Input-output efficiency, productivity dynamics, and determinants in western China’s higher education: A three-stage DEA, global Malmquist index, and Tobit model approach

Amid rapid globalization and the expansion of the knowledge economy, enhancing input-output efficiency of higher education is essential for regional development and national competitiveness. In resource-constrained regions like western China, it is of utmost significance to obtain efficiency gains by accurately assessing this efficiency and identifying its determinants, which are crucial for balanced regional development and educational equity. This study employs a comprehensive research methodology, combining a three-stage Data Envelopment Analysis, the global Malmquist productivity index, and a Tobit model to systematically evaluate input-output efficiency, productivity dynamics, and factors influencing technical efficiency in higher education across 12 provinces in western China from 2010 to 2022. The findings reveal that environmental factors and random errors significantly affect the input-output efficiency of higher education in western China, resulting in an overestimation of overall efficiency. Adjusted values for technical efficiency, pure technical efficiency, and scale efficiency are 0.8510, 0.9761, and 0.8707, respectively. Although most western provinces demonstrate relatively high pure technical efficiency, deficiencies in scale efficiency reduce overall technical efficiency, particularly in Tibet, Qinghai, and Ningxia. Total factor productivity exhibits a modest annual growth rate of 1.05%, driven by both technical efficiency advancements and technological progress, with technical efficiency change-primarily via enhanced scale efficiency-acting as the main contributor. Moreover, human capital structures and educational funding allocations significantly impact technical efficiency. Specifically, the proportion of full-time faculty with senior or associate senior academic titles and per-student education expenditure have a significantly negative influence on technical efficiency, whereas the share of operating expenses in total higher education expenditure and the proportion of employees with at least a college education are positively correlated with technical efficiency. This study offers empirical evidence to inform the formulation of targeted policies for the development of higher education in western China.

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Journal
PLoS ONE
Published
2025-06-11
DOI
https://doi.org/10.1371/journal.pone.0325901
Citations
4
Primary Topic
Efficiency Analysis Using DEA
Type
article
Field-Weighted Citation Impact
8.43
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article

Input-output efficiency, productivity dynamics, and determinants in western China’s higher education: A three-stage DEA, global Malmquist index, and Tobit model approach

Meng Ye, Rui Guo
4 citations
PLoS ONE
Efficiency Analysis Using DEA
8.43
article

Input-output efficiency, productivity dynamics, and determinants in western China’s higher education: A three-stage DEA, global Malmquist index, and Tobit model approach

Meng Ye, Rui Guo
article en
4 citations

Abstract

Amid rapid globalization and the expansion of the knowledge economy, enhancing input-output efficiency of higher education is essential for regional development and national competitiveness. In resource-constrained regions like western China, it is of utmost significance to obtain efficiency gains by accurately assessing this efficiency and identifying its determinants, which are crucial for balanced regional development and educational equity. This study employs a comprehensive research methodology, combining a three-stage Data Envelopment Analysis, the global Malmquist productivity index, and a Tobit model to systematically evaluate input-output efficiency, productivity dynamics, and factors influencing technical efficiency in higher education across 12 provinces in western China from 2010 to 2022. The findings reveal that environmental factors and random errors significantly affect the input-output efficiency of higher education in western China, resulting in an overestimation of overall efficiency. Adjusted values for technical efficiency, pure technical efficiency, and scale efficiency are 0.8510, 0.9761, and 0.8707, respectively. Although most western provinces demonstrate relatively high pure technical efficiency, deficiencies in scale efficiency reduce overall technical efficiency, particularly in Tibet, Qinghai, and Ningxia. Total factor productivity exhibits a modest annual growth rate of 1.05%, driven by both technical efficiency advancements and technological progress, with technical efficiency change-primarily via enhanced scale efficiency-acting as the main contributor. Moreover, human capital structures and educational funding allocations significantly impact technical efficiency. Specifically, the proportion of full-time faculty with senior or associate senior academic titles and per-student education expenditure have a significantly negative influence on technical efficiency, whereas the share of operating expenses in total higher education expenditure and the proportion of employees with at least a college education are positively correlated with technical efficiency. This study offers empirical evidence to inform the formulation of targeted policies for the development of higher education in western China.

PLoS ONEVol. 20(6)
Dalian Maritime University (CN)
Openalex Percentile: Top 3%
Efficiency Analysis Using DEA
8.43
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