Science mapping the knowledge domain of energy performance research in the AEC industry: A scientometric analysis

领域(数学分析) 工程类 数据科学 计算机科学 数学 数学分析
作者
Mahshad Azima,Senem Seyis
出处
期刊:Energy [Elsevier BV]
卷期号:264: 125938-125938 被引量:5
标识
DOI:10.1016/j.energy.2022.125938
摘要

This study aims to reveal the current state of energy performance research in the AEC industry. The research objectives are to identify hot topics (i.e., knowledge domain) and hot keywords (i.e., knowledge base), productive countries and institutions, research gaps, and emerging areas in this domain (i.e., knowledge evolution). For this purpose, systematic bibliometric and scientometric analyses were performed by referring to 5489 bibliometric records published between 1991 and 2023. CiteSpace, VOSviewer, and Gephi were used for performing scientometric analysis. The key points include (1) promoting research collaborations between countries and institutions, (2) uncovering gaps and requirements of optimizing energy performance through pre-construction, construction, operation and maintenance, (3) identifying the target market for stakeholders and financiers, and (4) guiding to specify the common grounds for international regulations and policies. Further, this study presents a knowledge map summarizing the prominent research results. The contribution is to provide a holistic comprehension of the recent status, hot keywords and topics, productive countries and institutions, research gaps, and emerging areas of energy performance. The gaps revealed in this study show possible future research directions, necessities, and the fields that should be investigated. Accordingly, this research would be a valuable guideline for professionals addressing energy performance. • 5489 publications on energy performance in the AEC industry are systematically reviewed. • Co-word, cluster, co-author, and co-citation analyses are conducted. • Knowledge base, knowledge domain, and knowledge evolution of the field are revealed. • CiteSpace, VOSviewer, and Gephi are used for performing scientometrics. • A knowledge map presenting the prominent results is established.

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