Study on the matching degree of major groups and industrial groups in higher vocational colleges

Abstract

Major groups matching industrial groups in higher vocational colleges is the requirement of integration of industry and education. It is a talent cultivation mode based on the demand of regional advantageous industrial groups for talent quality. It is significant to improve the rationality of professional settings in colleges and promote the development of the economy. This study takes the Yi-Jing-Jing Metropolitan area as a case and uses the coupling coordination model to measure the matching degree of the industrial groups and the major groups. The conclusion is as follows: major groups and industrial groups in this region do not match well, and pay insufficient attention to the development of emerging advantageous industries. Some majors have not adapted to the characteristics of the current era and cannot meet the future development of the industry. According to the research results, it is proposed to strengthen policy guidance, based on changes in demand, and adjust the course content and other aspects to promote the matching of major groups and regional advantageous industrial groups.

1. Introduction

Higher education major groups (MGs) not aligning with regional industrial groups (IGs) and the resulting mismatch between knowledge supply and demand are problems faced by many countries [1,2]. This issue can lead to a shortage of professional talent, not meeting the needs of industrial development, affecting economic growth, and resulting in negative consequences such as reduced wages, decreased skill returns, and declining quality of jobs [[3], [4], [5]]. This is particularly important for vocational colleges, as they directly produce high-level technical workers who are more susceptible to market demand fluctuations due to factors like technological changes [6]. Taking China as an example, as of 2020, there were 1,468 vocational colleges in China with an enrollment of 4.8361 million students, making it the largest vocational education system in the world. The quality of vocational education will have profound implications for socio-economic development.

In recent years, China has successively introduced several policies and measures to advocate MGs matching IGs and promote the integration of “industry” and “education”, “enterprise” and “school”, “production” and “teaching” in vocational education [7,8]. MGs matching IGs in higher vocational colleges (HVCs)is a talent training mode based on the needs of regional advantageous IGs for talent quality. It is a requirement to improve the rationality of major settings in higher education institutions and enhance the competitiveness of IGs [9], which can ease the employment pressure, promote regional development, and accelerate the spread of S&T innovation and professional division of labor. Existing studies focused on the reasons, mechanisms, and paths of the matching of MGs and IGs, but few directly measured the matching degree. This study takes the Yi-Jing-Jing Metropolitan area in China as a case study to explore the matching degree of MGs and IGs. The Yi-Jing-Jing Metropolitan area is an integrated area composed of three cities, Yichang, Jingzhou, and Jingmen, in central China. It is an important link between central and western China. In the next five years, it is expected to feature a green economy and strategic emerging industries and become the important fulcrum for the development of central China. Taking this region as a research case, it is representative.

This study analyzes regional MGs and IGs using quantitative and mathematical models, constructs an evaluation index system to measure their alignment, and proposes countermeasures for matching MGs with IGs. This study has practical significance as it provides a feasible path for scientifically setting up majors for vocational colleges and other educational institutions, and offers references for government planning of education and industry. The main innovations of this study include empirical analysis and testing of the alignment between MGs and IGs in a case city using mathematical models, providing realistic samples for assessing the status of coordinated development between MGs and IGs and proposing improvement suggestions, thus expanding existing research conclusions. The rest of the paper includes the following contents: literature review, data and methods, empirical results, conclusions and policy recommendations.

2. Literature review

Scholars have carried out some research achievements on MGs matching IGs, mainly summarized as follows:

• (1)The guiding ideology of MGs matching IGs: the theory of integration of education and industry.

This theory believes that the vocational education system and the industrial system are integrated and interactive. The effective measure of higher education reform is to realize the integration and interaction between vocational education and the industrial system. Freeman [10], Lundvall [11], and Nelson [12] proposed the concept of a “national innovation system,” wherein enterprises play a leading role in innovation, and institutions such as universities are required to form an effective and stable innovation system network centered around enterprises, leveraging their respective functional advantages to promote optimal resource allocation and innovation realization. Etzkowitz [13], in his triple helix theory, suggests that the industry, the government, and universities are equally significant social institutions. These entities break down organizational boundaries and jurisdictional limits, with their forces permeating, substituting, and blending, thus fostering an upward spiral of innovative activities conducive to knowledge creation, transformation, and application. This environment promotes the realization of the innovation objective value where “1 + 1+1 > 3”. Frolund et al. [14] argue that collaboration between businesses and universities is a key driver of the innovation economy and a mainstay of corporate R&D -- from creating a knowledge base to acting as an expanded platform for solving short-term, incremental problems, to provide a stream of new talent. Kessels and Kwakman [15] believe that universities and enterprises can form closely cooperative knowledge networks to integrate learning and work. Chen [16,17] believes that in the relationship between the major and the industry, the industry is the primary, and the major is the secondary, and the major can also affect the future appearance of the industry. The development and growth of the industry and the construction of its core competitiveness provide broad prospects for the development of MGs in universities. The construction of MGs to match regional industries is not only the endogenous value pursuit of vocational education but also the external environment requirement for the sustainable development of vocational education. The theory of industry-education integration elucidates the significance of matching and coordinating the development of MGs and IGs.

• (2)The internal mechanism of matching MGs and IGs: the supply chain of professional talents is coupled with the demand chain of industrial talents.

Meng [18] posits that the formation of IGs accompanies talent aggregation, with MGs serving as manifestations of talent aggregation. The interactive relationship between IGs and MGs will influence the construction of vocational education specialties and the growth of MGs. Strengthening the alignment of the talent chain with the industry chain is a crucial orientation for the construction of MGs. The coupling relationship between the talent chain and the industry chain is primarily characterized by a high degree of consistency, connectivity, and overlap in terms of goals, substance, influencing factors, and other aspects [19]. The talent chain supports the refinement and upgrading of the industry chain, serving as the foundational condition for the normal operation of the industry chain, and driving the technological upgrading of the industry chain, thereby promoting its innovative development. Conversely, the industry chain guides the formation and enrichment of the talent chain, providing the material foundation, practical platform, and broad space for the formation of the talent chain [20]. In the process of constructing MGs, vocational colleges should focus on promoting the alignment of the talent chain with the industry chain, emphasizing the highlighting of the characteristics, sharing, and innovation of IGs, maintaining advancement, and achieving effective integration with regional IGs.

• (3)The matching approach of MGs and IGs.

The alignment of MGs with regional industries necessitates diverse governance involving the government, industries, and vocational institutions. From a governmental standpoint, Hu et al. [21] advocate for leveraging the government's guiding role in collaborative governance and utilizing governance tools like planning, early warning systems, and communication platforms to enhance the coupling quality between MGs and industries through collaborative governance. Improved institutions can enhance the macroeconomic returns of human capital by reallocating it to applications with greater social productivity. Concerning vocational institutions, scholars focus on aspects such as training objectives of majors, talent development models, curriculum development, and faculty teams. Chen [22]proposes various development paths, including promoting cooperation between schools and enterprises, reforming talent development models, innovating curriculum systems of major, and cultivating “dual-qualified” teaching teams, to achieve four major alignments: aligning major construction with industry talent demand, aligning curriculum development with vocational job competency requirements, aligning faculty team construction with industry experts, and aligning practice platform construction with industry research and development demand, thus establishing a mechanism for synchronized adjustment between MGs and industrial groups' development. Wang [23] suggests that vocational colleges should focus on restructuring curriculum groups as the foundation, supporting grassroots teaching organizational reforms as the backbone, ensuring “dual-qualified” teaching teams as the safeguard, and promoting the shift of MG construction from traditional administrative orientation to demand-driven orientation, with technical innovation platforms as the reliance, thereby leading MG construction from adaptation to leading industrial development. From the industrial perspective, scholars [[24], [25], [26]] suggest that enterprises can promote the matching of MGs with IGs through avenues such as offering customized courses, participating in curriculum development with schools, co-establishing industrial colleges with schools, and dispatching skilled technical workers to participate in school teaching. These measures serve to facilitate the alignment between MGs and IGs.

• (4)The problems existing in the matching of MGs and IGs

Matching MGs with IGs requires efforts from the government, schools, and enterprises. Scholars have also analyzed the existing problems in the matching of MGs and IGs from these three aspects. Firstly, from the perspective of schools, the external docking mechanism is not sound, making it difficult to keep up with the pace of industrial development. The internal knowledge system is closed, making it difficult to integrate internal and external resources. Organizational collaboration is not smooth, making it difficult to form a concerted effort for construction and development. Insufficient innovation capacity makes it difficult to establish sustained competitive advantages, which remain prominent issues in the current construction of MGs in HVCs. This is mainly manifested in the lag in the construction of vocational education majors compared to industrial development [27], insufficient capacity of vocational education to undertake industrial transfer, and the synergy of industry-education integration and collaborative innovation has not yet formed. The industrial orientation of major education objectives is not strong, and there is insufficient industrial adaptability in the process of skills training. The talent training mode in the construction of MGs needs to be reformed, driving changes in curriculum systems, teacher capabilities, teaching methods, and other aspects [[28], [29], [30]]. Secondly, from the perspective of government macro-control, institutional bottlenecks still need to be overcome, there are disparities in educational resources, and talent distribution is uneven. Lastly, from the perspective of enterprises, enterprises are the demand side for the symbiotic integration of vocational education and industry [31]. However, in the process of participating in vocational education, enterprises are influenced by multiple internal and external factors, mainly manifested as contradictions between short-term capital investment and long-term effectiveness, explicit capital investment and implicit effectiveness, and direct introduction and cooperative development [32]. Some enterprises require obvious attributes of “short, flat, and fast” in investment, which further leads to trends unfavorable to the development of the integration of vocational education and industry, which is more evident for small and medium-sized enterprises (SMEs). Therefore, the effective implementation of industry-education integration by enterprises will still require a long process, which is more pronounced for SMEs.

• (5)The impact of mismatches between MGs and IGs

Scholars believe that the biggest problem caused by the mismatch between MGs and IGs may be skill mismatch. Skill mismatch generally falls into three categories: over-skilling, under-skilling (including skill shortages and skill obsolescence), and domain mismatch. This means either vertically, where there is an excess or lack of skills: employees' level of education is higher or lower than what is required for their current job [33], or horizontally, where there is a significant difference between the job they are doing and their educational background [34,35]. This mismatch can have negative impacts on individuals, employers, and society. At a macro level, it can result in the wastage of educational resources or a shortage of human resources [36,37], leading to a decrease in workers’ effective skills and affecting productivity [38], thus impacting industrial development. At a micro level, it can lead to lower wages for workers, increased unemployment rates, and decreased job effectiveness [39,40].

From the above summary, academia has already conducted relatively mature discussions on the significance, mechanisms, pathways, and problems of matching MGs with IGs. However, existing research has less involved quantitative analysis of the matching between MGs and IGs. Before proposing reasonable policy suggestions, it is necessary to measure the degree of matching between MGs and IGs. This is precisely the focus of this study.

3. Methodology

3.1. Method design

Firstly, this study sorted out the advantageous industries of the case region, sorted out the enrollment majors of HVCs through the catalog of enrollment majors of all HVCs in the case region in 2023, and made a preliminary comparative analysis of the matching list of MGs and IGs. Then the coupling coordination model is used to measure the matching degree of the MG and the IG. The industrial data used in this study are mainly from government documents such as the 2022 Statistical Yearbook of the case region and the Statistical Bulletin of National Economic and Social Development. The major data came from the official websites of vocational colleges.

The matching degree of the IG and the higher vocational MG refers to the degree to which the development supply of the higher vocational MG matches the development demand of the IG. The coupling coordination degree model uses the coupling degree to explain the relationship between multiple subsystems and then uses the coordination degree to evaluate and study the whole system comprehensively, which is simple and easy to calculate and the results are intuitive. Drawing on previous studies [41], a modified coupled coordination model was used for data analysis in this study. First, the raw data were standardized; Secondly, the entropy method was used to determine the weight of each evaluation index. Third, the development level function of the MG and the IG was calculated respectively; Finally, the coupling coordination degree model was to analyze the matching degree of the two groups. The main steps and formula for matching degree measurement are as follows:

• (1)Processing of initial data

The raw data of each indicator are standardized according to (1), (2).

$$v_{ij}=\frac{v_{ij}-\mathit{min}{v}_{ij}}{\mathit{max}{v}_{ij}-\mathit{min}{v}_{ij}},v_{ij}\text{represents}\text{positive}\text{index}$$ (1)

$$v_{ij}=\frac{\mathit{max}{v}_{ij}-v_{ij}}{\mathit{max}{v}_{ij}-\mathit{min}{v}_{ij}}，v_{ij}\text{represents}\text{reverse}\text{index}$$ (2)

In the formula, $v_{ij}$ is the standardized value of the jth index of the system i; $v_{ij}$ is the original value of the jth index of the system i; max $v_{ij}$ and min $v_{ij}$ represent the maximum and minimum values of the jth index of the system i respectively. To avoid that logarithms cannot be obtained when partial index values are 0, the indexes are non-zeroized.

• (2)Processing of index weights

This study uses the entropy weight method (see Formula 3) to determine the weight of each index.

$$w_{j=\frac{1-H_j}{m-{\sum }_{j=1}^m{H}_j}}$$ (3)

$H_j$ is the entropy value corresponding to the jth index, which is calculated by formula (4).

$$H_j=-k{\sum }_{i=1}^n\left(f_{ij\times }In{f}_{ij}\right)$$ (4)

and k = $\frac{1}{Inm}$, $f_{ij}$ = $\frac{y_{ij}}{{\sum }_{i=1}^n{y}_{ij}}$_。

• (3)Calculating the development level of IGs and MGs

First, the standardized values of the two subsystems are calculated by (5), (6).

$${\mathrm{U}}_1\left(\mathrm{x}\right)=\sum _{i=1}^{m_1}{a}_i{x}_i$$ (5)

$${\mathrm{U}}_2\left(\mathrm{y}\right)=\sum _{i=1}^{m_2}{b}_i{y}_i$$ (6)

where， $m_1$, $m_2$ , is the number of the first and second sub-system indicators respectively. $a_i,b_i$ represents the weight of each indicator.

Second, using the entropy weight method, that is, (1), (2) to determine the weight of the standardized value of each subsystem; Finally, according to the standardized value and weight, further calculate the comprehensive development level function of each subsystem (see Formula 7).

$$\mathrm{T}=\sum _{i=1}^n{a}_i\times U_i,\sum _{i=1}^n{a}_i=1$$ (7)

In the formula, $U_i$ is the standardized value of the ith subsystem; $a_i$ represents the weight of the ith subsystem.

• (4)Calculating the coupling degree

The coupling degree model reflects the relationship between IGs and MGs, whether they are interdependent or antagonistic. Formula (8) is the coupling degree model formula when n = 2:

$$\mathrm{C}=\sqrt{\left[1-\sqrt{{\left(U_2-U_1\right)}^2}\right]\times \frac{U_1}{U_2}}=\sqrt{\left[1-\left(U_2-U_1\right)\right]\times \frac{U_1}{U_2}}$$ (8)

C represents the relationship between two systems. The value ranges from 0 to 1. The larger the value of C, the smaller the degree of antagonism and the higher the degree of dependency between subsystems. On the contrary, the degree of dependency between subsystems is low.

• (5)Calculating the coordinated development degree (matching degree)

The degree of the coordinated development synthesizes the degree of development and the degree of coupling, and can quantitatively express the changing trend of the coordination relationship between the subsystems. The formula for calculating the degree of coordinated development D is as follows (see Formula 9):

$$\mathrm{D}=\sqrt{C\times T}=\sqrt{{\left[\frac{\prod _{i=1}^n{U}_i}{\frac{1}{n}{\sum }_{i=1}^n{U}_i}\right]}^{\frac{1}{n}}\times \frac{1}{n}{\sum }_{i=1}^n{U}_i}=\sqrt{\frac{{\left(\prod _{i=1}^n{U}_i\right)}^{\frac{1}{n}}}{\frac{1}{n}{\sum }_{i=1}^n{U}_i}\times \frac{1}{n}{\sum }_{i=1}^n{U}_i}=\sqrt[2n]{\prod _{i=1}^n{U}_i}$$ (9)

The coordinated development degree can be divided according to the following criteria [42] (see Table 1). The higher the D value, the higher the degree of coordination between systems.

Table 1.

Division standard of coordination development degree.

Interval	D value	Categories
[ 0,0.1]	Extreme incoordination	Dissonant recession
[0.1,0.2]	Severe incoordination
[0.2,0.3]	Moderate incoordination
[0.3,0.4]	Mild incoordination
[0.4,0.5]	near incoordination	Transitional development
[0.5,0.6]	Barely coordination
[0.6,0.7]	Primary coordination	Coordinated development
[0.7,0.8]	Intermediate coordination
[0.8,0.9]	Well-coordinated
[0.9, 1]	Quality coordination

3.2. Index system design

The demand for industrial development involves the output value of the industrial development, the knowledge involved, and technical personnel. The development supply MGs refer to the total output of knowledge, technology, and other related majors in HVCs and industries [[43], [44]]. Based on this idea, and referring to the existing research literature, this paper establishes the evaluation index system of MGs-IGs matching degree (see Table 2). The index data is standardized by (1), (2), and the weights of each index and subsystem are determined by (3), (4).

Table 2.

Evaluation index of MGs - IGs matching degree.

First level index	Second level index	Three level index	unit	attribute	weight	Subsystem weight
Major groups	Resources	Educational expenditure by the government	10k¥	+	0.0507	0.6141
		Number of ordinary high school graduates	People	+	0.1151
		Number of secondary vocational school graduates	People	+	0.0502
		Number of staff and staff in institutions of higher learning	People	+	0.0554
	Scale	Number of students enrolled in higher education institutes	People	+	0.1234
		Number of students in higher education institutes	People	+	0.0496
	performance	Number of college graduates	People	+	0.0557
		Technical market turnover	100 m ¥	+	0.0516
		Number of patents granted	–	+	0.0622
Industrial groups	Resources	Total population	10k People	+	0.056
		The natural growth rate of the total population	%	+	0.0668	0.3859
	Scale	Gross regional product	100 m ¥	+	0.0787
		Number of urban workers and staff	10k People	+	0.0826
	Services	Share of employment in manufacturing	%	+	0.0508
		Registered urban unemployment rate	%	–	0.051

The development level of higher vocational MGs system can be measured by three secondary indexes, such as system resource occupancy, system scale, and system performance. It includes nine third-level indicators, such as the situation of education funds, the number of students in HVCs, and the turnover of technology markets in various regions. The development level of the industrial system can also be measured from three aspects, such as the occupancy of system resources, the size of the system, and the level of system service, and can be subdivided into nine indicators such as the total population of each region, the natural growth rate of the total population of each region, and the regional GDP.

According to Table 2, the index weights of the MG and IG are 61.41 % and 38.59 % respectively, which means that the MG has a more important impact on the matching degree. This may be because, compared with IGs, MGs are more directly involved in the aspects of talent training and technological innovation. IGs, on the other hand, focus more on the overall development of the regional economy, including various fields such as manufacturing and service industries, and their influencing factors are more extensive.

In terms of MGs, the factors affecting the matching degree are considered from the three dimensions of resources, scale, and performance respectively. In terms of resources, the number of common high school graduates in each region has the greatest influence on the matching degree, and its weight is 0.1151. In addition, it is also considered that the impact of the number of ordinary high school graduates, secondary vocational school graduates, and ordinary higher education staff on the matching degree. In terms of scale, the number of students from colleges and universities has the greatest influence on the matching degree, and its weight is 0.1234. In terms of service, the number of patents granted by region has the greatest influence on the matching degree, and its weight is 0.0622. In terms of IGs, the factors affecting the matching degree are also considered from the three dimensions of resources, scale, and service. The total population, the natural growth rate of the total regional population, the gross regional product, the number of urban workers, the proportion of manufacturing employees, and the urban registered unemployment rate have a more balanced impact on the matching degree.

4. Results and discussion

4.1. Statistical analysis of matching between regional advantageous industries and higher vocational majors

• (1)Analysis of advantageous industries

Through the analysis of the top nine industries in the industrial output value of Yi-Jing-Jing, It can be found that the advantageous industries in this region are obvious, among which the chemical industry, the agricultural and sideline products processing industry, and the non-metallic mineral products industry, are the common advantageous industries of the three cities. The electrical machinery and equipment manufacturing are the dominant industries of Yichang and Jingzhou (see Table 3).

• (2)The status of the matching between MGs and IGs in higher vocational education

Table 3.

The top industries of Yi-Jing-Jing metropolitan area.

Region industry ranking	1	2	3	4	5	6	7	8	9
Yichang	Chemical industry	Non-metallic mineral products industry	Electricity, heat production and supply industry	Agricultural and sideline product processing industry	Liquor, beverage, and refined tea manufacturing industry	Pharmaceutical manufacturing industry	Food manufacturing industry	Metal products industry	Electrical machinery and equipment manufacturing
Jingzhou	Agricultural and sideline products processing industry	Chemical industry	Electrical machinery and equipment manufacturing	Non-metallic mineral products industry	automotive industry	Computer, communications, and electronic equipment manufacturing	Textile industry	Metal products industry	Special equipment manufacturing industry
Jingmeng	Agricultural and sideline product processing industry	Chemical industry	Non-metallic mineral products industry	Oil, coal, and other fuel-processing industries	General equipment manufacturing	Rubber and plastic products industry	Textile industry	Abandoned resource utilization industry	Non-metallic mining and beneficiation industry

The case region comprises 10 vocational colleges, distributed as follows: 3 in Yichang City, including Hubei Three Gorges Polytechnic, Three Gorges Vocational College of Electric Power, and Three Gorges Tourism Vocational and Technical College; 5 in Jingzhou City, including Hubei College of Chinese Medicine; Jingzhou College; Jingzhou Institute of Technology; Jingzhou Vocational College of Technology; Yangtze River Art Engineering Vocational College; and 2 in Jingmen City, including Jingchu College of Technology, Jingmen Vocational College. This study conducted a comparative analysis of the majors offered by all vocational colleges in the region and the dominant industrial industries. It particularly emphasized the overall situation of the relevant majors offered by vocational colleges and the dominant industrial industries in the region (see Table 4), as well as the alignment between IGs and MGs within different cities (see Table 5). Hubei College of Chinese Medicine was not included in the comparative analysis because its majors were all medical.

Table 4.

Overall comparative analysis of relevant majors offered by vocational colleges and dominant industrial industries in the Yi-Jing-Jing region.

Dominant Industrial Industry	Related Majors	Colleges Offering Related Majors	Total Number of Colleges Offering Majors (Subject)	Percentage (%)
1. Chemical industry	Chemical Engineering and Technology	Jingzhou College	4	44.44
	Applied Chemical Engineering; Applied Chemical Engineering Technology	Jingzhou Institute of Technology
	Applied Chemical Engineering Technology; Chemical Automation Technology; Analysis and Testing Technology;	Hubei Three Gorges Polytechnic
	Applied Chemical Engineering Technology	Jingchu College of Technology
2. Non-Metallic Mineral Product Manufacturing	Exploration Technology and Engineering; Resource Exploration Engineering; Geographic Information Science	Jingzhou College	3	30
	Applied Chemical Engineering Technology; Chemical Automation Technology; Analysis and Testing Technology;	Hubei Three Gorges Polytechnic
	Metallurgical Engineering	Jingmen Vocational College
3. Agricultural and By-Product Processing Industry;	Modern Agricultural Economic Management; Modern Agricultural Technology;	Hubei Three Gorges Polytechnic	4	44.44
	Horticultural Technology	Jingzhou Institute of Technology
	Plant Science and Technology; Horticultural Technology	Jingchu College of Technology
	Agriculture; Horticulture;	Jingmen Vocational College

Table 5.

Comparative analysis of IGs - MGs in the Yi-Jing-Jing region by city.

Region	Dominant Industrial Industries (Top 5)	Related MGs	Number of Institutions Offering Related Majors
Yichang	1. Chemical industry	Applied Chemical Engineering Technology; Chemical Automation Technology; Analysis and Testing Technology	Hubei Three Gorges Polytechnic
	2. Non-Metallic Mineral Product Manufacturing	Applied Chemical Engineering Technology …	Three Gorges Tourism Vocational and Technical College
	3. Electricity, Heat Production, and Supply	Power Plants and Electrical Systems; Power System Automation; Thermal Power Engineering Technology …	Three Gorges Vocational College of Electric Power
		Electrical Automation Technology	Three Gorges Tourism Vocational and Technical College
	4. Agricultural and By-Product Processing Industry	Modern Agricultural Economic Management; Modern Agricultural Technology	Three Gorges Tourism Vocational and Technical College
	5. Liquor, beverage, and refined tea manufacturing industry	Tea Art and Culture; Food Inspection and Testing Technology	Three Gorges Tourism Vocational and Technical College
		Tea Art and Culture	Hubei Three Gorges Polytechnic
Jingzhou	1. Agricultural and By-Product Processing Industry.	Horticultural Technology	Jingzhou Institute of Technology
	2.Manufacture of Chemical Raw Materials and Chemical Products Industry	Chemical Engineering and Technology	Jingzhou College
		Applied Chemical Engineering Technology	Jingzhou Institute of Technology
	3.Electrical Machinery and Equipment Manufacturing Industry	Mechanical Design and Manufacturing and Automation	Jingzhou College
		Mechatronics Technology; Mechanical Design and Manufacturing	Jingzhou Vocational College of Technology
		Mechanical Design and Manufacturing …	Jingzhou Institute of Technology
	4. Non-Metallic Mineral Product Manufacturing	Exploration Technology and Engineering; Resource Exploration Engineering; Geographic Information Science	Jingzhou College
	5. Automobile Manufacturing Industry	New Energy Vehicle Technology	Yangtze River Art Engineering Vocational College
		Automobile Manufacturing and Testing Technology; New Energy Vehicle Technology; Automobile Intelligent Technology; …	Jingzhou Institute of Technology
		Automobile Manufacturing and Testing Technology; Mechatronics Technology; Mechanical Design and Manufacturing	Jingzhou Vocational College of Technology
		New Energy Science and Engineering	Jingzhou College
Jingmen	1.Agricultural and By-Product Processing Industry	Plant Science and Technology; Horticultural Technology	Jingmen College of Technology
		Agriculture; Horticulture	Jingmen Vocational College
	2. Chemical Industry	Applied Chemical Engineering Technology	Jingmen College of Technology
	3.Metal Mineral Product Industry Petroleum	Metallurgical Engineering	Jingmen Vocational College
	4.Coal and Other Fuel Processing Industry	/	/
	5.General Equipment Manufacturing Industry	Mechanical Engineering	Jingmen College of Technology
		Mechanical Design and Manufacturing; Precision Machinery Technology; …	Jingmen Vocational College

This study compares the majors with the advantageous industrial industries and finds that the MGs of HVCs in the region have a basis for matching IGs. The chemical industry is the dominant industry in Yi-Jing-Jing Metropolitan. About half of the HVCs in the city group offer related majors, and some colleges and universities have begun to build green chemical industry colleges together with the industry. Tourism is the dominant industry in Yichang, two out of the three vocational colleges offer tourism-related majors, and there is a special school for tourism. Yichang is the location of the Three Gorges Dam, “electricity, heat production and supply industry” is also an advantage of the city's industrial industries, the city also has a special school for electricity. Some HVCs are based on regional development, and pay attention to emerging industries or future advantageous industries, such as new energy vehicles and large health industries. However, they face more severe challenges:(i) Most HVCs do not pay much attention to the development of regional emerging advantageous industries. For example, the focus of future industrial development in Yichang is the biopharmaceutical industry, intelligent manufacturing industry, integrated circuit industry, new energy and new materials, and so on, but there are not enough HVCs involving related majors. (ii)The majors are relatively old, some majors have not adapted to the characteristics of the Internet era, and do not focus on the future development of the industry.

4.2. Measurement of matching degree between IGs and MGs

Based on the above analysis, this study further measured the matching degree of IGs and MGs in the region.

• (1)Measurement results of the development level of IGs and MGs in the case area

The index data is substituted into (5), (6), (7) to obtain the comprehensive development level of IGs and MGs and the comprehensive development level of IGs and MGs in each city. According to Table 6, the comprehensive development level of IGs and MGs in Yichang City is higher, followed by Jingzhou City, and Jingmen City is relatively lower. The reasons for this difference may be multiple. In terms of IGs, different cities have differences in industrial structure, economic base, policy support and other aspects, which may affect their comprehensive development level. In terms of MGs, different cities may also have differences in technical fields, talent conditions, research, and development investment, etc., which may affect their comprehensive development level. The comprehensive development level of IGs and MGs in Yichang is relatively high, which may be related to the fact that Yichang is the central city in this region. Yichang has a good location advantage and a relatively complete industrial structure. In addition, Yichang vigorously promotes scientific and technological innovation, actively introduces various high-end talents, continuously improves technological content and core competitiveness, and promotes the overall development of the city. The comprehensive development level of Jingmen City in terms of IGs is only 0.0023, which may be due to the relatively simple industrial structure of Jingmen City: mainly the traditional manufacturing industry. In terms of MGs, the comprehensive development level of Jingmen is also relatively low, Jingmen needs to increase investment in scientific and technological innovation and talent training, improve the city's core competitiveness and industrial transformation, and upgrade its ability, to promote the promotion of comprehensive development level. In terms of the development of the regional IG and the MG, the development index of the regional IG was higher than that of the MG as a whole.

Table 6.

Comprehensive development level of IGs - MGs.

	Yichang	Jingzhou	Jingmen	Overall
IGs	0.4532	0.4127	0.0023	0.2894
MGs	0.2919	0.1775	0.0737	0.1811

The overall development level of IGs and MGs is also relatively low. This situation may hurt the industrial upgrading and innovative development of the region.

Take the phosphorus chemical industry, the dominant industry in this region, for example, which occupies a certain position in the country. As shown in Table 7, the number of chemical raw materials and chemical products manufacturing enterprises in the case area accounted for about 10 % of China, and the total industrial output value and main business income accounted for about 40 % of Hubei Province in that year. The average annual number of all employees accounts for about 43 % of Hubei Province. The phosphate fertilizer production of the district accounts for about 15 % of the country, especially the phosphate fertilizer production of Yichang, which accounts for more than 10 % of the country. Located in Yichang, Hubei Xingfa Group, Hubei Yihua Group Co., LTD., located in Jingmen, Hubei Xinyangfeng Fertilizer Co., LTD., Hubei Ezhong Chemical Co., LTD., all belong to the country's main phosphorus chemical enterprises.

Table 7.

Analysis table of Yi-Jing-Jing chemical industry.

Industry-related parameters	Yichang	Jingzhou	Jingmen	Hubei	The proportion of three cities in the province (%)	Nation	Three cities in the country (%)
Number of enterprises (units)	105	87	90	949	30	21596	10 1
Total industrial output value (current price) (ten thousand yuan)	7997027	2427935	4823197	38015800	40	//	//
Phosphate rock (30 % phosphorus pentoxide) production (10000 tons)	2142.15	/	332.31	/	/	/ /	/ /
Monoamine phosphate (tons)	/	44.40	98.57	/	/	/	/
Diamine phosphate (tons)	/	66	56	/	/	/	/
Sodium tripolyphosphate (tons)	72371	/	/	/	/	/	/
Phosphate fertilizer (tons)	151	14	32	/	/	1308	15
Yellow phosphorus (tons)	52208	/	/	/	/	/	/

In the phosphorus chemical industry chain, the upstream is the raw material phosphate ore, the middle reaches are the organic matter and inorganic matter containing phosphorus, and the downstream is the product made, and finally applied to all walks of life. As can be seen from Table 8, the phosphorus chemical industry in various cities of Yi-Jing-Jing has similar products and no regional division. The products are concentrated in the fertilizer model with low added value and heavy pollution, and phosphate rock products are not effective in deep processing and comprehensive utilization, which is not conducive to the green, low-carbon, and sustainable development of the regional economy. The local chemical industry needs professionals who lead its green development to drive the adjustment of industrial layout and realize the upgrading and iteration of the industry chain to the advanced level.

• (2)Measurement results of coupling coordination degree of the IG and the MG in the case area

Table 8.

Measurement results of coupling degree of IGs - MGs.

Regions	Coupling
Yichang	0.9763
Jingzhou	0.9172
Jingmen	0.3406
Overall	0.7447

Then the results are substituted into the common formula (8), and the coupling degree measurement results of the two subsystems are obtained, as shown in Table 8. The overall coupling degree between the IG and the MG is 0.7447, indicating that there is interdependence between the IG and the MG. Yichang and Jingzhou had a relatively high degree of dependency, while Jingmen had a relatively low degree of dependency. To some extent, this result is consistent with the results in Table 4. It can be seen that HVCs in Yichang and Jingzhou actively set up majors around the advantageous industries, and almost every advantageous industry has two or more schools offering related majors. HVCs in Jingmen region are relatively backward, and the advantageous industry in this region generally has only one higher vocational college offering related majors, and some advantageous industries even have no local colleges offering related majors.

The matching degree between the IG and the MG in Yichang and Jingzhou is relatively high (see Table 9), which is 0.6178 and 0.5434 respectively. The primary coordination between the IG and the MG in Yichang has been achieved, while the coordination in Jingzhou is barely in the state. The matching degree of the Jingmen IGs and MGs is low, only 0.1008, which is in a seriously disordered state. This result shows that in Yichang and Jingzhou, the connection and dependence between the IG and the MG are closer, and the matching degree is higher. In contrast, the connections and dependencies between IGs and MGs in Jingmen are relatively weak, and the matching degree is low.

Table 9.

Measurement results of matching degree of IGs - MGs.

Regions	Match degree	Degree of match
Yichang	0.6178	Primary Match
Jingzhou	0.5434	Barely match
Jingmen	0.1008	Severe mismatch
Overall	0.4207	Near mismatch

4.3. Discussion

From the above calculations, it is evident that the MG development in the case region lags behind the development of the industries, resulting in a less optimistic matching between MGs and IGs. This aligns with existing research conclusions. For instance, Song ‘s study [45] on the coupling relationship between MGs and IGs in different provinces of China indicated that after 2010, the overall development level of China's industrial system index surpassed that of the vocational MG system index, with the gap between the two gradually increasing, although both showed an overall upward trend. In the study of vocational college MGs and IGs in Jiangsu Province over the past six years, Jiang and Zhang [46] pointed out that while the MG system and the industrial system in Jiangsu Province are both developing in the same direction, the coordination between them is generally lacking, and their coordination level needs optimization. In a study of the Guangxi Zhuang Autonomous Region, Sun and Guo [47] found that from the perspective of major settings, although vocational education in the region shows spontaneous adaptability to industrial adjustment and upgrading, there are still issues such as blind and homogeneous major settings and insufficient precision in industry alignment.

Some scholars [48] have also analyzed the degree of talent matching in different industries. For instance, in the field of public health in HVCs, it has been observed that the professional training of technical skills in the public health sector generally matches the job requirements. The curriculum settings and teaching implementations generally meet the needs of talent cultivation, but there are deficiencies and intersections in the major positioning, and the professional ethics of skilled talents lack contemporary characteristics. In the analysis of the match between the demand for technical skills in the green building industry and the major settings of HVCs, scholars [49] believe that the major distribution in HVCs is aligned with the industrial layout. However, there is a mismatch between the scale of talent demand and talent cultivation, with a significant gap in the number of undergraduate students in HVCs. Additionally, the content of the course cannot fully match the development trend. In the research on the major settings of agricultural vocational education in Guangxi, scholars [50] believe that current agricultural vocational education mainly focuses on the primary industry. There is a lack of coupling and adaptation to serve the development of the entire agricultural industry chain. There exists a structural imbalance between the supply and demand of talents in secondary vocational, higher vocational, and vocational undergraduate education in the process of agricultural industrial structure upgrading.

There are many reasons for the low matching degree between MGs and IGs. Macroscopically, it is mainly affected by the economic cycle and structural factors. Take China as an example, with the progress of technology, many new industries have emerged in recent years, but the development of majors has not kept up with the pace of industrial development, resulting in a low matching degree between MGs and IGs. At the same time, the old talent training structure, the constantly adjusting industrial structure, and the gradually aging population structure all directly or indirectly affect the matching degree. At the micro level, there is a lack of evaluation mechanisms for professional construction and industry matching. The long-term mechanism of school-enterprise cooperation has not been established and other factors also affect the matching degree of MGs and IGs.

The difficulty in effectively aligning human capital with industrial technology will lead to a distortion in the ratio of production technology to human capital investment, which in turn will lead to a decrease in the marginal output of human capital, which is detrimental to nurturing and upgrading a country's dynamic comparative advantage in industries, especially hindering the adjustment of human capital structure towards one conducive to industrial upgrading. Currently, most HVCs in China do not adapt to the scale of economic development in various cities. There is a general shortage of high-tech and high-skill talents, as evidenced by the talent shortage directories released by various regions, such as Shenzhen City's List of Skilled Talents in Short Supply (2022), Hangzhou City's List of Skilled Talents in Short Supply (2022), and so on. Therefore, enhancing the adaptability of vocational education to regional industrial structure, promoting structural reform on the supply side of vocational education, and achieving precise matching between talent cultivation supply and demand sides are urgent in China today.

5. Conclusions and suggestions

5.1. Conclusions

The main conclusions of this study are as follows:

• (1)The region has recognized the importance of matching IGs and MGs, and there is a certain basis for MGs to match IGs, but the matching degree is still not optimistic overall: IGs and MGs are on the verge of mismatch.
• (2)From the perspective of spatial characteristics, there are significant regional differences in the matching degree of IGs and MGs among the three cities: the HVCs in Yichang and Jingzhou have set up MGs around IGs, and the matching degrees of them have achieved primary matching and barely matching respectively. In Jingmen the HVCs have relatively lagged in action, the matching degree of IGs and major groups are still on the brink of mismatch.
• (3)The development level of the MG in this region lags the industrial development, which is consistent with the overall development of the national IGs and MGs. This indicates that the industry has developed rapidly due to favorable factors such as macro stimulus policies, industrial technology innovation, and international trade exchanges. However, the construction of MGs lacks foresight and has not fully kept up with and surpassed the development of the industry.

5.2. Suggestions

Given the above problems, the case area can improve the matching between MGs and IGs from the following aspects.

• (1)Strengthen policy guidance to promote the size matching between MGs and IGs

The matching of MGs with regional industries is inseparable from the guidance of the government. The government should be based on regional integration and coordinate the development of MGs and IGs. First, it is necessary to strengthen top-level design, plan the professional layout and talent training of all HVCs in the region, and integrate MGs into regional economic development planning. Focus on supporting and giving priority to the development of majors and MGs that meet the growth requirements of key regional characteristic industries and strategic emerging industries. Second, we should establish a well-structured and operable policy system for the construction of vocational education majors, and introduce combined incentive policies for HVCs with outstanding results in the construction of MGs. The third is to play a communication and coordination role between the industry and colleges and promote the effective docking of majors and industries.

• (2)Adjust the supply of higher vocational majors in response to industrial changes, and promote the structural matching between MGs and IGs

Skills education should be forward-looking and adapt to the adjustment and upgrading of industrial structure. The supply of talent should not only meet the needs of current industrial development but also provide talent support for future industrial development. HVCs should fully understand and accurately grasp the corresponding positions and talents required by regional relevant industry chain links, especially emerging industries, actively respond to the requirements of regional economic development, keep up with technological progress, production mode change, industrial structure adjustment, and upgrading, and enhance the adaptability of vocational education and regional economic and social development. The layout and direction of the construction of MGs should be clearly defined, the structure of the major should be optimized, the key majors should be established, and the development needs of the related industry chain should be seamlessly connected and appropriately ahead of the curve.

• (3)Adjust the course content according to the knowledge demand, and promote the matching of MGs and IGs

The construction of MGs should finally be implemented in the course setting and development. According to the requirements of employees' knowledge, ability, and quality in the future development of advantageous industries, courses should be set up. The course content was developed by connecting post standards and the working process, and the MG curriculum system was developed by connecting post groups. Through the cooperation of different course modules, students' professional knowledge and technical skills should be effectively improved, and students' practical ability and forward-looking employment adaptability training should be paid attention to, so that students can adapt to the needs of industrial development and effectively meet the needs of positions.

• (4)The enterprise participation in the construction of majors to facilitate seamless alignment between MGs and IGs

Enterprises should participate in the construction of majors through the joint establishment of industrial colleges, and training bases, and employing enterprise experts as part-time teachers. This ensures that knowledge transmission is closely integrated with practical social needs, thereby achieving seamless alignment between MGs and IGs. To achieve this goal, it is necessary, first, to improve the integration management system of industry-education integration. This involves fundamentally clarifying the different responsibilities, rights, and obligations between enterprises and schools as dual subjects, as well as within enterprises and schools themselves, thereby changing the current situation where various departments manage regulations in isolation and do not cooperate. Second, it is essential to improve the subsidy system for enterprise curriculum construction. Scientifically calculate the costs incurred by enterprise experts participating in curriculum system construction and provide reasonable compensation funds to enterprises.

Data availability

All data generated or analyzed during this study are included in this published article.

CRediT authorship contribution statement

Xueqing Zhao: Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing.