Document Co-citation Analysis Research Articles

Exploring and investigating the complementarity and multidimensionality of innovation for sustainability research: Past present and future

Innovation and sustainability are distinct but complementary topics, and hence, complex, multidimensional, and multidisciplinary. It is thus natural that research on ‘innovation for sustainability’, though important, is largely scattered and unstructured. This article aims to rectify this gap by developing a systematic study, quantitatively depicting the knowledge structure and the intellectual progress of innovation for sustainability in the business management literature. To this end, we applied bibliometric analysis to study 1842 innovation for sustainability articles from the ‘Web of Science’ database. Our robust methodology included deploying the document co-citation analysis, co-word analysis, and thematic evolution to trace the intellectual structure and conceptual structure of the innovation for sustainability field. Further, through a thorough qualitative content analysis, we developed a comprehensive conceptual framework comprising drivers, innovation practices, and performance indicators of innovation for sustainability. Additionally, we examined the latest trending articles based on total local citations (TLC) and total global citations (TGC) to delineate the potential future research directions. Overall, thus, this research contributed to the innovation for sustainability literature by combining a tripartite methodology of bibliometric analysis, qualitative content analysis, and analysis of trending articles to determine the intellectual structure and potential future research directions.

Soil desiccation in the context of vegetation restoration: A scientometric analysis

AbstractThis research aims to fill the gap in understanding the evolution of soil desiccation studies, focusing on its impact on sustainable crop production in China's Loess Plateau. The study explores trends, influential works, authors, journals, and emerging research areas within the field of soil desiccation. To achieve this, this study pioneers a comprehensive scientometric exploration of soil desiccation. The study analyzed 1952 publications on soil desiccation from January 2013 to December 2023, sourced from the Web of Science. Various co‐citation techniques such as author co‐citation analysis (ACA), document co‐citation analysis (DCA), journal co‐citation analysis (JCA), and keyword analysis are employed. Network development, visualization tools, and text‐mining methods are utilized to discern patterns and relationships within the dataset. Here, for the first time, nine distinct clusters were identified through DCA. The findings reveal the impactful emergence of significant clusters, such as the one focusing on the Loess Plateau, marking a significant advance in our understanding of soil desiccation. Multiple research frontiers or sub‐specialties emerge, including topics such as different vegetation types, the impact on grain yield, water use efficiency, growth, soil water content, hydraulic redistribution, drought, soil moisture, and modeling. This innovative scientometric review of soil desiccation outlines the current scientific and technological trends while identifying knowledge gaps. The findings are beneficial for researchers, graduate students, and professors interested in understanding research trajectories, pivotal publications, and influential scholars shaping this field.

A mapping-knowledge-domain analysis of ERP research on language processing.

The event-related potentials (ERPs) technique represents a newly developed methodology in cognitive neuroscience and has significantly extended the scope of linguistic studies, offering valuable insights into cognitive processes related to language. While extant literature reviews have addressed specific facets of ERP research on language processing, a comprehensive overview of this domain remains notably absent. This study aims to fill this gap by pioneering a mapping-knowledge-domain analysis of ERP research on language processing using Citespace, a visualized bibliometric software. The current study conducted a meticulous survey and evaluation of relevant literature extracted from the Web of Science core collection. Initially, this study outlines the spatial-temporal distribution within this domain. Subsequently, employing document co-citation analysis, keyword co-occurrence analysis, cluster analysis, and burst detection analysis, this study delved deeper into the research landscape. Findings reveal that key areas in ERP research on language processing predominantly focus on sentence comprehension, reading comprehension, and mismatch negativity, with notable emphasis on topics such as speech perception, temporal dynamics, and working memory. The current study advocates for future investigations to concentrate on larger linguistic units, explore the integration of ERP components and their functional significance, and scrutinize individual differences among participants. These directions are imperative for advancing the understanding of language processing mechanisms.

INNOVATION AND PRODUCTIVITY RESEARCH IN THE LAST FIVE DECADES: A BIBLIOMETRIC ANALYSIS

Purpose: This study aims to reveal research trends by revealing the evaluation in this field by making a holistic analysis of academic studies that have examined the concepts of innovation and productivity in the last five decades. This analysis aims to reveal the general structure of academic studies that deal with the concepts of innovation and productivity. Methodology: Articles searched in the ‘‘Social Science Citation Index (SSCI)’’, ‘‘Science Citation Index Expanded (SCI-EXPANDED)’’ and ‘‘Emerging Sources Citation Index (ESCI)’’ in the ‘‘Web of Science (WoS)’’ database, researching innovation and productivity together between 1980-2023. It was analysed and mapped using the VOSviewer 1.6.19 software and manual methods. Co-occurrence Keyword Analysis, Document Co-citation Analysis and manual analysis methods were used in the mapping. Findings: This study reveals how research in innovation and productivity has developed over the last five decades and what trends it has. It has been determined that the most published areas are Economy, Management and Business. The most frequently used keywords were found to be "innovation", "productivity", "research-and-development", "growth", "performance" and "impact". The most published topics on a cluster basis are "impact", "innovation and productivity", "growth", "research and development" and "performance", respectively. In the document co-citation analysis, it was determined that the publication in which all publications were linked included the study titled "Research, Innovation and Productivity: an econometric analysis at the firm level", published by Crépon et al. (1998). This information can be a valuable resource for future research and policy-making and can be used to drive innovation and productivity progress. Originality: While the study is the first and only content analysis to reveal the combined trends in this field by examining the "innovation and productivity" studies together, it is thought that the results obtained can guide researchers and professionals.

Knowledge domains and emerging trends in non-invasive brain stimulation: A bibliometric analysis via CiteSpace

In recent decades, new non-invasive brain stimulation techniques and protocols have been developed, such as transcranial magnetic stimulation and transcranial direct current stimulation. To identify and visualize the intellectual structure of non-invasive brain stimulation through document co-citation analysis. We analyzed 30,854 Web of Science-indexed manuscripts and their 1,615,692 references regarding non-invasive brain stimulation, all published from 1988 to 2022. We drew a document co-citation network map using CiteSpace software. The most productive journal was Clinical Neurophysiology. The most published institution was the University College London, and the country with the most reports was the USA. The most productive author was Alvaro Pascual-Leone and the most cited author in the non-invasive brain stimulation field was J. C. Rothwell. In addition, the most cited study was that of Rossi et al. (2009). The safe application of non-invasive brain stimulation techniques and their effects on motor or executive functions is an emerging trend in this research area. The current investigation displayed a quantitative scientometric approach and delved into the advancement of non-invasive brain stimulation research by examining the references published in this domain. These findings can be valuable for professionals to picture the patterns of recognition and emerging directions in the field.

Performance-enhancing substances in sport: A scientometric review of 75 years of research.

The use of performance-enhancing substances not only undermines the core values of sports but also poses significant health risks to athletes. In a fast-evolving doping environment, where sport professionals are constantly seeking novel and illegal means to bypass doping tests, and new substances are regularly detected on the drug market, it is crucial to inform authorities with updated evidence emerging from scientific research. The current study aims to (i) outline the structure of knowledge in the literature on performance enhancers in sports (i.e., most active countries, main sources, most productive authors, and most frequently used keywords); (ii) identify the most impactful documents in the field; and (iii) uncover the main domains of research in the literature. To do so, we conducted a comprehensive scientometric analysis of the literature on doping, sourcing our data from Scopus. Our research involved a document co-citation analysis of 193,076 references, leading to the identification of the 51 most influential documents and seven key thematic areas within the doping literature. Our results indicate that the scientific community has extensively studied the most prevalent doping classes, such as anabolic agents and peptide hormones, and little is still known about the use of contaminated supplements or other types of enhancers identified as emergent trends. Concurrently, technological advancements contributed to the development of more sophisticated doping detection techniques, using blood or urine samples. More recently, the focus has shifted towards the athlete biological passport, with research efforts aimed at identifying biomarkers indicative of doping. The dynamic nature of doping methods underlines the necessity for more robust educational campaigns, aiming at raising awareness among sports professionals and their entourage about the dangers of doping and the intricacies of its control mechanisms.

MAPPING THE INVESTMENT EFFICIENCY: A CO-CITATION ANALYSIS

This research pioneers a shift in investment efficiency exploration by transcending traditional measurement approaches. The study identifies three main research areas: (1) Factors influencing investment efficiency, (2) Competition, green Research and Development (R&D) and cooperation in the supply chain, and (3) Environmental and renewable considerations in investment efficiency. This is achieved through a document co-citation analysis of 38 highly cited documents. Multidimensional scaling visually maps the intellectual landscape, emphasising the dominance of factors influencing investment efficiency. A 10-year analysis reveals dynamic trends with implications for financial transparency, strategic ownership, social responsibility and technological advancements. The study offers actionable insights for scholars and practitioners, emphasising the necessity of aligning financial goals with sustainability. Despite acknowledged limitations related to data source bias, this research contributes a nuanced understanding of investment efficiency trends, paving the way for future explorations in this vital domain.

Infants on the move: bibliometric analyses of observational vs. digital means of screening infant development.

Neurodevelopmental disorders are on the rise, yet their average diagnosis is after 4.5 years old. This delay is partly due to reliance on social-communication criteria, which require longer maturation than scaffolding elements of neuromotor control. Much earlier criteria could include reflexes, monitoring of the quality of spontaneous movements from central pattern generators and maturation of intentional movements and their overall sensation. General Movement Assessment (GMA) studies these features using observational means, but the last two decades have seen a surge in digital tools that enable non-invasive, continuous tracking of infants' spontaneous movements. Despite their importance, these tools are not yet broadly used. In this work, using CiteSpace, VOSViewer and SciMAT software, we investigate the evolution of the literature on GMA and the methods in use today, to estimate how digital techniques are being adopted. To that end, we created maps of key word co-occurrence networks, co-author networks, document co-citation analysis and strategic diagrams of 295 publications based on a search in the Web of Science, Dimensions and SCOPUS databases for: 'general movement assessment' OR 'general movements assessment'. The nodes on the maps were categorized by size, cluster groups and year of publication. We found that the state-of-the-art methodology to diagnose neurodevelopmental disorders still relies heavily on observation. Several groups in classical GMA research have branched out to incorporate new techniques, but few groups have adopted digital means. We report on additional analyses of methods and biosensors usage and propose that combining traditional clinical observation criteria with digital means may allow earlier diagnoses and interventional therapies for infants.

Digital Supply Chain Management

Digital transformation in supply chain management has garnered significant attention from both industry and academia. Numerous studies have focused on the emerging concept of digital supply chain management (DSCM). In this research, the authors present a background and context of DSCM. Furthermore, they conduct a systematic bibliometric analysis encompassing a dataset of 1053 scholarly papers published from 1995 to 2021. During the literature review, various methods including network analysis, document co-citation analysis, author co-citation analysis, and journal co-citation analysis are employed. The results of the study provide an overview of the concept of DSCM and highlight key authors, affiliations, and countries in the field. Additionally, the study examines emerging research topics, including blockchain technology, digital twin, and circular economy, within the context of DSCM. Finally, limitations and potential direction for future studies are noted. The authors hope this research could provide a basic understanding of DSCM for industries and academics.

Trends in Research Studies on Menstrual Distress and Selfefficacy Among Adolescent Girls: A Bibliometric Analysis

Menstrual hygiene is a complex issue that requires coordinated efforts at various levels, especially for adolescent girls. However, the lack of basic facilities like sanitary products, water supply, and a safe environment for changing pads limits their options for safe menstrual hygiene. To understand more about menstrual distress and self-efficacy among schoolgoing girls, we analyzed 6,681 publications from the Web of Science (WoS) Core Collection and 4,974 records from 2008 to 2022. The study used CiteSpace 6.1.R6 software for a thorough analysis, including Document Co-citation Analysis (DCA) to identify important studies and research clusters, as well as keyword co-occurrence analysis to reveal emerging trends in the literature. Furthermore, temporal analysis was conducted to examine publication trends over time, showing a notable rise in research output, especially in the past five years. The research on menstrual distress and selfefficacy is primarily focused in countries like the United States, England, China, Australia, and Canada, and institutions like the University of California, University of London, Harvard University, Pennsylvania Commonwealth System of Higher Education, and the University of North Carolina. Keywords like distress, life event, psychopathology, memory, and salivary cortisol indicate emerging trends in this field. The Document Co-citation Analysis (DCA) revealed that the studies on young women in middle-income countries are the predominant cluster in the domain of menstrual distress and self-efficacy. This bibliometric analysis helps identify potential contributors for future research on menstrual distress and hygiene among adolescent girls.

A Scientometric Analysis of Language Teacher Emotions (2004-2022): Spotlight on the Impact of the COVID-19 Pandemic on LTE Research

Frontline language teachers have experienced anxiety, vulnerability, and emotional burnout as a result of the sudden transition to online teaching due to the COVID-19 pandemic. This study extracted Language Teacher Emotions (LTE) literature from the Scopus database during the period 2000-2022. During the first round of data extraction, 169 relevant documents written in English were identified. Furthermore, the researchers conducted a scientometric analysis using the literature analysis tool, CiteSpace (v.5.8.R3), and employed co-citation techniques involving visualization and text mining. Our results indicate the following: (1) The first LTE publication was released in 2004, followed by a growing number of publications in the first decade. Nevertheless, more studies were published during 2020-2022; (2) The five countries with the highest number of publications were the USA, China, Iran, the UK, and Turkey; (3) According to Author Co-citation Analysis (ACA), the majority of researchers had expertise in language education, teaching methods, educational assessment, teacher education, and applied psychology; (4) Based on the Document Co-citation Analysis (DCA), emotional labour, emotional burden, and vulnerability were the primary topics of interest; (5) Cluster analysis of keywords indicates that the LTE research trajectory was inevitably affected by the COVID-19 pandemic. As the first scientometric review of LTE research, this study calls for a greater understanding of the impact of online and blended teaching during the post-pandemic period. It will be of interest to inter-domain researchers and frontline teachers in terms of identifying influential scholars, publications, and research trends, as well as considering future research projects.

A Systematic Review of Radiative Transfer Models for Crop Yield Prediction and Crop Traits Retrieval

Radiative transfer models (RTMs) provide reliable information about crop yield and traits with high resource efficiency. In this study, we have conducted a systematic literature review (SLR) to fill the gaps in the overall insight of RTM-based crop yield prediction (CYP) and crop traits retrieval. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 76 articles were found to be relevant to crop traits retrieval and 15 for CYP. China had the highest number of RTM applications (33), followed by the USA (13). Crop-wise, cereals, and traits-wise, leaf area index (LAI) and chlorophyll, had a high number of research studies. Among RTMs, the PROSAIL model had the highest number of articles (62), followed by SCOPE (6) with PROSAIL accuracy for CYP (median R2 = 0.62) and crop traits (median R2 = 0.80). The same was true for crop traits retrieval with LAI (CYP median R2 = 0.62 and traits median R2 = 0.85), followed by chlorophyll (crop traits median R2 = 0.70). Document co-citation analysis also found the relevancy of selected articles within the theme of this SLR. This SLR not only focuses on information about the accuracy and reliability of RTMs but also provides comprehensive insight towards understanding RTM applications for crop yield and traits, further exploring possibilities of new endeavors in agriculture, particularly crop yield modeling.

Global status of research on gastrointestinal cancer patients’ quality of life: A bibliometric and visual analysis from 2003 to 2023

ObjectiveTo analyze the current research status, hotspots, and frontiers in the field of Gastrointestinal (GI) cancer and quality of life (QoL) through the bibliometrics method, and to provide references and guidance for future research. MethodsLiterature related to GI cancer and QoL from April 1, 2003 to March 31, 2023 was retrieved from the Web of Science Core Collection database. CiteSpace 6.2.R1 was performed for collaboration analysis, keyword co-occurrence analysis, and document co-citation analysis. ResultsA total of 1224 publications were included in this study. There has been a significant increase in the number of publications in this field over the past two decades. The United States, the Karolinska Institute and the University of Amsterdam, and Pernilla Lagergren are the most prolific country, institution, and author, respectively. The links between most of the research constituents were relatively thin (centrality <0.1). The keyword analysis indicates that the benefits of physical activity on QoL, the levels of psychological distress and its relationship with QoL, as well as the development and validation of QoL measurement tools have been the research hotspots. Open-label/double-blind trials exploring therapeutic interventions and more targeted new drugs or more effective drug combinations, and longitudinal studies determining the direction of the association between psychological distress and QoL at different time points, may be emerging trends in this field. ConclusionThe cooperation among countries, institutions, and authors in this field should be strengthened. In addition, the health benefits of light physical activity, interventions for QoL, trajectory and direction of the relationship between psychological distress and QoL may be the focus of future research.

Document Co-citation Analysis using Concept Lattice

Document Co-citation Analysis (DCA) is a method to identify and analyze the relationships between co-cited documents. In this paper, we attempt to use concept lattice for DCA. Concept lattice is a graph structure given in Formal Concept Analysis (FCA), a branch of mathematics based on the concept and its hierarchy. The experiments are conducted on an extensive repository of citations extracted from DBLP, ACM, MAG (Microsoft Academic Graph), and other sources, having a total of 5,354,309 papers and 48,227,950 citation relationships. In this paper, it is established that the concept lattice supports DCA and helps to identify a set of co-cited documents and their co-citation strength. It also provides navigation to reflect the subset-superset relationship of the co-citations. Further, the concept lattice helps identify the hierarchy among the documents and answers the most relevant queries related to DCA.

Fifty years of research on questionable research practises in science: quantitative analysis of co-citation patterns.

Questionable research practises (QRPs) have been the focus of the scientific community amid greater scrutiny and evidence highlighting issues with replicability across many fields of science. To capture the most impactful publications and the main thematic domains in the literature on QRPs, this study uses a document co-citation analysis. The analysis was conducted on a sample of 341 documents that covered the past 50 years of research in QRPs. Nine major thematic clusters emerged. Statistical reporting and statistical power emerged as key areas of research, where systemic-level factors in how research is conducted are consistently raised as the precipitating factors for QRPs. There is also an encouraging shift in the focus of research into open science practises designed to address engagement in QRPs. Such a shift is indicative of the growing momentum of the open science movement, and more research can be conducted on how these practises are employed on the ground and how their uptake by researchers can be further promoted. However, the results suggest that, while pre-registration and registered reports receive the most research interest, less attention has been paid to other open science practises (e.g. data sharing).

Detecting and visualizing research trends of blended learning: A bibliometric analysis of studies from 2013-2022

Blended learning (BL), an innovative, technology-supported pedagogical approach, has been extensively adopted in schools and universities. The learning effectiveness of BL has been investigated in multiple domains of education, computer science, nursing, engineering, and psychology. To uncover the major trends of BL research, this study embarked on a bibliometric analysis of a total of 719 studies published in the recent 10 years (2013-2022) and indexed in the Web of Science core collection. Adopting a quantitative approach and the visual analytical tool of CiteSpace, the review study identified the development trends, the influential researchers and research institutions, and pivotal studies and topics of the field and informed its future progression. The findings revealed a growing trend in BL research in the past decade as reflected in the exponential growth in the number of publications and citations. Charles R. Graham, Chang Zhu, Robert A. Ellis, and Feifei Han were the most prolific, influential researchers in the field, and the Griffith University, the University of Hong Kong, the Vrije Universiteit Brussel, the Monash University, and the National Taiwan Normal University were the prominent research institutions, which engaged in frequent collaborations with others. The United States, China, and Australia were the top-3 contributors to BL research measured by the number of publications, and the studies conducted and reported by researchers in the USA, Turkey, Taiwan, and Spain were cited the most often. Document co-citation analysis unveiled the pivotal studies and topics of the research field, including blended course designs, institutional adoption, achievement, higher education, active BL, flipped classroom, and communication skills.

Multimedia glosses and their impact on second language vocabulary acquisition: insights from a meta-analysis and document co-citation analysis

ABSTRACT Multimedia glosses have been examined extensively by researchers for over three decades to determine their possible effects in second language (L2) vocabulary acquisition. Many meta-analytic studies aimed to determine the extent to which glosses can impact L2 vocabulary learning and the moderators that can mediate the results of meta-analytic studies. This study integrated meta-analytic studies with document co-citation analysis (DCA) to elicit a fine-grained view of the thematic associations of relevant citing studies with the issue of glosses and L2 vocabulary learning. To address this issue, 18 target studies (N = 2991 participants) were selected as the study sample. Results revealed that glosses had an overall large effect size on L2 vocabulary acquisition (Hedge’s g = 1.27); however, the effect size varied from small to large, depending on the level of proficiency of the learners. Concerning the tests type moderator, the effect size was large for recognition test but medium for vocabulary recall test. Results of the DCA (18 cited articles and 802 citing articles) identified 10 core papers, with highly significant co-citations, and 257 citing references, indicating the highly thematic relatedness of the target studies, and citing references to the issue under investigation.

Sleep Profiles in Eating Disorders: A Scientometric Study on 50 Years of Clinical Research.

Sleep and diet are essential for maintaining physical and mental health. These two factors are closely intertwined and affect each other in both timing and quality. Eating disorders, including anorexia nervosa and bulimia nervosa, are often accompanied by different sleep problems. In modern society, an increasing number of studies are being conducted on the relationship between eating disorders and sleep. To gain a more comprehensive understanding of this field and highlight influential papers as well as the main research domains in this area, a scientometric approach was used to review 727 publications from 1971 to 2023. All documents were retrieved from Scopus through the following string "TITLE-ABS (("sleep" OR "insomnia") AND ("anorexia nervosa" OR "bulimia nervosa" OR "binge eating" OR "eating disorder*") AND NOT "obes*") AND (LIMIT-TO (LANGUAGE, "English"))". A document co-citation analysis was applied to map the relationship between relevant articles and their cited references as well as the gaps in the literature. Nine publications on sleep and eating disorders were frequently cited, with an article by Vetrugno and colleagues on nocturnal eating being the most impactful in the network. The results also indicated a total of seven major thematic research clusters. The qualitative inspection of clusters strongly highlights the reciprocal influence of disordered eating and sleeping patterns. Researchers have modelled this reciprocal influence by taking into account the role played by pharmacological (e.g., zolpidem, topiramate), hormonal (e.g., ghrelin), and psychological (e.g., anxiety, depression) factors, pharmacological triggers, and treatments for eating disorders and sleep problems. The use of scientometric perspectives provides valuable insights into the field related to sleep and eating disorders, which can guide future research directions and foster a more comprehensive understanding of this important area.

Mental Health in the Post-Lockdown Scenario: A Scientometric Investigation of the Main Thematic Trends of Research.

Since the outbreak of COVID-19, researchers and clinicians have published scientific articles on the SARS-CoV-2 virus and its medical, organizational, financial, and psychological implications. However, many effects have been observed in the post-lockdown scenario. In this study, we adopted a scientometric-bibliometric approach to drawing the state of the art regarding the emotional and psychological effects of the pandemic after the lockdown. In Scopus, we found 791 papers that were subsequently analyzed using CiteSpace. The document co-citation analysis (DCA) computation generated a network of eight major clusters, each representing a central area of investigation. Specifically, one major cluster-cluster no. 1-focuses on the long-term effects of the COVID-19 pandemic and individuals' ability to develop adaptive coping mechanisms and resilience. The results allow us to frame the fields covered by researchers more precisely and the areas that still need more investigation.

Understanding Sleep Disturbances in Prostate Cancer-A Scientometric Analysis of Sleep Assessment, Aetiology, and Its Impact on Quality of Life.

Prostate cancer is the most commonly diagnosed cancer in the United Kingdom. While androgen-deprivation therapy is the most common treatment for prostate cancer, patients undergoing this treatment typically experience side effects in terms of sleep disturbances. However, the relation between prostate cancer and sleep and the way in which sleep interventions may benefit oncological patients is underinvestigated in the literature. The current study aims to review in a data-driven approach the existing literature on the field of prostate cancer and sleep to identify impactful documents and major thematic domains. To do so, a sample of 1547 documents was downloaded from Scopus, and a document co-citation analysis was conducted on CiteSpace software. In the literature, 12 main research domains were identified as well as 26 impactful documents. Research domains were examined regarding the link between prostate cancer and sleep, by taking into account variations in hormonal levels. A major gap in the literature was identified in the lack of use of objective assessment of sleep quality in patients with prostate cancer.