Search results

Research in customer engagement (CE) has gained momentum in the last decade, thanks to its growing popularity among scholars and practitioners. The Marketing Science Institute (MSI), for instance, has been continually listing CE as part of its Tier I research priorities since 2010. CE scholars have also studied the construct in the international marketing context. Hofstede's characterization of cultures as either individualist or collectivist helped scholars explain the need for different CE strategies across countries, and the domain seems to be evolving ever since. The ever-growing interest of CE scholars in the international market and cross-cultural scenarios requires a comprehensive and scientific review of the literature. Using bibliometric analysis, this study fills this critical gap by mapping the intellectual structure of CE research in the context of international marketing and provides future research directions to scholars in this domain.

The authors have used VOSviewer and Biblioshiny software packages to conduct a bibliometric analysis of 109 articles in the domain.

The major findings include the most influential countries, journals, articles and authors, the different research streams and their development and the future research directions in the domain. When CE is considered in an international marketing context, four broad themes emerged. The first theme is about differences in customer engagement behaviors across cultures. The second theme is about the development of CE and related constructs. The third theme relates to how brands have used CE and CBE (customer brand engagement) across different international contexts. The fourth theme is all about the conceptual and methodological support for the study of CE.

This study is a novel attempt at providing a comprehensive bibliometric analysis of CE research in the international marketing context, using a combination of VOSviewer and Biblioshiny software packages.

This bibliometric mapping study aimed to provide comprehensive insights into the global research landscape of cybernetics. Utilizing the biblioshiny function in R Studio, we conducted an analysis spanning 1958 to 2023, sourcing data from Scopus. This research focuses on key terms such as cybernetics, cybernetics systems, complex adaptive systems, viable system models (VSM), agent-based modeling, feedback loops and complexity systems.

The analysis leveraged R Studio’s biblioshiny function to perform bibliometric mapping. Keyword searches were conducted within titles, abstracts and keywords, targeting terms central to cybernetics. The timespan, 1958–2023, provides a comprehensive overview of the evolution of cybernetics-related literature. The data were extracted from Scopus to ensure a robust and widely recognized source.

The results revealed a rich and interconnected global research network in cybernetics. The word cloud analysis highlights prominent terms such as “agent-based modeling,” “complex adaptive systems,” “feedback loop,” “viable system model” and “cybernetics.” Notably, the journal Kybernetes has emerged as a focal point, with significant citations, solidifying its position as a key source within the cybernetics research domain. The bibliometric map provides visual clarity regarding the relationships between various concepts and their evolution over time.

This study contributes original insights by employing advanced bibliometric techniques in R Studio to map the cybernetics research landscape. The comprehensive analysis sheds light on the evolution of key concepts and the global collaborative networks shaping cybernetics research. The identification of influential sources, such as Kybernetes, adds value to researchers seeking to navigate and contribute to the dynamic field of cybernetics. Furthermore, this study highlights that cybernetics not only provides a useful framework for understanding and managing major economic shocks but also offers perspectives for understanding phenomena in various fields such as economics, medicine, environmental sciences and climate change.

Purpose: This chapter aims to review the research literature on the insurance industry and map the emerging research trends in this field through a bibliometric analysis and network visualisation exercise.

Design/methodology/approach: The research literature gathered from the Web of Science (WoS) databases was applied to bibliometric analysis in this article. With the help of Biblioshiny, this research was utilised to identify documents, most prolific institutions, countries, resource titles, and WoS categories in the insurance industry. In addition, bibliometric mapping was used to identify national and institutional collaboration networks.

Findings: The author discovered that the literature had increased drastically in the academic discourse during the last two decades. According to the bibliometric data, developed countries such as the United States and the United Kingdom reign research in this sector. The research highlights the most prominent studies and writers in the insurance field and the evolution of the domain from its inception to the contemporary. It also highlights theoretical disagreements and contradictions between theoretical conceptualisation and empirical measures by presenting the significant concerns in the literature.

Originality/value: This chapter delivers the first comprehensive bibliometric analysis of the insurance sector’s literature production in connection to emerging technology, which will aid researchers and practitioners in better understanding the relationships between themes and outsiders to understand the domain area better. The author makes recommendations for future perspectives study directions and highlights the critical conceptual framework that can build future research. Overall, this research contributes to a better understanding of the insurance industry and offers new perspectives.

This research aims to conduct a literature review of Lean Six Sigma (LSS) in the Indian context and related research publications and apply bibliometric analysis and the author's visualization to map research trends in this area.

This article conducts a bibliometric analysis of LSS-related research in the Indian context using data gathered from Scopus and Web of Science databases from 2011 to 2022. The review provides information on LSS-related research in the Indian context and evaluates performance based on primary sources, authors, keywords, countries, affiliations, and documents. The analysis employs the Biblioshiny app and Bibliometrix R-tool for data analysis and scientific mapping.

The results of the bibliometric analysis indicate that the LSS culture has widely spread in India. The International Journal of Lean Six Sigma and Production Planning and Control were found to be the most productive sources for publishing LSS-related research articles. Antony J. was identified as the most active author in this field, contributing the most over the years. Among all organizations, NITs have conducted the most comprehensive research on LSS, indicating their significant investment of resources and efforts in studying this methodology and its applications in India. Additionally, the study examined the intellectual, social, and conceptual structures to identify implicit gaps and future research opportunities.

The findings of this study can inform academicians, researchers, practitioners, and policymakers about the state-of-the-art and the specifics of the most prolific studies. This study will facilitate their exploration of emerging research areas in LSS.

To the best of the authors knowledge, this is the first bibliometric analysis of LSS in the Indian context, providing an overview of relevant publications published between 2011 and 2022. This study analyzed 194 articles on LSS in India, which can help researchers and academics identify emerging research areas, suitable collaborators, and relevant journals for future publications.

Websites, search engines, recommender systems, artificial intelligence and digital libraries have the potential to support serendipity for unexpected interaction with information and ideas which would lead to favored information discoveries. This paper aims to explore the current state of research into serendipity particularly related to information encountering.

This study provides bibliometric review of 166 studies on serendipity extracted from the Web of Science. Two bibliometric analysis tools HisCite and RStudio (Biblioshiny) are used on 30 years of data. Citation counts and bibliographic records of the papers are assessed using HisCite. Moreover, visualization of prominent sources, countries, keywords and the collaborative networks of authors and institutions are assessed using RStudio (Biblioshiny) software. A total of 166 papers on serendipity were found from the period 1989 to 2022, and the most influential authors, articles, journals, institutions and countries among these were determined.

The highest numbers of 11 papers were published in the year 2019. Makri and Erdelez are the most influential authors for contributing studies on serendipity. “Journal of Documentation” is the top-ranking journal. University College London is the prominent affiliation contributing highest number of studies on serendipity. The UK and the USA are the prominent nations contributing highest number of research. Authorship pattern for research on serendipity reveals involvement of single author in majority of the studies. OA Green model is the most preferred model for archiving of research articles by the authors who worked on serendipity. In addition, majority of the research outputs have received a citation ranging from 0 to 50.

To the best of the authors’ knowledge, this paper may be the first bibliometric analysis on serendipity research using bibliometric tools in library and information science studies. The paper would definitely open new avenues for other serendipity researchers.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

This paper aims to facilitate researchers, practitioners and policymakers in understanding and managing the impact of the black swan event – COVID-19 on work from home in the social science subject area through bibliometric analysis. For this purpose, the authors analyzed publications from the Scopus database.

In this paper, the authors conducted bibliometric analysis based on two major techniques: performance analysis and science mapping. The authors applied VOSviewer and Biblioshiny to address the research questions of present study. The study explored the hot trend topics and summarized them with discussions and implications.

Based on the analysis of 500 publications, the authors present an overview of performance and science mapping from the perspective of different aspects such as publication output and authors. Also, authors visualized the text mining by co-word analysis forming nine clusters as well as mapping trend topics. The existing publications were divided into ten clusters according to different keyword analyses: Leadership, Mental health, Technology, Crisis Management, Gender, Challenges, well-being and Work-life balance.

Sample from the Scopus database is not exhaustive, and the dataset may be skewed due to the adoption of the selection criteria. The authors’ concentration was on academic publications in English that excludes potentially intriguing and pioneering studies done in other languages. The study area was limited to social science only.

The paramount lesson is that the COVID-19 quandary is multifaceted, necessitating not simply adaptations to current strategies but also an understanding and analysis of advancements in the economy, commerce and society. According to the analysis presented above, to overcome the COVID-19 “black swan event”, managers must think ahead. The analysis gives leaders and decision-makers a range of useful information on work from home (WFH) difficulties in COVID-19, as well as initiatives and revisions that must be implemented at the economic, social and scientific aspects when dealing with such uncertainties. The findings also aid managers in forecasting the need for sophisticated technology, organizational agility and resilience to attain the desired direction of progress.

With a focus on addressing WFH during COVID-19 from social science perspective and to synthesize its future research directions systematically, the authors performed Bibliometric analysis both with VOSviewer and Biblioshiny, in order to enhance the overall analysis for higher accuracy and more reliable results that is unique value addition and contribution to the existing literature.

This research aims to shed light on the trend of humanitarian supply chain (HSC) studies in the era of pre, during and post coronavirus disease 2019 (COVID-19) pandemic outbreaks. This study provides comprehensive bibliometric mapping published in the 21 top vintage sources globally providing detailed metadata on HSC articles. The manuscript objectives are threefold: to explore the documents that are published in the field of humanitarian logistics and supply chain; second, to identify details of articles in humanitarian logistics and supply chain and thirdly, to explore research the critical area published in the HSC in pre, during and post era of pandemic COVID-19.

This research adopts bibliometric analysis of HSC studies using the Biblioshiny, a shiny app for the Bibliometrix R package. The tool employed in this study decodes the data extracted from the Scopus database to various visualized forms. The review of the HSC studies in this research covers all related publications from 2006 to early 2022. The record of the article was scanned and refined accordingly.

A multi perspectives of HSC studies were explored, discussed and identified. The bibliometric analysis findings offer significant information on the current and future trend publications in the area of humanitarian logistics and supply chain. Additionally, it also provides significant information on the highly cited documents in humanitarian logistics and supply chain studies, most productive contributors, keywords analysis findings, most productive countries and sources, network analysis data on co-occurrence network and themes mapping information in the field of humanitarian logistics supply chain before and after pandemic COVID-19.

A multi-perspective of HSC studies was explored only within the online Scopus database. It excludes other articles published in other databases. Future research could explore related articles published in other recognized databases.

Practitioners can use multi perspectives findings from pre, during and post-pandemic COVID-19 issues discussed in this paper to get new insight and perception of the issue to facilitate their current and future operation and strategy.

To the best of the researchers’ knowledge, this is the first bibliometric study to analyze the trend of HSC studies using Biblioshiny focusing on pre, during and post COVID-19 pandemic. The review highlights annual publication trends, most productive authors, most cited papers, most productive countries, most productive institutions and most productive sources, which leads to a number of future research agendas for future studies.

The purpose of this paper is to present a comprehensive analysis of the current status and development of the digital journalism field from 1987 to 2021 using the Dimensions database.

Using the Dimensions.ai database, 1734 articles were identified through search strategies which were published from 1987 to 2021. The downloaded results were analysed using specific parameters with the help of bibliometric and science mapping tools: Biblioshiny, VOSviewer and CiteSpace. The key contributions of the present comprehensive bibliometric study of the digital journalism field can be seen in terms of the following aspects: (1) Publication analysis from the perspectives of publication growth, key journals, contributing authors, institutions and countries done through Biblioshiny package. (2) Citation network analysis from the perspective of co-citation structure of papers, authors, countries and institutions done through VOSviewer. (3) Timeline analysis and keywords burst detection to identify hotspots and research trends in digital journalism with the help of CiteSpace.

The first paper with the keyword digital journalism was published in the year 1989. From 2011 onwards, there has been growth in digital journalism literature. The most popular journal in digital journalism studies is Digital Journalism, Journalism, Journalism Practice, Journalism Studies. Lewis, S.C. has contributed the most number of papers in digital journalism. Further, authors from the countries the USA, Spain, Brazil and UK have contributed immensely. The citation network of authors, institutions and countries contributing to digital journalism studies has also been explored in the study. Through burst analysis, hot topics in digital journalism were identified.

The paper provides a complete overview of the growth of digital journalism literature published from 1987 to 2021. The originality of this work lies in the triangulation of Biblioshiny, VOSviewer and CiteSpace software to present various aspects of bibliometric study. Findings of the study can help the researchers to identify areas as well as journals, authors, institutions working actively in the field of digital journalism.

The advent of social media has led to the emergence of influencers and the domain of influencer marketing (IM). Despite being a popular and evolving research domain, it still lacks a comprehensive and systematic bibliometric analysis in the field. This study attempts to fill this critical gap by mapping the influence of IM to understand the intellectual structure and propose a future research agenda for scholars working in the domain.

The authors have used VOSviewer and Biblioshiny packages for conducting a variety of analyses such as citation analysis, bibliographic coupling, keyword analysis and three-field plot analysis.

The main findings include identifying six clusters in the domain, i.e. “mechanism of IM,” “measuring the impact of IM,” “persuasive cues in IM,” “likability factors of influencers,” “authenticity of influencers” and “understanding followers.” Future research guidelines have been proposed in each of the six clusters, followed by research and managerial implications, conclusion and limitations.

This study is probably the first attempt at providing a comprehensive bibliometric analysis in the domain using a combination of VOSviewer and Biblioshiny packages.