Institutional repository research 2005-2015: a trend analysis using bibliometrics and text mining

2017 ◽  
Vol 33 (3) ◽  
pp. 264-278 ◽  
Author(s):  
Sujira Ammarukleart ◽  
Jeonghyun Kim
Keyword(s):  
Text Mining ◽  
Information Science ◽  
Open Data ◽  
Research Field ◽  
Intellectual Structure ◽  
Growth Trend ◽  
Comprehensive Overview ◽  
Content Type ◽  
Research Themes ◽  
Keywords And Phrases

Purpose This paper aims to investigate the longitudinal trends of research in the area of institutional repositories (IR) using bibliometric and text-mining methods. Design/methodology/approach The Library and Information Science Abstracts and the Web of Science citation databases were used as data sources. A total of 603 articles published in 109 peer-reviewed journals from 2005 to 2015 were collected and analyzed. The articles were analyzed in terms of publication trends, authorship patterns and keywords and phrases appearing in the article titles and abstracts. Findings The study shows that there has been a notable growth trend in research outputs, along with more participation and collaboration among institutes and countries. The study also found significant variability in the topics covered in the literature. In a comparison of the first period of 2005-2010 and the second period of 2011-2015, new research themes and foci, including research data, data management, linked open data, students and student research and an international audience, are observed in the later period. Originality/value This paper provides a comprehensive overview of publication, authorship and research themes in the IR research field. It describes the evolution of the intellectual structure of IR as a research field.

Knowledge management within a strategic alliances context: past, present and future

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nisha Bamel ◽  
Vijay Pereira ◽  
Umesh Bamel ◽  
Giuseppe Cappiello
Keyword(s):  
Knowledge Management ◽  
Strategic Alliances ◽  
Design Methodology ◽  
Strategic Alliance ◽  
Average Rate ◽  
Research Field ◽  
Intellectual Structure ◽  
Content Type ◽  
Current State ◽  
Literature Reviews

Purpose This paper aims at reviewing the extant knowledge management (KM) research field within a strategic alliance context to understand the historical roots, its temporal progression, current state and potential future in a meaningful way. Design/methodology/approach Data for this study was retrieved from the Scopus database using a systematic literature search process. The bibliometric characteristics of 393 research documents were analyzed using bibliometric and structured network analysis. Findings The findings of the study suggest that the publication in the field have been growing with an average rate of 8.48%. This analysis also lists the most productive and impactful authors, main outlets, and the most impactful secondary and primary publication in the field. In addition, the conceptual and intellectual structure of the research field was constructed and discussed. Originality/value This paper uses an objective and quantitative approach by reviewing the related publications and virtually included all the relevant publications in the analysis, which was seen to be uneconomical when doing traditional literature reviews.

scholarly journals The sharing economy: a bibliometric analysis of the state-of-the-art

2020 ◽  
Vol 26 (8) ◽  
pp. 1769-1786 ◽  
Author(s):  
Sascha Kraus ◽  
Hongbo Li ◽  
Qi Kang ◽  
Paul Westhead ◽  
Victor Tiberius
Keyword(s):  
Citation Analysis ◽  
Food System ◽  
Sharing Economy ◽  
Research Field ◽  
Tourism Industry ◽  
Data Set ◽  
Products Liability ◽  
Content Type ◽  
Research Themes ◽  
Profile Characteristics

PurposeQuantitative bibliometric approaches were used to statistically and objectively explore patterns in the sharing economy literature.Design/methodology/approachJournal (co-)citation analysis, author (co-)citation analysis, institution citation and co-operation analysis, keyword co-occurrence analysis, document (co-)citation analysis and burst detection analysis were conducted based on a bibliometric data set relating to sharing economy publications.FindingsSharing economy research is multi- and interdisciplinary. Journals focused upon products liability, organizing framework, profile characteristics, diverse economies, consumption system and everyday life themes. Authors focused upon profile characteristics, sharing economy organization, social connections, first principle and diverse economy themes. No institution dominated the research field. Keyword co-occurrence analysis identified organizing framework, tourism industry, consumer behavior, food waste, generous exchange and quality cue as research themes. Document co-citation analysis found research themes relating to the tourism industry, exploring public acceptability, agri-food system, commercial orientation, products liability and social connection. Most cited authors, institutions and documents are reported.Research limitations/implicationsThe study did not exclusively focus on publications in top-tier journals. Future studies could run analyses relating to top-tier journals alone, and then run analyses relating to less renowned journals alone. To address the potential fuzzy results concern, reviews could focus on business and/or management research alone. Longitudinal reviews conducted over several points in time are warranted. Future reviews could combine qualitative and quantitative approaches.Originality/valueWe contribute by analyzing information relating to the population of all sharing economy articles. In addition, we contribute by employing several quantitative bibliometric approaches that enable the identification of trends relating to the themes and patterns in the growing literature.

scholarly journals The human factor in SCM

2017 ◽  
Vol 47 (4) ◽  
pp. 238-262 ◽  
Author(s):  
Timm Schorsch ◽  
Carl Marcus Wallenburg ◽  
Andreas Wieland
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Research Field ◽  
Future Research ◽  
Comprehensive Overview ◽  
Social Phenomena ◽  
Chain Management ◽  
Content Type ◽  
Research Opportunities ◽  
Meta Theory

Purpose The purpose of this paper is to advance supply chain management by describing the current state of behavioral supply chain management (BSCM) research and paving the way for future contributions by developing a meta-theory for this important field. Design/methodology/approach The results are generated by applying the systematic literature review methodology and an iterative theory-building approach involving a panel of academics. Findings This review provides a comprehensive overview of the BSCM research landscape. Additionally, a meta-theory of BSCM is presented that encompasses all central elements of the research field and introduces the concept of emergence to the field of BSCM. Furthermore, five promising future research opportunities are formulated. Research limitations/implications The critical discussions and the formulated research opportunities will help scholars in positioning their research to enhance its contribution. Practical implications Results from this research indicate that supply chain decisions benefit from explicit consideration for cognitive and social phenomena. Originality/value This review is the first to provide a comprehensive overview of the field of BSCM research and facilitates BSCM in advancing further.

Intellectual structure of research in business ethics

2017 ◽  
Vol 8 (1) ◽  
pp. 100-120 ◽  
Author(s):  
Huilin Xiao ◽  
Yanling Wang ◽  
Weifeng Li ◽  
Zhenzhong Ma
Keyword(s):  
Business Ethics ◽  
Citation Analysis ◽  
Stakeholder Management ◽  
Leadership Role ◽  
Intellectual Structure ◽  
Content Type ◽  
Research Themes ◽  
Political Csr ◽  
Ethics Research ◽  
Time Periods

Purpose The study aims to map the intellectual structure of business ethics studies by analyzing 17,246 citations of 225 papers published in Business Ethics Quarterly (BEQ) in the year between 2005 and 2014. Specifically, the purpose of the study is to describe the current state of BEQ, identify the most influential journals and works, identify the key themes of business ethics studies during 2005-2014 and, at the same time, report the changes in themes by making a comparison between two time periods – 2005-2009 and 2010-2014. Design/methodology/approach First, the study presents the information of the authors, institutions and countries that contribute to BEQ with a statistical analysis. Second, the study identifies the most cited journals and works in BEQ during 2005-2014 with a citation analysis. Third, the study identifies the key research themes in business ethics studies with a co-citation analysis. With the help of factor and social network analysis (NA), the study groups the research themes and maps their links. Findings First, the statistical results show that many well-known researchers from famous US institutions publishing in BEQ. Second, the citation analysis results show that quite a few journals become mature gradually in business ethics domain. Besides, most of the influential works are normative and theoretical. Third, the co-citation results indicate that “stakeholder management” and “corporate social responsibility” (CSR) are two main themes in business ethics studies in the past decade. Specifically, “stakeholder management” attracts the most research interests in both two sub-time periods. In addition, compared with the pure studies on CSR during 2005-2009, increasing researchers are keen on the theme of “political CSR under globalization” in the second five years. Meanwhile, other focus like “society, state and business ethics” earns a certain degree of attention in the time window 2005-2009. And “accountability in MNCs” and “political philosophy” are the new concerns in the year between 2010 and 2014. Originality/value The study confirms BEQ’s leadership role in business ethics domain. And, it further proves that business ethics has evolved as an independent discipline. It also helps the researchers to have a concise knowledge of the main contents and key points of business ethics research. Methodologically, co-citation analysis combined with factor and NA provides clear results and visualized figures which can be understood easily by the researchers and practitioners.

Determining the critical thresholds for co-word network based on the theory of percolation transition

2019 ◽  
Vol 76 (2) ◽  
pp. 462-483 ◽  
Author(s):  
Muh-Chyun Tang ◽  
Weijen Teng ◽  
Miaohua Lin
Keyword(s):  
English Literature ◽  
Detection Algorithm ◽  
Intellectual Structure ◽  
Percolation Transition ◽  
Knowledge Domain ◽  
Content Type ◽  
Word Similarity ◽  
Buddhist Studies ◽  
Similarity Threshold ◽  
Research Themes

Purpose One of the chief purposes of bibliometric analysis is to reveal the intellectual structure of a knowledge domain. Yet due to the magnitude and the heterogeneous nature of bibliometric networks, some sorts of filtering procedures are often required to make the resulting network interpretable. A co-word analysis of more than 135,000 scholarly publications on Buddhism was conducted to compare the intellectual structure of Buddhist studies in three language communities, Chinese, English and Japanese, over two periods (1957–1986 and 1987–2016). Six co-word similarity networks were created so social network analysis-based community-detection algorithm can be identified to compare major research themes in different languages and eras. The paper aims to discuss this issue. Design/methodology/approach A series of filtering procedures was performed to exclude less discriminatory keywords and spurious relationships of a large, cross-language co-word network in Buddhist studies. Chief among the filtering heuristics was a percolation-transition based method to determine the similarity threshold that involves observing the relative decrease of nodes in the giant component with the increasing similarity threshold. Findings It was found that the topical patterns in the Chinese and Japanese scholarship of Buddhism are alike and observably distinct from that of the English scholarship. Furthermore, a far more drastic changes of research themes were observed in the English literature relative to the Chinese and Japanese literature. Originality/value The filtering procedures were shown to greatly enhance the modularity values and limited the number of modularity classes; thus, domain expert interpretation is feasible.

Customer experience research: intellectual structure and future research opportunities

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jorge H.O. Silva ◽  
Glauco H.S. Mendes ◽  
Paulo A. Cauchick Miguel ◽  
Marlene Amorim ◽  
Jorge Grenha Teixeira
Keyword(s):  
Conceptual Framework ◽  
Methodological Approach ◽  
Customer Experience ◽  
Research Field ◽  
Intellectual Structure ◽  
Future Research ◽  
Content Type ◽  
Research Opportunities ◽  
Integrative View ◽  
Research Propositions

PurposeThis article aims to synthesize and integrate current research on customer experience (CX), identifying the intellectual structure of the field, systematizing a conceptual framework and identifying future research opportunities.Design/methodology/approachTo analyze 629 articles published in peer-reviewed journals in almost four decades, this study employs both bibliometric co-keyword and thematic literature analysis in a complementary way.FindingsThis article maps the CX literature by describing its intellectual structure in terms of three research domains (customer, organizational and technological), their corresponding most relevant research themes and topics. Moreover, this study develops a conceptual framework and research propositions to summarize and integrate the CX literature. This work recognizes technology as an important driver for the development of CX research. Lastly, this article provides future research opportunities for moving the field forward, considering an integrative view among domains.Originality/valueThis paper complements other reviews on CX by using a novel methodological approach (co-keyword and thematic analysis) that enables the identification and visualization of the CX intellectual structure. In addition, the study explores the increasing connection between technology and CX research, by raising evidence that technology, by continuously modifying services and consequently CX, has become a transversal component in the research field. These outcomes may be useful for academics and practitioners.

Mapping the intellectual structure of business-to-business loyalty literature: a bibliometric analysis approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Prathamesh Kittur ◽  
Swagato Chatterjee ◽  
Amit Upadhyay
Keyword(s):  
Bibliometric Analysis ◽  
Design Methodology ◽  
Intellectual Structure ◽  
Future Directions ◽  
Content Type ◽  
Emerging Trends ◽  
Research Themes ◽  
Knowledge Area ◽  
Intellectual Knowledge ◽  
Business To Business

Purpose This study aims to identify evolution and advancement in the field of business-to-business (B2B) loyalty knowledge area by analyzing its intellectual structure. Design/methodology/approach The authors use bibliometric analysis for quantitative evaluation of scholarly studies published on B2B loyalty area over a period of 27 years (1993–2020). The authors analyze intellectual knowledge base of B2B loyalty area by looking into 263 studies with 14,028 references authored by 693 researchers. Findings The results provide a comprehensive review of B2B loyalty area by identifying its foundations, influential works and intellectual communication linkage between these works. Notably, the analysis reveals most cited studies, key authors, important keywords, intellectual turning points and emerging trends of research in the discipline. Research limitations/implications This study creates a baseline for presenting precise and comprehensive insights into research themes in B2B loyalty area, and identifies progressive trends over a period. This study is also helpful for researchers in identifying future directions of research in the discipline. Originality/value This study reveals the intellectual structure of B2B loyalty area.

Intellectual structure of information science 2011–2020: an author co-citation analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dangzhi Zhao ◽  
Andreas Strotmann
Keyword(s):  
Citation Analysis ◽  
Information Science ◽  
Research Evaluation ◽  
Information Behavior ◽  
Intellectual Structure ◽  
Knowledge Domain ◽  
Science Field ◽  
Content Type ◽  
History Of ◽  
Time Periods

PurposeThis study continues a long history of author co-citation analysis of the intellectual structure of information science into the time period of 2011–2020. It also examines changes in this structure from 2006–2010 through 2011–2015 to 2016–2020. Results will contribute to a better understanding of the information science research field.Design/methodology/approachThe well-established procedures and techniques for author co-citation analysis were followed. Full records of research articles in core information science journals published during 2011–2020 were retrieved and downloaded from the Web of Science database. About 150 most highly cited authors in each of the two five-year time periods were selected from this dataset to represent this field, and their co-citation counts were calculated. Each co-citation matrix was input into SPSS for factor analysis, and results were visualized in Pajek. Factors were interpreted as specialties and labeled upon an examination of articles written by authors who load primarily on each factor.FindingsThe two-camp structure of information science continued to be present clearly. Bibliometric indicators for research evaluation dominated the Knowledge Domain Analysis camp during both fivr-year time periods, whereas interactive information retrieval (IR) dominated the IR camp during 2011–2015 but shared dominance with information behavior during 2016–2020. Bridging between the two camps became increasingly weaker and was only provided by the scholarly communication specialty during 2016–2020. The IR systems specialty drifted further away from the IR camp. The information behavior specialty experienced a deep slump during 2011–2020 in its evolution process. Altmetrics grew to dominate the Webometrics specialty and brought it to a sharp increase during 2016–2020.Originality/valueAuthor co-citation analysis (ACA) is effective in revealing intellectual structures of research fields. Most related studies used term-based methods to identify individual research topics but did not examine the interrelationships between these topics or the overall structure of the field. The few studies that did discuss the overall structure paid little attention to the effect of changes to the source journals on the results. The present study does not have these problems and continues the long history of benchmark contributions to a better understanding of the information science field using ACA.

Toward understanding the topical structure of hospitality literature

2018 ◽  
Vol 30 (11) ◽  
pp. 3386-3411 ◽  
Author(s):  
Eunhye (Olivia) Park ◽  
Bongsug Chae ◽  
Junehee Kwon
Keyword(s):  
Machine Learning ◽  
Topic Modeling ◽  
Research Field ◽  
Intellectual Structure ◽  
Machine Learning Techniques ◽  
Research Topics ◽  
Evolutionary Patterns ◽  
Content Type ◽  
Learning Techniques ◽  
Academic Publications

Purpose This paper aims to identify the intellectual structure of four leading hospitality journals over 40 years by applying mixed-method approach, using both machine learning and traditional statistical analyses. Design/methodology/approach Abstracts from all 4,139 articles published in four top hospitality journals were analyzed using the structured topic modeling and inferential statistics. Topic correlation and community detection were applied to identify strengths of correlations and sub-groups of topics. Trend visualization and regression analysis were used to quantify the effects of the metadata (i.e. year of publication and journal) on topic proportions. Findings The authors found 50 topics and eight subgroups in the hospitality journals. Different evolutionary patterns in topic popularity were demonstrated, thereby providing the insights for popular research topics over time. The significant differences in topical proportions were found across the four leading hospitality journals, suggesting different foci in research topics in each journal. Research limitations/implications Combining machine learning techniques with traditional statistics demonstrated potential for discovering valuable insights from big text data in hospitality and tourism research contexts. The findings of this study may serve as a guide to understand the trends in the research field as well as the progress of specific areas or subfields. Originality/value It is the first attempt to apply topic modeling to academic publications and explore the effects of article metadata with the hospitality literature.

scholarly journals An overview of literature on COVID-19, MERS and SARS: Using text mining and latent Dirichlet allocation

2020 ◽  
pp. 016555152095467
Author(s):  
Xian Cheng ◽  
Qiang Cao ◽  
Stephen Shaoyi Liao
Keyword(s):  
Text Mining ◽  
Latent Dirichlet Allocation ◽  
Information Science ◽  
Medical Community ◽  
Main Research ◽  
Mining Technique ◽  
Research Theme ◽  
Research Themes ◽  
Similarity And Difference ◽  
Dirichlet Allocation

The unprecedented outbreak of COVID-19 is one of the most serious global threats to public health in this century. During this crisis, specialists in information science could play key roles to support the efforts of scientists in the health and medical community for combatting COVID-19. In this article, we demonstrate that information specialists can support health and medical community by applying text mining technique with latent Dirichlet allocation procedure to perform an overview of a mass of coronavirus literature. This overview presents the generic research themes of the coronavirus diseases: COVID-19, MERS and SARS, reveals the representative literature per main research theme and displays a network visualisation to explore the overlapping, similarity and difference among these themes. The overview can help the health and medical communities to extract useful information and interrelationships from coronavirus-related studies.

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