Efficiency evaluation of regional economic development of mining and metallurgy city based on DEA model

被引:0
作者
Xiong Y. [1 ]
Zhang S. [2 ]
Lan J. [2 ]
Chen F. [2 ]
机构
[1] Research Centre of Mining and Metallurgy Culture and Socio-economic Development in, Hubei Polytechnic University, 16, Guilin North Road, Huangshi
[2] School of Economics and Management, Hubei Polytechnic University, 16, Guilin North Road, Huangshi
来源
International Journal of Applied Decision Sciences | 2019年 / 12卷 / 03期
关键词
CCR model; Data envelopment analysis; DEA; Decision making unit; DMU; Efficiency evaluation;
D O I
10.1504/IJADS.2019.100439
中图分类号
学科分类号
摘要
As the second largest city in Hubei province in the past, Huangshi city’s mining and metallurgy culture has a long history. As data collection difficulty and research integrity, this study includes the Hubei province as research scope. Mining and metallurgy economy is an important content of mining and metallurgy culture. Based on the input-output data of Hubei province from 2012 to 2016, the study applies CCR model of the DEA method to setup an evaluation indicator system of regional economy development efficiency. As a typical representative of mining and metallurgy city, Huangshi is taken as an example to be made the projection analysis on some non-DEA efficient areas. Based on the angle of mining and metallurgy city, some measures are put forward the in improving the efficiency of regional economic development. The established indicators system has a certain significance in enriching the existing research and projection analysis of the assessment results have certain guiding significance to adjust the input and output of major municipalities. Copyright © 2019 Inderscience Enterprises Ltd.
引用
收藏
页码:242 / 256
页数:14
相关论文
共 42 条
[1]  
Agreh O.Y., Ghaffarihadigheh A., Application of Dempster-Shafer theory in combining the experts’ opinions in DEA, Journal of the Operational Research Society, 9, pp. 1-11, (2018)
[2]  
Aji Y., An AHP-DEA-based vendor selection approach for an online trading platform, International Journal of Applied Decision Sciences, 6, 1, pp. 66-82, (2013)
[3]  
Banker R.D., Chang H., Zheng Z., On the use of super-efficiency procedures for ranking efficient units and identifying outliers, Annals of Operations Research, 250, 1, pp. 21-35, (2017)
[4]  
Bo H., Shu L.C., Yu M.M., Shen L.K., Wang D.J., Performance evaluation of the Taiwan Railway Administration, Annals of Operations Research, 259, 1-2, pp. 1-38, (2017)
[5]  
Charnes A., Cooper W.W., Rhodes E., Measuring the efficiency of decision making units, European Journal of Operation Research, 2, 6, pp. 429-444, (1978)
[6]  
Chen H., He P., Zhang C.X., Liu Q., Efficiency of technological innovation in China’s high tech industry based on DEA method, Journal of Interdisciplinary Mathematics, 20, 6-7, pp. 1493-1496, (2017)
[7]  
Chen Q., Evaluation on city’s construction of ecological civilization of mining and metallurgy based on gray correlation theory, International Journal of Smart Home, 10, 1, pp. 243-250, (2016)
[8]  
Cheng X., Li F.R., Wang Q.L., Xie C., On the relationship between the mining & metallurgy culture and the development of Huangshi – Based on the content analysis of news reports from 2005 to 2017, Journal of Hubei Polytechnic University (Humanities and Social Science), 35, 5, pp. 10-13, (2018)
[9]  
Cook W.D., Du J., Zhu J., Units invariant DEA when weight restrictions are present: Ecological performance of us electricity industry, Annals of Operations Research, 255, 1-2, pp. 1-24, (2017)
[10]  
Eyni M., Tohidi G., Mehrabeian S., Applying inverse DEA and cone constraint to sensitivity analysis of DMUs with undesirable inputs and outputs, Journal of the Operational Research Society, 68, 1, pp. 1-7, (2017)