, Volume 114, Issue 3, pp 1275–1326 | Cite as

Energy efficiency in buildings: analysis of scientific literature and identification of data analysis techniques from a bibliometric study

  • Talita Mariane Cristino
  • Antonio Faria Neto
  • Antonio Fernando Branco Costa


This study uses bibliometrics methods to analyze the specialized literature of energy efficiency in buildings, including the Scopus database during the period of time ranging from 1980 to 2016, to identify the most relevant publications, authors, researcher groups, the evolution of the theme over the years, journals, geographical areas and eventually data analysis techniques employed. The countries with the most contributions have been the USA, China and the UK, where the Lawrence Berkeley National Labor, Hong Kong Polytechnic University and City University of Hong Kong were the three institutions with the most publications in this area. The publications have been concentrated primarily in thirty-three journals. The three most important journals are Energy and Buildings, Applied Energy, and Energy and are categorized primarily in engineering, energy and environmental sciences. The key terms may be divided into seven clusters: Buildings and Energy Uses; Building Energy Conservation; Energy Consumption; Energy Consumption Forecasting and Computational Intelligence; Energy Efficiency and Climate Effects; Building Energy Efficiency and Multivariate Statistics; and Building Energy Analysis and Stochastic Processes. The Data Analysis Techniques contained seven groups: Regression Analysis, Descriptive Statistics, Multivariate Analysis, Computational Intelligence, Stochastic Processes, Inferential Statistics and Design of Experiments. The data analysis techniques identified in this article raise the possibility of reformulation and adequacy of the curricula of the undergraduate and graduate courses in the area of energy and smart buildings. The results of this research have shown a general perspective regarding the energy efficiency in buildings, which can be useful in showing relevant themes for further research.


Bibliometrics methods Energy efficiency Buildings Data analysis techniques 



The authors would like to thank the National Council for Scientific and Technological Development (CNPq) for supporting this research.


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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2017

Authors and Affiliations

  1. 1.São Paulo State University (UNESP), School of EngineeringGuaratinguetáBrazil

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