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This research aims to update the literature about the importance of reliability in supply chain (SC) and to find out the SC determinants.

This research surveys while contributing to the academic grasp of supply chain reliability (SCR) concepts. The study found 45 peer-reviewed publications using a structured survey technique with a four-step filtering process. The filtering process includes data reduction processes such as an evaluation of abstract and conclusion. The filtered study focuses on SCR and its determinants.

One of the major findings is that most of the study has focused on mathematical and conceptual studies. Also, this study provides the answer to a question like how can reliability be better accepted and evolved within the SC after finding the determinants of SCR.

The observed methodological gap in understanding and development of SCR was identified and classified into three categories: mathematical, conceptual and empirical studies (case studies and survey’s mainly). This research will aid academics in developing and understanding the determinants of SCR.

Sustainable tourism plays a crucial role in fostering community development, particularly in regions where indigenous tribal communities are economically disadvantaged despite their rich cultural heritage. India is home to diverse tribal populations with distinct traditions. This chapter explores the potential of sustainable tourism to drive community development in India's tribal regions. The key objectives include understanding the cultural significance of these communities as tourism assets, assessing the economic empowerment potential of sustainable tourism, evaluating environmental sustainability, exploring social inclusivity and scrutinising the role of policy and governance.

Disruptive technologies are transforming the insurance market, affecting individuals' and organizations' behavior and adaptability. Effective data utilization has become critical to success in the dynamic insurance sector.

The current research utilized electronic Scopus databases to include all pertinent prior studies. Employing cutting-edge technology, highlighting benefits, resolving challenges, identifying emerging trends, and identifying new practices, the study chapter explores how data practices alter the insurance industry.

The emergence of novel technologies, namely the Internet of Things, mobile devices, blockchains, cryptocurrencies, cloud computing, artificial intelligence, machine learning, and cognitive systems, alter the competitive environment on multiple fronts and at different stages. Insurance companies gain essential insights to enhance their decision-making procedures by addressing data accuracy, integration, and regulatory compliance.

The overview highlights new developments that are radically changing the evolving domain of the insurance business, including augmented analytics, blockchain, predictive analytics, telematics, and ethical AI. This technology is being used so insurers can improve client happiness, handle risks more effectively, and stay competitive. The insurance industry achieves increased efficiency, stimulates innovation, and strategically uses data to strengthen resilience in today's data-centric economy.

This study aimed to identify factors influencing AI/chatbot usage in education and research, and to evaluate the extent of the impact of these factors.

This study used a mixed approach of qualitative and quantitative methods. It is based on both primary and secondary data. The primary data were collected through an online survey. In total, 177 responses from teachers were included in this study. The collected data were analyzed using a statistical package for the social sciences.

The study revealed that the significant factors influencing the perception of the academic and research community toward the adoption of AI/interactive tools, such as Chatbots/ChatGpt for education and research, are challenges, benefits, awareness, opportunities, risks, sustainability and ethical considerations.

This study highlighted the importance of resolving challenges and enhancing awareness and benefits while carefully mitigating risks and ethical concerns in the integration of technology within the educational and research environment. These insights can assist policymakers in making decisions and developing strategies for the efficient adoption of AI/interactive tools in academia and research to enhance the overall quality of learning experiences.

The present study adds value to the existing literature on AI/interactive tool adoption in academia and research by offering a quantitative analysis of the factors impacting teachers' perception of the usage of such tools. Furthermore, it also indirectly helps achieve various UNSDGs, such as 4, 9, 10 and 17.

This study aims to systematically review the literature on digital consumers’ decision-making in the banking, financial services and insurance (BFSI) sector and proposes an integrative framework.

By combining databases such as Web of Science and Elton B. Stephens Company (EBSCO), we identified, analyzed and synthesized 53 peer-reviewed empirical articles that explore the connection between digital solutions in the BFSI sector and various phases and constructs of the consumer decision-making process. We examined the dependent variables (DVs) used to operationalize consumer decision-making, performed a thematic analysis of the papers and proposed an integrative framework.

The reviewed articles have garnered more attention from marketing researchers than from BFSI or artificial intelligence scholars, often employing traditional behavioral and experimental methodologies that have several limitations. We identified 38 DVs used to operationalize consumer decision-making, with the most frequently recurring constructs being “Intention to use,” “Utilization,” “Satisfaction,” “Perceived usefulness” and “Trust.” We propose an integrative framework that groups these DVs into three main clusters: subjects’ perceptions, user experience and adoption/usage choice. This systematic literature review highlights the increasing importance of emotion in recent decades and underscores the difficulty of establishing a framework where relationships between variables are direct and unidirectional, as traditional economic theories assume.

To the best of the authors’ knowledge, this is the first study to provide a comprehensive and systematic understanding of the DVs and the research methods used to study the impact of recent digital solutions on consumer decision-making in the BFSI sector. Further, a framework is proposed that can offer a new perspective for consumer research.

The authors aim to study a conceptual model based on behavioural theories (UTAUT-3 model) to evaluate the adoption, usage and recommendation for neobanking services in India.

The authors propose this model based on the UTAUT-3 integrated with perceived risk constructs. Hypotheses were developed to determine the relationships and empirically validated using the PLSs-SEM method. Using the survey method, 680 Delhi NCR respondents participated in the survey.

Empirical results suggested that behavioural intention (BI) to usage, adoption and recommendation affects neobanking adoption positively. The research observed that performance expectancy (PE), effort expectancy (EE), perceived privacy risk (PYR) and perceived performance risk (PPR) are the essential constructs influencing the adoption of neobanking services.

Limited by geographic and Covid-19 constraints, a cross-sectional study was conducted. It highlights the BI of neobanking users tested using the UTAUT-3 model during the Covid-19 period.

The study's outcome offers valuable insights into Indian Neobanking services that researchers have not studied earlier. These insights will help bank managers, risk professionals, IT Developers, regulators, financial intermediaries and Fintech companies planning to invest or develop similar neobanking services. Additionally, this research provides significant insight into how perceived risk determinants may impact adoption independently for the neobanking service.

The objective of this study is to examine the various factors that exert an influence on the green economy. This study also investigates the impact of foreign direct investment (FDI) on the Malaysian economy, specifically focusing on its position as a mediator. This research also examines the correlation between FDI and its influence on the contemporary green economy.

The authors employed quantitative methodologies and a self-administered survey to evaluate data and derive a definitive conclusion. The result was constructed using SPSS and SEM-PLS as the analytical software.

The study reveals that technological advancement, investment country and government policy significantly and positively affect the green economy, catalyse SDG goals and restructure the economy in better shape.

The current empirical research bridges the research gap in the context of technology advancement in government policy from emerging economies by exploring important factors, proposing their impact on the performance of the green economy, and empirically testing those hypothesized relationships. This study deciphers that FDI influences the green economy, where the investment country plays a significant role. Also, for a graphical presentation of this abstract, see the online appendix.

Previous research has found that family characteristics, including family income, entrepreneurship/business experience and family size, can influence offspring’s entrepreneurial potential and perception of the barriers to entrepreneurship. This paper aims to extend this proposition to women in Oman to determine whether family income, entrepreneurship/business experience and family size influence women’s perception of barriers to entrepreneurship

This study is based on primary data that was collected through a structured questionnaire from 123 female respondents at an Omani private university. The data was analysed using PCA, correlation and regression analysis to determine the influence of the family characteristic on the perception of barriers to entrepreneurship.

The findings concluded that the three family characteristics being tested were not able to predict a change in the perception of barriers to entrepreneurship. This contradicts previous research conducted in Western contexts and highlights the potential weakness in family support for female entrepreneurship in Oman.

These results challenge some of the extant findings in the literature, thus enriching the current perspectives on female entrepreneurship and the impact of Omani family characteristics, in terms of income, economic background and family size, on the perception of barriers that hinder entrepreneurship among female students