Energy transition at local level: Analyzing the role of peer effects and socio-economic factors on UK solar photovoltaic deployment

Balta-Ozkan N., Yıldırım Öcal J., Connor P. M., Truckell I., Hart P.

Energy Policy, vol.148, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 148
  • Publication Date: 2021
  • Doi Number: 10.1016/j.enpol.2020.112004
  • Journal Name: Energy Policy
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, International Bibliography of Social Sciences, PASCAL, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Communication Abstracts, EconLit, Environment Index, Greenfile, Index Islamicus, INSPEC, PAIS International, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Spatial modelling, Local energy, Energy transition, Peer effect, Geographically weighted regression, TECHNOLOGY ADOPTION, CO2 EMISSIONS, DIFFUSION, DETERMINANTS, SYSTEMS, GROWTH, URBAN, CONSERVATION, INNOVATIONS, PATTERNS
  • TED University Affiliated: Yes


© 2020 The AuthorsA growing literature highlights the presence of spatial differences in solar photovoltaic (PV) adoption patterns. Central to forward planning is an understanding of what affects PV growth, yet insights into the determinants of PV adoption in the literature are limited. What factors do drive the adoption at local level? Are the effects of these factors geographically uniform or are there nuances? What is the nature of these nuances? Existing studies so far use aggregate macro datasets with limited ability to capture the role of peer effects. This paper considers some established variables but also broadens the base of variables to try to identify new indicators relating to PV adoption. Specifically, it analyses domestic PV adoption in the UK at local level using data on the number of charities as a proxy to capture the opportunities to initiate social interactions and peer effects. A geographically weighted regression model that considers the spatially varying relationship between PV adoption and socio-economic explanatory variables reveals significantly more variability than the global regression. Our results show that charities and self-employment positively influence PV uptake while other socio-economic variables such as population density has bidirectional impacts.