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Student engagement is a multifaceted concept that encompasses various dimensions that significantly influence students and their learning journey. This study aims to explore the extent of engagement among management students outside the confines of the classroom, specifically focusing on their engagement with the campus and community and assessing the outcomes resulting from this engagement.

The literature review provided the basis for developing a student engagement framework, focusing on campus and community engagement and their outcomes. Established scales measured these variables through surveys administered to 386 UG and PG management students. In-depth analysis using PLS-SEM technique revealed the interplay of variables, beyond demographic and descriptive examinations.

The study found that campus and community engagement fosters a sense of responsibility. Campus engagement also cultivates long-term loyalty to the institution, while community engagement enhances social consciousness. Additionally, no significant differences in engagement levels were observed based on gender or educational level among management students.

The study faces limitations that need addressing for balanced understanding and future research guidance. Firstly, varying definitions across studies lead to inconsistent outcomes and comparability challenges. Secondly, accurate measurement is difficult due to reliance on self-reporting tools, which are prone to biases. Cultural and contextual differences also limit generalizability, and quantitative data alone may not capture the full picture. In India, identifying specific skills and competencies as engagement outcomes in outcome-based education is challenging, requiring precise variable identification.

The study would contribute to improving the efficacy of efforts beyond the classroom engagement activities as it tests, validates, and projects them as outcome-driven by showcasing learning both as generic competencies in a broad sense and higher-order competencies in particular.

The literature indicates higher education institutes' activities beyond classroom teaching enhance students' campus and community relationships. This study measures these engagements' outcomes and suggests new research dimensions in student engagement.

The purpose of this paper is to explore the life priorities of Gen Y, the largest cohort of generation in India. Further variations in the life priorities of Gen Y with regard to their demographics have also been analyzed.

Ten-item Schwartz Value Inventory was subjected to factor analysis to explore defining factors for studying the life priorities of Gen Y in Indian context. Respondents ranking of the factors so revealed will allow us to study their preferred life priorities. The effect of demographics was assessed by employing an independent sample t-test.

Factor analysis revealed two factors, “materialism” and “altruism,” and Gen Y preferred materialism over altruism as their life priority. Gender and work experience did not show significant differences with regard to the life preferences Gen Y.

Gen Y is increasing its presence at workplaces across the world, and limited research has been done to study their motivations, needs and expectations at work in Indian context. This study could help managers gain insightful information related to the life priorities of Gen Y which could be harnessed to make effective strategies for their recruitment and retention.

The paper provides a valuable contribution by measuring the life priorities of Gen Y in India and adds to the scant literature on this cohort of generation.

Student engagement is a multifaceted concept that directly impacts students and their education. The purpose of this paper is to discuss student engagement conceptually by offering a framework to better understand the deliverables of engagement in the form of generic and targeted outcomes.

The design of the study is based on a detailed literature review, to identify different types of engagement which graduates are expected to experience during their higher education studies. These types of engagement(s) are mapped with their outcomes.

The findings of this study would be an analysis of relevant studies to create an outcome-oriented conceptual framework for student engagement.

The practical implications of the study would be to provide a guide for enhancing student engagement through which both generic competencies and higher order competencies of students may be augmented.

The available literature suggests that many students lack focus when learning on campus, especially in meeting targeted outcomes, and do not engage in the community. The current study has incorporated generic and targeted outcomes expected as a result of the different types of engagement. The study has put forward certain propositions, suggesting new dimensions of research in the domain of student engagement.

The study aims to evaluate the components of entrepreneurship education and training (EET) in India. The paper proposes a framework for an effective EET regime for amalgamating entrepreneurship education as fundamental to mainstream higher education in India.

The current study utilises a qualitative research technique, that is, the narrative inquiry methodology based on in-depth interviews. The study respondents included sixteen educators who are actively engaged in EET and related activities for a minimum of ten years.

The study identified five broad “meaning units” or “themes,” that is, “incremental pedagogical efficiency and flexible evaluation systems,” “entrepreneurial experience of the faculty,” “extended support,” “holistic mentoring” and “experiential learning” as components of an effective EET regime.

The study will help the policymakers and higher education institutions (HEIs) revisit their policy frameworks and practices to promote entrepreneurial capacity and entrepreneurial intentions among students. The study will also help to gain deeper insights into EET components and will propose a framework for an effective EET regime based on its findings.

This study aims to propose a conceptual model that examines the role of ethical climate on work–family enrichment in the restaurant industry, which is one of the most vulnerable sectors affected by global crises such as the COVID-19 pandemic. The mediating effects of psychological attachment and psychological capital and the moderating effects of job autonomy were also investigated to enrich understanding of ethical climate and work–family enrichment.

The conceptual model was evaluated by using a quantitative–qualitative mixed-methods approach. In Study 1, survey data was collected from a sample of 405 restaurant frontline employees and analyzed using partial least squares structural equation modeling. In Study 2, interviews were conducted with eight restaurant frontline employees and analyzed thematically. The data for Study 1 and Study 2 was collected from Jharkhand, a state in eastern India.

The results of Study 1 show a direct relationship between ethical climate and work–family enrichment. The mediating effect of psychological attachment and psychological capital on that direct relationship was also established, whereas job autonomy was found to be a significant moderator that negatively affects psychological attachment and work–family enrichment. The qualitative insights in Study 2 shed additional light on the rationales of the effects observed in Study 1 through the voices of restaurant frontline employees whilst triangulating the quantitative findings in Study 1.

This research contributes novel insights that explain how ethical climate positively shapes work–family enrichment through the lens of psychological attachment and psychological capital, albeit cautiously, given the negative effect of job autonomy. Nevertheless, this research remains limited to restaurant frontline employees, thereby necessitating future research in other service industries to improve the generalizability of its findings.

This research offers a seminal extension of the direct effect of ethical climate on work–family enrichment (i.e. the “what”) by theorizing and validating the mediating (i.e. the “why”) and moderating (i.e. the “how”) effects of psychological attachment, psychological capital and job autonomy.

The healthcare sector in India is witnessing phenomenal growth, such that by the year 2022, it will be a market worth trillions of INR. Increase in income levels, awareness regarding personal health, the occurrence of lifestyle diseases, better insurance policies, low-cost healthcare services, and the emergence of newer technologies like telemedicine are driving this sector to new heights. Abundant quantities of healthcare data are being accumulated each day, which is difficult to analyze using traditional statistical and analytical tools, calling for the application of Big Data Analytics in the healthcare sector. Through provision of evidence-based decision-making and actions across healthcare networks, Big Data Analytics equips the sector with the ability to analyze a wide variety of data. Big Data Analytics includes both predictive and descriptive analytics. At present, about half of the healthcare organizations have adopted an analytical approach to decision-making, while a quarter of these firms are experienced in its application. This implies the lack of understanding prevalent in healthcare sector toward the value and the managerial, economic, and strategic impact of Big Data Analytics. In this context, this chapter on “Predictive Analytics in Healthcare” discusses sources, areas of application, possible future areas, advantages and limitations of the application of predictive Big Data Analytics in healthcare.

This study aims to analyse the ethical implications associated with the development of artificial intelligence (AI) technologies and to examine the potential ethical ramifications of AI technologies.

This study undertakes a thorough examination of existing academic literature pertaining to the ethical considerations surrounding AI. Additionally, it conducts in-depth interviews with individuals to explore the potential benefits and drawbacks of AI technology operating as autonomous ethical agents. A total of 20 semi-structured interviews were conducted, and the data were transcribed using grounded theory methodology.

The study asserts the importance of fostering an ethical environment in the progress of AI and suggests potential avenues for further investigation in the field of AI ethics. The study finds privacy and security, bias and fairness, trust and reliability, transparency and human–AI interactions as major ethical concerns.

The implications of the study are far-reaching and span across various domains, including policy development, design of AI systems, establishment of trust, education and training, public awareness and further research. Notwithstanding the potential biases inherent in purposive sampling, the constantly evolving landscape of AI ethics and the challenge of extrapolating findings to all AI applications and contexts, limitations may still manifest.

The novelty of the study is attributed to its comprehensive methodology, which encompasses a wide range of stakeholder perspectives on the ethical implications of AI in the corporate sector. The ultimate goal is to promote the development of AI systems that exhibit responsibility, transparency and accountability.

The increasing awareness and adoption of technology, particularly artificial intelligence (AI), reshapes industries and daily life, fostering a proactive approach to risk management and leveraging advanced analytics, which may affect the stock price crash risk (SPCR). The main objective of the current study is to explore how AI adoption influences SPCR.

This study employs an Ordinary Least Squares (OLS) fixed-effect regression model to explore the impact of AI on SPCR in Chinese A-share listed companies from 2010 to 2020. Further, number of robustness analysis (2SLS, PSM and Sys-GMM) and channel analysis are used to validate the findings.

The primary findings emphasize that AI adoption significantly reduces SPCR likelihood. Further, channel analysis indicates that AI adoption enhances internal control quality, contributing to a reduction in firm SPCR. Additionally, the observed relationship is notably more pronounced in non-state-owned enterprises (non-SOEs) compared to state-owned enterprises (SOEs). Similarly, this distinction is heightened in nonforeign enterprises (non-FEs) as opposed to foreign enterprises (FEs). The study finding also supports the notion that financial analysts enhance transparency, reducing the SPCR. Moreover, the study results consistently align across different statistical methodologies, including 2SLS, PSM and Sys-GMM, employed to effectively address endogeneity concerns.

Our study stands out for its distinctive focus on the financial implications of AI adoption, particularly how it influences firm-level SPCR, an area that has been overlooked in previous research. Through the lens of information asymmetry theory, agency theory, and the economic implications of integrating AI into financial markets, our study makes a substantial contribution in mitigating SPCR.

This study underscores the pivotal role of AI adoption in influencing stock markets for enterprises in China. Embracing digital strategies, fostering transparency and prioritizing talent development are key for reaping substantial benefits. The study recommends regulatory bodies and service providers to promote AI adoption in strengthening financial supervision and ensure market stability, emphasizing the importance of investing in technologies and advancing talent development.

Buy-now, pay-later (BNPL) services can put consumers into a debt trap by encouraging consumers to buy things they cannot afford, leading to a culture of materialism and consumerism. Therefore, this research aims to investigate how materialism can influence BNPL use and impulsive and compulsive buying. Additionally, the authors examine if BNPL use and impulsive buying mediate between materialism and compulsive buying.

Data from 556 participants were collected through a structured questionnaire via an online survey. Structural equation modeling (SEM) using SMART PLS 4 was employed to analyze the relationship between variables and to test the proposed hypotheses.

Materialism impact BNPL use and increases the inclination for impulse buying, precipitating compulsive buying behavior. However, BNPL use does not directly influence compulsive buying. The mediating relationship was identified, where BNPL use, and impulsive buying mediate the relationship between materialism and compulsive buying.

BNPL use alone does not inevitably lead to compulsive buying. The only way BNPL use could lead to compulsive buying is through impulsive buying. Therefore, BNPL service providers need to foster responsible buying habits due to the rise in impulsive buying, which, if not controlled, could lead to a debt trap resulting from compulsive buying.

This study contributes to the limited BNPL literature because there is speculation, but the scarcity of empirical evidence to substantiate, how materialism influences BNPL use and increases the inclination for impulse buying, precipitating compulsive buying behavior.

The objective of this research is to identify and prioritize the critical factors that influence the adoption of blockchain technology within the banking sector.

A well-known theoretical framework, the “Technology Organization Environment (TOE),” was chosen to analyze what criteria and sub-criteria affect blockchain adoption in the banking sector after a thorough assessment of the prior literature. Following that, 3 evaluation criteria and 14 sub-criteria were selected and verified using expert opinion. A survey design was created, and data for the study has been collected from various information technology (IT) managers/officers in the banking sector. A fuzzy analytic hierarchy process (Fuzzy-AHP) was then used to meet the purpose of the research.

The study identified that the organizational dimension is the most significant criteria for blockchain adoption in the banking sector, followed by the environmental dimension. In contrast, the technological dimension is the least influential criterion. Clientele pressure, IT resources, financial resources, pressure from competitors and relative advantage are the most influential sub-criteria for blockchain adoption.

This study provides valuable insights to bank managers, blockchain and IT developers, third-party service providers and policymakers. For instance, adopting the same blockchain platform is easier for both large and small banks for banking operations by using third-party service provider. At the same time, banks should have the banks' own core team to implement the blockchain-based systems or to have control over the third-party service providers during the adoption stage.

To the best of the authors' knowledge, no empirical studies have used a holistic organizational context to understand the factors influencing the adoption of blockchain technology from traditional to blockchain-based banking systems.