scholarly journals A Systematic Literature Network Analysis of Existing Themes and Emerging Research Trends in Circular Economy

2020 ◽  
Vol 12 (4) ◽  
pp. 1633 ◽  
Author(s):  
Fatima Khitous ◽  
Fernanda Strozzi ◽  
Andrea Urbinati ◽  
Fernando Alberti

The debate about Circular Economy (CE) has been increasingly enriched by academics through a vast array of contributions, based on several theoretical perspectives and emanating from several research domains. However, current research still falls short of providing a holistic and broader view of CE, one that combines existing themes and emerging research trends. Accordingly, based on a Systematic Literature Network Analysis, this paper tackles this gap. First, a Citation Network Analysis is used to unearth the development of the CE literature based on papers’ references, whilst the Main Path is traced to detect the seminal papers in the field through time. Second, to consider the literature in its broader extent, a Keywords Co-Occurrence Network Analysis is conducted based on papers’ keywords, whereby all papers in the dataset, including the non-cited papers, are assessed. Additionally, a Global Citation Score analysis is conducted to uncover the recent breakthrough research, in addition to the Burst Analysis used to detect the dynamic development of CE literature over time. By doing so, the paper explores the development of the CE body of knowledge, reveals its dynamic evolution over time, detects its main theoretical perspectives and research domains, and highlights its emerging topics. Our findings unfold the evidence of eight main trends of research about CE, unearth the path through which the CE concept emerged and has been growing, and concludes with promising avenues for future research.

2021 ◽  
pp. 004051752110362
Author(s):  
Ka-Po Lee ◽  
Joanne Yip ◽  
Kit-Lun Yick ◽  
Chao Lu ◽  
Chris K Lo

Receptivity towards textile-based fiber optic sensors that are used to monitor physical health is increasing as they have good flexibility, are light in weight, provide wear comfort, have electromagnetic immunity, and are electrically safe. Their superior performance has facilitated their use for obtaining close to body measurements. However, there are many related studies in the literature, so it is challenging to identify the knowledge structure and research trends. Therefore, this article aims to provide an objective and systematic literature review on textile-based fiber optic sensors that are used for monitoring health issues and to analyze their trends through a citation network analysis. A full-text search of journal articles was conducted in the Web of Science Core Collection, and a total of 625 studies was found, with 47 that were used as the sample. Also, CitNetExplorer was used for analyzing the research domains and trends. Three research domains were identified, among them, “Flexible sensors for vital signs monitoring” is the largest research cluster, and most of the articles in this cluster focus on respiratory monitoring. Therefore, this area of study should probably be on the academic radar. The collection of data on textile-based fiber optic sensors is invaluable for evaluating degree of rehabilitation, detecting diseases, preventing accidents, as well as gauging the performance and training successfulness of athletes.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Syed Asif Raza ◽  
Srikrishna Madhumohan Govindaluri

PurposeThe purpose of this paper is to conduct a structured literature review using advanced bibliometric tools to understand the existing knowledge base, understand the trends in omni-channel (OC) research and identify emerging research topics.Design/methodology/approachMore than 500 articles selected through a keyword combination search from reputed databases of peer-reviewed academic sources from period 2009–19 are analyzed for the purposes of this study. The study first presents an exploratory analysis to determine influential authors, sources and regions, among other key aspects. Second, several network analyses including co-citation and dynamic co-citation network analyses are conducted to identify themes. These allow identifying research clusters and emerging research topics algorithmically. Both centrality and modularity-based clustering are employed. A content analysis of the most influential groups within OC literature for each cluster is included.FindingsThe findings of this paper make unique contributions by using advanced tools from network analysis along with the standard bibliometric analysis tools to explore the current status of OC research, identify existing themes and the guidance for potential areas of future research interest in OC.Practical implicationsThis research provides a comprehensive view of the range of topics of importance that have been discussed in the literature of OC management. These research trends can serve as a quick guide to researchers and practitioners to improve decision making and also develop strategies.Originality/valueThe paper employs advanced tools for the first time to review the literature of OC retailing. The sophisticated tools include co-citation and dynamic co-citation network analysis.


2016 ◽  
Vol 138 (3) ◽  
Author(s):  
Dar-Zen Chen ◽  
Ya-Yun Lee

This paper presents a longitudinal analysis through bibliometrics from three perspectives: geospatial analysis of research productivity, citation network analysis of journals, and top productive researchers with research communities. The purpose of these analyses is to detect the development and research trends of mechanism and machine theory (MMT) field. The results indicate that the productivity of MMT publications shows a growing trend. The United States (U.S.) has dominated MMT publications, but its ratio has dropped off approximately twenty percent in the past three decades, while China (CN) has rapidly grown in its quantity and ratio of MMT publications. The concentration of MMT publications among various countries has declined over time. Through citation network analysis, the relationships between journals in the MMT field are identified and their variations over periods are derived. The citations have been centered between five related journals and three core journals. Additionally, the evolution of research communities corresponding to the top 30 productive researchers and the distribution of the publications in each community among countries are identified.


Author(s):  
Erika Fujii ◽  
Takuya Takata ◽  
Hiroko Yamano ◽  
Masashi Honma ◽  
Masafumi Shimokawa ◽  
...  

AbstractCertain innovative technologies applied to medical product development require novel evaluation approaches and/or regulations. Horizon scanning for such technologies will help regulators prepare, allowing earlier access to the product for patients and an improved benefit/risk ratio. This study investigates whether citation network analysis and text mining of scientific papers could be a tool for horizon scanning in the field of immunology, which has developed over a long period, and attempts to grasp the latest research trends. As the result of the analysis, the academic landscape of the immunology field was identified by classifying 90,450 papers (obtained from PubMED) containing the keyword “immune* and t lymph*” into 38 clusters. The clustering was indicative of the research landscape of the immunology field. To confirm this, immune checkpoint inhibitors were used as a retrospective test topic of therapeutics with new mechanisms of action. Retrospective clustering around immune checkpoint inhibitors was found, supporting this approach. The analysis of the research trends over the last 3 to 5 years in this field revealed several candidate topics, including ARID1A gene mutation, CD300e, and tissue resident memory T cells, which shows notable progress and should be monitored for future possible product development. Our results have demonstrated the possibility that citation network analysis and text mining of scientific papers can be a useful objective tool for horizon scanning of life science fields such as immunology.


2018 ◽  
Vol 19 (4) ◽  
pp. 512-530 ◽  
Author(s):  
Mike C. Parent ◽  
Tyler C. Bradstreet ◽  
Kevin A. Harmon ◽  
Jay McAndrew ◽  
Allison Comiskey ◽  
...  

2019 ◽  
Author(s):  
Denis REALE ◽  
KHELFAOUI ◽  
Pierre-Olivier Montiglio ◽  
YVES GINGRAS

In this paper we used a co-citation network analysis to quantify and illustrate the dynamic patterns of research in ecology and evolution over 40 years (1975–2014). We addressed questions about the historical patterns of development of these two fields. Have ecology and evolution always formed a coherent body of literature? What ideas have motivated research activity in subfields, and how long have these ideas attracted the attention of the scientific community? Contrary to what we expected, we did not observe any trend towards a stronger integration of ecology and evolution into one big cluster that would suggest the existence of a single community. Three main bodies of literature have stayed relatively stable over time: population/community ecology, evolutionary ecology, and population/quantitative genetics. Other fields disappeared, emerged or mutated over time. Besides, research organization has shifted from a taxon-oriented structure to a concept-oriented one over the years, with researchersworking on the same topics but on different taxa showing more interactions.


Author(s):  
Leonardo B. Furstenau ◽  
Bruna Rabaioli ◽  
Michele Kremer Sott ◽  
Danielli Cossul ◽  
Mariluza Sott Bender ◽  
...  

The COVID-19 pandemic has affected all aspects of society. Researchers worldwide have been working to provide new solutions to and better understanding of this coronavirus. In this research, our goal was to perform a Bibliometric Network Analysis (BNA) to investigate the strategic themes, thematic evolution structure and trends of coronavirus during the first eight months of COVID-19 in the Web of Science (WoS) database in 2020. To do this, 14,802 articles were analyzed, with the support of the SciMAT software. This analysis highlights 24 themes, of which 11 of the more important ones were discussed in-depth. The thematic evolution structure shows how the themes are evolving over time, and the most developed and future trends of coronavirus with focus on COVID-19 were visually depicted. The results of the strategic diagram highlight ‘CHLOROQUINE’, ‘ANXIETY’, ‘PREGNANCY’ and ‘ACUTE-RESPIRATORY-SYNDROME’, among others, as the clusters with the highest number of associated citations. The thematic evolution. structure presented two thematic areas: “Damage prevention and containment of COVID-19” and “Comorbidities and diseases caused by COVID-19”, which provides new perspectives and futures trends of the field. These results will form the basis for future research and guide decision-making in coronavirus focused on COVID-19 research and treatments.


Sign in / Sign up

Export Citation Format

Share Document