Business Breakthrough University

This study aims at the contribution of education to ASEAN low-and-lower-middle-income countries (LLMICs) economic development and particularly the role of higher education in avoiding the low-and-lower-middle-income trap (LLMIT). Panel data analysis indicates a positive relationship between GDP per capita and higher education enrollment, though with its full effect constrained by persistent skill mismatches and poor digital infrastructure. Besides the quantitative findings, qualitative findings derived from the grounded theory approach (GTA) uncover severe impediments and propose measures such as e-learning, spin-offs from universities, and stabilizing community networks. The result underlines the need for continuous investment in higher education combined with primary and secondary education development as the foundation for human capital formation. In nations such as Cambodia, Laos, Myanmar, the Philippines, and Vietnam, issues like low tertiary participation, increasing privatization, and digital divides continue to be high hurdles. To overcome them, governments need to introduce inclusive education policies and increase access to the internet. At the same time, institutions of higher learning are urged to promote more inclusiveness, implement global academic standards, and spur innovation through entrepreneurship led by universities.

The middle-income trap (MIT) states that middle-income economies have found it challenging to upgrade to reach the high-income stage over an extended period. Overcoming MIT has long been discussed as an essential social issue related to fewer job opportunities and unstable income, notably in Southeast Asia. Previous studies demonstrated several factors contributing to MIT, including governance, infrastructure, and the labor market. Official Development Assistance (ODA) has been employed to help developing countries accelerate further development as development cooperation. Despite the massive financial aid, the Philippines has the longest-running history of operating under LMIT. Much less research on the unclouded evidence on the relationship between the ODA and MIT in the developing world and on the strategic study relevant to ODA for overcoming the lower-middle-income trap (LMIT) in the Philippines was identified from the updated government development plans were identified in the existing research. Using secondary data compiled between 2002 and 2021, primarily from the World Development Indicators, UNCTAD, UNDP, and OECD database, and POLS modeling, the strength of the Japan ODA predicting the percentage change in R2 variance in the LMIT was evaluated in nine Southeast Asian economies. Using natural data, ODA was found to be a significant predictor (F [1, 130] = 26.553 p = .000) and is thus a substantial factor in escaping LMIT. Using the analytical approach of Murdoch School of critical political-economy, state actors’ wasteful procrastination and excessive dependency on the donor were found to be significant culprits. Also, a development strategy for overcoming LMIT through the ODA was suggested by conceptually integrating three processes of problem-setting, strategy, and tactics, into one concept. Development cooperation can be re-defined as “glocal” activities by state actors collaborating with non-state actors to maximize national capabilities. Building a further trustful relationship with ASEAN and Japan is desirable for the Philippines.

This study applies the state of the Japanese university industry to a theoretical model of monopolistic competition. Using a model of spatial economics, it is possible to identify how and why an increasingly competitive university environment leads to university agglomeration and dispersion. The study analyses whether the location of universities will be less unevenly distributed in cities and whether the number of universities and students in rural areas will increase. Using a model of spatial economics, the study analyses two aspects: the demand aspect of the choice of universities by students and the supply aspect of location by universities. A decrease in the number of students per university results in a decrease in the quality of education through a decrease in university income. The results of this study can also explain the impact on the quality of education. The analysis leads to the following conclusions. The higher the cost of inter-regional travel during the job search, the fewer students are willing to move from one region to another to find a job, and the lower the number of students enrolled. When the substitutability between university varieties is weak, the number of universities increases because prospective students need more variety, and the number of students per university decreases. When fixed inputs are low, e.g. when the fixed costs of a university are low due to online etc., the number of universities increases because it is easier to establish new universities and the number of students and graduates per university decreases. In a model that assumes two types of students within the same university who want to work in their region or another region, there will be more students who move between regions. The location of universities is determined by the balance between market size and the level of competition. As people move from one region to another in the course of their job search, there will be competitors in the other region, and the effect of new competition will be weaker in regions with more universities than in regions with fewer universities. Thus, regions with more universities will have a larger market relative to the level of competition, and more universities than their share of the population will be located there. Even in a model with two regions, one with universities in higher education and the other with homogeneous goods in non-university production, the region with the largest population has a larger share of university enrolments than its share of the population. This means that even if the two regions have the same level of technology and resources, they will experience a reduction in enrolment simply because of their small population size. Smaller universities in rural areas mean that a negative spiral of declining enrolments will occur.

The relationship between engineering and marketing departments has not always been a happy one.