The current study examines the impact that technological innovation, foreign direct investment, economic growth, and globalization have on tourism in top 10 most popular tourist destinations in the world. The information on the number of tourists, foreign direct investment, growth in gross domestic product, GFCF, use of FFE, and total energy consumption were extracted from the World Development Indicators. The United Nations Conference on Trade and Development (UNCTAD) database was used for collecting the statistics about technological innovation.  The source ETH Zurich has been utilized to gather panel data for the time period 2008 to 2022 to calculate the KOF Index of Globalization. Theoretically, FDI and Economic growth are the endogenous variables for the Tourism model. Whereas, TI, Glob, Energy Consumption, and GFCF are the exogenous variables. Hence, the analysis is based on the System Equation—Simultaneous equations, after checking identification that confirms the problem of simultaneity in system of 3 equations. The empirical outcomes suggest that TI, FDI, globalization index, GDP growth, and energy consumption are the most important factors that contribute to an increase in tourism. Likewise FDI as the endogenous variable is favorably impacted by globalization, technological innovation, fossil fuel energy consumption, gross fixed capital formation, and tourism. Nevertheless, the coefficient of GFCF is only insignificant in the study. While, globalization, TI, and FFE are also favorably affecting the FDI. GDP growth is the second endogenous variable in this research, and it is positively influenced by globalization, FDI, and tourism in the case of the top 10 nations that are most frequently visited by tourists.

 Entrepreneurial intentions, considered to be the best predictor of entrepreneurial behaviour, have attracted extensive attention among academics, practitioners, and policymakers. This study examines the mediating role of the theory of planned behaviour between university students’ proactive personality, entrepreneurship education, entrepreneurial opportunities, and entrepreneurial intentions. The results of this study showed that both attitudes toward entrepreneurship and perceived behavioural control mediated these relationships, except that perceived behavioural control did not mediate the effect of entrepreneurship education on entrepreneurial intentions, and subject norm did not mediate any relationship. Lastly, this study guides universities, policymakers and practitioners to fully focus on developing attitude entrepreneurship and perceived behaviour control through education and training among graduates and employees. Suppose there is a presence of good entrepreneurial opportunities. In that case, they will form stronger intentions to start new businesses and expand their businesses to drive socio-economic growth, innovation and job creation among graduates.

Purpose: This research aims to examine the influence of intellectual capital disclosure and the geographical location of universities on the sustainability of higher education institutions in Southeast Asia. Design/methodology/approach: This research is quantitative and uses secondary data obtained through the annual reports of universities that have the Universitas Indonesia Green Metric Rank. This research uses two stages of data analysis techniques, namely the content analysis stage to determine the number of Intellectual Capital disclosures and the hypothesis testing stage. The analysis tool uses the SPSS version 23 application. The population of this research includes all universities in Southeast Asia that are included in the UI Greenmetric World University Rankings. The sampling technique used was purposive sampling technique, which resulted in 86 analysis units of higher education institutions in Southeast Asia. Findings: The research results prove that the geographical location of universities has a negative and significant influence on Universitas Indonesia Green Metric’s performance in Southeast Asia and human capital has a positive influence on UIGM’s performance in Southeast Asia. However, the structural capital and relational capital components do not affect the UIGM performance of universities in Southeast Asia. Originality/value: The originality of the research is the use of higher education sustainability variables with UIGM proxies and modified IC indicators for universities and geographical areas that have not been widely used to see whether there are fundamental differences in the disclosure of intellectual capital for higher education institutions in Southeast Asia.

The study examines the impact of COVID-19 on the economies of Gulf Corporation Council (GCC) member states. The event study methodology was used to analyze Cumulative Abnormal Return (CAR) of GCC member states’ stock indexes: Kuwait Stock Exchange Index (KSE), Dubai Financial Market Index (DFM), Saudi Arabia Tadawul Index (TASI), Qatar Exchange Index (QE), Bahrain All Share Index (BHB), Oman’s Muscat Stock Exchange Index (MSM), Abu Dhabi Stock Exchange Index (ADX) while the S&P GCC Composite Index was used as a reference. Data obtained from 28 July 2019 to 27 July 2020, and 1 March 2020, designated as the event day, abnormal returns (AR) and cumulative average abnormal returns (CAARs) were examined across various time intervals. The findings reveal significant market reactions to the pandemic, characterized by fluctuations in abnormal returns and CAARs. Statistically significant abnormal returns and CAARs during certain time periods underscore the dynamic nature of market responses to the COVID-19 event. These results provide valuable insights for policymakers and market participants seeking to understand and navigate the economic implications of the pandemic on GCC economies. The study recommends that other GCC states, particularly Oman, consider the policies undertaken by Qatar, UAE, and Saudi Arabia, to avoid a long economic crisis.

Increasing number of smart cities, the rise of technology and urban population engagement in urban management, and the scarcity of open data for evaluating sustainable urban development determines the necessity of developing new sustainability assessment approaches. This study uses passive crowdsourcing together with the adapted SULPiTER (Sustainable Urban Logistics Planning to Enhance Regional freight transport) methodology to assess the sustainable development of smart cities. The proposed methodology considers economic, environmental, social, transport, communication factors and residents’ satisfaction with the urban environment. The SULPiTER relies on experts in selection of relevant factors and determining their contribution to the value of a sustainability indicator. We propose an alternative approach based on automated data gathering and processing. To implement it, we build an information service around a formal knowledge base that accumulates alternative workflows for estimation of indicators and allows for automatic comparison of alternatives and aggregation of their results. A system architecture was proposed and implemented with the Astana Opinion Mining service as its part that can be adjusted to collect opinions in various impact areas. The findings hold value for early identification of problems, and increasing planning and policies efficiency in sustainable urban development.