Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81528
Title: Mapping knowledge in the economic areas of green building using scientometric analysis
Authors: Xiao, X 
Skitmore, M
Li, H 
Xia, B
Keywords: Economic area
Green building
Knowledge map
Review
Scientometric
Issue Date: 2019
Publisher: Molecular Diversity Preservation International (MDPI)
Source: Energies, 2019, v. 14, no. 15, 3011 How to cite?
Journal: Energies 
Abstract: This paper presents the first inclusive scientometric review of the economic areas of green building (GBE). The aim is to methodically examine and summarize the state-of-the-art of the GBE body of knowledge. To this end, this study analyses 1713 GBE-related bibliographic records retrieved from the Web of Science by using the quantitative method of knowledge mapping. The knowledge base, knowledge domain, and knowledge evolution of how they interacted with each other are explored using document co-citation analysis and keywords co-citation analysis of the existing body of literature. The research findings are informative in recognizing and interpreting the underlying structure and trends in GBE. A knowledge map provides a valuable and instructive understanding of the evolution and status quo of the GBE knowledge body, as well as assisting in recognizing the gaps and deficiencies involved. The results will help in understanding how GBE knowledge is evolving and its role played in green building, and thus provide suggestions of how academic research can enhance sustainability practices in terms of economic area in the future.
URI: http://hdl.handle.net/10397/81528
EISSN: 1996-1073
DOI: 10.3390/en12153011
Rights: © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
The following publication Xiao X, Skitmore M, Li H, Xia B. Mapping Knowledge in the Economic Areas of Green Building Using Scientometric Analysis. Energies. 2019; 12(15):3011, is available at https://doi.org/10.3390/en12153011
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