Efficiency of Listed Real Estate Companies in China Based on the Two-stage DEA

被引:0
作者
Li Ming-di [1 ]
Ge Hong [1 ]
Guo Yu-wei [1 ]
机构
[1] Harbin Inst Technol, Sch Management, Harbin 150001, Peoples R China
来源
2014 INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE & ENGINEERING (ICMSE) | 2014年
关键词
efficiency; listed company; real estate; two-stage DEA;
D O I
暂无
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
With the rapid development of the real estate industry in China, a growing number of real estate companies have chosen to be listed on the stock market. In order to assess the ability of raising funds in the market and its impact on the enterprise performance, a real estate company is divided into the operating stage and the financing stage, and both stages are connected in series. This paper aimed to evaluate the operational efficiency and market efficiency of some top-100 companies in 2012 listed in Shanghai and Shenzhen stock market by conducting two-stage DEA. The results show that about 75.9% of the companies involved in evaluation have a high operational efficiency, and only 14.8% of them are performing better in the market. The main reason for the inefficiency comes from the financing stage, and the low market efficiency leads to the inefficiency of the companies. By decomposing the technical efficiency into pure technical and scale efficiency, we found that it is the pure technical efficiency in the financing stage results in the market inefficiency. It comes out that under the current economic condition in China, real estate firms should be make cautious decision regard to financing by listing in the market.
引用
收藏
页码:1313 / 1318
页数:6
相关论文
共 50 条
[41]   A Two-stage Evaluation Model for IT Investment Based on Interval DEA [J].
Zhang, Xiuzhi ;
Xia, Zhijie .
PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON ELECTRONIC COMMERCE AND SECURITY, VOL II, 2009, :400-+
[42]   Energy consumption, CO2 emissions, and agricultural disaster efficiency evaluation of China based on the two-stage dynamic DEA method [J].
Fang-rong Ren ;
Ze Tian ;
Hang-sheng Chen ;
Yu-ting Shen .
Environmental Science and Pollution Research, 2021, 28 :1901-1918
[43]   Evaluating the Efficiency of Decision Making Units in Fuzzy two-stage DEA Models [J].
Shureshjani, Roohollah Abbasi ;
Askarinejad, Sara ;
Foroughi, Ali Asghar .
FUZZY INFORMATION AND ENGINEERING, 2022, 14 (03) :291-313
[44]   A two-stage variational jump point detection algorithm for real estate analysis [J].
Choy, Siu-Kai ;
Yu, Carisa K. W. ;
Lee, Tanki C. L. ;
Lam, Benson S. Y. ;
Wong, Catherine Y. W. .
LAND USE POLICY, 2021, 111
[45]   Evaluating Taiwanese Bank Efficiency Using the Two-Stage Range DEA Model [J].
Kong, Wei-Hsin ;
Fu, Tsu-Tan ;
Yu, Ming-Miin .
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2017, 16 (04) :1043-1068
[46]   Energy consumption, CO2 emissions, and agricultural disaster efficiency evaluation of China based on the two-stage dynamic DEA method [J].
Ren, Fang-rong ;
Tian, Ze ;
Chen, Hang-sheng ;
Shen, Yu-ting .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2021, 28 (02) :1901-1918
[47]   A TWO-STAGE DEA MODEL TO EVALUATE AGRICULTURAL EFFICIENCY IN CASE OF SERBIAN DISTRICTS [J].
Horvat, Aleksandra Marcikic ;
Radovanov, Boris ;
Popescu, Gheorghe H. ;
Panaitescu, Casen .
EKONOMIKA POLJOPRIVREDA-ECONOMICS OF AGRICULTURE, 2019, 66 (04) :965-974
[48]   Efficiency Decomposition for the Relational Two-Stage Network DEA Approach with Satisfaction Degree [J].
Chen, Jie ;
Zou, Zezhou ;
Gao, Jinwu .
2024 10TH INTERNATIONAL CONFERENCE ON BIG DATA AND INFORMATION ANALYTICS, BIGDIA 2024, 2024, :467-473
[49]   Application of DEA in the Value Optimization Study of China Listed Media Companies [J].
Jiang, Hui-chen ;
Liu, Shan-cun .
PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT: INNOVATION AND PRACTICE IN INDUSTRIAL ENGINEERING AND MANAGEMENT (VOL 2), 2016, :761-769
[50]   Efficiency Decomposition in two-stage Data Envelopment Analysis: An application to Life Insurance companies in India [J].
Suvvari Anandarao ;
S. Raja Sethu Durai ;
Phanindra Goyari .
Journal of Quantitative Economics, 2019, 17 :271-285