Research on the configurational paths for establishing high-level municipal industry-education consortiums in China: from the perspective of symbiosis theory.

The municipal industry-education consortium(MIEC) is a crucial component of the development of education in China, and the provincial-level administrative regions (PARs) are committed to building high-level MIECs. However, there are significant differences in the efficiency of building MIECs in different regions across China. A province is a macro-level industry-education integration ecosystem, whereas a MIEC is a micro-level ecosystem. Symbiotic units such as industrial parks, universities, and enterprises within the provincial industry-education integration ecosystem(PIEIE) cooperate and exchange resources with each other in institutional, innovative, and digital environments to achieve the symbiotic model of industry-education integration, ultimately forming high-level MIECs. Based on the theory of symbiosis and employed the fuzzy set qualitative comparative analysis (fsQCA), this study analyzed the complex causal mechanisms through which symbiotic elements of PIEIEs influenced the construction of high-level MIECs, using data from the 31 PARs in China, excluding Hong Kong, Macao and Taiwan. This paper found that the development of high-level MIECs was not determined by any single symbiotic element; instead, it resulted from the coordinated development and combined effects of three key symbiotic factors: symbiotic units, symbiotic environment, and symbiotic models. There were six configurational pathways to building high-level MIECs, grouped into three types: the "Economy-Driven" model, the "Digital-Enabled Industry-Education Integration" model, and the "Assistance-Driven" model. The findings provide a theoretical foundation and practical guidance for PARs in developing high-level MIECs.

• Publication year

  2026

• Venue

  PLoS ONE

• Publication date

  2026-02-27

• Fields of study

  Medicine, Business, Economics, Education

• Identifiers
  DOI 10.1371/journal.pone.0336145PMID 41758921PMCID PMC12948090
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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