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With the evolving landscape of technology and innovations, metaverse has revealed a huge potential for changing the world. Gradually, it has expanded its wings to different sectors, including higher education. The key purpose of this research work is to synthesize the existing literature on metaverse in higher education and develop future research directions for researchers.

The present study uses the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)” technique to recognize relevant articles from the database, i.e. SCOPUS. Furthermore, it conducts a “bibliometric analysis and systematic literature review” to explore the research area of metaverse in higher education.

The findings reveal that the synthesis and analysis of existing literature led to the identification of an intellectual structure, which resulted in the formation of four clusters. These clusters are defined as attributes related to metaverse applications in higher education, sustainable management of complex learning practices, customization of the teaching–learning process through the metaverse and model development. The theoretical structure informs the co-word analysis and thematic map, identifying four themes: the basic theme, motor theme, niche theme and decline theme. Finally, the social structure is assessed in terms of the author’s network and collaboration across countries.

The study investigated the conceptual structure by developing a thematic map and social structure by measuring the relationship between country–author collaboration through bibliographic coupling (BC). The study also identified future research avenues based on the “TCCM (theory, context, characteristics, and methodology)” framework for future researchers and practitioners.

The research study thrives on enlarging the review scope to measure the metaverse’s role in higher education. Though bibliometric studies have been developed in the metaverse, no study has attempted to measure the relationship between metaverse in higher education using bibliometric and TCCM framework. Thus, developing a synthesized work provides a comprehensive picture of the research domain.

The growth and promotion of green tourism destinations can have many potential benefits from artificial intelligence (AI). The literature on AI and applications of AI in promoting green destinations is very less. The major areas of research in this direction are related with nature-based tourism or sustainable tourism. There is a great potential to research in this area as AI can play an important role in promoting green destinations. Simultaneously, AI can play the role of enabler to achieve environmental targets by promoting various green destinations. The major finding of this chapter is that the research in this area is majorly revolving around tourist destinations and sustainable development. Another area of research where AI is used is eco-tourism and sustainable tourism. With the help of various decision support systems, sustainable tourism can be promoted. Social media platforms and digitalization of tourism is a great enabler of using AI in the field of tourism.

This book is essential for anyone in artificial intelligence (AI) and destination management in the tourism industry or government. The book includes both theoretical and practical writings for stakeholders. In all chapters, we provide titles including AI, regenerative and green destinations, sustainable tourism, tourist motivations and expectations, good examples of smart destinations and regions, the regeneration of the tourism industry via AI, rethinking tourism activities and products, current issues in robots, self-service technology, effect of pandemic on smart destinations, sustainable gastronomy and regenerative tourism and tourism issues are discussed in the management plans of the centralisation. This book provides cases and empirical studies that deal in depth with the current situation, challenges, solutions and future strategies after technological development of tourism and increasing interest on smart destinations from a responsible perspective, for readers with an equitable interest or involvement with the organizations in inquiry.

This study aims to understand the effect of cultural dimension (individualism/ collectivism) on promotional rewards (social or economic) resulting in incentivizing consumers to engage in electronic word-of-mouth (eWOM), further impacting their repurchase intentions.

In Study 1, a 2 (culture: individualism vs collectivism) × 2 (promotional rewards: social vs economic) between-subjects design was used. Structural equation modeling was used to test the hypotheses. In Study 2, culture was measured instead of just being manipulated. The authors used regression analysis in this study.

Owing to the characteristics of collectivistic individuals, consumers in collectivistic cultures were more likely to respond to social rewards as an incentive to engage in eWOM. However, consumers in individualistic cultures were more motivated to engage in eWOM when economic rewards were offered.

Despite the global nature of eWOM, little research has explored the effects of cultural traits on consumer response to amplified eWOM strategy. Additionally, though many organizations now offer various promotional incentives to reviewers, little research has explored the effects of promotional offers on a reviewer’s subsequent behavior, and no research has explored the relationship between cultural dimensions and current and future response to promotional eWOM rewards.

This study aims to identify a sustainable university’s key features. It is an essential step in tracing the topics discussed in the context of a sustainable university and their evolution in the scientific discourse.

This paper relies on a systematic literature review (SLR) conducted using two scholarly databases: Emerald and Scopus. The timeframe selected by the authors for reviewing the available sources spans from 2001 to 2021.

The analysis distinguished seven sustainable university categories, each revealing critical features of sustainable higher education. Each of these categories represents an intriguing area for in-depth analysis. The SLR reveals gaps requiring further scientific exploration.

The performed literature review was determined by the choice of entries (keywords) to identify the scientific papers in the selected databases. Moreover, as the authors aimed to focus on peer-reviewed sources, this SLR did not include books and doctoral dissertations dealing with the studied issues.

The results of the analysis can be used practically by both researchers and practitioners in the field of sustainable development (SD). Identified scientific gaps become a potential research field, and practitioners interested in the transition toward SD may contribute by accompanying universities in this journey. Collaboration and networking with business stakeholders are critical vectors for spreading the idea of SD.

Society’s growing concern for climate change requires accurate and specific actions from institutions. As entities educating future generations, universities have a unique role in transforming toward SD. The findings allow us to get acquainted with the existing main activities undertaken by higher education institutions in this field and understand the importance of this topic for researchers.

SLR is a cornerstone of research synthesis and helps integrate scientific evidence from qualitative and quantitative published studies. Conducted research presents knowledge about university sustainability and can help scientists find research gaps.

Purpose: This chapter aims to unveil the challenges of adopting and using banking chatbots in India and identify the challenges of Chat Generative Pre-trained Transformer (ChatGPT) for future banking.

Need for the study: Unveiling the challenges of chatbots and ChatGPT in the banking industry in India is crucial to understand the limitations and areas of improvement to enhance customer experience, ensure data security, and maintain regulatory compliance.

Methodology: The researchers conducted a narrative review systematically summarising and analysing existing literature on chatbots and ChatGPT, providing a comprehensive overview of the challenges faced in the industry.

Findings: The authors identify perceived risk, platform quality, connectivity and infrastructure, data privacy and security, user education and acceptance, existing legacy systems, and regulatory guidelines as the challenges of adopting chatbots. Additionally, the findings reveal that the challenges posed by ChatGPT in future banking include the potential reduction of traditional banking jobs, linguistic diversity, data privacy and security, ethical considerations and bias mitigation, explainability and accountability, integration with existing banking systems, and user trust and acceptance. However, implementing these new technologies also presents opportunities for individuals with unique human skills, such as critical thinking, empathy, and creativity, which are difficult to replace with technology.

Practical implications: By minimising the challenges of ChatGPT and chatbots, the banking industry could achieve improved customer service, cost efficiency, automation of routine tasks, and 24/7 availability, leading to enhanced customer satisfaction and operational efficiency in the banking industry. Additionally, these artificial intelligence (AI) tools enable data-driven insights, personalised experiences, scalability, and efficient handling of large customer volumes, contributing to better decision-making and enhanced customer engagement.

This paper aims to analyze the monitoring role of board and product market competition in relation to firm performance. Further, this paper analyzes the moderating role of product market competition in influencing the board monitoring and firm value relationship in the context of an emerging economy, India.

A large sample of 3,854 firm-year observations has been used over a period of 10 years (2007-2016). Industry and year-fixed effect regression methodology has been used to test the hypothesized relationships.

The empirical findings indicate that board monitoring adds negatively to the firm value. The results also indicate that product market competition bears an insignificant moderating effect on the effectiveness of board monitoring in India. However, a more in-depth analysis reveals that product market competition complements the weak board monitoring of business-group firms. Further, the effectiveness of the board monitoring (which is relatively stronger in business-group firms) is weakened by the increased level of product market competition for stand-alone firms.

A significant negative effect of board independence on the firm value raises the effectiveness of various policies advocating the board independence to strengthen the governance structure of the firms. The findings relating to the moderating role of product market competition for the business-group and stand-alone firms are helpful in understanding the governance behavior of the firms in relation to the external product market competition.

External governance mechanisms such as the market for corporate control and product market competition have been described as significant corporate governance mechanisms. However, the empirical efficacy of these governance mechanisms has not been explored in a greater detail in the context of the emerging markets. This study aims to address this research gap.