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The transportation industry is characterized as a capital-intensive industry that plays a crucial role in economic and social development, and the rapid expansion of this industry has led to serious environmental problems, which makes the eco-efficiency analysis of the transportation industry an important issue. Previous research paid little attention to the regulatory scenarios and suffered from the incomparability problem, hence this paper aims to reasonably estimate the eco-efficiency and identify its evolutionary characteristics. We measure the eco-efficiency and the corresponding global Malmquist–Luenberger productivity index using a modified model of the data envelopment analysis framework, in which different regulatory constraints are incorporated. Based on the empirical study on the transportation industry of thirty provinces in China, we find that the eco-efficiency of Chinese transportation industry experienced a slight increase during 2015–2016, a sharp decline during 2016–2017, and a continuous rise since year 2017. The Middle Yangtze River area was the best performer among the eight regions in terms of eco-efficiency, while the Southwest area was placed last. The global Malmquist–Luenberger productivity index showed an earlier increase and later decrease trend, which was quite consistent with the reality of the variation of inputs and outputs and the emergence of COVID-19. Moreover, the best practice gap change was found to be the main driven force of productivity. The empirical results verify the practicability of our measurement models and the conclusions can be adopted in guiding the formulation of corresponding policies and regulations. [ABSTRACT FROM AUTHOR]

This paper attempts to examine whether the environmental Kuznets curve (EKC) hypothesis is supported in MENA countries. We use, a novel RAM (range-adjusted measure)-based global Malmquist-Luenberger productivity index, accounting for slacks of inputs as well as desirable and undesirable outputs, to evaluate and decompose "green" productivity growth rates into technical change, pure efficiency change and scale change. By employing a panel smooth transition regression (PSTR) model, we investigate the income elasticity of environmental performance with respect to the decomposition factors. Our empirical results show that there are double thresholds when technical change and scale change are taken as transition variables, then leading to an inverted N-shaped curve between income and environmental performance. A single threshold is found when pure efficiency change is considered as a transition variable, yielding to an inverted U-shaped curve. Thus, our research does not find support for the EKC hypothesis. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the scientific productivity of China's science system. This paper employs the Malmquist productivity index (MPI) based on Data Envelopment Analysis (DEA). The results reveal that the overall efficiency of Chinese universities increased significantly from 2009 to 2016, which is mainly driven by technological progress. From the perspective of the functions of higher education, research and transfer activities perform better than the teaching activities. As an implication, the indicator selection mechanism, investigation period and the MPI model can be further extended in the future research. The results indicate that Chinese education administrative departments should take actions to guide and promote the teaching activities and formulate reasonable resource allocation regulations to reach the balanced development in Chinese universities. This paper selects 58 Chinese universities and conducts a quantified measurement during the period 2009–2016. Three main functional activities of universities (i.e. teaching, researching, and application) are innovatively categorized into different schemes, and we calculate their performance, respectively. [ABSTRACT FROM AUTHOR]

- Raising the aggregation issue in CSP measurement. - Reliability of DEA without explicit input as an aggregated measure of CSP. - Raising the endogeneity issue in the CSP – FP relationship. - Appropriateness of using GMM estimator in observational panel data. - Negative significant relationship between CSP and FP. The aim of this paper is twofold: to provide a novel methodology for the development of a multidimensional and aggregated measure of Corporate Social Performance (CSP) based on Data Envelopment Analysis (DEA), and to investigate the relationship between CSP and financial performance (FP) while accounting for endogeneity issues. Hence, we exploit several estimators from both static panel and dynamic panel data models to show that the GMM estimator is more adequate than the traditional estimators based on fixed or random effects. Our results show that corporate social performance impacts negatively and significantly financial performance. [ABSTRACT FROM AUTHOR]