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

Author

Listed:
  • Talita Mariane Cristino

    (São Paulo State University (UNESP), School of Engineering)

  • Antonio Faria Neto

    (São Paulo State University (UNESP), School of Engineering)

  • Antonio Fernando Branco Costa

    (São Paulo State University (UNESP), School of Engineering)

Abstract

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.

Suggested Citation

  • Talita Mariane Cristino & Antonio Faria Neto & Antonio Fernando Branco Costa, 2018. "Energy efficiency in buildings: analysis of scientific literature and identification of data analysis techniques from a bibliometric study," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 1275-1326, March.
    • Handle: RePEc:spr:scient:v:114:y:2018:i:3:d:10.1007_s11192-017-2615-4
    DOI: 10.1007/s11192-017-2615-4
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    References listed on IDEAS

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    Cited by:

    1. Cristino, T.M. & Lotufo, F.A. & Delinchant, B. & Wurtz, F. & Faria Neto, A., 2021. "A comprehensive review of obstacles and drivers to building energy-saving technologies and their association with research themes, types of buildings, and geographic regions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    2. Hamdi A. Al-Jamimi & Galal M. BinMakhashen & Lutz Bornmann, 2022. "Use of bibliometrics for research evaluation in emerging markets economies: a review and discussion of bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5879-5930, October.
    3. Thaís Vieira Nunhes & Enzo Viviani Garcia & Maximilian Espuny & Vitor Homem de Mello Santos & Raine Isaksson & Otávio José de Oliveira, 2021. "Where to Go with Corporate Sustainability? Opening Paths for Sustainable Businesses through the Collaboration between Universities, Governments, and Organizations," Sustainability, MDPI, vol. 13(3), pages 1-31, January.
    4. Zezhou Wu & Kaijie Yang & Xiaofan Lai & Maxwell Fordjour Antwi-Afari, 2020. "A Scientometric Review of System Dynamics Applications in Construction Management Research," Sustainability, MDPI, vol. 12(18), pages 1-16, September.
    5. Dejian Yu & Zeshui Xu & Wanru Wang, 2019. "A bibliometric analysis of Fuzzy Optimization and Decision Making (2002–2017)," Fuzzy Optimization and Decision Making, Springer, vol. 18(3), pages 371-397, September.

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