TY - JOUR
T1 - Analysis of the trend in the knowledge of environmental responsibility research
AU - Yang, Rui
AU - Wong, Christina W.Y.
AU - Miao, Xin
N1 - Funding Information:
This work is supported by the National Natural Science Foundation of China (Grant No. 71471047 ), the Research Grants Council of Hong Kong Special Administration Region (Grant No. GRF PolyU 152031/17B ), and the Hong Kong Polytechnic University (Grant No.: SB1F ).
Publisher Copyright:
© 2020 Elsevier Ltd
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - With the rapid increase of environmental responsibility (ER) research in the past few years, it is common to see interdisciplinary studies in this field. Thus, it is important to conduct a comprehensive analysis of the knowledge progress of ER to better navigate the future research activities. This paper combines the advantages of the traditional bibliometric tools with the strengths of the latest bibliometric software CiteSpace to achieve a comprehensive knowledge review of ER. First, this work conducts a comprehensive assessment and provides descriptive statistics on the sample papers. We extracted the top 52 keywords in 3656 ER papers from the Web of Science published in the past five years. By using co-word analysis, cluster analysis and social network analysis, this paper obtains keyword networks that cover five major categories of ER research: (1) stakeholder participation; (2) ER related theories; (3) management and performance; (4) sustainable development supply chain; (5) drivers. Using the method of multi-dimensional scaling, we proposed a spatial framework that identifies the main spatial structure of the current ER research by summarizing the high-frequency terminologies. We used the time-line mapping and strong citation burst in CiteSpace to present the knowledge evolution path of ER, revealing how ER-related research evolved over time, and to triangulate the results of cluster analysis. We also summarize three features of ER research and thus identifies research opportunities. At last, we build a knowledge graph model of ER research by integrating knowledge base, knowledge domain, and knowledge evolution in ER field.
AB - With the rapid increase of environmental responsibility (ER) research in the past few years, it is common to see interdisciplinary studies in this field. Thus, it is important to conduct a comprehensive analysis of the knowledge progress of ER to better navigate the future research activities. This paper combines the advantages of the traditional bibliometric tools with the strengths of the latest bibliometric software CiteSpace to achieve a comprehensive knowledge review of ER. First, this work conducts a comprehensive assessment and provides descriptive statistics on the sample papers. We extracted the top 52 keywords in 3656 ER papers from the Web of Science published in the past five years. By using co-word analysis, cluster analysis and social network analysis, this paper obtains keyword networks that cover five major categories of ER research: (1) stakeholder participation; (2) ER related theories; (3) management and performance; (4) sustainable development supply chain; (5) drivers. Using the method of multi-dimensional scaling, we proposed a spatial framework that identifies the main spatial structure of the current ER research by summarizing the high-frequency terminologies. We used the time-line mapping and strong citation burst in CiteSpace to present the knowledge evolution path of ER, revealing how ER-related research evolved over time, and to triangulate the results of cluster analysis. We also summarize three features of ER research and thus identifies research opportunities. At last, we build a knowledge graph model of ER research by integrating knowledge base, knowledge domain, and knowledge evolution in ER field.
KW - Environmental responsibility
KW - Knowledge graph
KW - Knowledge progress
KW - Research opportunities
UR - http://www.scopus.com/inward/record.url?scp=85089592748&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2020.123402
DO - 10.1016/j.jclepro.2020.123402
M3 - Review article
AN - SCOPUS:85089592748
SN - 0959-6526
VL - 278
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 123402
ER -