Operation Performance Evaluation and Optimization Based on SUPER-SBM DEA Model in Railway Industry in China

Li, Zhongdong

doi:10.1109/iscc-c.2013.96

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…Based on the above considerations, the superefficient SBM model (Super-SBM created by Tone and Sahoo) [22] combines the advantages of both the superefficient and nonradial models, takes the problem of slack variables into consideration, and effectively distinguishes efficiency differences of decisionmaking units. Using this model, Li [23], Gong et al [24], and Li and Zhai [25], respectively, analyzed China's railway transportation efficiency, industrial fossil energy use efficiency, and general airline operations efficiency.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of the Green Innovation Efficiency of Chinese Industrial Enterprises: Research Based on the Three-Stage Chain Network SBM Model

Chen

Wang

Peng

et al. 2020

Mathematical Problems in Engineering

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Green innovation is an important capability for an enterprise’s sustainable development. Evaluating the green innovation efficiency of China’s industrial enterprises can greatly affect its improvement. Considering the existing research results of green innovation efficiency evaluation, this paper added the impact of environmental factors in the technology industrialization stage. Various negative environmental externality indicators produced by industrial enterprise activities were incorporated into the undesired output, and an index system and model were constructed for evaluating the green innovation efficiency of China’s industrial enterprises. Combined with the actual data, a three-stage chain network SBM (slack-based measure) model was used to dynamically evaluate and analyze the industrial enterprises in 29 Chinese provinces. The results show that the overall efficiency of green innovation in China’s industrial enterprises has an upward trend, and the rise fluctuates during the technological development, achievement transformation, and industrialization stages. In the three major regions of China, industrial enterprises in the eastern area have the highest green innovation efficiency, and the industrial enterprises in the west and central regions have lower efficiencies. Based on the evaluation results, the corresponding countermeasures are proposed.

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Section: Methodsmentioning

confidence: 99%

Evaluation of the Green Innovation Efficiency of Chinese Industrial Enterprises: Research Based on the Three-Stage Chain Network SBM Model

Chen

Wang

Peng

et al. 2020

Mathematical Problems in Engineering

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“…The input factors employed for measuring the green economy efficiency are physical capital, human capital, and resource energy, and the expected output is the regional GDP (Table 2) [42]. The undesired output indicators consist of industrial waste, industrial waste emissions, and industrial solid waste emissions.…”

Section: Indicators and Datamentioning

confidence: 99%

The Impact of High-Tech Industry Agglomeration on Green Economy Efficiency—Evidence from the Yangtze River Economic Belt

et al. 2019

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Development is the eternal theme of the times. However, the transformation of the development mode is imminent, and we should abandon the extensive economic development mode and turn to the efficient development of an intensive mode. The high-tech industry will be the decisive force in future industrial development. The agglomeration of the industry will help form economies of scale, thereby improving the effective allocation of resources and promoting productivity. The increase in green economy efficiency is a key factor in achieving green development and an important indicator of achieving the coordinated development of economic development and environmental protection. Therefore, in this study, we try to improve the efficiency of the green economy through industrial agglomeration to achieve green development. In order to solve this problem, we took the Yangtze River Economic Belt as the research object, used Super Slacks-based Measure (SBM) data envelopment analysis (DEA) and general algebraic modeling system (GAMS) to study the green economy efficiency, and then used the system generalized moment method (SGMM) to study the impact of high-tech industry agglomeration on green economy efficiency. According to the empirical test, we found that (1) the green economy efficiency of the Yangtze River Economic Belt shows a volatile upward trend, (2) the green economy efficiency of the Yangtze River Economic Belt differs with time and by region, (3) the agglomeration of the high-tech industry has a lagging effect on the improvement of green economy efficiency, and (4) the regression coefficients of economic development and foreign direct investment are positive and those of environmental regulation and urbanization are negative. Finally, in this paper, we provide corresponding policy recommendations to promote the agglomeration of high-tech industries, thereby improving the efficiency of the green economy.

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“…For evaluation of the inter-regional railway operation performance for 30 provinces in China, [123] adopted the SUPER-SBM DEA method dealing with uncontrollable factors. By DEA, in [66] the relative operational efficiency of 24 European railways in capacity utilization was studied.…”

Section: Data Envelopment Analysis (Dea)mentioning

confidence: 99%

Modern Railway Engineering

Hessami¹

2018

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Innovation at Vega Systems. His expertise is in systems assurance, safety, security, sustainability, and knowledge management methodologies and has a background in design and development of critical safety systems. His project managed the safety analysis of the European Rail Traffic Management System's ETCS for the European Commission and led the development of an advanced and systematic safety management system under SAMRail project in support of railway safety directive. He represents the UK on CENELEC & IEC safety systems and hardware and software standards for railway applications and served as a convenor for review of EN50128 software safety and TR50506-1 standards. He is also a member of CENELEC WG26, Railway Cyber Security Standardization. He is a visiting professor at the

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Operation Performance Evaluation and Optimization Based on SUPER-SBM DEA Model in Railway Industry in China

Cited by 4 publications

References 14 publications

Evaluation of the Green Innovation Efficiency of Chinese Industrial Enterprises: Research Based on the Three-Stage Chain Network SBM Model

Evaluation of the Green Innovation Efficiency of Chinese Industrial Enterprises: Research Based on the Three-Stage Chain Network SBM Model

The Impact of High-Tech Industry Agglomeration on Green Economy Efficiency—Evidence from the Yangtze River Economic Belt

Modern Railway Engineering

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