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This systematic literature review used bibliometric and science mapping as a means of exploring and understanding the evolution and landscape of research in the counterfeiting of products and goods. The review sought to document the size, growth trajectory and geographic distribution of counterfeiting research, identify high-impact scholars and documents, and explore the intellectual structure of the field. We identified 403 peer-reviewed articles published in the SCOPUS database, within subject areas of business, social sciences, economics, decision-making, arts and humanities, and psychology. We used VOSviewer software to analyse the data set of SCOPUS-indexed articles. Using citation analysis, the review identified the most cited scholars, documents, journals and most productive countries publishing research on counterfeiting. Aiming to identify highly influential documents whose impact in counterfeiting research has been sustained over time, we conducted a co-citation analysis. Apart from identifying main aspects of knowledge production through citation and co-citation analysis, we employed keyword co-occurrence analysis to illuminate research fronts in counterfeiting research, notably: anti-counterfeiting strategies for combating crime; counterfeiting and intellectual property rights; counterfeiting of luxury products; consumer ethics; consumer psychology and brand protection. We conclude that bibliometric analysis and science mapping offer a novel and useful means of investigating the development of this field of study.

The proliferation of bibliometric review articles is a true reflection of how bibliometrics is gaining popularity and has been widely adopted in various disciplines. The growing interest of scholars has encouraged us to dwell upon the what, why, when, how, and where of bibliometric literature reviews. The study explained the bibliometric review with the standpoint that it can be considered a strong review method for analyzing a large volume of data and scholars can supplement their traditional reviews with bibliometric reviews to strengthen their knowledge. This will help researchers to justify the (a) need for a study on the particular topic; (b) type or method of review chosen; (c) number of articles selected; (d) inclusion and exclusion criterion; (e) method of analysis; and (f) presentation of the findings.

Artificial neural networks (ANNs), which represent computational models simulating the biological neural systems, have become a dominant paradigm for solving complex analytical problems. ANN applications have been employed in various disciplines such as psychology, computer science, mathematics, engineering, medicine, manufacturing, and business studies. Academic research on ANNs is witnessing considerable publication activity, and there exists a need to track the intellectual structure of the existing research for a better comprehension of the domain. The current study uses a bibliometric approach to ANN business literature extracted from the Web of Science database. The study also performs a chronological review using science mapping and examines the evolution trajectory to determine research areas relevant to future research. The authors suggest that researchers focus on ANN deep learning models as the bibliometric results predict an expeditious growth of the research topic in the upcoming years. The findings reveal that business research on ANNs is flourishing and suggest further work on domains, such as back-propagation neural networks, support vector machines, and predictive modeling. By providing a systematic and dynamic understanding of ANN business research, the current study enhances the readers' understanding of existing reviews and complements the domain knowledge.

The use of structured literature review methods like bibliometric analysis is growing in the management fields, but there is limited knowledge on how they can be facilitated by technology. Hence, we conducted a broad overview of software tools, their roles, and limitations in structured (bibliometric) literature reviewing activities. Subsequently, we show that several software tools are freely available to aid in searching the literature, identifying/ extracting relevant publications, screening/assessing quality of the extracted data, and performing analyses to generate insights from the literature. However, their applications may be confronted with several challenges such as limited analytical and functional capabilities, inadequate technological skills of researchers, and the fact that the researcher's insights are still needed to generate compelling conclusions from the results produced by software tools. Consequently, we contribute toward advancing the methodologies for performing structured reviews by providing a comprehensive and updated overview of the knowledge base of key technological software tools and the conduct of structured or bibliometric literature reviews.

Purpose: Since its inception in 1987, the literature on the VUCA that represents the volatile, uncertain, complex, and ambiguous nature of the business environment has progressively increased. This study systematically evaluates the vast literature on the VUCA world. Since review-based studies have been criticised as biased, this study uniquely amalgamates bibliometric analysis with content analysis, thereby taking a research triangulation discourse.

Need of the Study: This study was conducted to consolidate the literature about the VUCA environment and uncover the foundational and emerging themes for future research agendas.

Design/Methodology/Approach: This study conducts a performance analysis and science mapping of 193 carefully selected articles (using PRISMA) published in various sources during 2012–2023. Articles for the study were procured from the SCOPUS database. While performance analysis focused on analysing publication and citation evolution, thematic evolution, leading publications, country publication analysis, and most relevant authors and sources. On the other hand, science mapping revealed conceptual structures (keyword plus co-occurrence analysis and thematic maps) and intellectual structures (co-authorship analysis). VOSviewer and Biblioshiny (R-tool for comprehensive science mapping) were used for this study’s choice of application.

Findings: This chapter concludes with future research agendas using content analysis of the ‘scope for the future research’ section of selected publications and bibliographic coupling (to unearth emerging themes).

Practical Implications: The work presented in this chapter will help the researchers gain a structured conceptual, intellectual, and social understanding of the vast literature on the VUCA environment.

This chapter analyses the evolution of strategic corporate social responsibility (CSR). Despite extensive research on the strategic aspects of CSR, the absence of a well-defined theoretical concept has hindered the development of the field. The authors build on the four mechanisms that conceptually distinguish strategic CSR from CSR in general: enhancing firm reputation, increasing stakeholder reciprocation, mitigating firm risk, and strengthening innovation capacity. By using bibliometric methods, we analyze the main topics, references, and sources of papers, found in the Web of Science Core Collection database. The analysis of the strategic CSR field discusses main topics through three periods (1991–2009, 2010–2014, and 2015–2019). The findings help identify the mapping of conceptual space of the strategic CSR field and suggest grounds for continuing the debates on how to advance the micro-level perspectives on CSR.

Purpose: The study’s objective is to look at the link between money laundering and economic and financial performance, emphasising the effectiveness of the literature and possible later research directions using science mapping, which allows for scientific knowledge analysis.

Need for the Study: This study is related to a better understanding of the field’s historical evolution in terms of publications.

Methodology: This study used bibliometric approaches to analyse a sample of 660 studies from the Web of Science between 1994 and 2022, concentrating on keywords, author, paper, journal, and subject analysis. This study focused on performance analysis and scientific mapping of articles using the R package.

Findings: The empirical results indicated that the research field’s primary issues include corporate governance, fraud, machine learning, fraud detection, financial fraud, financial statement, corruption, earnings management, ethics, governance, financial reporting, bankruptcy, internal control, or performance. M. S. Beasly, D. B. Farber, E. M. Fich, R. Romano, and A. Shivdasani are the most well-known authors on the issue of money laundering and financial and economic performance. At the same time, the most typical journals are the Journal of Business Ethics, Journal of Money Laundering Control, Accounting Review, Journal of Financial Economics, and Journal of Corporate Finance.

Practical Implications: This study will act as a guide for researchers of various fields to evaluate the development of scientific publications in a particular theme over time, especially for those who are in the field of money laundering and financial performance.

This chapter applies science mapping analysis (SciMat) and literature review as research methods to examine literature about higher education institutions (HEIs) during the Covid-19 pandemic. User acceptance, satisfaction, and perception are identified as the most productive research themes in the sample of 561 Web of Science (WoS) indexed articles about HEIs during the pandemic. The literature review of the top themes reveals that user acceptance is influenced by the perceived usefulness of online learning and ease of using online tools. The level of satisfaction among students in online learning is relatively high and linked with the perceived benefits of online courses. Conditions influencing user acceptance and perceived satisfaction differ between students and lecturers. Technology-related themes appeared to be relatively under-researched as standalone themes, but technological aspects turned out to be important components of the most prolific research themes identified.

In recent decades, interconnections between countries have increased substantially worldwide as the process of integration and globalisation intensifies, with a positive impact in terms of economic development, but, also with a vulnerability to external shocks, such as the financial contagion phenomenon. The analysis of this research field becomes even more relevant in the context of a new major exogenous shock, but which, this time, has different specificities, being a sanitary crisis. Thus, the chapter aims to investigate the impact of crises on capital market volatility for the period of 1995–2021, using the bibliometric analysis highlighting the dynamics of the literature and potential future research directions through a science mapping that enables investigating scientific knowledge. In order to explore the development of the research field in terms of publications, author impact, affiliated institutions and countries, citation patterns, trending topics, relationship between keywords–authors–journals, abstracts’ analysis, authors and documents clustering by coupling, multiple correspondence analysis of major research themes, keyword analysis, co-citation analysis and authors, institutions and countries collaboration analysis have been applied. Hence, almost 500 publications from Web of Science database covering the period 1995–2021 have been extracted. The empirical findings emphasise the conceptual structure, with clusters focussing mainly on long-term receivables, market efficiency, volatility, dynamic conditional correlation (DCC)-GARCH models, asymmetric effects. According to the intellectual structure of the field, Lambertides N., Zopiatis A., McAleer M. or Savva C. S. are the most representative authors for the sub-area of volatility topic; whilst Balcerzak A. P., Pietrzak M. B., Zinecker M., Meluzin T. and Faldzinski M. are the reference names for the whole spectrum of DCC-GARCH models’ topic. Jayasekera R., Lundblad C., Choundhry T., Gupta R. and Demirer R. are the authors mostly associated with asymmetric effects’ topic, whilst Thorp S., Bouchaud J. P. and Dungey M. with the quantitative finance. The Journal of Banking & Finance, the Journal of International Money and Finance and the International Review of Financial Analysis as well as Economic Modelling, Research in International Business and Finance and the International Journal of Finance & Economics are the most prolific journals in the field of capital flow and financial crises. This chapter’s main contribution is to build a structure of knowledge for the impact of crises on capital market volatility, elaborate and classify empirical research into relevant dimensions that can be used as a reference for comprehensively developing research. Finally, the bibliometric analysis results may provide insight into future research prospects. Our conclusions offer some recommendations for market practitioners and policy-making.