Examination of the Interconnection and Coordination Degree between Higher Vocational Professional Groups and Industrial Structure, along with Spatiotemporal Dynamic Evolution

DOI: https://doi.org/10.62517/jhve.202516207

Author(s)

Xudong Liu, Yurong Zhao*, Runhua Li

Affiliation(s)

School of Applied Science and Technology, Beijing Union University, Beijing, China

Abstract

Professional clusters in higher vocational education help develop human capital in the manufacturing sector, working in harmony with the external industrial framework to advance social and economic growth. This study explores the spatial distribution patterns, sources of disparity, and spatio-temporal evolution trends of the two coupling coordination levels using panel data from 29 Chinese provinces from 2015 to 2022 and the coupling coordination model, Dagum Gini coefficient, kernel density function, and spatial Markov chain model. The analysis shows that coupling coordination gradually increased to 0.4413 in 2022. Positive global spatial autocorrelation shows a “high-high” agglomeration in the east and a “low-low” in the west. Positive regional spatial distribution of coupling coordination level. Eastern-western differences are the main cause of the growing regional gap. The developmental trajectory from low-order to high-order, with significant inter-regional nuclei. Geographic variables cause path dependency in the transition to coordinated development, defined by club convergence, making leapfrog development difficult in the short term. To advance the synergistic evolution of higher vocational education and industrial economic development, vocational education must be more adaptable, the inter-regional synergistic development strategy deepened, and a new framework for industrial innovation and integrated development must be created.

Keywords

Higher Vocational Professional Group; Industrial Structure; Coupling Coordination; Spatiotemporal Evolution

References

[1] Schultz T W. Investment in human capital. The American economic review, 1961, 51(1): 1-17. [2] Denison E F. Education, economic growth, and gaps in information. Journal of Political Economy, 1962, 70(5, Part 2): 124-128. [3] Romer P M. Increasing returns and long-run growth. Journal of political economy, 1986, 94(5): 1002-1037. [4] Lucas Jr R E. On the mechanics of economic development. Journal of monetary economics, 1988, 22(1): 3-42. [5] Tilak J B G. Vocational education and training in Asia//International handbook of educational research in the Asia-Pacific region: Part one. Dordrecht: Springer Netherlands, 2003: 673-686. [6] Hanushek E A, Schwerdt G, Woessmann L, et al. General education, vocational education, and labor-market outcomes over the lifecycle. Journal of human resources, 2017, 52(1): 48-87. [7] Rijal N. Role of Technical and Vocational Education in Economic Development of Nepal. Available at SSRN 3502894, 2019. [8] Indrawati S M, Kuncoro A. Improving competitiveness through vocational and higher education: Indonesia’s vision for human capital development in 2019–2024. Bulletin of Indonesian Economic Studies, 2021, 57(1): 29-59. [9] Onatere-Ubrurhe J O, Ubrurhe E. The Role of Technical and Vocational Education and Training (TVET) and Rail Transportation in the Socio-Economic Development of Nigeria. International Journal of Vocational and Technical Education Research, 2024, 10(2): 13-27. [10] Arrow K J. Higher education as a filter. Journal of public economics, 1973, 2(3): 193-216. [11] Ren X, Zhou Y. Coupling and coordinated development of higher vocational education and economic development in the Yangtze River economic belt from 2008 to 2020. Computational Intelligence and Neuroscience, 2022, 2022(1): 2643635. [12] Xiong H, Chang K. The Impact of Vocational Education on the High-Quality Development of Local Economy in the New Era. Advances in Vocational and Technical Education, 2022, 4(4): 63-69. [13] Xu Qiuyan, Shao Xiuhua, Hao Han. An empirical study on the impact of China's vocational education hierarchy on industrial structure upgrading. Mathematical Statistics and Management, 2023, 42 (06): 1103-1112. [14] Shi Weiping, Fan Qiyin, Huang Songjie. Mechanism, evaluation and enlightenment of coupling coordination between higher vocational education and regional economy in China. Modern Education Management, 2024 (04) : 106-118. [15] Hu Dexin, Pang Dandan. Measurement of the coupling coordination level between higher vocational education and industrial development under the perspective of new quality productivity. Educational Academic Monthly, 2024 (05) : 27-36. [16] He Jingshi, Xu Lan, Ye Shanchun, et al. Spatial spillover effect of higher vocational education in China on the optimization and upgrading of industrial structure. Chongqing Higher Education Research, 2024, 12 (01): 74-85. [17] Tomal M. Evaluation of coupling coordination degree and convergence behaviour of local development: A spatiotemporal analysis of all Polish municipalities over the period 2003–2019. Sustainable Cities and Society, 2021, 71: 102992. [18] Gedamu W T, Plank-Wiedenbeck U, Wodajo B T. A spatial autocorrelation analysis of road traffic crash by severity using Moran’s I spatial statistics: A comparative study of Addis Ababa and Berlin cities. Accident Analysis & Prevention, 2024, 200: 107535. [19] Martin A J F, Conway T M. Using the Gini Index to quantify urban green inequality: A systematic review and recommended reporting standards. Landscape and Urban Planning, 2025, 254: 105231. [20] Xie Z, Yan J. Kernel density estimation of traffic accidents in a network space. Computers, environment and urban systems, 2008, 32(5): 396-406. [21] Shepero M, Munkhammar J. Spatial Markov chain model for electric vehicle charging in cities using geographical information system (GIS) data. Applied energy, 2018, 231: 1089-1099. [22] Agovino M, Crociata A, Sacco P L. Proximity effects in obesity rates in the US: A Spatial Markov Chains approach. Social Science & Medicine, 2019, 220: 301-311.