Citation Network Analysis Research Articles

Machine learning in occupational accident analysis: A review using science mapping approach with citation network analysis

The present study reviews the publications that examine the application of machine learning (ML) approaches in occupational accident analysis. The review process includes four phases of analysis, namely bibliometric search, descriptive analysis, scientometric analysis, and citation network analysis (CNA). In the bibliometric search, a total of 232 articles are systematically screened out from 1995 to 2019 (up to May). Then, descriptive analysis and scientometric analysis are carried out to find the influences of journals, authors, authors’ keywords, articles/documents, and countries/regions in developing the domain. Thereafter, CNA is carried out to classify the publications according to the research themes and methods used. From this extensive review, several key findings are obtained in the application of ML approaches in occupational accident analysis. USA, China, and Taiwan are the leading countries/regions in publishing articles. The four major research domains are (i) prediction of incident outcomes, (ii) extraction of rule based patterns, (iii) prediction of injury risk, and (iv) prediction of injury severity. Then, a taxonomy of the ML algorithms used is developed. Finally, research gaps and safety issues are highlighted and the scope for future is discussed.

Current State and Future Trends: A Citation Network Analysis of the Academic Performance Field.

Background: In recent years, due to its complexity and relevance, academic performance has become a controversial research topic within the health and educational field. The main purposes of this study were to analyze the links between publications and authors via citation networks, to identify the different research areas and to determine the most cited publications. Methods: The publication search was performed through the Web of Science database, using the term “Academic Performance” for a time interval from 1952 to 2019. The software used to analyze the publications was the Citation Network Explorer. Results: We found a total of 16,157 publications with 35,213 citations generated in the network, and 2018 had the highest number of publications of any year. The most cited publication was published in 2012 by Richardson et al. with a citation index score of 352. By using the clustering function, we found nine groups related to different areas of research in this field: health, psychology, psychosociology, demography, physical activity, sleep patterns, vision, economy, and delinquency. Conclusions: The citation network showed the main publications dealing with the different factors that affect academic performance, and it was determined that psychological and psychosocial factors were the most relevant.

Resilience of athletes: a systematic review based on a citation network analysis

The aims of the present study are to understand indicators and the scope of theoretical models adopted to describe athletes’ resilience, as well as to analyze their impact on investigations about such resilience. A search for original academic publications within a 10-year period was conducted in the PubMed / Medline, Web of Science, Taylor and Francis, Lilacs, Scopus, Humam Kinects and Science Direct databases, to substantiate a systematic literature review on athletes’ resilience. Articles were analyzed based on their methodological characteristics and citation network analysis. In total, 47 articles were identified and the most referenced one was Fletcher and Sarkar (2012), which was followed by Galli and Vealey (2008). The Grounded Theory of Psychological Resilience and Optimal Sport Performance by Fletcher and Sarkar (2012) seems to encompass the basic theoretical elementary aspects to better understand athletes’ resilience, so far. To conclude resilience is an on-going dynamic process based on individual characteristics and interactions with the environment.

A structural analysis approach to identify technology innovation and evolution path: a case of m-payment technology ecosystem

Purpose The evolution of technology has become the mainstream of the current technological innovation era. Technological change is organized in its unique pattern and a new approach that takes place in a systematic and selective manner. Such change is generally molded with the amalgamation of various factors, namely, economic, social or scientific and technological. This paper aims to focus on identifying technological trajectories in a technological ecosystem with the case of m-payment technology. Design/methodology/approach This study constructs a patent citation network for mobile payment service technology through patent citation data and identifies the main evolution process using the main path analysis of the network. The scope of this study focuses on key innovation using social network analysis and patent citation network, validated using the case of a mobile payment system and analyzing its technological trajectory. Findings Analyzing technology evolution provides a greater insight of the overall technology landscape to the researcher and practitioner. Analyzing the m-payment technology landscape gives three main categories of m-payment systems: the mobile financial transaction system), the payee mobile device payment selection system and e-wallet services. Originality/value The novelty of this research lies in the process of identifying technological evolution using social network and patent citation network analysis. The case of m-payment technology ecosystem is studied quantitatively which is not explored by previous researchers. This research provides a way to develop the main path technology of innovative products or services to identify technology evolution using the case of m-payment landscape.

Reviewing ISO Compliant Multifunctionality Practices in Environmental Life Cycle Modeling

The standard ISO 14044:2006 defines the hierarchical steps to follow when solving multifunctionality issues in life cycle assessment (LCA). However, the practical implementation of such a hierarchy has been debated for twenty-five years leading to different implementation practices from LCA practitioners. The first part of this study discussed the main steps where the ISO hierarchy has been implemented differently and explored current multifunctionality practices in peer-reviewed studies. A text-mining process was applied to quantitatively assess such practices in the 532 multifunctional case studies found in the literature. In the second part of the study, citation network analysis (CNA) was used to identify the major publications that influenced the development of the multifunctionality-debate in LCA, i.e., the key-route main path. The identified publications were then reviewed to detect the origins of the different practices and their underlying theories. Based on these insights, this study provided some “food for thought” on current practices to move towards consistent methodology. We believe that such an advancement is urgently needed for better positioning LCA as a tool for sustainability decision-making. In particular, consistent allocation practices could be especially beneficial in bioeconomy sectors, where production processes are usually multifunctional, and where current allocation practices are not harmonized yet.

The most cited and co-cited COVID-19 articles: Knowledge base for rehabilitation team members.

The COVID-19 outbreak pandemic is a situation without a tested action plan. Rehabilitation team members have been called for duty with new responsibilities in addition to their conventional roles in the healthcare system. The infectious disease specialists are updating the knowledge base in limited time in clinical settings. The number of articles in PubMed grows at an increasing rate. The purpose of this study is to identify core COVID-19 articles by citation and co-citation network analysis in the PMC subset of PubMed. Citation and co-citation network analysis methods were used to identify core articles and knowledge base. COVID-19 terms query retrieved 15,387 articles in PubMed. These articles formed a citation network with 6,778 articles and 25,163 PMC-PubMed citations. The main article cluster in the co-citation network consists of 2,811 articles and 78,844 co-citations. The number of COVID-19 articles in PubMed is increasing at a very high rate. Citation and co-citation network analysis are advantageous techniques to identify knowledge base in a scientific discipline. These techniques may help rehabilitation specialists to identify core articles efficiently.

Trends in Life Insurance Demand and Lapse Literature

Abstract The article analyzes the interconnectedness and gaps between two interrelated streams of literature, evolving in different time periods, by employing bibliometric tools. The research on the factors of life insurance demand started in the late 1960s and early 1970s, while more intensive works on the drivers of lapses in life insurance appeared during the 2000s. We map the research fields using our own criteria to create clusters and visualize the flow of knowledge within and between the clusters employing citation network analysis (CNA). We contribute by providing the most comprehensive systematic review that integrates both fields, additionally encapsulating studies on the demand for policy loans. The article detects the most important drivers of life insurance policyholder behavior during his/her lifetime and opens new horizons for future research.

Exploring knowledge flow within a technology domain by conducting a dynamic analysis of a patent co-citation network

Purpose This paper aims to present a methodology by which future knowledge flow can be predicted by predicting co-citations of patents within a technology domain using a link prediction algorithm applied to a co-citation network. Design/methodology/approach Several methods and approaches are used: a dynamic analysis of a patent citation network to identify technology life cycle phases, patent co-citation network mapping from the patent citation network and the application of link prediction algorithms to the patent co-citation network. Findings The results of the presented study indicate that future knowledge flow within a technology domain can be predicted by predicting patent co-citations using the preferential attachment link prediction algorithm. Furthermore, they indicate that the patent – co-citations occurring between the end of the growth life cycle phase and the start of the maturation life cycle phase contribute the most to the precision of the knowledge flow prediction. Finally, it is demonstrated that most of the predicted knowledge flow occurs in a time period closely following the application of the link – prediction algorithm. Practical implications By having insight into future potential co-citations of patents, a firm can leverage its existing patent portfolio or asses the acquisition value of patents or the companies owning them. Originality/value It is demonstrated that the flow of knowledge in patent co-citation networks follows a rich get richer intuition. Moreover, it is show that the knowledge contained in younger patents has a greater chance of being cited again. Finally, it is demonstrated that these co-citations can be predicted in the short term when the preferential attachment algorithm is applied to a patent co-citation network.

Learning Analytics Research in Relation to Educational Technology: Capturing Learning Analytics Contributions with Bibliometric Analysis

In this study the authors conducted an empirical, bibliometric analysis of current literature in learning analytics. The authors performed a citation network analysis and found three dominant clusters of research. A qualitative thematic review of publications in these clusters revealed distinct context, goals, and topics. The largest cluster focused on predicting student success and failure, the second largest on using analytics to inform instructional design, and the third on concerns in implementing learning analytics systems. The authors suggest that further collaboration with educational technology researchers and practitioners may be necessary for learning analytics to reach its interdisciplinary goal. The authors also note that learning analytics currently does not often take place in K-12 settings, and that the burden of creating learning interventions still seemed to reside mainly with practitioners.

Destination food research: a bibliometric citation review (2000–2018)

PurposeThe purpose of this paper is to explore the knowledge infrastructure of destination food research based on a systematic literature review. This bibliometric analysis involves authors, institutions, countries and co-citation networks and discloses trending developments in the field.Design/methodology/approachThis study is based on 176 articles published in hospitality and tourism journals during the period 2000–2018 and bibliometric data downloaded from the ISI Web of Science. This review applies bibliometric analysis, citation network analysis and content analysis to examine the structure and networks of destination food knowledge so as to provide destination food researchers with a reference guide to the context, methods and focus of previous studies.FindingsThe findings demonstrate the development and trends of destination food research. This is the first study to address the limitations of prior systematic literature reviews by applying network analysis to reveal the interrelated structures and properties of the destination food research domain.Practical implicationsPractitioners can also discover trends in the design of development strategies, as well as identify extended themes that may be integrated with research in the field of destination food at present.Originality/valueAs a summary of key characteristics, this report is a useful reference guide to previous studies for researchers. This study presents core content about the destination food field and identifies development trends within destination food research. Based on the results, further research directions are provided.

Measuring Spillover Effects from Defense to Civilian Sectors –A Quantitative Approach Using LinkedIn

ABSTRACT Spillover effects describe the process of a company benefiting from the R&D activities of another one and thereby gaining an economic advantage. One prominent approach for measuring spillover effects is based on the analysis of patent citation networks. Taking social media analytics and knowledge economics into account, this paper presents a complementary approach to quantify spillover effects from defense to civilian research and development, analyzing 513 employment biographies from the social network LinkedIn. Using descriptive network analysis, we investigate the emigration of personnel of the German defense industry to other civilian producers. Thereby, our study reveals that in the last decade, employees of defense suppliers have changed positions significantly less often, with 3.24 changes on average than professionals who have worked more than 50% of their jobs in the civilian sector, having changed 4.61 times on average. Our work illustrates the churn behavior and how spillover effects between defense and civilian sectors can be measured using social career networks such as LinkedIn.

The Role of Information Systems in the Sustainable Development of Enterprises: A Systematic Literature Network Analysis

Information Systems (IS) play an important role in improving the efficiency of firms’ operations and supply chains, which links to sustainability. Therefore, this study conducted a systematic literature network analysis to review 132 articles that discuss current trends in the IS discipline. Based on a citation network analysis, this study discovered three main research domains (sustainable competitive advantage, environmental sustainability, and sustainable online social communities), and two emerging research domains (the role of IS in developing countries and sustainable information infrastructures). Furthermore, a main path analysis was conducted to understand the knowledge structure of each research domain. This addresses how different trends are reflected in the IS literature related to improving firms’ competitive advantages and environmental sustainability. The results found that the sustainable competitiveness of enterprises is improved by the synergy between IS and other recourses within in the enterprises. Green IS initiatives not only solve the issues of environmental sustainability, but also enhance sustainable competitive advantage (i.e., stock price). As social media becomes the optimal enterprise communication channel, this study discusses the factors affecting sustainable online social community, such as structural dynamics (i.e., membership size, communication activity), social dynamics (the basic nature of interactions among members), participation costs, and topic consistency. Overall, the Information System literature is highly focused on three areas—economy, environment, and society, which supports Triple Bottom Line theory.

Omni-channel management in the new retailing era: A systematic review and future research agenda

Omni-channel retailing is a popular strategy in a new retailing era when digitalization, social media, big data and other emerging technologies (e.g., Artificial Intelligence (AI), virtual reality (VR), augmented reality (AR), blockchain, etc.) are transforming the retail business models. Meanwhile, omni-channel related operations impose a challenge on either well-established firms or new setups that they have to make “right” decisions to fit in the new retail environment. This review paper endeavors to reveal the established knowledge behind the omni-channel retailing literature, generate managerial implications for firms, and provides a guideline for future research. We conduct this systematic review by adopting citation network analysis (CNA). The CNA helps identify seven independent and interdependent research domains, which depict (or constitute) a whole picture of “omnichannel management”. The main path analysis reveals that each identified research domain is under study. We also find that the extant literature seldom examines the roles of how new technologies play in the “omnichannel management”. Moreover, the domain of supply chain management and inventory management in the omnichannel environment is absent in this systematic literature review. Therefore, we propose a prescribed framework for “omnichannel management” (PFOM), which contributes to the literature on “omnichannel management” and provides important managerial applications to the retail firms that plan to implement the omnichannel strategy.

The intellectual contours of corporate social responsibility literature

PurposeCorporate Social Responsibility (CSR) deliberated regarding business firms' actions for doing well to society and natural environment. Specifically, CSR has been about firms contributions towards stakeholder management. As world economy has prospered over the last couple of centuries, business firms have had also increased its footprints in social landscape. In such a scenario, the roles and responsibilities of business firms have expanded in society. Over the years, CSR as a domain of research and literature has developed into a very potent and rich field. Presently, CSR literature as a body of knowledge has become substantial. The authors in this literature review study attempts to conceptually map this complex field of CSR literature.Design/methodology/approachThe objective of this literature review study was to present a visual mapping of intellectual structure of CSR in five-dimensions and to identify the subfields of CSR research concluded by co-citation analysis. All the citation research documents which were listed in the Web of Knowledge (WoK) database between 1998 and 2019 were analysed. Multivariate analysis was undertaken for the literature review. The study conducted a sequence of statistical analyses comprising of factor analysis, multidimensional scaling and cluster analysis.FindingsThis literature review research study summarised the contours and status of CSR research by categorizing the CSR literature into five classification factors, namely CSR Drivers CSR, Contextual Grounding of CSR, Historical Legacy of CSR, Strategic CSR and CSR Implementation. Further, based upon the analysis of literature review of extant research in CSR, both the contemporary and imminent CSR-related research themes were also deliberated upon.Research limitations/implicationsThe results were helpful for academic scholars of CSR to comprehend both the gamut and focus of CSR literature over the years (between the years 1998 and 2019). The sequence of analyses involved factor, multidimensional scaling and cluster analysis. CSR literature was categorized into five factors namely- CSR Drivers, Contextual Grounding of CSR, Historical Legacy of CSR, Strategic CSR and CSR Implementation.Originality/valueThis study was one of the first set of studies to review the literature on CSR research articles by using citation, co-citation and social network analysis.

Generating Graphs by Creating Associative and Random Links Between Existing Nodes

The study and analysis of real-world social, communication, information and citation networks for understanding their structure and identifying interesting patterns have cultivated the need for designing generative models for such networks. A generative model generates an artificial but a realistic-looking network with the same characteristics as that of a real network under study. In this paper, we propose a new generative model for generating realistic networks. Our proposed model is a blend of three key ideas namely preferential attachment, associativity of social links and randomness in real networks. We present a framework that first tests these ideas separately and then blends them into a mixed model based on the idea that a real-world graph could be formed by a mixture of these concepts. Our model can be used for generating static as well as time evolving graphs and this feature distinguishes it from previous approaches. We compare our model with previous methods for generating graphs and show that it outperforms in several aspects. We compare our graphs with real-world graphs across many metrics such as degree, clustering coefficient and path length distributions, assortativity, eigenvector centrality and modularity. In addition, we give both qualitative and quantitative results for clarity.

Community psychology and urban studies: Common connections and missed opportunities

ABSTRACT Community psychology is an international subfield of psychology that focuses on encouraging well-being by examining transactions between individuals and larger social systems including organizations (e.g., schools, workplaces), local neighborhoods, and cities. Although the fields of community psychology and urban studies both address metropolitan problems, urban social change, and urban policy, it is unclear to what extent these fields inform each other. In this paper, I first trace the history and development of community psychology in three localities to urban issues such as access to community mental health services, unemployment, and urban poverty. Second, I describe how contemporary community psychologists have focused their research on a range of urban topics including urban education, homelessness and housing policy, and local politics. Third, using a network analysis of journal citations, I explore the extent to which community psychology and urban studies have informed each other over the past 10 years. Finally, I explore future directions for encouraging interdisciplinarity between community psychology and urban studies.

Mapping the Travels of Intersectionality Scholarship: A Citation Network Analysis.

In this study, we conducted a citation network analysis of intersectionality scholarship. We aimed to elucidate content domains in this scholarship's citation network. In addition, we explored a citation-based genealogy of this scholarship, attending to the representation of women of color identified in prior critical analyses of intersectionality scholarship as key but under-acknowledged contributors to intersectional thought and praxis. We used CitNetExplorer to analyze a network of 17,332 records and 60,132 citation links. The analysis yielded 17 clusters, with the five largest clusters focusing on (1) conceptualizing intersectionality theory, methodology, and analysis; (2) psychology, identity stigma, and multiple minority statuses; (3) sociology of gender inequality, labor markets, and organizations; (4) political science, political systems and policy, including in the European context; and (5) violence against women, gender and health, and health equity. Although some of the key women of color contributors to intersectional thought were among the most cited authors in the network, others were cited infrequently or not at all across the network and clusters. Taken together, the analyses revealed substantial and ongoing engagement with efforts to define and refine intersectionality as epistemology and methodology. However, the analyses pointed to the need for scholars to reengage with, cite, and follow the examples of the women of color who contributed to intersectional thought by actually doing intersectional praxis that directly advances social justice aims. Some of the smaller clusters in the citation network reflected content domains, such as environmental justice and community planning, ripe for such activist-scholar work. Online slides for instructors who want to use this article for teaching are available on PWQ's website at http://journals.sagepub.com/doi/suppl/10.1177/0361684320902408.

Scientific Attention to Sustainability and SDGs: Meta-Analysis of Academic Papers

Scientific research plays an important role in the achievement of a sustainable society. However, grasping the trends in sustainability research is difficult because studies are not devised and conducted in a top-down manner with Sustainable Development Goals (SDGs). To understand the bottom-up research activities, we analyzed over 300,000 publications concerned with sustainability by using citation network analysis and natural language processing. The results suggest that sustainability science’s diverse and dynamic changes have been occurring over the last few years; several new topics, such as nanocellulose and global health, have begun to attract widespread scientific attention. We further examined the relationship between sustainability research subjects and SDGs and found significant correspondence between the two. Moreover, we extracted SDG topics that were discussed following a convergent approach in academic studies, such as “inclusive society” and “early childhood development”, by observing the convergence of terms in the citation network. These results are valuable for government officials, private companies, and academic researchers, empowering them to understand current academic progress along with research attention devoted to SDGs.

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

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.

Non-Invasive Treatment of Adolescent Idiopathic Scoliosis: Systematic Literature Review by Using Citation Network Analysis

There are many nonsurgical treatment options from adolescent idiopathic scoliosis (AIS) to control the progression of the spinal curvature. However, the existing studies are so diverse and diffuse that it is challenging to find potential trends for further studies without a more comprehensive review in place for reference purposes. Thus, the objective of this review article is to conduct a systematic literature review on the noninvasive treatment of AIS with a citation network analysis. The Web of Science (WoS) was searched using 9 reference keywords to collect published articles in English on nonsurgical treatment options for AIS from 1979 to 2019. Each eligible article focused on the nonsurgical options for treating AIS. In addition, the HistCite and the UCINet softwares were referred to for article distribution and citation network analysis. Only non-invasive treatment options of AIS were included. Studies that estimated the amount of spinal curvature, causes of or risk factors for AIS and any invasive treatments, such as surgery, were not focused on. The articles were independently extracted by 3 authors based on the predefined eligibility criteria. The title, authors, year of publication, country or region of publication, reference list, keywords and other bibliographic information from each article was extracted and analyzed purely based on the data with the HistCite and UCINet programs. At last, a total of 146 articles out of 1594 articles were selected for the literature review after the exclusion of 1357 irrelevant articles and 91 inappropriate studies, such as letters and proceedings papers. Of these 146 articles, the majority were empirical studies (74.0%). There was also a lack of meta-analyses in this research field. Based on the results of the citation network analysis, most of the top 10 articles with the highest local citation scores (LCSs) focused on bracing as a treatment. The popularity of bracing as a research topic was also supported by the citation network structure, as brace treatment was in the largest of the five research clusters; this cluster also included posture training through exercise, managing the corrective forces of braces, 3D analysis of braces and quality of life during brace treatment. However, most of these studies focused on rigid braces. A few studies on non-rigid braces and other types of nonsurgical treatment were available in the current literature, which might indicate potential research areas for future studies. To conclude, noninvasive treatment for AIS has been on the academic radar recently; but there are still research gaps, such as the lack of research on semi-rigid and flexible braces or posture training exercises with biofeedback systems. Further studies could explore these research directions.