Social Acceptance of Energy Retrofit in Social Housing: Beyond the Technological Viewpoint

  • Jessica BalestEmail author
  • Daniele Vettorato
Conference paper
Part of the Green Energy and Technology book series (GREEN)


Optimized energy systems are achieved by an increase in energy efficiency in parallel with energy savings. SINFONIA is an FP7 European-funded project that aims to implement smart initiatives for optimized energy systems through deep-energy retrofit of social housing buildings in middle-size European cities (i.e., Bolzano, Italy). From a technical viewpoint, the project’s main challenge is facing retrofit interventions in inhabited flats; from a social one, the challenge is engaging tenants in the project to achieve an effective decrease in energy consumption through a change in energy use, behaviors, and practices. The bridge between technical and social viewpoints is created thanks to an engagement process of tenants that has the support of some tools, such as the smart-energy meter. The involvement of tenants in engagement activities and smart-energy meter interaction must necessarily account for their characteristics as social actors. A thorough description and analysis of tenants’ characteristics is therefore one of the most important starting points in such a research project. The aim of our work is to support experts in the design of smart-energy meters providing them with a methodology for the description and analysis of tenants’ characteristics and social contexts. We perform a cluster analysis on the socio-demographic data of tenants involved in the Bolzano SINFONIA case study, identifying three relevant clusters according to family characteristics. Our future research will focus on the design of smart-energy meters and the development of participatory and learning activities addressed to SINFONIA tenants in order to ensure energy savings.


Smart-energy meter Energy retrofit Social housing Cluster analysis Tenants’ profile 



We are thankful to Dr. Petra Scudo (EURAC research), who edited the text of the present investigation.

Work described in this paper is funded by the SINFONIA project which has received funding from the European Union’s Seventh Framework Programme for research, technological development, and demonstration under grant agreement No. 609019. The European Union is not liable for any use that may be made of the information contained in this document which is merely representing the authors’ view.


  1. Charrad, M., Ghazzali, N., Boiteau, V., & Niknafs, A. (2014). NbClust: An R package for determining the relevant number of clusters in a data set. Journal of Statistical Software, 61(6), 1–36.CrossRefGoogle Scholar
  2. Chirot, D. (1994). How Societies Change (pp. 184). Pine Forge Press.Google Scholar
  3. COP22. (2016, November). Informal Consultation on the First Session of the Conference of the Parties Serving as the Meeting of the Parties to the Paris Agreement (CMA 1) and on Item 4 of the Agenda of COP22.Google Scholar
  4. D’Oca, S., Corgnati, S. P., & Buso, T. (2014). Smart meters and energy savings in Italy: Determining the effectiveness of persuasive communication in dwellings. Energy Research & Social Science, 3, 131–142.CrossRefGoogle Scholar
  5. European Community. (2009). Directive 2009/28/EC of the European Parliament and of the Council on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC. Official Journal of the European Union, 60.Google Scholar
  6. European Union. (2012). Directive 2012/27/EU of the European Parliament and of the Council on Energy Efficiency, amending Directive 2009/125/EC and 2010/30/EU and repealing Directives 2004/8/EC and 2006/32/EC. Official Journal of the European Union, 56.Google Scholar
  7. Fischer, C. (2008). Feedback on household electricity consumption: A tool for saving energy? Energy Efficiency, 1(1), 79–104.CrossRefGoogle Scholar
  8. Frederiks, E., Stenner, K., & Hobman, E. (2015). The socio-demographic and psychological predictors of residential energy consumption: A comprehensive review. Energies, 8(1), 573–609.CrossRefGoogle Scholar
  9. Geelen, D., Reinders, A., & Keyson, D. (2013). Empowering the end-user in smart grids: Recommendations for the design of products and services. Energy Policy, 61, 151–161.CrossRefGoogle Scholar
  10. Haas, R., Auer, H., & Biermayr, P. (1998). The impact of consumer behavior on residential energy demand for space heating. Energy and Buildings, 27(2), 195–205.CrossRefGoogle Scholar
  11. Hardle, W. K., & Simar, L. (2015). Applied Multivariate Statistical Analysis (p. 800). Berlin, Heidelberg: Springer.zbMATHGoogle Scholar
  12. Hargreaves, T., Nye, M., & Burgess, J. (2010). Making energy visible: A qualitative field study of how householders interact with feedback from smart energy monitors. Energy Policy, 38(10), 6111–6119.CrossRefGoogle Scholar
  13. Johansson, R. (2003). Case study methodology. In International Conference Methodologies in housing research. Stockholm: Royal Institute of Technology and International Association of People-Environment Studies.Google Scholar
  14. Mietola, R., Miettinen, S., & Vehmas, S. (2017). Presenting and representing others: Towards an ethics of engagement. International Journal of Social Research Methodology, 20(3), 299–309.CrossRefGoogle Scholar
  15. Moore, N. (2012). The politics and ethics of naming: Questioning anonymisation in (archival) research. International Journal of Social Research Methodology, 15(4), 331–340.CrossRefGoogle Scholar
  16. Moriarty, P., & Honnery, D. (2012). Preparing for a low-energy future. Futures, 44(10), 883–892.CrossRefGoogle Scholar
  17. Rösch, C., Bräutigam, K., Kopfmüller, J., Stelzer, V., & Lichtner, P. (2017). Indicator system for the sustainability assessment of the German energy system and its transition. Energy, Sustainability and Society, 7, 13.Google Scholar
  18. Shove, E. (2003). Comfort, cleanliness and convenience: the social organization of normality (p. 240). Berg Publishers.Google Scholar
  19. Unfccc. (2015). Paris Agreement (22nd April 2016).Google Scholar
  20. Whitmarsh, L., O’Neill, S., & Lorenzoni, I. (2011). Engaging the public with climate change: Behaviour change and communication (p. 288). Routledge.Google Scholar
  21. Zografakis, N., Menegaki, A. N., & Tsagarakis, K. P. (2008). Effective education for energy efficiency. Energy Policy, 36(8), 3226–3232.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.EURAC ResearchBolzanoItaly

Personalised recommendations