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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.

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.

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.

In this article, the results of the bibliometric analysis applied to research on “Water Governance” are presented in order to observe behavior patterns in the key areas of this field of knowledge (progression, most productive authors, etc.). This research is complemented with a co-citation analysis. When considering two databases, a comparative study is carried out between both databases through coverage, overlap, dispersion, or concentration indicators. The results indicate that this area of knowledge has evolved rapidly and has gained popularity and importance among researchers, especially since 2009, when the real boom of the discipline took place, with about two-thirds of the papers being published in the last five years. The main authors, the most relevant articles based on the citation criterion, the institutions, and countries with the highest number of investigations and the journals where this topic is published are also identified. Scopus is the database that performs better coverage by collecting a higher number of articles and obtaining a greater number of citations.

Purpose The evolution of the socio-cognitive structure of the field of knowledge management (KM) during the period 1986–2015 is described. Design/methodology/approach Records retrieved from Web of Science were submitted to author co-citation analysis (ACA) following a longitudinal perspective as of the following time slices: 1986–1996, 1997–2006, and 2007–2015. The top 10% of most cited first authors by sub-periods were mapped in bibliometric networks in order to interpret the communities formed and their relationships. Findings KM is a homogeneous field as indicated by networks results. Nine classical authors are identified since they are highly co-cited in each sub-period, highlighting Ikujiro Nonaka as the most influential authors in the field. The most significant communities in KM are devoted to strategic management, KM foundations, organisational learning and behaviour, and organisational theories. Major trends in the evolution of the intellectual structure of KM evidence a technological influence in 1986–1996, a strategic influence in 1997–2006, and finally a sociological influence in 2007–2015. Research limitations Describing a field from a single database can offer biases in terms of output coverage. Likewise, the conference proceedings and books were not used and the analysis was only based on first authors. However, the results obtained can be very useful to understand the evolution of KM research. Practical implications These results might be useful for managers and academicians to understand the evolution of KM field and to (re)define research activities and organisational projects. Originality/value The novelty of this paper lies in considering ACA as a bibliometric technique to study KM research. In addition, our investigation has a wider time coverage than earlier articles.

Purpose Previous commonly used author co-citation analysis (ACA) methods have limited the ability to deal with accidental co-citation in constructing a raw co-citation matrix. Therefore, the purpose of this paper is to propose a new method, called author tri-citation analysis (ATA), to better map knowledge domains and depict scientific intellectual structures. Design/methodology/approach Different from the previous method of using ACA that captures author co-citation relationships, the ATA method seeks tri-citation relationships among authors. Compared with ACA, ATA can ignore some accidental co-citation relationships between authors and can improve the accuracy of mapping knowledge domains. Findings Although ATA does not mine more sub-fields than ACA does, the results of the empirical studies show that ATA, the newly proposed method, performs better in knowledge domain maps based on publications in the field of computer science. Research limitations/implications The definition of ATA in this article is simple and still insufficiently informative. Many other pieces of information can be involved; for example, all authors’ information, authors’ sequence in the author list, reference published time and similar. These can be enhanced in future studies. Practical implications This research will enrich the methods of mapping knowledge domains due to its new perspective. Social implications Knowledge domain mapping is important to understand a discipline, and this research provides more potential methods for this, which benefits the performance of the maps. Originality/value ATA can provide a methodological awareness for mapping knowledge domains. This value lies in not only a tri-citation perspective, but also author bibliographic tripling and author tri-operation perspectives (“tri-” perspectives).

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.

Purpose – The purpose of this paper is to further explore the co-citation and bibliographic-coupling relationship among the core authors in the field of Chinese information science (IS), to expose research activity and author impact, and to make induction analyses about Chinese IS research patterns and theme evolution. Design/methodology/approach – The research data include 8,567 papers and 70,947 cited articles in the IS field indexed by Chinese Social Sciences Citation Index from 2000 to 2009. Author co-citation analysis, author bibliographic-coupling analysis, social network analysis, and factor analysis were combined to explore co-citation and bibliographic-coupling relationships and to identify research groups and subjects. Findings – Scholars with greatest impact are different from the most active scholars of Chinese IS; there is no uniform impact pattern forming since authors’ impact subjects are scattered and not steady; while authors’ research activities present higher independence and concentration, there is still no steady research pattern due to no deep research existing. Furthermore, Chinese IS studies can be delineated by: foundation or extension. The research subjects of these two parts, as well as their corresponding/contributing authors, are different under different views. The general research status of core authors is concentrated, while their impact is broad. Originality/value – The combined use of some related methods could enrich the development and methodology research of the discipline, and the results establish a reference point on the development of IS research.