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The study seeks to apply Web co‐word analysis to the Chinese business environment to test the feasibility of the method there.

The authors selected a group of companies in two Chinese industries, collected co‐word data for the companies, analyzed the data with multidimensional scaling (MDS), and then compared the MDS maps generated from the co‐word data with business situations to find out if the co‐word method works.

The study found that the Web co‐word method could potentially be applied to the Chinese environment. The study also found the advantages and disadvantages of the Web co‐word method vs the Web co‐link method.

Knowing the applicability of the Web co‐word method to the Chinese environment contributes to the knowledge of this new Webometrics method. Mining business information from the Web is more valuable when applied to a foreign country where language and culture barriers exist. To use the co‐word method, one does not have to be able to read or write in that language. One only needs to have the names of the companies to study, which can be easily obtained without knowledge of the language. The value of business information about countries such as China is obvious given the global nature of contemporary business competition and the significance of the Chinese economy to the world.

This paper aims to map the evolution of research in business ethics from 1991 to 2018. It aims to identify the major themes and how they have evolved. It also aims to identify gaps in the literature for recommending future research agenda.

This study uses co-word network analysis. Co-word network analysis is a bibliometric technique used to objectively identify research themes via article keywords. The study examines articles from 1991 to 2018, which is a span encompassing a greater number of articles than previous bibliometric studies in business ethics. This time span was split into four periods and major research themes were identified for each period to map the changes in research agendas in the business ethics discipline over time.

The findings point to increasing maturation of the discipline, a slight decline in ethical decision-making research, a rise in research at the intersection of leadership and ethics and exponential growth in studies on corporate social responsibility. Ethical issues in business-to-business contexts are understudied. Research in environmental disclosures and leadership is expected to grow in the future.

This is the first study in business ethics to use keywords for analyzing the evolution of a discipline. This study encompasses more articles than any other study in business ethics. Finally, this is the only study to use co-word network analysis to study business ethics literature.

The purpose of this article is to investigate the use of word co-occurrence analysis method in mapping of the scientific fields with emphasis on the field of Informetrics.

This is an applied study using scientometrics, co-word analysis and network analysis and its steps are summarised as follows: collecting the data related to the Informetrics field indexed in Web of Science (WOS) database, refining and standardising the keywords of the extracted articles from WOS and preparing a selected list of these keywords, drawing the word co-occurrence map in the Informetrics field and analysing of results.

Based on the resulted maps the concepts such as information science, library, bibliometric analysis, innovation and text mining are the most widely used topics in the field of Informetrics. The co-word occurrence maps drawn at different periods show the changes and stabilities in the concepts related to the field of Informetrics. A number of topics such as “bibliometric analysis” are present in all years, whereas others such as “innovation” have disappeared. New topics emerge as a recombination of existing topics and in interaction with new (technological) developments.

The results of these analytical studies can be used as a guide for determining research priorities in the scientific fields, and also for planning and management in academic institutions.

The purpose of this paper is to analyze the origins and evolution of the concept of servitization by studying the definitions of servitization provided in the literature. Servitization represents an academic field that has grown rapidly since its inception. However, the conceptualization of servitization varies greatly, in part because of the number of studies on this topic and the fact that it has been analyzed in a range of disciplines using a number of theoretical approaches. There is a need to standardize the vocabulary to create a general definition that can support the development of theory in this domain and help legitimize servitization as a research area.

This study conducts a systematic, quantitative analysis of a broad set of definitions of servitization. Specifically, this study performs content analysis (combining co-word analysis and social network analysis) and consensus analysis. This study develops a strategic diagram to represent the morphology of the research network.

The definitions of servitization are deconstructed and analyzed in depth to create a comprehensive picture of the research on this topic. This analysis reveals the origins and evolution of this research area. The results show a low degree of consensus among scholars regarding the concept of servitization. This study proposes a definition that should be widely accepted thanks to its inclusion of the core terms from other definitions. Explicit recognition of multiple approaches to defining the term can help practitioners and researchers. Predictions about future progress in this area are discussed.

A universal definition of servitization is proposed based on the results of co-word and network analysis. This definition unifies a range of multidisciplinary viewpoints. From a practical perspective, the key vocabulary in servitization research is highlighted.

This paper aims to help scholars know about the focus and frontier in the field of corporate social responsibility (CSR). Although related research in CSR started 60 years ago, there is not much systematical literature review on CSR in recent years. This paper applies scientometric method, especially co-word analysis, to explore the frontier and focus of CSR in the twenty-first century, based on the articles from 2001 to 2014 in SSCI database.

In this paper, the authors first use the scientometric method and co-word analysis for keywords filtering and apply social network methodology to investigate the networks of high-frequency keywords and high-frequency authors.

The authors summarize the current state of CSR research in two aspects. By co-word analysis of high-frequency keywords, the findings show that the focus and frontier are highly related to CSR. Based on the findings of social network analysis, this paper concludes four important research directions and possible future research of CSR.

The findings in this paper will help scholars of CSR or other related fields to realize the focus and frontier of CSR and provide some guidance for their future research.

This paper aims to provide a comprehensive bibliometric analysis of the current state of social media literature by examining co-word network analysis and thematic keyword analysis of both scholars and hospitality and tourism journals in three sub-periods (2002-2006, 2007-2012 and 2013-2018).

This research used a bibliometric analysis of social media literature in the field of hospitality and tourism by synthesizing the literature of a large sample of 601 studies over an extended time period (2002-2018).

The jump in the number of examined contexts, platforms, methodological approaches and research implications during 2007-2012 has marked the start of social media as a new phenomenon in hospitality and tourism research. Interestingly, International Journal of Contemporary Hospitality Management was a leading contributor to social media research between 2017 and 2018. The period 2013-2018 has witnessed newly emerging trends such as “big data,” “e-tourism,” “green experience” and “smart tourism.” This study’s analysis indicated that few keywords in social media appeared in the maturity stage. New platforms such as “Expedia,” “Foursquare,” “Flickr,” “Pinterest,” “Couchsurfing” and “Twitter” appeared between 2013 and 2018.

The scope of past research on the evolution of social media was limited to either a few of the most popular cited journals and/or analysis within a narrow time span. In contrast, the present study aims to uncover the rapid progress in social media research between 2002 and 2018, addressing growth in breadth and depth of thematic areas. Finally, this paper concluded with the proposal of knowledge-based life cycle framework that identifies key themes related to social media research. This framework provided insights into what has been addressed in previous literature (maturity and decline stages) and reported the topics that have been under-researched (introduction and growth stages).

Using science mapping analysis approach and co-word analysis, the present study explores and visualizes research fields and thematic evolution of the coronavirus. Based on this method, one can get a picture of the real content of the themes in the mentioned thematic area and identify the main minor and emerging themes.

This study was conducted based on co-word science mapping analysis under a longitudinal study (from 1988 to 2020). The collection of documents in this study was further divided into three subperiods: 1988–1998, 1999–2009 and 2010–2020. In order to perform science mapping analysis based on co-word bibliographic networks, SciMAT was utilized as a bibliometric tool. Moreover, WoS, PubMed and Scopus bibliographic databases were used to download all records.

In this study, strategic diagrams were demonstrated for the coronavirus research for a chronological period to assess the most relevant themes. Each diagram depended on the sum of documents linked to each research topic. In the first period (1988–1998), the most centralizations were on virology and evaluation of coronavirus structure and its structural and nonstructural proteins. In the second period (1999–2009), with due attention to high population density in eastern Asia and the increasing number of people affected with the new generation of coronavirus (named severe acute respiratory syndrome virus or SARS virus), publications have been concentrated on “antiviral activity.” In the third period (2010–2020), there was a tendency to investigate clinical syndromes, and most of the publications and citations were about hot topics like “severe acute respiratory syndrome,” “coronavirus” and “respiratory tract disease.” Scientometric analysis of the field of coronavirus can be regarded as a roadmap for future research and policymaking in this important area.

The originality of this research can be considered in two ways. First, the strategic diagrams of coronavirus are drawn in four thematic areas including motor cluster, basic and transversal cluster, highly developed cluster and emerging and declining cluster. Second, COVID-19 is mentioned as a hot topic of research.

This study aims to contribute to the relevant body of knowledge by examining the bibliometric studies related to tourism and hospitality indexed in the Web of Science (WoS) database from a bibliometric perspective (evaluative and relational techniques).

The WoS database was used to obtain studies to be reviewed. A total of 136 studies were analyzed and visualized in terms of evaluative and relational techniques, and a subject categorization was made.

“Tourism management” and “tourism and hospitality” are the two fields of research where bibliometric studies are carried out more frequently. Evaluative techniques were used in most studies while relational techniques, such as co-word, co-author, co-citation analysis and bibliographic coupling, were performed less. Relational techniques indicate that the words “bibliometric analysis” and “tourism” are frequently used together in the studies examined; the most common authorship cooperation is between China and USA.

This study provides an overview of bibliometric studies in tourism and hospitality literature. It expands the previous literature and shows study topics that are more focused by examining the abstracts and contents of articles published in journals in different WoS categories.

Findings related to evaluative and relational techniques can serve as useful information for researchers, who are new to the field.

This study contributes to the current knowledge accumulation by its lack of year, country, region and language limits.

This study aims to discern emerging trends and provide a longitudinal perspective on merchandising research by identifying relationships between merchandising-related subdomains/themes.

This study sourced 657 merchandising-related articles published since 1960, from the Scopus database and 425 from Web of Science. After processing and normalizing the data, this study performed co-word and thematic network analyses. Taking a text mining approach, this study used topic modeling to identify a set of coherent topics characterized by the keywords of the articles.

This study identified the following merchandising-related themes: branding, retail, consumer, behavior, modeling, textile and clothing industry and visual merchandising. Although visual merchandising was the first type of merchandising to be used in-store, only recently has it become an emerging topic in the academic literature. There has been a further trend over the past decade to understand the adoption of simulation technology, such as computer-aided design, particularly in supply chain management in the clothing industry. These and other findings contribute to the discussion of the merchandising concept, approached from an evolutionary perspective.

The conclusions of this study hold implications at the intersection of merchandising, sectors, new technologies, research methodologies and merchandising-practitioner education. Research trends suggest that, in the future, virtual reality and augmented reality using neuroscientific methods will be applied to the e-merchandising context.

The different dimensions of merchandising can be used to leverage store managers’ decision-making process toward an integrated store-management strategy. In particular, by adopting loyalty merchandising tactics, the store can generate emotional attachment among consumers, who will perceive its value and services as unique, thanks to merchandising items designed specifically with that aim in mind. The stimulation of unplanned purchases, the strategic location of products and duration of each merchandising activity in the store, the digitalization of merchandising and the application of findings from neuroscience studies are some of the most relevant practical applications.

This study provides the first-ever longitudinal review of the state of the art in merchandising research, taking a holistic perspective of this field of knowledge spanning a 60-year period. The work makes a valuable contribution to the development of the marketing discipline.

The co‐word analysis method is commonly used to cluster‐related keywords into the same keyword domain. In other words, traditional co‐word analysis cannot cluster the same keywords into more than one keyword domain, and disregards the multi‐domain property of keywords. The purpose of this paper is to propose an innovative keyword co‐citation approach called “Complete Keyword Pair (CKP) method”, which groups complete keyword sets of reference papers into clusters, and thus finds keywords belonging to more than one keyword domain, namely bridge‐keywords.

The approach regards complete author keywords of a paper as a complete keyword set to compute the relations among keywords. Any two complete keyword sets whose corresponding papers are co‐referenced by the same paper are recorded as a CKP. A clustering method is performed with the correlation matrix computed from the frequency counts of the CKPs, for clustering the complete keyword sets. Since keywords may be involved in more than one complete keyword set, the same keywords may end up appearing in different clusters.

Results of this study show that the CKP method can discover bridge‐keywords with average precision of 80 per cent in the Journal of the Association for Computing Machinery citation bank during 2000‐2006 when compared against the benchmark of Association for Computing Machinery Computing Classification System.

Traditional co‐word analysis focuses on co‐occurrence of keywords, and therefore, cannot cluster the same keywords into more than one keyword domain. The CKP approach considers complete author keyword sets of reference papers to discover bridge‐keywords. Therefore, the keyword recommendation system based on CKP can recommend keywords across multiple keyword domains via the bridge‐keywords.