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.
This paper aims to provide a comprehensive view of the E-Government Development Index analysis in Southeast Asia. Through a review of the results of an annual survey of 192 United Nations (UN) member states, the study identified 11 countries with the E-Government Development Index in Southeast Asia. The findings in this study revealed that the E-Government Development Index (EGDI) in Southeast Asian countries displays different levels of development. Singapore, Malaysia, and Brunei are the countries in the region with the highest EGDI scores. Singapore leads the area with a high EGDI score. These countries have effectively implemented advanced e-government services, such as online public services, digital infrastructure, and e-participation, which have greatly improved the quality of life of their citizens and the efficiency of their government function. On the other hand, countries such as Cambodia, Laos, and Myanmar lag in their e-government development as a result of factors such as limited Internet access, inadequate digital infrastructure, and low levels of digital literacy among the populations of these countries. In addition, some moderate progress has been made in the development of e-government in mid-level countries, such as Thailand, Indonesia, the Philippines, and Vietnam. These countries continue to improve their digital infrastructure and enhance their e-service offerings to close the digital divide. Overall, EGDI in Southeast Asia reflects different levels of digital transformation in the region, with each country facing its distinct set of difficulties and opportunities when it comes to leveraging technology for better governance and public service delivery.
As China’s urbanization process accelerates, it has become common for rural men to go out to work and women to stay at home. The implementation of China’s rural revitalization strategy is in dire need of a large amount of high-quality human capital, and education and training are an important way to improve human capital and empower left-behind women. Starting from the background of China’s rural revitalization, this study focuses on the education and training of rural left-behind women, a topic that has received less attention. Through in-depth interviews and participatory observation, we analyzed the factors affecting rural left-behind women’s participation in education and training, as well as the problems that exist in China’s rural education and training process, and proposed strategies to solve them. The study found that education level, traditional attitudes, economic income, knowledge of education and training, and mental health are important factors affecting the participation of left-behind women in education and training in rural China. At the same time, there are some problems in the process of education and training, such as a single main body of supply and training methods, a lack of teachers, and a lack of management, etc., which affect the development of education and training, and thus also the promotion of rural revitalization.
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