Investigation into the Coincidence between Specialty Setting in Higher Vocational Colleges and Industrial Structure Utilizing a Coupling Coordination Evaluation Framework

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Abstract

The coincidence between specialty setting and industrial structure within higher vocational colleges epitomizes the tangible foundation for the amalgamation of industry and education in advanced vocational training, serving as an essential element in Ningbo's regional economic evolution. Through an examination of Ningbo's prevailing industrial composition and the regional specialty setting of higher vocational colleges, this study evaluates the congruity between specialty setting and industrial structure by fashioning a deviation degree model. Concurrently, it calculates the comprehensive development level of specialty setting and regional industry through entropy weight method, and then probes the coupling coordination magnitude between specialty setting and regional industry through the construction of a coupling assessment coordination framework on this basis. The findings reveal that the specialty setting and industrial structure of higher vocational colleges in Ningbo exist in a state of significant coupling, and the interconnection degree between the two is commendable. Nevertheless, the overall deviation is notably substantial, indicating that the coupling coordination demands further refinement. Hence, it becomes imperative to augment the synchronized advancement between specialty setting in higher vocational colleges and regional industries within Ningbo, focusing on three vital dimensions: the optimal utilization of the government's comprehensive planning capability, the predominant role of higher vocational colleges, and the synergistic collaboration with enterprises within the context of higher vocational education.

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APA

Lu, Z., Zhou, C., & Zhoudan. (2023). Investigation into the Coincidence between Specialty Setting in Higher Vocational Colleges and Industrial Structure Utilizing a Coupling Coordination Evaluation Framework. Applied Mathematics and Nonlinear Sciences, 8(2), 3355–3370. https://doi.org/10.2478/amns.2023.2.01134

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