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This study aims to model tourist activities in a network and explore the properties of the network. Such network enables the author to explain and quantify how tourist activities are connected in determining tourist consumption as well as the organization of destination supply.

The author developed a network formation mechanism to create edges between nodes based on the joint probability of a pair of activities undertaken by tourists at a destination. By adjusting network sparsity, the author created an ensemble of four topologically similar networks for empirical testing. The author used tourist activity data of Hong Kong inbound tourists to test the network model.

The author found a robust hub–periphery topological structure of the tourist activity network. In addition, the network is featured by high clustering, short diameter and positive correlations between four node centralities, namely, degree, closeness, betweenness and eigenvector centralities. The author also generated the k-cores of the networks to further unravel the structure of hub nodes. The author found that the k-cores are dominated by tourist activities related to shopping or sightseeing, suggesting the high complementarity of these activities.

This study provides a different lens through which tourist consumption can be understood from a macroscopic angle by examining network topology and from a microscopic angle by examining node centralities.

To the best of the author’s knowledge, this is the first study attempting to model tourist activity and consumption in a network and explore the properties of the network. Not only has this study provided a new real-world network for network research, but it has also suggested an innovative modeling approach for tourist behavior research.

Over the years, the impact of personality attributes on work behavior has constituted a broad research domain. The manner in which employees view themselves have been regarded as significant in analyzing their work behavior and eventual employee performance from the organizational perspective. The purpose of this paper is to investigate the relationship between self-concept and performance, with resilience as a mediator and Machiavellianism as a moderating variable.

Data were collected from 271 employees from four medium-sized private sector companies in India after excluding missing data. Correlation, regression and Hayes Macro analysis were conducted to test the hypotheses.

Resilience mediates the relationship between self-concept and performance. Second, Machiavellianism moderated the relationship between self-concept and resilience and moderated the mediation effect of resilience on the relationship between self-concept and performance. The role of personality attributes has been found to profoundly impact the employee's perception of self and work performance. Resilience, which refers to the individual's ability to bounce back amidst adverse situations, is simultaneously moderated by one of the dark triad personalities, Machiavellianism.

Understanding the self-concept dimension, the dual effects of resilience and the Machiavellianism personality have gradually become immensely significant for improvising employee work performance in the organization.

This original research has examined a model of untested variables and explored the mediating effect of resilience by connecting self-concept to performance along with the moderated-mediated impact of Machiavellianism on the variables, which is a novel attempt.

The study's objectives are to conduct a comprehensive review of existing knowledge, thoroughly understand the present state of green finance, identify emerging research trends, perform content analysis and offer valuable guidance for advancing this field.

Data has been collected by selecting highly indexed databases, Scopus and Web of Science. These databases are well-known repositories of academic papers, journals and other scholarly publications related to various fields of study. This research uses the PRISMA methodology for conducting a structured literature review and employs a bibliometric approach to summarize the findings of the previous studies. “R” studio and Biblioshiny are used to clean the data and visualize the results. The TCCM framework is utilized to propose potential avenues for future research in the domain of green finance.

The research uncovers the potential areas in the domain of green finance for future work, encompassing green bonds, the green economy, connectivity, forces, constraints and sustainable development. Furthermore, this process enhances the theoretical underpinnings of scholarly investigations within the discipline by succinctly synthesizing and evaluating preexisting literature. This contribution could facilitate more informed and focused research endeavors in green finance.

The research findings have practical implications for researchers, practitioners, regulators, legislators, issuers and investors involved in green finance. The results can take initiatives to improve practices related to issuing and pricing green financial products and enhance the understanding of interconnectedness within the field.

This ground-breaking research sheds light on various emerging areas by taking a new approach, including the most widely read articles, authors and journals and the broader conceptual and intellectual framework. That includes finding and expanding original research streams, summarizing the most seminal works, and suggesting new research pathways.

In recent years, technological advancement has played a crucial role in the growth of emerging economies. However, as with any novel technological development, there are often concerns and hesitations surrounding its implementation. This study aims to investigate the factors influencing blockchain adoption and usage. Thereby evaluating its impact on supply chain performance.

This is a deductive research based on the modified form unified theory of acceptance and use of technology, which is a persuasive model that has been used in numerous studies on the acceptance and usage of information technology systems. For this study, valid data was collected from 129 management-level supply chain professionals and policymakers working in diverse manufacturing industries. The collected data was used for testing hypotheses by deploying the structural equation modeling technique.

The findings of this study reveal that facilitating conditions and technology readiness highly are key influencers for organizations to implement this disruptive technology. Moreover, blockchain adoption and usage can significantly enhance supply chain performance.

Blockchain technology is a novel and promising disruptive technology that industries are looking forward to adopting and using. For the policymakers and supply chain strategists working in a developing country, this study offers a comprehensive viewpoint on the swift acceptance and usage of blockchain technology to facilitate supply chain operations.