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Article
Publication date: 1 November 2021

Russell K. Lemken and Marc H. Anderson

The purpose of this study is to examine the historical continuity of James March’s contributions to management scholarship by tracing the co-citations that appear within the…

Abstract

Purpose

The purpose of this study is to examine the historical continuity of James March’s contributions to management scholarship by tracing the co-citations that appear within the textual contexts of articles in premier management journals that cite both March and Simon’s 1958 book Organizations and other works co-authored by March.

Design/methodology/approach

This study uses within-citation context analysis to examine 522 passages from eight premier management journals that contain co-citations to Organizations and any another work co-authored by March. This entails coding the citing passages to identify the specific knowledge claims from March’s works and how citing authors used them, which establishes linkages between the content in different works of March’s works as used by citing authors.

Findings

This study finds that 31 other works by March are co-cited within the same citation contexts along with Organizations. The vast majority (71%) of these co-citations of March’s later works are to Cyert and March’s A Behavioral Theory of the Firm. The four other most highly co-cited works are Levitt and March (1988); March (1991); Cohen et al. (1972); and Levinthal and March (1993). Of the eight summary codes used in the analysis corresponding with the contents of Organizations, two summary codes – “Routines and Programs” and “Cognitive Limits” – accounted for the clear majority (60.1%) of all co-citation contexts in this study.

Research limitations/implications

This study only examined the co-citations to Organizations in eight premier journals in organization studies, and a larger selection of journals might have altered the results to some degree. A truly comprehensive analysis might consider every citation context in the published literature where citing authors jointly mention any two or more of March’s works. Given the extraordinarily large number of citations to March’s works, this was impractical and unfeasible.

Practical implications

A time-bound and rigorous review of co-citations in common contexts allows both scholars and practitioners to recognize the genuine threads of theory presented by leading scholars and trace them through subsequent works to see how theories have evolved both in practice – reflected in empirical work – and in conception – reflected in theoretical development.

Social implications

Prior research into citation methodology has shown the proliferation of references over time. It is not uncommon for contemporary works to list 100 or more references for a single paper. This research encourages and facilitates a greater discipline in understanding and using citations by tracing the roots of citations and the extent of their importance in citing works.

Originality/value

This paper presents an historical perspective of the influence of James March’s body of scholarship by tracking within context co-citations that link a seminal early work of March to his most cited works in premier journals. This study tracks specific knowledge claims that have persisted throughout March’s corpus of scholarship. This historical method is a systematic approach to tracing how subsequent scholarship ties together and uses multiple works to support specific knowledge claims, enabling an objective analysis of the commonalities among a scholar’s works over time. This is the first example of research using this bibliographic method to form an historical perspective of a seminal author or a classic work.

Details

Journal of Management History, vol. 28 no. 1
Type: Research Article
ISSN: 1751-1348

Keywords

Article
Publication date: 3 April 2018

Ali Akbar Khasseh, Faramarz Soheili and Afshin Mousavi Chelak

This research aims to examine the intellectual structure of iMetrics through author co-citation analysis.

Abstract

Purpose

This research aims to examine the intellectual structure of iMetrics through author co-citation analysis.

Design/methodology/approach

This research uses common techniques in bibliometrics and social network analysis. It analyses 5,944 records from the Web of Science in the field of iMetrics that are published between 1978 and 2014.

Findings

Findings indicated that researchers including “Garfield”, “Egghe”, “Glanzel”, “Leydesdorff” and “Price” have received many co-citations. The author co-citation analysis in iMetrics resulted in eight thematic clusters, including “theoretical foundations and citation analysis”, “sociology of science”, “science mapping and visualization”, “network analysis”, “classic laws of bibliometrics”, “webometrics”, “technometrics” and “miscellaneous”. “Theoretical foundations and citation analysis” is the biggest cluster which comprises 59 authors. The results suggest the crucial role of price medallists in shaping the intellectual structure of knowledge in iMetrics.

Originality/value

Extracting the patterns embedded in the knowledge structure of iMetrics studies provides beneficial information for both researchers and policymakers. This research study is valuable that used an appropriate set of records regarding both recall and precision. Furthermore, this study helps us better understand the characteristics of iMetrics, its subject areas, and the prominent authors in those areas.

Details

The Electronic Library, vol. 36 no. 2
Type: Research Article
ISSN: 0264-0473

Keywords

Article
Publication date: 12 April 2013

Rekha Mittal

The purpose of this paper is to explore and map the intellectual structure of biofuel research.

557

Abstract

Purpose

The purpose of this paper is to explore and map the intellectual structure of biofuel research.

Design/methodology/approach

The study attempts to present the structure of biofuel research through document co‐citation patterns of core references. Document co‐citation analysis was performed using the Web of Science of the Thomson‐ISI database. A sample of 26 cited references was identified and the co‐citation frequencies were analyzed and represented them systematically within groups of similar researched topics.

Findings

The study shows the co‐citation analysis method suitable for depicting structure of biofuel research in document clusters by performing multivariate analysis: cluster analysis, factor analysis, multidimensional scaling and network analysis.

Research limitations/implications

The study is limited to research articles and co‐citation data for the first author only. For the co‐citation analysis, the cited references rather than the cited authors were used as the units for analysis.

Practical implications

Co‐citational analysis using multivariate tools provides a useful technique to explore and document the development of the field supplementing the insights normally available from the routine co‐citational analysis.

Originality/value

Specialties in biofuel research are identified and this may provide a valuable building block for future research.

Article
Publication date: 6 July 2012

Sascha Kraus, Matthias Filser, Fabian Eggers, Gerald E. Hills and Claes M. Hultman

Entrepreneurial marketing (EM) is at the brink of becoming an established discipline. To advance the field further and to better guide research efforts in different sub…

1999

Abstract

Purpose

Entrepreneurial marketing (EM) is at the brink of becoming an established discipline. To advance the field further and to better guide research efforts in different sub categories, the purpose of this paper is to examine the field's intellectual structure with the help of citation and co‐citation analysis.

Design/methodology/approach

This paper is based on a two‐stage research design. First a citation analysis is carried out through which thematic clusters are identified. In a second step a co‐citation analysis is conducted to determine the intellectual structure of EM research.

Findings

This study exposes the most influential authors and publications and emphasizes conjunctions among scholars and their findings. Results show three streams that are the foundation of EM research: theoretical foundations of management, entrepreneurship, and marketing; the research interface of marketing and entrepreneurship; SME and new venture marketing.

Research limitations/implications

The results of a bibliometric analysis are limited by the publications that have been selected as a starting point. However, through the selection criteria chosen to identify the database for analysis, the authors are confident that the results illustrate the intellectual structure of EM research in its entirety. The authors recommend that future research should be conducted in one of the three sub‐fields identified in this study.

Practical implications

By laying out different research streams within EM it is hoped that future research will be guided in different directions. “Fine‐tuning” of research efforts will benefit small, new, and entrepreneurial firms.

Originality/value

The analyses conducted in this paper draw a picture of the field that is based on a quantitative approach and therefore sets itself apart from other literature reviews that have a qualitative core.

Details

Journal of Research in Marketing and Entrepreneurship, vol. 14 no. 1
Type: Research Article
ISSN: 1471-5201

Keywords

Article
Publication date: 12 May 2021

Maryam Yaghtin, Hajar Sotudeh, Alireza Nikseresht and Mahdieh Mirzabeigi

Co-citation frequency, defined as the number of documents co-citing two articles, is considered as a quantitative, and thus, an efficient proxy of subject relatedness or prestige…

Abstract

Purpose

Co-citation frequency, defined as the number of documents co-citing two articles, is considered as a quantitative, and thus, an efficient proxy of subject relatedness or prestige of the co-cited articles. Despite its quantitative nature, it is found effective in retrieving and evaluating documents, signifying its linkage with the related documents' contents. To better understand the dynamism of the citation network, the present study aims to investigate various content features giving rise to the measure.

Design/methodology/approach

The present study examined the interaction of different co-citation features in explaining the co-citation frequency. The features include the co-cited works' similarities in their full-texts, Medical Subject Headings (MeSH) terms, co-citation proximity, opinions and co-citances. A test collection is built using the CITREC dataset. The data were analyzed using natural language processing (NLP) and opinion mining techniques. A linear model was developed to regress the objective and subjective content-based co-citation measures against the natural log of the co-citation frequency.

Findings

The dimensions of co-citation similarity, either subjective or objective, play significant roles in predicting co-citation frequency. The model can predict about half of the co-citation variance. The interaction of co-opinionatedness and non-co-opinionatedness is the strongest factor in the model.

Originality/value

It is the first study in revealing that both the objective and subjective similarities could significantly predict the co-citation frequency. The findings re-confirm the citation analysis assumption claiming the connection between the cognitive layers of cited documents and citation measures in general and the co-citation frequency in particular.

Peer review

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-04-2020-0126.

Article
Publication date: 17 June 2020

Vladimir Smojver, Mario Štorga and Goran Zovak

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…

Abstract

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.

Details

Journal of Knowledge Management, vol. 25 no. 2
Type: Research Article
ISSN: 1367-3270

Keywords

Article
Publication date: 1 May 2006

Derry Tanti Wijaya and Stéphane Bressan

Querying search engines with the keyword “jaguars” returns results as diverse as web sites about cars, computer games, attack planes, American football, and animals. More and more…

Abstract

Querying search engines with the keyword “jaguars” returns results as diverse as web sites about cars, computer games, attack planes, American football, and animals. More and more search engines offer options to organize query results by categories or, given a document, to return a list of links to topically related documents. While information retrieval traditionally defines similarity of documents in terms of contents, it seems natural to expect that the very structure of the Web carries important information about the topical similarity of documents. Here we study the role of a matrix constructed from weighted co‐citations (documents referenced by the same document), weighted couplings (documents referencing the same document), incoming, and outgoing links for the clustering of documents on the Web. We present and discuss three methods of clustering based on this matrix construction using three clustering algorithms, K‐means, Markov and Maximum Spanning Tree, respectively. Our main contribution is a clustering technique based on the Maximum Spanning Tree technique and an evaluation of its effectiveness comparatively to the two most robust alternatives: K‐means and Markov clustering.

Details

International Journal of Web Information Systems, vol. 2 no. 2
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 2 August 2022

Yanhui Song, Lixin Lei, Lijuan Wu and Shiji Chen

This paper focuses on the differences in domain intellectual structure discovery between author bibliographic coupling analysis (ABCA) and author co-citation analysis (ACA…

Abstract

Purpose

This paper focuses on the differences in domain intellectual structure discovery between author bibliographic coupling analysis (ABCA) and author co-citation analysis (ACA) considering all authors. The purpose of this study is to examine whether and in what ways these two all-author network approaches yield different results.

Design/methodology/approach

The sample was collected from the database of Web of Science, including all articles published in Scientometrics and Journal of Informetrics from 2011 to 2020. First, 100 representative authors were selected from each set, and ABCA matrices and ACA matrices were constructed. Second, factor analysis was carried out on the matrices, to detect the intellectual structure of scientometrics and informetrics.

Findings

The intellectual structures identified by ABCA and ACA are similar overall, but the results differ somewhat when it comes to specific structures. The ABCA is more sensitive to some highly collaborative research teams and presents a clearer picture of current intellectual structures and trends while ACA seems to have some advantages in representing the more traditional and proven research topics in the field. The combined use of ABCA and ACA allows for a more comprehensive and specific intellectual structure of research fields.

Originality/value

This paper compares the performance of ABCA and ACA detecting the intellectual structure of the domain from the perspective of all authors, revealing the intellectual structure of scientometrics and informetrics comprehensively.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2020-0540.

Details

Online Information Review, vol. 47 no. 1
Type: Research Article
ISSN: 1468-4527

Keywords

Article
Publication date: 24 February 2021

Syed Asif Raza and Srikrishna Madhumohan Govindaluri

The 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…

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Abstract

Purpose

The 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/approach

More 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.

Findings

The 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 implications

This 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/value

The 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.

Details

Benchmarking: An International Journal, vol. 28 no. 9
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 15 June 2020

Fangfang Wei and Guijie Zhang

This paper aims to present a longitudinal and visualizing study using scientometric approaches to depict the historical changes in the academic community, intellectual base and…

Abstract

Purpose

This paper aims to present a longitudinal and visualizing study using scientometric approaches to depict the historical changes in the academic community, intellectual base and research hotspots within the business domain.

Design/methodology/approach

Two mapping methods are used, namely, co-citation analysis and co-occurrence analysis. Both the co-citation analysis and co-occurrence analysis in this study are conducted using CiteSpace, a Java-based scientific visualization software.

Findings

This paper detects changes in academic communities in 24 business journals chosen by the University of Texas at Dallas as leading journals (UTD24) and identifies the research hotspots such as corporate governance, organizational research and capital research. Many authors and academic communities appear in two or even three periods, which indicates the lasting academic vitality of scholars in this field. This paper determines the evolution of scholars' research interests by identifying high-frequency keywords during the entire period.

Originality/value

This paper reveals a systematic and holistic picture of the developmental landscape of the business domain, which can provide a potential guide for future research. Furthermore, based on empirical data and knowledge visualization, the intellectual structure and evolution of the business domain can be identified more objectively.

Details

The Electronic Library , vol. 38 no. 3
Type: Research Article
ISSN: 0264-0473

Keywords

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