Fujian’s Industrial Eco-Efficiency: Evaluation Based on SBM and the Empirical Analysis of lnfluencing Factors

Abstract

The coordinated development of industrialization and its ecological environment are vital antecedents to sustainable development in China. However, along with the accelerating development of industrialization in China, the contradiction between industrial development and environment preservation has turned out to be increasingly evident and inevitable. Eco-efficiency can be seen either as an indicator of environmental performance, or as a business strategy for sustainable development. Hence, industrial eco-efficiency promotion is the key factor for green industrial development. This study selects indicators relevant to resources, economy, and the environment of industrial development, and the indicators can well reflect the characteristics of industrial eco-efficiency. The SBM (Slacks-Based Measure) model overcomes the limitations of a radial model and directly accounts for input and output slacks in the efficiency measurements, with the advantage of capturing the entire aspect of inefficiency. This study evaluates the industrial eco-efficiency of nine cities in Fujian province during the period of 2006–2016, based on undesired output SBM (Slacks-Based Measure) model and also uses a Tobit regression model to analyze the influencing factors. The results show that there is a positive correlation among the economic development level, opening level, research and development (R&D) innovation, and industrial eco-efficiency in Fujian Province. However, a negative correlation was found between the industrial structure and industrial eco-efficiency in Fujian Province. Moreover, environmental regulation in Fujian Province was not found to significantly influence the industrial eco-efficiency. Hence, through the systematic analysis of industrial eco-efficiency and its influencing factors in Fujian, the study gives further insight on how policy-making can help achieve sustainable development, balancing between economic benefits and ecological improvements.

China’s Provincial Environmental Efficiency Evaluation and Influencing Factors of the Mining Industry Considering Technology Heterogeneity

“…This paper used Tobit model to estimate the influencing factors of the EE of CMI. The MFEE, a restricted dependent variable, has its value between 0 and 1 Using ordinary least squares (OLS) will cause biased estimates and regression coefficient inconsistency [56,61,62].Thus, we used Tobit panel econometric model for regression analysis so that we could get a consistent estimate of the parameters. The data of influencing factors were collected from China Statistical Yearbook [50], China Science and Technology Statistical Yearbook [63], China Environmental Statistical Yearbook [64], China Industrial Statistical Yearbook [49] and China Land and Resources Statistical Yearbook [7].The Tobit econometric model is established as Eq.…”

“…In recent years, the research between environmental regulation and environmental efficiency has attracted extensive attention from scholars [17,55,56]. The mining industry is a high consumption, high pollution, high emission ("three highs") industry and China has issued a number of policies aiming at improving the resource utilization efficiency of mining industry and reducing pollutant emissions.…”

“…5. Industrial structure Differences in industrial structure will affect the demand for mineral products, which will have a certain impact on the development of the mining industry [56,58]. This paper uses the proportion of the tertiary industrial added value to the secondary industrial added value to measure the heightening of the industrial structure, and explores the impact of the industrial structure of each province on the environmental efficiency of the mining industry.…”

An Empirical Study on the Ecological Economy of the Huai River in China

“…The basic form of the DEA model is the Charnes-Cooper-Rhodes (CCR) model [26]. The DEA model was improved to the Banker-Charnes-Cooper (BCC) [27] and slacks-based measure (SBM) [28] models on the basis of the CCR model. The comprehensive ecological economic efficiency [29] of the decision-making units can be measured by constructing multiple input indicators and output indicators in the CCR model under the assumption that the cone condition is satisfied.…”

Sustainable Innovation Governance: An Analysis of Regional Innovation with a Super Efficiency Slack-Based Measure Model

“…Karadayi and Ekinci [50] evaluated the R&D performance of EU countries using categorical DEA models and examined the relationship between R&D performance and political-regulatory-economic situation of the countries. Wang et al [51] evaluated the industrial eco-efficiency of Fujian province in China with an SBM-DEA model. He et al [52] analyzed the impact of government competition on regional R&D efficiency through the DEA model.…”