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This study aims to provide empirical insights pertaining to the impact of trait emotional intelligence on the mental well-being of students in higher education institutions (HEIs) in India.

In the current study, responses from a total of 252 students were randomly taken from different universities of Uttarakhand (India). The analysis was done using structural equation modelling AMOS 23.

The current study empirically established the positive impact of trait emotional intelligence (TEI) on the mental well-being of students and highlighted the relevance of TEI in curbing the psychological distress in students of HEIs.

This study endeavours to bridge the empirical and population gap by examining the emotional intelligence and its impact on mental well-being of the students of Indian HEIs, where studies are still scant and demand massive exploration of the perceptions of students. Strong emotional intelligence is pivotal in strengthening the mental well-being of students so that they can make appropriate decisions pertaining to their career and personal life.

The paper investigates the dynamic relationship among the stock markets of South Asian Association of Regional Cooperation (SAARC) countries during the COVID-19 pandemic.

Daily time-series data of four SAARC countries: India, Bangladesh, Pakistan, and Sri Lanka, from February 13th, 2013 to March 31st, 2021 are used. The study considers stock prices prior to the blowout of COVID-19 and during the onset of the pandemic. The novel estimation procedure of the autoregressive distributed lag model is used while the results are also confirmed by post-estimation techniques.

The study confirms that the COVID-19 contagion has adversely influenced the stock returns of SAARC countries. The findings signify that the pattern of cointegration has significantly different regularities in the pattern of causality in the long run and short run during the COVID-19 crisis. Overall, the study revealed that the COVID-19 pandemic has weakened the dynamic connection among the stock markets of SAARC countries.

To dampen uncertainties generated by the COVID-19 pandemic, the authorities and central banks should be equipped with efficient strategies and guidelines to cope with the crisis created by the pandemic. Further, governments should focus on assuaging the panic faced by investors and enhancing the confidence of domestic as well as foreign investors. Further, the weakened integration of financial markets during the crisis offers opportunities for speculative and arbitrage gains for investors.

The research work is an innovative effort to analyze the impression led by COVID-19 on the SAARC stock markets integration.

ChatGPT, a cutting-edge language model, stands as an unparalleled, unmatched conversational ally, showcasing novel versatility and intelligence in its responses. This research delves into the incorporation of ChatGPT, a powerful generative AI tool, into professional communication. This study utilizes the information system success model (ISSM) to examine the role of ChatGPTs in strengthening information quality (IQ), system quality (SQ) and service quality (SEQ) for improving customer usage intention (UI) and satisfaction (SAT). The study also investigates the moderating impact of perceived innovativeness between these relationships.

The research collected data from a sample of 400 customers through an online survey and validated the hypothesized relationships using structural equation modelling (SEM). Process Macros 4.1 in SPSS 22.0 is used to test the moderating role of perceived innovation between IQ, SQ and SEQ and UI and SAT.

The results of SEM analysis indicate that IQ, SQ and SEQ all positively support UI to use ChatGPT for professional communication with SAT. The result also establishes that perceived innovativeness positively moderates the relationship between IQ, SQ and SEQ and UI and SAT.

This research study offers novel contributions to the literature and body of knowledge by establishing the moderating role of perceived innovativeness in strengthening the relationship between IQ, SQ and SEQ and UI and SAT. Further, this study also proposes a 2*2 matrix to segment the UI and SAT of ChatGPT users in professional communication with varying degrees of perceived innovativeness.

The purpose of this study is to assess the impact of consumption values on customer satisfaction and intention to consume millet-based foods. This study examines both tangible and intangible values of the millet-based food to the customer.

Based on consumption value theory (CVT), the present study evaluates the impact of consumption value factors such as emotional, epistemic, health, price, prestige and taste/quality values on satisfaction and intention to use millet-based foods and develops a unique research model. Later, leveraging a dataset comprising more than 410 responses from Pune city in India, a rigorous empirical examination of the proposed model was conducted employing SmartPLS 4.0 software.

The study's finding unveils both the significant and insignificant impacts of various consumption values, both from the tangible and intangible consumption value perspectives on satisfaction and intention to consume millet-based foods. The study also provides a validated food consumption model which can be used for other similar food consumption behaviour of the customers.

This study provides insights as to how different consumption values impact the satisfaction of the customers for the millet-based food. This study illuminates additional aspects of the tangible and intangible factors impacting the satisfaction level of customers to consume millet-based products. Also, this is a cross-sectional study, and the respondents are only based in Pune, India. Thus, the study results cannot be generalised.

This study employs CVT to explore the unexplored impact of consumption values on satisfaction and intention to use millet-based foods, which is unexplored in the past literature. Moreover, this study develops a theoretical model with high explanatory power, and the research model adds value to the existing body of literature from areas such as food preference, consumer behaviour and value consumption insights.

This study aims to analyze the mediating role of attitude in understanding the impact of online service convenience on user engagement and intention to continuously use e-resources. Five components of online service convenience have been adopted for the present study: These are access convenience, search convenience, evaluation convenience, transaction convenience and possession/ post-possession convenience.

A total of 500 PhD scholars and faculty members from two different states of India were approached to provide their responses through a structured questionnaire, which resulted in 224 complete responses. These responses were analyzed using structural equation modeling. The statistical analysis has been performed with the help of Smart-PLS 3.

The study findings have proven the proposed conceptual model by showing a significant relationship between all the variables. Furthermore, it has been identified that the attitude of the users also positively impacts intention to continuously use e-resources.

This study contributes to the literature on e-resources by providing implications for students, faculties, managers and society.

The purpose of this paper is to analyse the relationship between foreign direct investment (FDI) inflows and economic growth with a special focus on the institutional environment at the state level. FDI-led economic growth and economic growth-led FDI have two dominant theoretical foundations, but empirical research supports contradictory findings. These perspectives largely ignore the institutional environment, assuming institutions to be background information.

To examine the causal relationship between FDI, the Granger causality method has been used. The impact of FDI inflows and other institutional factors on economic growth has been examined using the panel data regression method. The principal component analysis (PCA) method has also been used to develop indexes for some variables.

Results indicate a two-way Granger causality between FDI inflows and economic growth at the state level. Infrastructures, education expenses, labour availability and gross fixed-capital formation (GFCF) are positive and significant determinants, whilst corruption and FDI inflows are leaving negative impact on state-wise economic growth.

This study contributes to the body of the literature in four different ways: first, it empirically examines the trends and patterns of subnational FDI inflow and economic growth disparity in India; second, it examines the causality between FDI and economic growth. Third, with the institution-based paradigm in international business, it investigates how institutional variables affect the expansion of the economy. Fourth, it extends prior research by examining the link at the state level using a large panel data set made up of 29 states and 7 union territories (UTs) over the years 2000–2019.

The present paper makes an attempt to investigate the determinants that affect FDI inflows distribution among Indian states. Together with traditional determinants, the impact of institutional determinants on state-level FDI inflows distribution in India has been analysed.

The study uses panel data for a period of 20 years (2000–2019) for 17 groups of Indian states (29 states and 7 UTs). The empirical evidence is based on the panel data method and the findings support Dunning's OLI theory. As the data for some indicators for the institutional environment is not available at the state level, hence we used component analysis to arrive at the single component for the institutional factor. The study takes into account corruption, legal system, industrial disputes, man-days lost, labour availability, political risk, protection of IPR and agglomeration as potential macroeconomic and institutional determinants.

Results show that FDI inflows into Indian states is driven mainly by institutional environment. From our analysis, the author infers that the institutional variables such as legal system, IPR, corruption, political instability play an important role in determining the distribution of FDI inflows at the state level in India. Together with that GFCF and agglomeration are also important determinants of state-wise FDI inflows.

The major limitation of the study is that it doesn't include moderated impact of economic and institutional determinants of FDI inflows in Indian states, which can be an avenue for future research. Future research can also carried out taking district-level data to further examine the determinants at district level in India.

The contribution of the present paper is three-fold, first, the author constructs a measure of different institutional variables, after normalization of data for the period 2000–2019, and the author choose the highest explaining factor with the highest variance explained then we constructed the indices for select variable, which further has been used in the panel data analysis technique. The author has found that macroeconomic variables, as well as institutional variables, are significant to attract FDI at the state level in India. The paper shows that corruption, political risk, IPR and legal system are the major institutional determinants of FDI inflows in India at the state level. States with higher domestic investment attract more FDI inflows, moreover, agglomeration is a very important determinant as the investors are more confident in investing at the same location, the reason behind this may be that the investors want to avoid the registration procedure for new land, administrative formalities or they feel more secure at the same place and keen to invest at the same place again.

This study examines the web accessibility issues faced by users with disabilities when using ChatGPT, a popular chatbot. It is crucial for users with disabilities to have barrier-free access to Internet communications technology to be on par with other users. Because of its roots in artificial intelligence (AI) technology, ChatGPT can empower individuals with various abilities, providing access to the Internet and potentially leading to a substantial boost in digital inclusion for these users.

The researchers focused on ensuring ease of access to ChatGPT’s webpage to achieve the study objective. They conducted manual testing with a visually impaired researcher. They used axe DevTools and Accessibility Insights to investigate the target page’s three most commonly used states for accessibility issues.

The researchers identified substantial and crucial web accessibility issues on the target page. These issues resulted in frustration and hindered complete access to information about ChatGPT’s features. The researchers stress the significance of prioritising web accessibility and urge web designers to integrate Web Content Accessibility Guidelines (WCAG) standards into the initial stages of web development rather than addressing them as corrective measures. Given the United Nations' recognition of access to information and communication technology (ICT) as a pivotal Sustainable Development Goal (SDG) for users with disabilities, it is imperative to elevate web accessibility to foster their economic self-reliance and independence. This study underscores this imperative.

In this study, researchers assessed the accessibility of ChatGPT on the Google Chrome and Microsoft Edge browsers. This investigation could potentially be broadened to encompass additional web browsers. Furthermore, the researchers focused on three distinct states of ChatGPT: the initial default state, the subsequent output state and the third state, which represents errors on the target page. Further, developers can employ the results to enhance the accessibility experience for users with varying abilities who interact with ChatGPT.

Following a comprehensive examination of the current body of literature, the study pinpointed a gap in research, highlighting the necessity to conduct accessibility assessments for ChatGPT with regard to these particular users.

Technological innovations have affected and modified practically every element of human life and work. Education is one of the areas that has been greatly influenced by its dynamism. Technology has created an ecosystem in which education can be delivered via e-modes. The objective of this chapter is to study the impact of personalized learning on the student’s concentration level. The research methodology is top-down and includes both primary and secondary data sources. The sample was drawn using a probability-random sampling procedure with a response distribution of 50%, a margin of error of 10%, and a confidence level of 90%. The inquiry was carried out in various Indian states throughout the academic year 2020–2023. A 419-student sample was used in the study, and they were evaluated in two rounds using a pre-tested questionnaire. The association was determined for the experiencing group utilizing SPSS Version 25 and the analytic methods of factor analysis. This chapter presents options for higher education institutions, governments, and regulators to embrace and adapt. We are convinced that the study’s various recommendations will contribute to the development of a long-term strategy and plan to achieve the aim of ‘education for all, work for all’. The study investigates how the existing education model might adapt in the near future to keep up with the shifting paradigm and the arrival of Education 5.0.

One of the open questions is how to define a complete semantic description of an Internet of Things (IoT) system and how to ensure the device’s identification in this type of system. To answer this question, the authors needed to propose a mechanism to describe an IoT system based on an IoT context ontology description. This mechanism is based on semantic web services creation to identify objects in IoT system. This paper aims to propose a model to describe the IoT system. The authors suggest an approach to describe each category of contextual information separately and ensure the adaptation in the IoT system.

One of the open questions is how to define a complete semantic description of an IoT system and how to ensure the device’s identification in this type of system. To answer this question, the authors needed to propose a mechanism to describe an IoT system based on an IoT context ontology description. This mechanism is based on semantic web services creation to identify objects in IoT system.

One of the open questions is how to define a complete semantic description of an IoT system and how to ensure the device’s identification in this type of system. To answer this question, the authors needed to propose a mechanism to describe an IoT system based on an IoT context ontology description. This mechanism is based on semantic web services creation to identify objects in IoT system. This paper aims to propose a model to describe the IoT system. The authors suggest an approach to describe each category of contextual information separately and ensure the adaptation in the IoT system.

One of the open questions is how to define a complete semantic description of an IoT system and how to ensure the device’s identification in this type of system. To answer this question, the authors needed to propose a mechanism to describe an IoT system based on an IoT context ontology description. This mechanism is based on semantic web services creation to identify objects in IoT system. This paper aims to propose a model to describe the IoT system. The authors suggest an approach to describe each category of contextual information separately and ensure the adaptation in the IoT system.