[논문]중국 31개 성 및 직할시의 도시화 효율성 분석에 관한 연구

주이희; 전준우; 김형호

doi:10.14400/jdc.2019.17.12.147

초록
AI-Helper

본 연구의 목적은 도시화 과정에서 생산되는 바람직한 산출과 기대 하지 않는 산출 모두를 포함하여 중국 31개 성과 직할시에 대해 도시화 효율성을 분석하는 것이다. 중국 31개 성 및 직할시의 2017년 도시화 관련 산출 데이터를 활용하여 SBM-DEA모델을 적용해 효율성을 분석하였다. 분석결과 동부지역의 도시화 효율이 가장 높고 중부와 동북지역의 도시화 효율이 그 다음으로 낮으며 서부지역은 도시화 효율이 상대적으로 가장 낮은 것으로 나타났다. 본 연구는 중국 31개 성 및 직할시의 도시화 추진의 효율성을 분석하고 지속적인 도시화 정책 추진의 방향을 제시하였다는데 의의가 있다. 이번 연구는 2017년 1년간의 횡단면적 분석만 시행하여 과거의 추이를 반영하지 못한 한계가 있으며, 향후 종단면적 분석을 추가적으로 실시하여 도시화 효율성을 종합적으로 평가할 필요가 있다.

Abstract ▼ AI-Helper

The purpose of this study is to analyze the efficiency of urbanization in 31 provinces and cities in China, including both desirable and non-expected outputs produced during the urbanization process. Efficiency was analyzed by applying the SBM-DEA model using the urbanization calculation data of 201...

The purpose of this study is to analyze the efficiency of urbanization in 31 provinces and cities in China, including both desirable and non-expected outputs produced during the urbanization process. Efficiency was analyzed by applying the SBM-DEA model using the urbanization calculation data of 2017 in 31 provinces and cities in China. The results show that the urbanization efficiency of eastern region is the highest, followed by central region and northeast region, and the urbanization efficiency of western region is the lowest. This study is meaningful in that it analyzes the efficiency of urbanization in 31 provinces and cities in China and suggests the direction of continuous urbanization policy. This study is limited in that it does not reflect the past trend only by conducting cross-sectional analysis for one year in 2017, and it is necessary to comprehensively evaluate urbanization efficiency by conducting additional longitudinal area analysis in the future.

Keyword

표/그림 (6)

표 Table 1. Input and output indexes for DEA Analysis
표 Table 2. Descriptive statistics of input-output factors in 2017
표 Table 3. Efficiency score and ranking (CCR-O) & (BCC-O) of 31 provinces and cities in 2017
표 Table 4. Non-efficiency (input index) of 31 provinces and cities
표 Table 5. Non-efficiency (output index) of 31 provinces and cities
표 Table 6. Comparison between BCC and CCR model

AI 본문요약
AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

가설 설정

Based on the above analysis results, we can get the following Implications. First, we should change the pattern of urban economic growth. The initial extensive, inefficient, high consumption and pollution urbanization is not the real urbanization.

제안 방법

According to the results of the research on the urbanization efficiency by the scholars using the DEA method, due to different research perspectives and different input-output index system, so the results of urban efficiency evaluation are also quite different. Therefore, based on the establishment of a reasonable urban input-output system, the purpose of this study uses the SBM-DEA model of non-expected output, and the relevant data of 31 provinces and cities in China, to analyze the urbanization efficiency, analyze the current situation of urbanization efficiency, the existing problems and the influencing factors of urbanization efficiency, in order to provide effective information and decision support for the formulation of corresponding management policies.
The difference from the traditional model, is that putting the slack variables into the objective function that can not only solve the problem of input and output relaxation, but also solve the problem of efficiency evaluation in the existence of non-expected output, which can avoid the deviation and influence caused by the difference of radial and angle to certain extent, and better reflect the essence of efficiency evaluation. Therefore, this paper adopts the SBM-DEA model with non-expected output to analyze and study the urbanization efficiency of 31 provinces and cities in China by using relevant data.
In Korea, there are studies on water supply efficiency with DEA [13], eco-efficiency in power plants with DEA [14], and kimchi-related manufacturers with DEA [15]. This study uses the sbm-dea model with non-expected output to study 31 provinces and cities in China, which is somewhat different from existing studies.
Ren Yufei set by the input index is the total cost of the fixed asset investment, the actual use of foreign capital value, the urban area is, the amount of water, the total number of employees, energy consumption and output index is where GDP, gross industrial output value, fiscal revenue, the added value of the third industry emissions, waste water, waste gas emission, smoke emissions[2]. After summarizing and analyzing the existing literature, based on the principle of index selection of comprehensiveness, feasibility and authenticity, consider the results of previous studies based on the index system of urbanization evaluate the efficiency of this paper(shown in Table 1).
And with the city's economic development, road construction, population is concentrated, building density, fires and the incidence of traffic accidents and other safety accidents will increase relatively, focuses on urban land use types in the second industry and the tertiary industry, impact on environment and resources, urban development problems such as high investment low output, so this study selected the number of fire occurrences, the number of traffic accidents, the wastewater and air pollutant emissions as undesired output index.
Then, input and output factors of 31 provinces and cities were analyzed using dea-bcc model, model, focusing on the output, and the results of efficiency analysis of urbanization were as follows (shown in Table 3). The efficiency analysis results of BCC-O show that the efficiency of Beijing, Tianjin, Shanghai, Guangdong, Hainan, Xizang, Qinghai and Ningxia is 1, with the best relative efficiency.
In order to find out the inefficiency of economies of scale, we compared the efficiency results of BCC analysis and CCR analysis. The results are shown in the following table (shown in Table 6).
Input index: The most basic production input factors for economic activities are capital, land and labor. In this study, land resources, financial resources and human resources are selected as input index, the area of urban built-up area is used to represent land resources, the total investment in fixed assets and financial expenditure are used to represent financial resources, and the number of employment is used to represent human resources.

대상 데이터

China has a vast country with uneven development levels in different regions, and there is a big gap in efficiency among different regions. This paper takes 31 provinces and cities as research objects. The data in this paper are from China Statistical Yearbook (2018), China Fire Yearbook (2018), and statistical yearbooks and statistical bulletins of provinces, autonomous regions and municipalities.
This paper takes 31 provinces and cities as research objects. The data in this paper are from China Statistical Yearbook (2018), China Fire Yearbook (2018), and statistical yearbooks and statistical bulletins of provinces, autonomous regions and municipalities. Data analysis was performed using DEA-Solver 8.

데이터처리

The data in this paper are from China Statistical Yearbook (2018), China Fire Yearbook (2018), and statistical yearbooks and statistical bulletins of provinces, autonomous regions and municipalities. Data analysis was performed using DEA-Solver 8.0 with the output of CCR and BCC models. Yuan Xiaoling analyzed the evolution characteristics of urban efficiency by using the number of employment, the local budget expenditure, the total investment in fixed assets of the whole society, the total amount of actually utilized foreign capital as input index, and GDP per capita, the local budget income, the total wages and the total retail sales of social consumer goods as output index[9].

이론/모형

This paper analyzes the urbanization efficiency of 31 provinces and cities in China by using SBM-DEA model. Input variables used in the analysis are area of urban built-up area, the total investment in fixed assets, financial resources table and the number of employment, and output variables are the ratio of tertiary industry, financial revenue, per capita consumption expenditure of residents, number of fires accidents, number of traffic accidents, waste water emission and air pollutant emission.

성능/효과

The input and output factors of 31 provinces and cities were analyzed by DEA-CCR model, focusing on the output, and the results of efficiency analysis of urbanization are shown as follows (shown in Table 3). The results of CCR-O efficiency analysis show that Tianjin, Shanghai, Hainan, Tibet, Qinghai and Ningxia had the highest urbanization efficiency, while the remaining 25 provinces, such as Beijing, Zhejiang, Jiangsu, Guangdong and Shandong, had relatively low urbanization efficiency. The urbanization efficiency of jilin, henan, guangxi, xinjiang and heilongjiang is less than 0.
What is interesting in the analysis is that the urbanization efficiency of Tibet, Qinghai and Ningxia in the western region is relatively optimal because the factories or enterprises that pollute the environment are few and the ecological environment is superior.

후속연구

This study is limited in that it does not reflect the past trend only by conducting cross-sectional analysis for one year in 2017, and it is necessary to comprehensively evaluate urbanization efficiency by conducting additional longitudinal area analysis in the future.

참고문헌 (15)

T. Y. Guo, Y. Xu & Z. Q. Wang. (2009). The Analyses of Metropolitan Efficiencies and Their Changes in China Based on DEA and Malmquist Index Models[J]. Acta Geographica Sinica, 64(4), 408-416. http://kns.cnki.net/kcms/detail/detail.aspx?FileNameDLXB200904005&DbNameCJFQ2009
Y. F. Renufei, C. L. Fang & X. Q. Lin. (2017). Evaluation of eco-efficiency of four major urban agglomerations in eastern coastal area of China[J]. Acta Geographica Sinica, 72(11), 2047-2063. http://www.cnki.com.cn/Article/CJFDTotal-HDJJ201709009.htm
Y. W. Wu et al. (2017). A Study on the Spatial Coupling Relationship between Urbanization Efficiency and Innovation Capability of Provincial-level Administrative Areas in China[J]. East China Economic Management, (9), 68-74. DOI:10.3969/j.issn.1007-5097.2017.09.009
G. Y. Sheng. (2012). Theoretical analysis of urbanization model[J]. Jiang-huai Tribune, 24(1), 24-30. DOI:10.16064/j.cnki.cn34-1003/g0.2012.01.024
G. X. Wang & J. M. Cai. (2008). Research on the method of quantifying the spatial boundary of metropolitan region[J]. Economic Geography, (2), 191-195. DOI:10.15957/j.cnki.jjdl.2008.02.001
W. Sun & G. P. Dong. (2010). The efficiencies and their changes of China's resources-based cities employing DEA and Malmquist Index Models[J]. Geographical Research, 29(12), 2155-2165. http://www.cnki.com.cn/Article/CJFDTotal-DLYJ201012005.htm
X. Y. Xu. (2014). Yangtze River Delta port group and urban efficiency research based on DEA analysis[J]. Special Zone Economy, (9), 25-28. http://www.cnki.com.cn/Article/CJFDTotal-TAJJ201409007.htm
J. T. Wang & L. Zhao. (2009). The Dynamic Evaluation on the Regional Urbanization Efficiency in China[J]. Soft Science, 23(7), 92-98. http://www.cnki.com.cn/article/cjfdtotal-xuxi200907020.htm
X. L. Yuan, B. S. Zhang & X. N. Zhang. (2008). Evolution Characters of China's Cities Based on The Super-efficient DEA. Urban Studies, 15(6), 102-107. http://www.cnki.com.cn/Article/CJFDTOTAL-CSFY200806022.htm
L. Yang & P. Du. (2016). Evolution and Regional Difference of Urban Efficiency in Guangdong Province Based on the SE-DEA Model[J]. Ecological Economy, 32(8), 82-86. http://www.cnki.com.cn/Article/CJFDTOTAL-STJJ201608017.htm
J. F. Zong & C. F Pan. (2016). Agglomeration Affect the Efficiency of Urban Development in China[J]. Regional Economic Review, (3), 83-90. DOI:10.14017/j.cnki.2095-5766.2016.0068
F. Cao. (2015). The efficiency test based on the three stages of DEA-Malmquist model of Chinese provincial urbanization and its convergent analysis[J]. Journal of Qingdao University of Science and Technology(Social Sciences), 31(4), 18-22. DOI:10.16800/j.cnki.jqustss.2015.04.004
K. H. Choi & J. K. Cho. (2014). Case Study on the Jeollabuk-do Local Water Supply Efficiency by using DEA and Malmquist Index. Journal of Digital Convergence, 12(12), 571-580. http://www.earticle.net/Article/A237238

원문보기 상세보기
J. H. Han. (2013). A Study on Eco-efficiency in power plants using DEA Analysis. Journal of Digital Convergence, 11(5), 119-133. http:///www.earticle.net/Article/A199716

원문보기 상세보기
K. H. Choi, H. J. Kwag & E. Y. Jung. (2014). Relative Efficiency and Statistical Analysis of Kimchi-related Manufacturers in Jeollabuk-do. Journal of Digital Convergence, 12(8), 139-146. http://www.earticle.net/Article/A229167

원문보기 상세보기

이 논문을 인용한 문헌

저자의 다른 논문 :

활용도 분석정보

상세보기

다운로드

내보내기

활용도 Top5 논문

해당 논문의 주제분야에서 활용도가 높은 상위 5개 콘텐츠를 보여줍니다.
더보기 버튼을 클릭하시면 더 많은 관련자료를 살펴볼 수 있습니다.

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증

[국내논문] 중국 31개 성 및 직할시의 도시화 효율성 분석에 관한 연구
A Study on Urbanization Efficiency analysis of China's 31 provinces and cities 원문보기

초록
AI-Helper

Abstract ▼ AI-Helper

Keyword

표/그림 (6)

표/그림 (6)

AI 본문요약
AI-Helper

가설 설정

제안 방법

대상 데이터

데이터처리

이론/모형

성능/효과

후속연구

참고문헌 (15)

이 논문을 인용한 문헌

저자의 다른 논문 :

활용도 분석정보

활용도 Top5 논문

관련 콘텐츠

원문 보기

원문 URL 링크

오픈액세스(OA) 유형

연관된 기능

이 논문과 함께 이용한 콘텐츠

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

선택된 텍스트

연합인증

[국내논문] 중국 31개 성 및 직할시의 도시화 효율성 분석에 관한 연구 A Study on Urbanization Efficiency analysis of China's 31 provinces and cities 원문보기

초록 AI-Helper

Abstract ▼ AI-Helper

Keyword

표/그림 (6) 모든 표/그림 보기

표/그림 (6) 슬라이드로 보기

AI 본문요약 엑셀 다운로드 AI-Helper

가설 설정

제안 방법

대상 데이터

데이터처리

이론/모형

성능/효과

후속연구

참고문헌 (15)

이 논문을 인용한 문헌

저자의 다른 논문 :

김형호 (28)

활용도 분석정보

활용도 Top5 논문 더보기

관련 콘텐츠

원문 보기

원문 URL 링크

오픈액세스(OA) 유형

연관된 기능

이 논문과 함께 이용한 콘텐츠

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

선택된 텍스트

[국내논문] 중국 31개 성 및 직할시의 도시화 효율성 분석에 관한 연구
A Study on Urbanization Efficiency analysis of China's 31 provinces and cities 원문보기

초록
AI-Helper

표/그림 (6)

표/그림 (6)

AI 본문요약
AI-Helper

활용도 Top5 논문