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The emergence of virtual reality (VR) has the potential to revolutionize various industries, including tourism, as it delivers a simulated environment that closely emulates real-life experiences. Therefore, this study aims to explore how the factors, i.e. enjoyment, emotional involvement, flow state, perceived privacy risk, physical risk and cost, influence the customers’ intention to use VR for tourism.

This study integrates the technology acceptance model, hedonic consumption theory with other factors, including cognitive response, authenticity, perceived privacy risk, perceived physical risk, perceived cost and perceived presence. Partial least squares structural equation modelling approach was used to test the proposed research model.

The finding based on the sample of 252 respondents revealed that authenticity is the most influential factor impacting behavior intention followed by perceived cost, attitude, cognitive response and enjoyment. Also, the study supported the moderating impact of personal innovativeness between attitude and behavioral intention to use VR for tourism.

The findings of the study offers practical implications for service providers, site managers, destination marketers, tourist organizations and policymaker to develop more effective strategies for offering VR services for tourism.

This study enriches the current understanding of VR adoption in context of tourism with empirical evidences.

This study aims to explore and conceptualize metaverse adoption using a systematic literature review (SLR). It also aims to propose a conceptual model that identifies significant factors affecting metaverse adoption in the entertainment, education, tourism and health sectors.

A SLR was conducted using the “preferred reporting items for systematic reviews and meta-analyses” report protocol and the “theory, context, characteristics, methods” framework to include all relevant articles published up to March 2023, which were sourced from the Scopus and Web of Science databases.

The reviewed literature revealed that the countries with the highest publications in the field of metaverse were China and the USA. It was also found that the technology acceptance model was the most used theoretical framework. Survey-based research using purposive and convenience sampling techniques emerged as the predominant method for data collection, and partial least square-structural equation modeling was the most used analytical technique. The review also identified the top six journals and the variables that help to develop a proposed model.

This review presents a novel contribution to the literature on metaverse adoption by forming a conceptual model that incorporates the most used variables in the entertainment, education, tourism and health sectors. The possible directions for future research with identified research gaps were also discussed.

Cryptocurrency has emerged as a significant component on the surface of the financial industry. With its growing popularity and blockchain as an underlying technology, cryptocurrency has the potential to disrupt the digital payments market. In light of this, this study aims to identify and empirically validate factors that influence the continuous intention of customers toward the adoption of cryptocurrency.

The study extends consumption value theory by incorporating additional variables – monetary value, perceived trust and perceived risk – to enhance the predictive power of the proposed model. The data were analyzed using the partial least square technique on the sample of 285 customers.

The results indicate that trust is the most significant factor to influence customers’ intention to use cryptocurrency, followed by conditional value, epistemic value, emotional value and monetary value. The authors also found the significant moderating effect of personal innovativeness on behavioral intention and actual usage of cryptocurrency.

The analysis of the study gives policymakers valuable information for the establishment of the regulatory framework that supports innovation while protecting the rights of the consumer.

The study embeds great theoretical and practical significance by generating a new technical thread that will facilitate multiple players to use their resources optimally.

Blockchain technology is spreading its roots and growing rapidly. With the advancement of blockchain technology, government organizations are focusing toward adopting blockchain technology. The purpose of this study is to identify the factors that affect the adoption of blockchain technology and provide a conceptual framework to adopt blockchain technology in government organizations.

To answer the research questions, this study has used systematic literature review (SLR). For achieving the quality and transparent process, this study has applied the PRISMA framework in the SLR.

With the help of SLR, this study has identified 72 factors that influence the adoption of blockchain technology. After critically examining the factors, this study has developed the conceptual framework for the adoption of blockchain technology in government organizations with four factors of the unified theory of acceptance and use of technology model and four additional factors, i.e. facilitating conditions, social influence, effort expectancy, performance expectancy, trust, transparency, cost and security.

To perform SLR, this study has used two databases: Web of Science and Google Scholar; future studies can consider other databases. This study has provided the framework but not validated it; future studies can use structural equation modeling and artificial neural network to validate the framework.

This study helps to provide insights about blockchain technology and help government and policymakers to take decisions for the adoption of blockchain technology and in determining the future action plan.

Few studies are available in the literature that have used SLR to identify blockchain technology adoption in government organizations.

Government is the biggest spender on cloud computing technology but a very limited study and data sets are available to assess the cloud adoption trends in government organizations in India. As India is ushering towards “Digital India” it becomes essential for the government to embrace the cloud to enhance governance and meet the citizen expectations. This paper aims to discuss the evolution of cloud computing (Meghraj) in government organizations by examining the various information technology (IT) and cloud policies, thereby focusing on the policy gaps. The second part of this study assesses the cloud adoption trend by analyzing adopted cloud services, deployments models, leading sectors in cloud adoption and cloud approach. Eventually, in consultation with experts, a conceptual framework for cloud adoption in the government organizations of India is developed for wider cloud adoption.

The authors reviewed various IT/cloud policies and related literature to find the policy gaps for slow cloud adoption in government organizations. Authors have researched to collect the data from the various government procurement portals and analysed the tender and contracts of 500 organizations for cloud requirements to infer the cloud adoption trends. Based on the review of policy gaps, adoption trends and by consulting the experts a conceptual cloud adoption framework has been developed for wider cloud adoption in government organizations.

This study can be a pathfinder where the most innovative findings are about the cloud adoption trends in the government organizations in the time frame from 2013 till 2020. Several key findings are – the public cloud are the most widely adopted, infrastructure as a service model is the most used services, the majority of the applications migrating to the cloud are legacy applications, the leading sector in cloud adoption are – IT, transport and education. It is observed that the pandemic Covid-19 has acted as a catalyst and accelerated cloud adoption in government organizations. Eventually, a conceptual cloud adoption framework has been suggested addressing the policy gaps, deficiencies, overcoming the gaps and their related outcomes for the wider cloud adoption in the government organizations.

The findings of this work highlight the cloud adoption trends in government organizations which can prove vital to the policymakers. This work will assist policymakers, government organizations, researchers, IT professionals and others interested in analyzing the state of cloud adoption. The conceptual cloud adoption framework developed endeavours to uncover the policy gaps, suggest the gap resolution mechanism and outcomes which may assist the organization for wider cloud adoption. This research work effectively connects the policies to practice by stimulating the interest in understanding the policies, strategies and thereby creating the enabling environment for cloud adoption. This study provides feedback on cloud adoption trends which can assist in policy refinement and further strengthen policy/strategies.

As of date, there is limited data available for cloud adoption in government organizations. This work uniquely presents the cloud projections which helps to gain insights on cloud adoption trends in government organizations. This study is the first of its kind, focusing on cloud adoption in the unexplored government sector. This study provides a comprehensive summary of adoption statistics, policy analysis and practice in government organizations of India.

The purpose of this paper is to examine the impact of Organisational Culture (OC) on total quality management (TQM) implementation in Indian small and medium enterprises (SMEs) in the auto component sector. Specifically; it attempts to propose a model linking OC and TQM for this sector.

Survey method was used for data collection by targeting the whole population of 482 Indian auto component SMEs drawn from Auto Component Manufacturers Association members’ database. Out of 482, 150 completely filled questionnaires were taken for data analysis. Proposed relationships among identified dimensions of OC and TQM interventions have been validated through parameter estimation statistics and goodness-of-fit statistics using path analysis technique of structural equation modelling using AMOS 18.0.

Based on the results, a culture influenced TQM model has been developed. The model demonstrates a linkage between cultural dimensions and TQM interventions, thereby suggesting that OC characterised by “openness”, “confrontation”, “trust”, “authenticity”, “proaction”, “autonomy”, “collaboration” and “experimentation” has a significant and positive impact on TQM implementation.

The study presents many practical implications, specifically for quality managers in Indian auto component SMEs. The study has developed a culture influenced TQM model which identifies dimensions of OC that promote TQM implementation. The study also identifies various interventions of TQM in their order of significance, which can be used by SMEs in mapping the critical links between OC and TQM through this model. Thus, findings of the present study will help SMEs in this sector to move up the value chain and sustain their global competitiveness.

The study provides a culture influenced TQM model which would assist managers in quality implementation in Indian auto component SMEs.

The case provides an opportunity to the students to learn some of the analytical processes in making a credit decision, including interpretation of financial ratios for credit analysis, forecasting a stress scenario, analysing cash flow adequacy, assessment of financial flexibility and, finally, recommend a credit decision.

The case discusses the analytical challenges facing a bank credit officer while assessing the credit quality of Kwality Ltd., an India-based dairy product manufacturer. Kwality Ltd. had undertaken a significant capacity expansion and business transformation to strengthen its market position in value-added dairy products business and improve its profit margins. The capacity expansion had recently been completed and the management, credit rating agency, equity analysts and investors appear to be optimistic regarding the company’s prospects. However, the capital investment had been almost entirely debt-funded and large long-term debt repayments would have become due shortly. The company had also built up large trade receivables. The banker had to assess if Kwality would be in a position to repay its debt and should his bank increase working capital disbursement to the company.

Complexity: Academic level. Applicability: MBA, Executive MBA.

Teaching Notes are available for educators only.

CSS1: Accounting and Finance.

Research in the domain of behavioral finance has proven that investors demonstrate irrational behavior while making investment decisions. In a similar domain, the primary objective of this research is to prioritize the behavioral biases that influence cryptocurrency investors' investment decisions in the Indian context.

A fuzzy analytic hierarchy process (F-AHP) was used to prioritize the behavioral factors impacting cryptocurrency investors' investment decisions. Overconfidence and optimism, anchoring, representativeness, information availability, herding, regret aversion, and loss aversion are among the primary biases evaluated in the present study.

The findings suggested that the two most important influential criteria were herding and regret aversion, with loss aversion and information availability being the least influential criteria. Opinions of family, friends, and colleagues about investment in cryptocurrency, the sale of cryptocurrencies that have increased in value, the avoidance of selling currencies that have decreased in value, the agony of holding losing cryptocurrencies for too long rather than selling winning cryptocurrencies too soon, and the purchase of cryptocurrencies that have fallen significantly from their all-time high are the most important sub-criteria.

This survey only covered active cryptocurrency participants. Additionally, the study was limited to individual crypto investors in one country, India, with a sample size of 467 participants. Although the sample size is appropriate, a larger sample size might reflect the more realistic scenario of the Indian crypto market.

The study is relevant to individual and institutional cryptocurrency investors, crypto portfolio managers, policymakers, researchers, market regulators, and society at large.

To the best of the authors' knowledge, no prior research has attempted to explain how the overall importance of various criteria and sub-criteria related to behavioral factors that influence the decision-making process of crypto retail investors can be assessed and how the priority of focus can be established, particularly in the Indian context.