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Augmented reality (AR) and virtual reality (VR) are becoming increasingly interwoven into people's daily lives, with applications in fields such as science, engineering, medical, the arts, education, finance and business. While much study has been conducted in the field of VR and AR in a variety of areas, less attention has been paid to online education. The purpose of this research is to conduct a systematic review of studies on AR and VR, as well as its applications in many disciplines of education, with a special emphasis on online education.

The data were gathered from the SCOPUS database under the subject “Augmented and Virtual Reality Applications in Online Education.” The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) format has been used to summarize the available literature and research in academics throughout the world. First, systematic literature reviews and later bibliometric analysis were conducted for performance and science mapping analysis.

The research adds to the body of knowledge about the role of AR and VR in online education and its future prospects. AR and VR have demonstrated a substantial contribution to facilitating teaching in a variety of fields, including engineering, medicine, nursing and chemistry. Additionally, this research indicates that AR and VR can be utilized to teach various areas and specialties. Additionally, it can be used in other aspects of online education, such as admissions, industry visits, training, internationalization and specific courses for students with disabilities.

This research lays the framework for educational institutions, legislators and researchers to investigate additional applications of VR and AR. Though this research suggests some possible uses for AR and VR in the online education system, more applications can be integrated into the online education system to fully leverage the potential of AR and VR worldwide. AR and VR have the potential to be a very cost-effective method of delivering online education on a wide scale in the future.

The article explores the applicability of VR and AR in education using bibliometric analysis. This is one of the first studies to do an assessment of VR and AR, evaluating their strengths, drawbacks and current applications. Future application areas are also identified as a result of the investigation.

The research paper investigated the intentions of superannuated persons toward the post-retirement work. This study aims to examine the role of attitude, job satisfaction and education in post-retirement work intensions.

A questionnaire was administered for collecting the data. It was submitted to the 300 government retirees. Data was analyzed by using Process macro. Intention toward work was used as an outcome variable. Attitude as a predictor variable, job satisfaction as a mediator and education as a moderator variable were used. The impact of attitude on intentions toward work was examined through job satisfaction and education.

The findings of the research showed the significance of experimented model. Therefore, the positive effect of attitude in determining the intentions has been proved and the effect of mediator-moderator was also significant.

The study is related to retired persons only and suggested that the level of education plays a major role in determining work intentions after retirement. This study addressed a research gap about how the interaction of job satisfaction and education affects the association among attitude and work intentions of superannuated persons.

ChatGPT, an artificial intelligence (AI)-powered chatbot, has gained substantial attention in the academic world for its potential to transform the education industry. While ChatGPT offers numerous benefits, concerns have also been raised regarding its impact on the quality of education. This study aims to bridge the gap in research by exploring teachers' perspectives on the adoption of ChatGPT, with a focus on identifying factors that motivate and inhibit them to adopt ChatGPT for educational purposes.

This research has employed a interpretative phenomenological analysis (IPA) qualitative approach. Through in-depth interviews among the teachers, data will be collected to identify the motivating and inhibiting factors that impact teachers' willingness to adopt ChatGPT. The data was collected from 34 teachers working across 10 branches of the University of Technology and Applied Sciences (UTAS) in Oman.

The analysis revealed four themes under motivating factors that encourage teachers to adopt ChatGPT for their educational purpose. These include Theme 1: Exploration of innovative education technologies, Theme 2: Personalization teaching and learning, Theme 3: Time-saving and Theme 4: Professional development. On the other hand, inhibiting factors includes five themes which includes Theme 1: Reliability and accuracy concerns, Theme 2: Reduced human interaction, Theme 3: Privacy and data security, Theme 4: lack of institutional support and Theme 5: Overreliance on ChatGPT.

This study contributes to the understanding of teachers' perspectives on the adoption of ChatGPT in education. By understanding teachers' perspectives, policymakers can design appropriate policies and service providers can customize their offerings to meet teachers' requirements. The study's findings will be valuable for higher education institutions (HEIs) in formulating policies to ensure the appropriate and effective utilization of ChatGPT. The study will provide suggestions to ChatGPT service providers, enabling them to focus on motivating factors and address inhibiting factors, thereby facilitating the seamless adoption of ChatGPT among teachers.

In comparison to previous studies, this study goes beyond merely discussing the possible benefits and limitations of ChatGPT in education. This research significantly contributes to the understanding of ChatGPT adoption among teachers by identifying specific motivating and inhibiting factors that influence teachers to adopt ChatGPT for educational purposes. The research enables to gain important new insights that were not previously found, giving a fresh dimension to the existing literature.

This paper aims to examine and discuss the factors affecting consumers' purchase intentions for ice cream in India.

This study is based on a primary survey of 340 respondents from India, collected through a well-structured questionnaire. The data has been analysed using partial least square-based structural equation modelling (PLS-SEM). The theory of planned behaviour (TBP) has been used to identify the determinants of the purchase intention of ice cream.

The measurement model shows that the constructs of the model have adequate convergent and discriminant validity. The findings of the structural model show the positive and significant impact of subjective norms, perceived behavioural control, and trustworthiness on attitudes and purchase intentions for ice cream. In addition, estimates also revealed that attitude has significant implications on purchase intention.

The study provides insight into the factors that influence ice cream purchase intentions in India. Corporate strategy makers and advertising managers who work for ice cream brands can look at the study to figure out how to market their products to get more customers.

The novelty and value of this study lie in choosing an unexplored product (ice cream) whose demand is continuously increasing. Perhaps this is the first study in an emerging economy like India to consider an extended version of the TPB by including health consciousness and trustworthiness to establish the relationship between ice cream purchase intention and health consciousness.

This study aims to delve into the perspectives of educators on integrating ChatGPT, an AI language model into management education. In the current research, educators were asked to talk as widely as possible about the perceived benefits, limitations of ChatGPT in management education and strategies to improve ChatGPT for management education. Also, shedding light on what motivates or inhibits them to use ChatGPT in management education in the Indian context.

Interpretative phenomenological analysis commonly uses purposive sampling. In this research, the purpose is to delve into educators’ perspectives on ChatGPT in management education. The data was collected from the universities offering management education in Uttarakhand, India. The final sample size for the study was constrained to 57 educators, reflecting the point of theoretical saturation in data collection.

The present study involved educators discussing the various advantages of using ChatGPT in the context of management education. When educators were interviewed, their responses were categorized into nine distinct sub-themes related to the benefits of ChatGPT in management education. Similarly, when educators were asked to provide their insights on the limitations of using ChatGPT in management education, their responses were grouped into six sub-themes that emerged during the interviews. Furthermore, in the process of interviewing educators about potential strategies to enhance ChatGPT for management education, their feedback was organized into seven sub-themes, reflecting the various approaches suggested by the educators.

In the qualitative study, perceptions and experiences of educators at a certain period are captured. It would be necessary to conduct longitudinal research to comprehend how perceptions and experiences might change over time. The study’s exclusive focus on management education may not adequately reflect the experiences and viewpoints of educators in another discipline. The findings may not be generalizable and applicable to other educational disciplines.

The research has helped in identifying the strengths and limitations of ChatGPT as perceived by educators for management education. Understanding educators’ perceptions and experiences with ChatGPT provided valuable insight into how the tool is being used in real-world educational settings. These insights can guide higher education institutions, policymakers and ChatGPT service providers in refining and improving the ChatGPT tool to better align with the specific needs of management educators.

Amid the rising interest in ChatGPT’s educational applications, a research gap exists in exploring educators’ perspectives on AI tools like ChatGPT. While some studies have addressed its role in fields like medical, engineering, legal education and natural sciences, the context of management education remains underexplored. This study focuses on educators’ experiences with ChatGPT in transforming management education, aiming to reveal its benefits, limitations and factors influencing adoption. As research in this area is limited, educators’ insights can guide higher education institutions, ChatGPT providers and policymakers in effectively implementing ChatGPT in Indian management education.

Operational performance is critical for the banking sector for both managers and other stakeholders as it strongly affects the overall performance of the banking system. Traditional performance measures such as ratio analysis encountered certain shortcomings. At this juncture, data envelopment analysis (DEA) approaches are increasingly applied in bank efficiency studies. However, basic DEA models ignored the interactions between consecutive terms and focused primarily on measuring performance independently for each study period. All this is required to develop an operational performance model that can enable the long-term decision model.

An attempt has been made to develop a dynamic DEA within a non-radial category to measure interconnection activities considering non-performing loans as an undesirable link. This study uses the Indian banking dataset from 2015 to 2019. The study's research design directs three directions: ‘comparison of the dynamic DEA with the traditional static DEA model, areas of inefficiencies that are investigated for each factor using the factor efficiency index and the robustness results highlighting the performance difference between bank categories.'

Comparing with static DEA results, the study confirms that the dynamic model best measures long-term operational performance due to the linkage between consecutive terms. The efficiency analysis concludes that the input factor that requires the most improvement is ‘fixed assets' and ‘deposits'. The output factor that needs the most progress is ‘non-interest income'. The robustness of the developed model is proven by ownership categories present within the Indian banking system. At a significance level of 10%, the result of both the separate and dynamic model for privately owned banks is significantly better than that of publicly owned banks.

This paper proposes an operational efficiency model for Indian banks in line with undesirable output. The mean factor efficiency analysis related to non-radial DEA modelling enhances managerial flexibilities in determining improvement initiatives.

One of the most marginalized communities in India is the Lesbian, Gay, Bisexual and Transgender (LGBT) community which commonly experiences discrimination. Many studies have countered that the LGBT community faces high discrimination in the banking and financing industry. As a result, this study concentrates on this marginalized community and its acceptance and continuation habit regarding mobile wallets. Consequently, this study has considered continuance intentions as a response to confirm the progress of the mobile-wallet industry. Also, this study tried to study the relationship between behavioral intention (BI) and continuous intention (CI) which is seriously lacks in the library of literature. The research operationalized the stimulus–organism–response (SOR) framework for the conceptual model and surveyed 100 self-proclaimed members of the LGBT community in India. The analysis has been done using the partial least structure (PLS). The findings demonstrate that variables like perceived trust (PT) directly influence the BI. On the other hand, variables like perceived ease of use (PEoU), social influence (SI), and satisfaction (S) doesn’t influence BI of the LGBT Community. The main outcome was a favorable association between BI and CI. It will help the stakeholders to understand how important this new market avenue is and how it can be explored. To ensure safe and secure transactions, a group think tank composed of important parties (financial institutions, mobile-wallet providers, the government, security specialists, etc.) should make recommendations. Mobile-wallet providers will attain benefit from this study’s understanding of user categories and ability to tailor their service offers as per the community.

The purpose of this paper is to extend the theoretical understanding of the disclosure dilemma experienced by lesbian, gay and bisexual (LGB) employees. The study focuses on examining the factors related to self-disclosure such as co-worker support and fear of disclosure. Further, the study also aims at testing the impact of coworker support on the psychological well-being of LGB employees.

The study adopts a concurrent triangulation research design, which involves a simultaneous collection of quantitative and qualitative data. Using a survey questionnaire, data from 200 LGB employees were collected. Semi-structured interviews were carried out with 10 LGB employees. The qualitative findings were treated as complementary to the relationship tested through the quantitative method.

Quantitative results reveal that co-worker support positively impacts self-disclosure by LGB employees. And the fear of disclosure mediates the relationship between coworker support and self-disclosure. Further, self-disclosure is positively related to psychological well-being. The qualitative study brings insights from the lived experiences around these factors. This research expands knowledge about the factors associated with the disclosure of LGB employees.

The study examines the factors related to the disclosure of sexual identity and the experiences of the dilemma of LGB employees in the workplace. Most of the studies in the context of LGB have adopted a quantitative research design. The current study adopts a mixed methods approach with a concurrent triangulation research design.

This paper aims to present a numerical study that investigates the flow of MgO-Al₂O₃/water hybrid nanofluid inside a porous elliptical-shaped cavity, in which we aim to examine the performance of this thermal system when exposed to a magnetic field via heat transfer features and entropy generation.

The configuration consists of the hybrid nanofluid out layered by a cold ellipse while it surrounds a non-square heated obstacle; the thermal structure is under the influence of a horizontal magnetic field. This problem is implemented in COMSOL multiphysics, which solves the related equations described by the “Darcy-Forchheimer-Brinkman” model through the finite element method.

The results illustrated as streamlines, isotherms and average Nusselt number, along with the entropy production, are given as functions of: the volume fraction, and shape factor to assess the behaviour of the properties of the nanoparticles. Darcy number and porosity to designate the impact of the porous features of the enclosure, and finally the strength of the magnetic induction described as Hartmann number. The outcomes show the increased pattern of the thermal and dynamical behaviour of the hybrid nanofluid when augmenting the concentration, shape factor, porosity and Darcy number; however, it also engenders increased formations of irreversibilities in the system that were revealed to enhance with the permeability and the great properties of the nanofluid. Nevertheless, this thermal enhanced pattern is shown to degrade with strong Hartmann values, which also reduced both thermal and viscous entropies. Therefore, it is advised to minimize the magnetic influence to promote better heat exchange.

The investigation of irreversibilities in nanofluids heat transfer is an important topic of research with practical implications for the design and optimization of heat transfer systems. The study’s findings can help improve the performance and efficiency of these systems, as well as contribute to the development of sustainable energy technologies. The study also offers an intriguing approach that evaluates entropy growth in this unusual configuration with several parameters, which has the potential to transform our understanding of complicated fluid dynamics and thermodynamic processes, and at the end obtain the best thermal configuration possible.