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The COVID-19 pandemic forced us not only to think but also to pause and objectively reflect on how to deal with the situation that has arisen and how to develop well-being and resilience strategies for the welfare of humanity at large. We long to be in those vicinities where we want to calm our minds in the quest for a deeper meaning of one existence. It can be a nature-based destination, a pilgrim destination or a part of a religious tour depending on one's faith, belief and orientation towards spirituality and bliss. The abundance of natural resources available in nature is the prime source of overall wellness in all parts of the world, as are the traditional Indian practices of Yoga, Ayurveda and the practices suggested by traditional holy scriptures. This chapter attempts to see the wave of spiritual gurus boosting the wellness sector associated with travelling. Gurus like Sri Sri Ravi Shankar, Sadguru Vasudev Jaggi and HH Dalai Lama are some of the international gurus who have influenced spiritual and wellness tourism to a large extent. The discourse analysis revealed that people long for spirituality for peace and wellness. It also reveals being spiritual has no fixed dimension; it varies from person to person.

Purpose. This chapter discusses the challenges and different strategies to increase skill development for the future workforce.

Methodology. Multiple sources on the topic were studied and reviewed in this chapter. The idea of skill and its development is discussed in the literature review.

Findings. Different nations’ governments have promoted human capital development by providing up-skilling and retraining programs to balance supply and demand. Skills gaps need to be brought to the attention of stakeholders, such as governments, businesses, and the educational system. Teachers, employers, and other stakeholders need to develop strategies and action plans to ensure that the skills gaps are appropriately identified and adequately addressed. These initiatives must be developed with input from various stakeholders.

Practical Implications. The research results would inform the curriculum, incorporating skill development processes tailored to various scenarios. These findings would aid business organisations in crafting skill development programs that address identified skill gaps. Challenges in skill development would be taken into account during course development, and relevant teaching–learning materials would be created. Key stakeholders, such as accrediting organisations, employers, and students, should exert more influence on academic institutions to prioritise societal demands for economic development.

Originality/Value. The uniqueness and significance of this chapter lie in its concise summary of the strategies to tackle the hurdles in skill development.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

Introduction: Historically, the corporate governance (CG) framework was designed primarily to safeguard the economic interests of shareholders, as a result of political and legal interventions, developing into an effective instrument for stakeholders and society in general.

Purpose: The core objectives of the study include: identifying journals/publications responsible for publishing CG studies in India, key CG issues covered by CG researchers, the amount of high-impact CG literature across different time periods, sectors/industries covered by CG researchers and different research instruments (quantitative or qualitative) used in CG studies in India.

Design/methodology: The chapter used a sample of 130 corporate governance studies that fulfil the selection criteria, drawn from the repository of over 100 reputed journals that are either recognised by the Australian Business Deans Council (ABDC) or indexed by SCOPUS. A systematic literature review has been carried out pertaining to CG issues in India, based on various statistical tools, data, industries, research outlets & citations, etc.

Findings: The results show an overwhelming number of studies have assessed the relationship between CG variables and firm performance, which could be measured through a variety of performance metrics such as ROA and ROI. Apart from empirical analysis, many conceptual studies use repetitive basic statistical tools like descriptive statistics or regression analysis. The chapter offers insights into current achievements and future development.

Originality/value: This bibliometric study is a useful guide for policymakers, corporate leaders, research organisations and management faculty to draw insights from work produced by eminent researchers in GC in India.

This chapter proposes a model for discovering suspicious financial operations such as money laundering. To achieve this, the authors reviewed research papers on money laundering and financial institutions’ cases and problems, especially those related to financial transfers. They also collected primary data through face-to-face semi-structured interviews with financial companies’ owners and experts in financial transfers to identify hypotheses that help discover suspicious transfers. The chapter discusses the six big data analysis cycle phases from problem discovery to model deployment to identify suspicious transfers. The chapter uses hypothetical data and models to discuss the results and focuses on exchange companies willing to analyze financial operations. The chapter proposes tools that exchange companies can use to monitor and prevent suspicious transfers including data visualization and machine learning algorithms.

The origins of corporate social responsibility (CSR) have been widely attributed to the work of scholars, and business managers as well, in North America and Western Europe. Inevitably, however, as the economic interaction of individual firms and entire nations has grown over the past several decades — call it globalization — so too has the concept and the practice of CSR spread throughout the world. It is certainly time to explore how CSR is being incorporated into the practice of business management in other regions and other countries. Therefore, in this chapter we will focus on Asia: specifically on Japan, South Korea, India, and China. It is interesting for academicians to understand how CSR is being absorbed and adapted into the business cultures of these four countries. Perhaps of even greater importance, it is vital that business managers know what to expect about the interaction between business and society as well as the government as their commercial activities grow in this burgeoning part of the world.

For each of these four countries, we will provide an overview of the extent to which CSR has become a part of the academic community and also how it is being practiced and incorporated in everyday management affairs. We will see that there are very significant differences among these countries which lead to the natural question: why? To answer this question, we will use an eight-part analytical framework developed specifically for this purpose. We will look at the history, the dominant religious beliefs, the relevant social customs, the geography, the political structures, the level of economic development, civil society institutions, and the “safety net” of each country. As a result of this analysis, we believe, academicians can learn how CSR is absorbed and spread into commercial affairs, and managers can profit from learning more about what to expect when doing business in this increasingly important region.

This chapter aims to assess the scope of India's gastronomic tourism post-COVID-19 and discuss the utilisation of vlogs to promote India as a gastronomic destination. First, the evolution of gastronomic tourism is reviewed. Next, opportunities and challenges associated with India's gastronomic offerings, both from international and domestic tourism perspectives, are discussed. Then, the role of vlogging to position and promote India as a gastronomic destination is established. The chapter suggests recommendations for the Ministry of Tourism, Government of India on utilising vlogging to promote gastronomic tourism.

Introduction: New ideas and concepts of big data have emerged in recent years in response to the astounding growth of data in many industries. Furthermore, the phenomenal increase in the use of the internet and social media has added enormous amounts of data to conventional data processing systems. Still, it has also created challenges for traditional data processing.

Purpose: A significant characteristic of the insurance sector is critically dependent on information. This sector generates a great deal of structured and unstructured data, which traditional data processing techniques cannot handle. As compared to conventional insurance data processing and decision-making requirements, this lesson shows an analysis of data technology’s value additions.

Research methodology: The author assesses the primary use of cases for data in the insurance industry via a case study analysis. From the perspective of the insurance sector, this chapter examines the concepts, technologies, and tools of big data. A few analytical reviews by the insurance company are also provided, which justified several gains gained either through inefficient processing of massive, diverse data sets or by supporting better decisions.

Findings: This chapter demonstrates the importance of adopting new business models that allow insurers to move beyond understand and protect and become more predictive and preventative by using the tools and technologies of big data technology.