Measurement of the Integration of Education and Industry in Guangdong, Hong Kong and Macao Greater Bay Area under the Background of Big Data and Analysis of Influencing Factors

Abstract

Abstract In this paper, the Herfindahl coefficient (HHI), intuitionistic fuzzy hierarchical analysis (IFAHP) and binary semantic evaluation methods are used to quantitatively measure the degree of industry-academia integration in Guangdong, Hong Kong and Macao and to explore the level hierarchy of the degree of industry-academia integration. The factors influencing the behavior of industry-academia cooperation between enterprises and higher vocational colleges were analyzed by selecting the employment of H, A and X institutions in the past five years. The results show that the level of industry-academia integration in the Greater Bay Area is 0.6833, and the obstacles in communication channels between enterprises and higher education institutions are the biggest influencing factors. The industrial structure deviation is 28.9, which indicates that there is a discrepancy between the university specialty settings and market demand in the region. The optimization countermeasures proposed in this paper have a positive significance in promoting the connection between local higher education and industry.