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This paper aims to present a summary of the green consumer behaviour (GCB) research conducted during the 2001–2021 period using the bibliometric analysis and to carry out a thematic and content analysis on the three clusters which comprise 57 articles resulting from the co-citation analysis and identify the significant green purchasing factors.

The three-pronged methodology applied to this research analysis includes performance analysis of the literature using biblioshiny and R Studio; network mapping analysis using VOSviewer and Gephi; thematic analysis using word clouds generated with R Software and content analysis of each paper with the aid of within and between-study analyses.

Cluster one acted as a base for the theoretical foundations of GCB which aids in understanding the basic concepts of green marketing, its evolution and the methodologies, whereas cluster two determined the predictors of everyday green behaviour, which helps in gaining knowledge about the everyday sustainable activities the consumers indulge and the factors motivating to do so. Cluster three mainly focused on the psycho-socio demographic determinants of GCB, which assists in segmentation and predicting the purchase behaviour of the various consumer segments.

The significant variables and major gaps in each of the clusters were identified and authors have drawn the implications for future researchers and marketing managers.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

Given the growing interest in the topic of knowledge management (KM) in family firms (FFs) and the subsequent increasing number of papers published, this study aims to review the field to identify and analyze the main themes and trends.

This study applies bibliometric techniques to a sample of 146 papers published from 2007 to 2023 and their 8,126 unique cited references. Bibliometric coupling is performed on the sample papers to explore the current intellectual structure of the field of KM in FFs, whereas cocitations analysis is performed to investigate the different literature streams that served as roots for the development of such a field.

Bibliographic coupling reveals that sample papers can be grouped into four clusters, and, through papers content analysis, the author identifies their core themes as knowledge sharing, innovation, knowledge-based dynamic capabilities and intellectual capital. Cocitation analysis of the cited references revealed four main clusters that can be considered the literature streams that served as roots for the development of the field, i.e. knowledge-based view, socioemotional wealth, strategic management and social capital (as a theory and as a resource).

This study contributes to the literature on KM in FFs by extending prior systematic review efforts with bibliometric analyses and combining these results to highlight connections between the main research themes around which scholars have debated (i.e. the clusters identified through bibliometric coupling) and their theoretical foundations (i.e. the clusters identified through cocitation analysis). This study also has practical implications by synthesizing and informing managers about FFs’ advantages and weaknesses in the KM process.

The purpose of this study is to provide a comprehensive analysis on the economic relationship between trade openness and economic growth and to identify current developments, potential research area and future directions. The emphasis is on the identification of annual growth of publications, country-wise distribution, publication pattern, intellectual structure and cluster analysis of scientific production in this field.

This study used evaluative techniques, text mining approach and performance analysis to identify possible patterns and correlation and to measure the impact of authors/citations/scientific production. Further, this study used the bibliometric mapping to represent the structural features of scientific production. This study emphasized on identification of the research hotspots based on occurrence of indexed keywords, productive researchers and journals during 2000–2022. Further, cluster analysis is performed using VOS viewer to analyze the current dynamics and future direction of the association between trade openness and economic growth (Eck and Waltman, 2011). Also, co-citation analysis is used in this study to identify the relations among authors or journals or documents using citation data, whereas the bibliographic coupling/mapping is intended to analyze the citing documents. Similarly, co-word analysis is used to study the article keywords that are mainly used to assess the conceptual structure of a concerning subject.

Economic growth is a function of trade openness, and it is important to analyze the relationship between trade openness and economic growth. Trade openness tends to become more liberalized over time, to contribute more to economic growth. Empirical evidence suggested that there exists a strong association between trade openness and economic growth. Further, keyword timeline analysis illustrated that the linkage between trade openness and economic growth is current area of interest among researchers. As per bibliometric analysis, China, Pakistan and Malaysia are the three most prolific countries in the terms of published articles on this theme. However, the most influential publications based on h-index and citation on trade openness–economic growth relationship is produced by Turkey. Based on cluster analysis, this study suggests that researchers are currently working on trade openness–economic growth relationship with other variables such as FDI, financial development, labor force, environment degradation and carbon emission, while in future, researchers could work on variables such as technology and sustainable development.

There are some limitations of this study. The first limitation is the authors have used Scopus database, leaving the possibility for future research to use Web of Science, Google Scholar or other similar sources. The second limitation is that the authors have used search terms “trade openness “and “economic growth,” although research could be performed using synonyms or even relevant terms in other languages.

Cluster analysis suggested that researchers are currently working on trade openness–economic growth relationship with other variables such as FDI, financial development, labor force, environment degradation and carbon emission, while in future, researchers could work on variables such as technology and sustainable development. Therefore, this study identified the potential research area in this research domain.

To confirm the originality of this study, to the best of the authors’ knowledge, this is the first study to combine bibliometric analysis and cluster analysis on trade openness–economic growth relationship. This study makes a comparison with phenomena/processes/events in contemporary economic and social reality in the field of trade openness and economic growth relationship.

The primary goal of this review is to identify emerging themes in the cold supply chain (CSC) and their future research directions, methodologies, and theories.

The review looks at CSC related articles from Scopus database published in the years 2000–2020. Thereafter, bibliometric and co-citation analyses have been conducted to identify emerging themes, methodologies, and theoretical perspectives related to CSC management.

This study revealed a clear research gap in CSC literature with emerging themes relevant to diverse aspects. Primarily, the most prominent authors, methodologies, and theories were identified from bibliometric analysis. Next, we generated clusters to identify the insights of each cluster using co-citation analysis. Consequently, the significance of clusters concerning the number of articles, theoretical frameworks, methodologies, and themes was recognized. Finally, a few future research questions regarding emerging themes have been identified.

The importance of co-citation and bibliometric analyses in studying the evolution of research over a definite time is emphasized in this work. As per emerging themes, implementing digital technologies has increased the efficiency of traditional CSC and transformed it into digital CSC.

As per the authors' knowledge, this work is the first in literature to explore the significance of identifying emerging areas and future research directions in managing CSC through literature review based on bibliometric and co-citation analysis.

Nanosensors have a wide range of applications because of their high sensitivity, selectivity and specificity. In the past decade, extensive and pervasive research related to nanosensors has led to significant progress in diverse fields, such as biomedicine, environmental monitoring and industrial process control. This led to better and more efficient detection and monitoring of physical and chemical properties at better resolution, opening new horizons in the development of novel technologies and applications for improved human health, environment protection, enhanced industrial processes, etc.

In this paper, the authors discuss the application of citation network analysis in the field of nanosensor research and development. Cluster analysis was carried out using papers published in the field of nanomaterial-based sensor research, and an in-depth analysis was carried out to identify significant clusters. The purpose of this study is to provide researchers to identify a pathway to the emerging areas in the field of nanosensor research. The authors have illustrated the knowledge base, knowledge domain and knowledge progression of nanosensor research using the citation analysis based on 3,636 Science Citation Index papers published during the period 2011 to 2021.

Among these papers, the bibliographic study identified 809 significant research publications, 11 clusters, 556 research sector keywords, 1,296 main authors, 139 referenced authors, 63 nations, 206 organizations and 42 journals. The authors have identified single quantum dot (QD)-based nanosensor for biological applications, carbon dot-based nanosensors, self-powered triboelectric nanogenerator-based nanosensor and genetically encoded nanosensor as the significant research hotspots that came to the fore in recent years. The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

This is a novel bibliometric analysis in the area of “nanomaterial based sensor,” which is carried out in CiteSpace software.

Construction experts acknowledge the adverse effects of rework on project performance. However, the limited understanding of its underlying causes remains a significant challenge. Therefore, this study aimed to thoroughly investigate the sources of construction rework.

A mixed review using bibliometric analysis as a quantitative method and content analysis as a qualitative method was performed to understand the current knowledge in the field. The Web of Science (WoS) was selected for its comprehensive collection of major research articles and integrated analytical tools for generating representative data. The study involved an extensive bibliometric analysis of 107 journal articles on rework causes from 1991 to 2023. RStudio Bibliometrix, an R statistical programming package, was used to analyze rework origins. This method involved mapping the research landscape, identifying research gaps and analyzing emerging trends.

The causes of rework can be classified into three main clusters: human- and contractual-based rework causes, design-, quality- and project management-based rework causes and organizational-based rework causes.

Although several studies have addressed rework causes from various perspectives and methods, the topic has not been investigated holistically. This study is the first to leverage the quantitative and qualitative analytical capabilities of the RStudio Bibliometrix package. Innovative approaches, including the use of metrics, such as the h-index, thematic mapping and trend topic analysis, were employed for a comprehensive understanding of rework causes.

The purpose of this paper is to examine the evolution of the literature on technology transfer and culture, identifying the main contents of the current body of knowledge encompassing culture and technology transfer (TT), thus contributing to a better understanding of the relationship between TT and culture based on bibliometric and multivariate statistical analyses of the relevant body of literature.

Data for this study were collected from the Web of Science (WoS) Core Collection database. Based on a bibliometric analysis and in-depth empirical review of major TT subjects, supported by multivariate statistical analyses, over 200 articles were systematically reviewed. The use of these methods decreases biases since it adds rigor to the subjective evaluation of the relevant literature base.

The exploratory analysis of the articles shows that first, culture is an important topic for TT in the literature; second, the publication data demonstrate a great dynamism regarding the different contexts in which culture is covered in the TT literature and third, in the last couple of years the interest of stimulating a TT culture in the context of universities has continuously grown.

This study focuses on culture in the context of TT and identifies the main contents of the body of knowledge in the area. Based on this first insight, obtained through more detailed bibliometric and multivariate analyses, it is now important to develop and validate a theory on TT culture, emphasizing the dimensions of organizational culture, entrepreneurial culture and a culture of openness that fosters economic and societal spillovers, and to link those dimensions to the performance of TT activities.

From the practical point of view, managers in companies and universities should be aware of the importance of identifying those dimensions of culture that contribute most to the success of their TT activities.

Despite several literature reviews on the TT topic, no studies focusing specifically on culture in the context of TT have been developed. Therefore, given the multifaceted nature of the research field, this study aims to expand and to deepen the analysis of the TT literature by focusing on culture as an important and commonly cited element influencing TT performance.

Purpose: As a result of the transition from the paradigm of ‘knowledge and skills’ learning to the university of uncertainty, the concept of VUCA has grown for the revision of various adaptive models of educational practices.

Need for Study: The primary goal is to explore the research field of the educational system and learning environments; the investigation of scientific knowledge is enabled by bibliometric analysis, revealing through it the fluctuations of the literature.

Methodology: To better view the historical evolution of publications in the educational system field, two data samples were integrated into this study, with the focus of the chapter being on the authors, keywords, articles, journals, subject analysis, word cloud analysis, and cluster analysis. The first includes 1,620 Web of Science-recorded documents published between 1991 and 2022, and the second sample comprises 159 Scopus-recorded papers published between 1978 and 2022.

Findings: The first empirical results show that interest in this subject escalated around 2008. The main concerns around this research field are the labour market, teaching-learning, technology, economic development, the medical field, and sustainability. After 2020, a new subject took amplitude, seemingly connected to the educational system and learning environment, that subject being ’COVID-19.

Practical Implications: The relationship between authors, keywords, and sources is illustrated through Sankey diagrams, from which valuable information can be extracted: nine of the Scopus authors have published articles in the ‘Journal of Higher Education Policy and Management’ documents that present the following list of keywords: ‘higher education’, ‘education’, ‘management’, ‘leadership’, and ‘tertiary education’.

The environmental characteristics of international football can vary significantly from one country to another. As a result, the economic and market possibilities and the objectives of each national league are very heterogeneous. This article aims to examine the differences in revenue structures amongst European national football leagues (n = 50) and cluster them based on these structures. It also investigates which revenue structure would be more effective for similar leagues, considering the previously mentioned varying environmental characteristics of international football.

The study utilises a theoretical framework of business modelling, applied in a unique way to league organisers of national championships. Data on sports and business aspects were collected from sources such as the Union of European Football Associations (UEFA) Financial Benchmarking Reports, transfermarkt.de and related sources for the period 2015 to 2018. K-means cluster analysis, using the Euclidean distance approach, was employed to develop clusters based on revenue sources over a four-year average.

The paper presents the characteristics and year-to-year changes of nine developed clusters. Throughout the analysis, variables such as average overpayment and inequality between player values amongst leagues were prioritised. The study's practical implications can assist league organisers in enhancing the competitiveness of their leagues, supported by short case studies that provide illustrative examples.

The novelty of the current article lies in introducing innovative variables such as the variance of player value whilst focussing on meso-level analysis, providing a fresh contribution to the existing literature in the field for understanding revenue structures and performance in European national football leagues.