Explore the vast range of titles available.

This paper complements a recent study by Ramos-Rodriguez and Ruiz-Navarro (2004) that investigated the intellectual structure of the strategic management field through co-citation analysis. By using authors as the units of analysis and incorporating all the citations that are included in the Science Citation Index and the Social Science Citation Index, we trace the evolution of the intellectual structure of the strategic management field during the period 1980-2000. Using a variety of data analytic techniques such as multidimensional scaling, factor analysis, and Pathfinder analysis, we (1) delineate the subfields that constitute the intellectual structure of strategic management; (2) determine the relationships between the subfields; (3) identify authors who play a pivotal role in bridging two or more conceptual domains of research; and (4) graphically map the intellectual structure in two-dimensional space in order to visualize spatial distances between intellectual themes. The analysis provides insights about the influence of individual authors as well as changes in their influence over time.

In the field of scientometrics, the principal purpose for author co-citation analysis (ACA) is to map knowledge domains by quantifying the relationship between co-cited author pairs. However, traditional ACA has been criticized since its input is insufficiently informative by simply counting authors’ co-citation frequencies. To address this issue, this paper introduces a new method that reconstructs the raw co-citation matrices by regarding document unit counts and keywords of references, named as Document- and Keyword-Based Author Co-Citation Analysis (DKACA). Based on the traditional ACA, DKACA counted co-citation pairs by document units instead of authors from the global network perspective. Moreover, by incorporating the information of keywords from cited papers, DKACA captured their semantic similarity between co-cited papers. In the method validation part, we implemented network visualization and MDS measurement to evaluate the effectiveness of DKACA. Results suggest that the proposed DKACA method not only reveals more insights that are previously unknown but also improves the performance and accuracy of knowledge domain mapping, representing a new basis for further studies.

Drawing on sociology of science foundations, we argue that, in order to survive and prosper, healthy applied disciplines must meet the dual demands of academic and practitioner audiences by demonstrating both focus and diversity in their research. First, we use this concomitant modality to explain why previous studies into the structure of the Information Systems discipline have reported contradictory results, with some finding a focused field while others conclude that the field is diverse. In support of our argument, we then present the results of a longitudinal, author co-citation analysis, looking across the full range of journals in which IS research is published. Our results suggest that the IS field has sustained a focus on research within three subfields over a 20-year period from 1986 to 2005: (1) a thematic miscellany of research on development, implementation, and use of systems in various application domains; (2) IS strategy and business outcomes; and (3) group work and decision support. At the same time, the field has demonstrated considerable diversity within and around these core subfields, with researchers responding flexibly to the rapidly changing field by investigating these areas with new paradigms and in new contexts, and by exploring new topics including inter-business and Internet applications, computer-supported collaborative work, virtual teams, and knowledge management. Finally, we demonstrate that, over the 20-year period from 1986 to 2005, the discipline has shifted from fragmented adhocracy to a polycentric state, which is particularly appropriate to an applied discipline such as IS that must address the dual demands of focus and diversity in a rapidly changing technological context.

As a frequently used method of depicting scientific intellectual structures, author co-citation analysis (ACA) has been applied to many domains. However, only count-based information is involved as the input of ACA, which is not sufficiently informative for knowledge representations. This article catches several metadata in full text of citing papers but not aims at content-level information, which increases the amount of information input to ACA without increasing computational complexity a lot. We propose a new method by involving information including the number of mentioned times in a citing paper and the number of context words in a citing sentence. We combine these pieces of information into the traditional ACA and compare the results between ACA and the proposed approach by using factor analysis, network analysis, and MDS-measurement. The result of our empirical study indicates that compared with the traditional ACA, the proposed method shows a better clustering performance in visualizations and reveals more details in displaying intellectual structures.

The current big data era has placed new challenges for the study and application of information management (IM). In this paper we visualized how IM evolved over thirty-six years (1980–2015). An author co-citation analysis was applied to a dataset extracted from Web of Science Core Collection®. To map the evolution, a longitudinal perspective was carried out by partitioning three homogeneous sub-periods of twelve years (1980–1991, 1992–2003, and 2004–2015). The 10% of most cited authors in each sub-period were clustered in bibliometric networks and then labeled into research areas. Likewise, we constructed a strategic diagram in order to describe internal relations within clusters and their interactions. Our findings evidenced 14 clusters from 1980 to 2015, representing several topics like management information systems, database systems, library automation, information management foundations, technology-based strategy, information technology management, health information management, personal information management, and motivated information management. The socio-intellectual structure shows a transition from an organizational to an individual approach in the study and application of IM. Our findings also point to an evolution from a technological orientation towards an informational orientation, since in the last sub-period there are mostly information scientists related to the study of information behavior and information retrieval. This study is the most comprehensive bibliometric research oriented to visualize the overall evolution IM.

Author co-citation analysis (ACA) is a well-known and frequently-used method to exhibit the academic researchers and the professional field sketch according to co-citation relationships between authors in an article set. However, visualizing subtle examination is limited because only author co-citation information is required in ACA. The proposed method, called modified author co-citation analysis (MACA), exploits author co-citation relationship, citations published time, citations published carriers, and citations keywords, to construct MACA-based co-citation matrices. According to the results of our experiments: (1) MACA shows a good clustering result with more delicacy and more clearness; (2) more information involved in co-citation analysis performs good visual acuity; (3) in visualization of co-citation network produced by MACA, the points in different categories have far more distance, and the points indicating authors in the same category are closer together. As a result, the proposed MACA is found that more detailed and subtle information of a knowledge domain analyzed can be obtained, compared to ACA.

This paper introduces author-level bibliometric co-occurrence network by discussing its history and contribution to the analysis of scholarly communication and intellectual structure. The difference among various author co-occurrence networks, which type of network shall be adapted in different situations, as well as the relationship among these networks, however, remain not explored. Five types of author co-occurrence networks were proposed: (1) co-authorship (CA); (2) author co-citation (ACC); (3) author bibliographic coupling (ABC); (4) words-based author coupling (WAC); (5) journals-based author coupling (JAC). Networks of 98 high impact authors from 30 journals indexed by 2011 version of Journal Citation Report-SSCI under the Information Science & Library Science category are constructed for study. Social network analysis and hierarchical cluster analysis are applied to identify sub-networks with results visualized by VOSviewer software. QAP test is used to find potential correlation among networks. Cluster analysis results show that all the five types of networks have the power for revealing intellectual structure of sciences but the revealed structures are different from each other. ABC identified more sub-structures than other types of network, followed by CA and ACC. WAC result is easily affected and JAC result is ambiguous. QAP test result shows that ABC network has the highest proximity with other types of networks while CA network has relatively lower proximity with other networks. This paper will provide a better comprehension of author interaction and contribute to cognitive application of author co-occurrence network analysis.

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.

This study explores weighted author co-citation analysis (ACA) through a comparison of results from four weighted citation counting methods. The data set used comprises full-text research articles published in four top-tier library and information science (LIS) journals from 2011 to 2018. It finds that in-text frequency-weighted counting performs as well as traditional counting in identifying major dimensions of the LIS field but also shows more detail. Re-citation-based counting appears to highlight well-integrated specialties and weaken the presence of more fragmented ones compared to traditional counting. In-text frequency weighted re-citation counting, expected to highlight “deep” impact, appears to effectively zoom into the field to show intense streams of research within it, but fail to identify major dimensions of the field, essentially providing a telescopic view of the LIS field instead of the panoramic one that the other three methods provide. Measuring deep impact may be interesting and important for research evaluation but fails to retain the broader context that makes the visualizations of research fields so informative. It appears that what may be “noise” when considering impact of individuals can provide the context that allows us to see the forest for the trees when examining intellectual structures of research fields as in the case of traditional ACA.

Purpose This study aims to conduct a literature review on factors that influence the implementation and design of performance measurement systems in nonprofit organizations. Design/methodology/approach The research strategy is conceived through a literature review focused on the analysis of authorship, supported by bibliometric techniques such as citation, co-citation and co-authorship social networks. Findings Models and theories proposed for measuring performance in non-profit organizations are being researched, starting to form an intellectual structure related to performance measurement systems and nonprofits. Three main research topics have been given more attention: strategic performance and public service performance, health-care performance and nonprofit operations strategy and performance measurement. Research limitations/implications The study is limited to scientific journal papers and could benefit from the addition of new sources of information such as conference papers, books and standards. The body of knowledge of this topic could also benefit from an in-depth investigation through a comprehensive review of models and theories, as a proposal for a future research agenda. Practical implications As practical applications are identified, groups of researchers in different countries and subjects that can generate research agendas, scientific communities used to investigate issues related to performance in nonprofit activities. Originality/value Performance measurement in nonprofit organizations is a topic of study that has been receiving considerable attention in recent years, to the point that the literature is revealing specific models for measuring performance in this type of organizations. Particular models and theories are being conceived, specializing existing models and theories related to performance measurement and management.