A quantitative assessment model of the fit between local undergraduate colleges' major settings and regional industries based on regression analysis

Abstract

This study integrates the coupled coordination degree model, relative development degree analysis, and the Cobb-Douglas production function regression model, which are used to quantitatively assess the fit between undergraduate colleges and universities' major structure and industry structure. Using 25 applied undergraduate colleges and universities in Area A as a sample, the empirical analysis is conducted for the period of 2018-2024.The overall coordination between the majors and industries of colleges and universities in Area A has steadily improved, with the degree of coordination increasing from 0.673 to 0.819, reaching the level of “highly coordinated”. However, the coordination between specific categorized disciplines and industries is not fully coordinated; agronomy and agriculture are precisely matched, with a coordination degree of 0.634 in 2024, but the synergy between science and technology and industry is seriously out of sync, with almost all of the seven years in a state of “low coordination”, which is an obvious shortcoming of industrial upgrading. Regression analysis further reveals its internal driving mechanism, every 1% increase in industrial output value can drive the percentage of students in science and engineering to increase by 0.463%, and the service industry is the core of the development of economics and management majors. The study not only diagnoses the effectiveness and problems of the synergy between the two, but also quantifies the industrial-economic contribution of the professional setting, which provides very powerful support for the region to formulate precise education-economic synergistic development policies.