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This study seeks to investigate the ability of blockchain technology (BCT) to increase circular economy (CE) practices in the electronics industry, emphasising India and Taiwan.

The study adopts a mixed-methods approach. Initial qualitative semi-structured interviews examined how BCT could inform CE practice. The qualitative aspects were followed by the Analytical Hierarchy Process (AHP), integrating qualitative and quantitative approaches, and fuzzy-set Qualitative Comparative Analysis (fsQCA), to analyse data from 391 industry experts surveyed.

The results show that the BCT has great potential to promote CE processes by improving the aspects of security, transparency and traceability. BCT adoption is driven by a conducive regulatory regime, stakeholder collaboration, and the availability of required technology.

By identifying key drivers and requisite requirements for successful BCT adoption in CE practices, this research offers critical guidance for policymakers, practitioners and researchers. It adds to the wider conversation about how emerging technologies can support sustainability and efficiency in industry.

This study contributes to the literature by providing a new lens to study BCT and CE practices intersectionality, particularly in the context of the emerging electronics industry and in countries such as India and Taiwan. Unlike previous research that studied either BCT or CE independently, this study uniquely illustrates how the principles underpinning these concepts, when implemented together, can positively impact sustainability outcomes within a resource-intensive industry notorious for generating highly significant waste streams.

This paper aims to explore the capabilities of virtual reality (VR) and augmented reality (AR) in enhancing the tourism experience and addressing physical travel constraints.

A survey was conducted among 412 tourists who had used VR and AR technologies for tourism purposes. Data was analysed using descriptive statistics, multidimensional scaling, multiple regression analysis, structural equation modelling and mediation and moderation analysis.

VR and AR enhance tourism via immersive experiences. They overcome traditional travel barriers, but accessibility concerns, like cost, persist. The perceived potential of these technologies strongly predicts future adoption, emphasising the need to highlight their immersive benefits.

This study offers ground-breaking insights into VR and AR in tourism. It acknowledges inherent limitations in accessibility, with VR and AR technologies not being universally adoptable due to costs and complexity. Theoretically, the research enriches academic discourse by highlighting the pivotal role of perceived potential in technology adoption. It also delineates the intricate relationship between VR/AR experience, satisfaction, destination image and revisit intention.

The findings emphasise crafting immersive VR and AR experiences for differentiation. By integrating these technologies into strategic marketing, organisations can enhance customer satisfaction and provide richer destination experiences.

The research underscores VR and AR’s potential to foster inclusive tourism, benefitting those with limitations. Additionally, promoting cultural exchange and sustainability, these technologies can drive societal harmony and contribute to economic growth through enriched tourism experiences.

This study stands out in its distinctive exploration of VR and AR in the tourism domain. The innovation lies in its comprehensive examination of the technologies’ immersive capabilities and their accessibility challenges. The value is accentuated by its insights, which bridge the gap between technological potential and its practical application in tourism.

This study aims to assess the impact of personality traits, risk perception and perceived coronavirus disease 2019 (COVID-19) disruption on the investment behavior of individual investors in the Indian stock market.

This study adopts a survey approach. The sample comprises 315 active retail investors investing in the Indian stock exchange. Two-stage analysis technique regression and Artificial Neural Network (ANN) were used for data analysis. Study hypotheses were tested through regression and ANN was adopted to validate the regression results.

Two regression models were modeled to test the research hypotheses. Findings showed that risk perception and COVID-19 disruption have a significant positive and neuroticism has a significant negative impact on short-term investment decisions, while the role of conscientiousness in determining short-term investment decisions was not found significant. Results also showed a positive impact of neuroticism and conscientiousness and a negative impact of risk perception on long-term investment decisions. The role of COVID-19 disruption was found negative but insignificant in predicting long-term investment decisions.

This study has practical implications for many parties like retail investors, financial advisors and policymakers. This study will assist the investors to realize that they do not always take rational financial decisions. This study will suggest the financial advisors to use the knowledge of behavioral finance in making the advisors' advisory and wealth management decisions. This study will also assist the policymakers to outline behaviorally well-informed policy decisions to protect the interests of investors.

India is one of the fast-growing economies in the world. India has a vast population of active investors and determining investors' investment behavior adds novelty to this study as developed economies have remained the main focus of previous studies. The other novel feature of this study is that this study tries to assess the impact of COVID-19 disruption along with personality traits and risk perception on investment behavior. The other valuable factor of this study is the use of ANN to predict the relative importance of the exogenous variables.