Spatiotemporal analysis for investment efficiency of China's rural water conservancy based on DEA model and Malmquist productivity index model

被引:29
作者
Yan, Jingning [1 ,2 ]
机构
[1] Hohai Univ, Coll Water Conservancy & Hydropower Engn, Xikang Rd 1, Nanjing 210098, Jiangsu, Peoples R China
[2] Nanchang Hangkong Univ, Sch Civil Engn & Architecture, Fenghenan Rd 696, Nanchang 330063, Jiangxi, Peoples R China
关键词
Rural water conservancy; Investment efficiency; Spatiotemporal analysis; China; Data envelopment analysis (DEA); Malmquist productivity index (MPI); DATA ENVELOPMENT ANALYSIS; INFRASTRUCTURE; CONSTRUCTION; SYSTEMS;
D O I
10.1016/j.suscom.2018.11.004
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Rural water conservancy is crucial to the development of agriculture which is the foundation of national economy in China. During the period of the 12th Five-Year Plan from 2011 to 2015, Chinese government promoted the rural water conservancy investment vigorously and obtained some achievements. Meanwhile, there were some problems faced in the rural water conservancy such as a weak foundation of rural water conservancy, an uneven distribution of rural water resources by time and space, low investment efficiency. Therefore, the investment efficiency of rural water conservancy needs to be systematically and comprehensively evaluated, and the evaluation results for the period of the 12th Five-Year Plan from 2011 to 2015 can provide reliable references for China's rural water conservancy investment over the period of the 13th Five-Year Plan from 2016 to 2020. Based on the existing study findings, this study conductes the empirical analysis for the investment efficiency of China's rural water conservancy during the period of 2011 to 2015 using the data envelopment analysis (DEA) model and Malmquist productivity index (MPI) model from the spatiotemporal perspective. The statistical data of the 31 provinces over the period of 2011 to 2015 are gathered as inputs and outputs of the DEA model and MPI model. It finds that the average investment efficiency of China's rural water conservancy in each year during the study period is 0.732 and the investment efficiency fluctuates for the same period, which is mainly caused by scale efficiency (SE). The investment efficiency of China's rural water conservancy is decreased by an average of 1.2% from 2011 to 2015, which is principally due to technology change (TC). From the regional aspect, the investment efficiency of rural water conservancy in the eastern, central, northeast and western regions increase successively, which means uneven distribution of investment efficiency among the four regions. Based on the MPI analysis of the four regions, only the investment efficiency of eastern region improved by an average of 4.3% for each year, while the investment efficiency of the other three regions all decreased. At the provincial level, disequilibrium in the investment efficiency of rural water conservancy existed in the 31 provinces. Only the four provinces including Shanghai, Hainan, Tibet and Xinjiang were DEA efficiency for each year during the study period. The improvement of the investment efficiency among the 31 provinces in China mainly relied on the investment expansion and the technology innovation of rural water conservancy. Furthermore, the method provided in this study can be not only used to analyze the investment efficiency of rural water conservancy in other developing countries, but also to evaluate the investment efficiency of the other fields in the time and space dimensions. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:56 / 71
页数:16
相关论文
共 50 条
[31]   Evaluating China's primary healthcare services' efficiency and spatial correlation: a three-stage DEA-Malmquist model [J].
Huang, Rui ;
Li, Wan ;
Shi, Baoguo ;
Su, Hao ;
Hao, Jing ;
Zhao, Chuanjun ;
Chai, Juhong .
FRONTIERS IN PUBLIC HEALTH, 2024, 12
[32]   DEA Malmquist productivity index based on a double-frontier slacks-based model: Iranian road safety assessment [J].
Ganji, S. S. ;
Rassafi, A. A. .
EUROPEAN TRANSPORT RESEARCH REVIEW, 2019, 11 (01)
[33]   The Operation Efficiency Evaluation for Listed Companies of China Aviation Industry Based on DEA and Malmquist Index [J].
XIA Wei-li ;
CHENG Jun-heng ;
WU Peng ;
GONG Shu-yan .
InternationalJournalofPlantEngineeringandManagement, 2012, 17 (04) :223-229
[34]   Measure of the Ecological Technological Innovation Efficiency of China's Industrial Sectors-Based on Super-efficiency DEA Model [J].
Xia Weili ;
Chen Chen ;
Jiang Jijiao .
PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON PRODUCT INNOVATION MANAGEMENT, VOLS I AND II, 2009, :389-397
[35]   Natural and Managerial Disposability Based DEA Model for China's Regional Environmental Efficiency Assessment [J].
Zhou, Xiaoyang ;
Chen, Hao ;
Wang, Hao ;
Lev, Benjamin ;
Quan, Lifang .
ENERGIES, 2019, 12 (18)
[36]   Efficiency and Productivity of Public Hospitals in Serbia Using DEA-Malmquist Model and Tobit Regression Model, 2015-2019 [J].
Medarevic, Aleksandar ;
Vukovic, Dejana .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2021, 18 (23)
[37]   Research on the investment efficiency based on grey correlation-DEA model [J].
Yu, Hongxin ;
Zhao, Yuanjun ;
Liu, Wei ;
Gao, Luwen .
ANNALS OF OPERATIONS RESEARCH, 2023, 326 (SUPPL 1) :53-53
[38]   Analysis of regional differences in green energy efficiency in countries along "the Belt and Road" Initiative zone-Based on super efficiency DEA model and Malmquist index method [J].
Li, Sumin ;
Wu, Meng ;
Song, Meizhe .
FRONTIERS IN ENERGY RESEARCH, 2023, 11
[39]   Evaluation of technological innovation efficiency of petroleum companies based on BCC-Malmquist index model [J].
Wang, Yanqiu ;
Zhu, Zhiwei ;
Liu, Zhenbin .
JOURNAL OF PETROLEUM EXPLORATION AND PRODUCTION TECHNOLOGY, 2019, 9 (03) :2405-2416
[40]   Exploring Northwest China's agricultural water-saving strategy: analysis of water use efficiency based on an SE-DEA model conducted in Xi'an, Shaanxi Province [J].
Mu, L. ;
Fang, L. ;
Wang, H. ;
Chen, L. ;
Yang, Y. ;
Qu, X. J. ;
Wang, C. Y. ;
Yuan, Y. ;
Wang, S. B. ;
Wang, Y. N. .
WATER SCIENCE AND TECHNOLOGY, 2016, 74 (05) :1106-1115