through access to data, as well as engagement through education or in participatory planning and control improve the awareness, long-term communication and trust of inhabitants and can counter inter alia disengagement due to complex technical control or split incentives.[16] Profiling people according to background, age, knowledge can help produce personality-based energy reporting (altruists, adaptive easygoers, traditionalists) through providing either information on most efficient peers or a frame of more and less efficient neighbours to help frame choices[17]. To create new practices, images, forms of knowledge and technologies are to be combined in order to identify change inducing elements, overcome cognitive bias and transition to systemic lessons (such as relation of scarcity, trust and children to ventilation) [18].

Generally, willingness (‘the quality or state of being prepared to do something’) to participate in community energy services is dependent on sense of community, trust, energy independence and environmental concern (not much applicable to social housing)[19]. Additional knowledge about RE and the availability of easy to use, cheap and beneficial alternatives increases the propensity to employ the technology.[20] Residents of social housing also prefer ordinary (automatic) arrangements without necessarily engaging in sustainable modes of living, yet they have a responsibility to acquire basic knowledge.[21]

Different settings result in different outcomes, which are not necessarily applicable to social housing. (In a working environment) Promoting behavioural change is useful when people are unaware, information is tailored and interventions[22], which is in contrast with private commitments for energy saving behaviour results in actions only if perceived as effortful[23]. Digital energy saving tips and eco-feedback also bear different results[24]. In industry Personnel just as important for the maintenance of deployed RE[25].

How to ensure that experimenting towards behaviourally enabled

social positive energy districts informs policy?

In order to transition from a micro to macro perspective one ought to employ a governance perspective. For collaborative governance to take place, one needs principled engagement, shared motivation, whereby social rules, values and beliefs, influenced by development context, lifestyles and livelihoods[26]. Strategies should materialize existing compatible development concepts (e.g. systems thinking, circular metabolism, integrated infrastructure planning from simbiocity, but also PEDs and justice)[27]. Behaviours, infrastructure, technology, cultural meanings, market settings should be seen as emergent qualities of sociotechnical configurations evolving marked by path dependence, whereby social practices adaptation  deterministically reflects on policy design[28]. Such deliberate practices[29] require new configuration or service, higher order learning in participants, change in interpretative frames and can result to bottom-up niche innovation, e.g. strategic planning, energy requirements, networks of change laboratories, or changes in discourse.

Particularly, PEDs can be defined as “an urban area with clear boundaries, consisting on buildings of different typologies that actively manage the energy flow between them and the larger energy system to reach an annual positive energy balance”, requires needs-based diagnosis of city priorities (retrofitting, RE, storage, reducing energy consumption from heating and cooling, district solutions, smart systems, storage), with  replication depending on the capacity to cooperate with stakeholders[30]. In reality, PED cases reveal tendency to integrate carbon sinks, biodiversity and innovations in urbanism (e.g. vertical solar and gardening) for quality of life, low/no emission transport, electricity trading (e.g. between price areas), innovation community[31].

To inform policy through the micro-behavioural scale, a participatory mechanism would inform over preferences towards alternatives of both energy efficiency (retrofitting, appliances sharing and turning off, usage of cooling and heating), renewable energy sources, financing models. Deriving from the capabilities approach, a model for creating societal capabilities and if possible, even financial gains, would be sought. Thus, a combination of engagement and education could produce capabilities for social housing dwellers to engage in society through the deployment of RE/PEDs. For being controlled voluntarily and democratically renewable energy cooperatives exhibit strong community features (in contrast to indifference and uncertainty of non-participants) and can induce a form of self-identity pertinent to the „fulfilment of criteria for any societal role“[32]. Participatory arrangements and reminders of detrimental effects to community needs also stimulate collective identity, cooperability and energy savings behaviour[33].

Last, but not least, as policy should take not of complexity, a perspective of a socio(institutional)-ecological-psychological nexus resulting in a panarchy[34] will be taken, whereby the analysis would seek to address the overlapping points between the three systems. As output one could have top-down, bottom-up, demand- and supply-side incentives, lessons for replicable epistemic arrangements that transcend the social network[35]. These should take note of proportionality as redistributive background institution for justice[36] that can overcome the split incentivization between social housing dwellers, public authority, energy providers and co-financing party. Modular policy adaptation[37] and reconfiguration of actors[38] could be based on human preferences and non-human conditions, thus ensuring Policy effectiveness contingent upon reflexivity over adaptive normative beliefs[39].

[1] Laurens X.W.Hesselink & Emile J.L.Chappin (2019) Adoption of energy efficient technologies by households – Barriers, policies and agent-based modelling studies, Renewable and Sustainable Energy Reviews Volume 99, January 2019, Pages 29-41

[2] Labanca & Bertoldi, Beyond energy efficiency and individual behaviours: policy insights from social practice theories, Energy Policy 115 (2018) 494–502

[3] Middlemis et al., Energy poverty and social relations: A capabilities approach, Energy Research & Social Science 55 (2019) 227–235

[4] Casal et al., Feedback and Efficient Behaviour, PLoS ONE 12(4): e0175738     

[5] Makivierikko et al., Exploring the viability of a local social network for creating persistently engaging energy feedback and improved human well-being, Journal of Cleaner Production 224 (2019) 789-801

[6] Csoknyai et al., Analysis of energy consumption profiles in residential buildings and impact assessment of a serious game on occupants’ behavior, Energy & Buildings 196 (2019) 1–20

[7] Bardsley et al., Domestic thermal upgrades, community action and energy saving: A threeyear experimental study of prosperous households, Energy Policy 127 (2019) 475–485

[8] Shen et al, Big Five Personality Traits, Demographics and Energy Conservation Behaviour: A Preliminary Study of Their Associations, Energy Procedia 158 (2019) 3458–3463

[9] N. Della Valle et al., In search of behavioural and social levers for effective social housing retrofit programs, Energy & Buildings 172 (2018) 517–524, p. 519

[10] Kearns et al., Occupant behaviour as a fourth driver of fuel poverty, Energy Policy 129 (2019), p. 1143–1155

[11] Bouzarovski & Petrova, A global perspective on domestic energy deprivation: Overcoming the energy poverty–fuel poverty binary, Energy Research & Social Science 10 (2015) 31–40, p. 34

[12] Kyprianou et al., Energy poverty policies and measures in 5 EU countries: A comparative study, Energy & Buildings 196 (2019) 46–60, p. 46-50

[13] Boeri et al., The Redevelopment of The Heritage of Social Housing in Italy: Survey and Assessment Instruments. The Case Study of Pilastro Neighborhood in Bologna, Procedia Engineering (2011) 997 – 1005

[14] Marco et al, Monitoring Of CasaNova Low Energy District: Result And Discussion, Energy Procedia 96 (2016), p. 897-905

[15] McCabe et al., The application of renewable energy to social housing: A systematic review, Volume 114, March 2018, Pages 549-557

[16] Ibid.

[17] Shen & Cui, Behavior Driven Energy Efficiency: A Customized Feedback Approach, Energy Procedia 78 ( 2015 ) 2112 – 2117

[18] Della Valle et al., In search of behavioural and social levers for effective social housing retrofit programs, Energy & Buildings 172 (2018) 517–524

[19] Koirala et al., Trust, awareness, and independence: Insights from a socio-psychological factor analysis of citizen knowledge and participation in community energy systems, Energy Research & Social Science 38 (2018) 33–40

[20] Zahari & Esa, Motivation to Adopt Renewable Energy among Generation Y, Procedia Economics and Finance 35 ( 2016 ) 444 – 453

[21] J. Johansson, Sustainable Social Housing, Technology and Users, Proceeding of the 6th International Conference on Sustainable Architecture (2019), p. 70-77

[22] Ornaghi et al., The effect of behavioural interventions on energy conservation in naturally ventilated offices, Energy Economics 74 (2018) 582–591

[23] Werff et al., Pull the plug: How private commitment strategies can strengthen personal norms and promote energy-saving in the Netherlands, Energy Research & Social Science 54 (2019) 26–33

[24] Han & Lu, The Influence and Effectiveness of Information Conveying Means in Energy Behavior Interventions, Energy Procedia 142 (2017) 2137–2142

[25] Stoldt et al., Resource Networks: Decentralised factory operation utilising renewable energy sources, Procedia CIRP 26 ( 2015 ) 486 – 491

[26] Foran et al., Understanding energy-related regimes: A participatory approach from Central Australia, Energy Policy 91 (2016) 315–324

[27] Joanna Williams, Can low carbon city experiments transform the development regime?, Futures 77 (2016) 80–96

[28] Labanca & Bertoldi, Beyond energy efficiency and individual behaviours: policy insights from social practice theories, Energy Policy 115 (2018) 494–502

[29] Kivimaa et al., Experiments in climate governance e A systematic review of research on energy and built environment transitions, Journal of Cleaner Production 169 (2017) 17-29

[30] Alpagut et al., Positive Energy Districts Methodology and Its Replication Potential, Proceedings 2019, 20, 8, p. 1-4

[31] Gollner, et al., Booklet Of Positive Energy Districts In Europe,  A compilation of projects towards sustainable urbanization and the energy transition, Urban Europe, 2019

[32] Bauwens, T., Devine-Wright, P., 2018. Positive energies? An empirical study of community energy participation and attitudes to renewable energy, Energy Policy 118, 612–625

[33] Della Valle & Poderi, What works for consumer engagement in the energy transition: Experimenting with a behavioural-sociological approach, Shape Energy Research Design Challenge

[34] C. S. Holling, Understanding the Complexity of Economic, Ecological, and Social Systems, Ecosystems 2001, 4: 390-405

[35] Eva Heiskanen & Kaisa Matschoss, Understanding the uneven diffusion of building-scale renewable energy systems: A review of household, local and country level factors in diverse European countries, Renewable and Sustainable Energy Reviews 75, 2017 580–591

[36] John Rawls, A Theory of Justice, Revised edition 1971, 1999, Harvard University Press

[37] Eva Heiskanen, Heli Nissilä & Pasi Tainio, Promoting residential renewable energy via peer-to-peer learning, Applied Environmental Education & Communication, 2017, 16:2, 105-116

[38] Darcy Parks, Energy efficiency left behind? Policy assemblages in Sweden’s most climate-smart city, European Planning Studies, 2019, 27:2, 318-335

[39] Peter H. Feindt & Sabine Weiland, Reflexive governance: exploring the concept and assessing its critical potential for sustainable development. Introduction to the special issue, Journal of Environmental Policy & Planning, 2018, 20:6, 661-674


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