Purpose: This study is undertaken to examine the role of information and communication technology (ICT), e-service quality and e-information quality towards brand image of universities by concentrating on students’ e-learning, e-word of mouth and satisfaction.Design/methodology/approach: The target population was the students of public and private universities in Pakistan. Data collected using an e-questionnaire by 408 students were subjected to PLS-SEM for analysis.Findings: Findings revealed that ICT, e-service quality and e-information quality are positively contributed toward students' e-learning which ultimately leads to create positive e-word of mouth and students' satisfaction. Meanwhile, results also identified that e-word of mouth and students' satisfaction lead to generate a positive brand image of universities.Practical implications: This study has unique implications for universities to develop an e-learning platform to facilitate their students in this situation of COVID-19. It provides guidelines for educational institutions to implement the learning management system effectively with a view to facilitate the students with education.Originality/value: This study has novel contribution in literature in the domain of digital learning. It is unique in a way to integrate the usage of technology with students' e-learning and satisfaction that ultimately create brand image of universities.

The main purpose of this empirical study is to explore the entrepreneurial self-efficacy, and entrepreneurial competency as antecedents to the entrepreneurial intentions in smart city of Neom Saudi Arabia. Additionally, the study has also examined the mediating role of entrepreneurial education on artificial intelligence in the relationship between the entrepreneurial self-efficacy, entrepreneurial competency, and the entrepreneurial intentions in smart city of Neom Saudi Arabia. The study has employed the SEM-PLS for the data analysis. A sample based on 550 students from private (n = 291, 52.9 %) and public universities (n = 259, 47.1 %) of KSA were randomly selected. The entrepreneurial self-efficacy, and entrepreneurial competency are reported to have a positive and significant influence on entrepreneurial intentions. The entrepreneurial education on artificial intelligence, medicate the relationship between the entrepreneurial competency, entrepreneurial self-efficacy, and entrepreneurial intentions The model is contextually suitable for motivating individuals to become self-sufficient and for enabling them to harness their creativity through entrepreneurial and profit-driven endeavors in smart cities. This study has significant implications for entrepreneurs, practitioners, and governments alike. The findings provide a guideline for governments in establishing an environment that supports the individual drive to embark on entrepreneurial endeavors. Among the stimulus for encouraging entrepreneurship include the provision of loans with reasonable interest rates and knowledge sharing sessions by prominent entrepreneurs. Drawing inferences from the empirical findings and discussions, this present study has made appreciable theoretical contributions to the existing body of literature, specifically, in the area of entrepreneurial intentions in smart city.

Stock market, is one of the most important financial market which has a close relationship with a country’s economy, due to which it is often called the barometer of the economy. Over the past 25 years, the stock markets have been affected by different global economic shocks. Various researchers have analyzed different aspects of these effects one by one, however, this study is an assessment of stock market interrelationship of emeriging Asian economies which include most of the East Asian, and Southeast Asian emerging economies with special focus on China for past decades during which different crisis occurred. We used Morgan Stanley capital international (MSCI) daily indices data for each stock market and compared Chinese stock market with the stock markets of India, Pakistan, Malaysia, Singapore, and Indonesia. We analyzed the data through the individual wavelet power spectrum, cross-wavelet transform and wavelet coherence, to determine the correlation and volatility among the selected stock markets. These model have the power to analyze co-movements among these countries with respect to both frequency and time spaces. Our findings show that there are co-movement patterns of higher frequencies during the crises periods of 1997, 2008 and 2015. The dependency strength among the considered economies is noted to increase in the crisis periods, which implies increased short- and long-term benefits for the investors. From a financial point of view, it has been determined that the co-movement strength among the emerging economies of Asia may have an effect on the VaR (Value at Risk) levels of a multi-country portfolio. Furthermore, the stock market of China shows a high correlation with the other six Asian stock emerging markets in both high and low-frequency spectrums. The association of the south and east Asian stock market with Chinese stock markets show the interconnection of these economies with the economy of China since past two decades. These findings are useful for investors, portfolio managers and the policymaker around the globe.