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An Empirical Comparison and Verification Study on the Seaport Clustering Measurement Using Meta-Frontier DEA and Integer Programming Models  

Park, Ro-Kyung (조선대학교 무역학과)
Publication Information
Journal of Korea Port Economic Association / v.33, no.2, 2017 , pp. 53-82 More about this Journal
Abstract
The purpose of this study is to show the clustering trend and compare empirical results, as well as to choose the clustering ports for 3 Korean ports (Busan, Incheon, and Gwangyang) by using meta-frontier DEA (Data Envelopment Analysis) and integer models on 38 Asian container ports over the period 2005-2014. The models consider 4 input variables (birth length, depth, total area, and number of cranes) and 1 output variable (container TEU). The main empirical results of the study are as follows. First, the meta-frontier DEA for Chinese seaports identifies as most efficient ports (in decreasing order) Shanghai, Hongkong, Ningbo, Qingdao, and Guangzhou, while efficient Korean seaports are Busan, Incheon, and Gwangyang. Second, the clustering results of the integer model show that the Busan port should cluster with Dubai, Hongkong, Shanghai, Guangzhou, Ningbo, Qingdao, Singapore, and Kaosiung, while Incheon and Gwangyang should cluster with Shahid Rajaee, Haifa, Khor Fakkan, Tanjung Perak, Osaka, Keelong, and Bangkok ports. Third, clustering through the integer model sharply increases the group efficiency of Incheon (401.84%) and Gwangyang (354.25%), but not that of the Busan port. Fourth, the efficiency ranking comparison between the two models before and after the clustering using the Wilcoxon signed-rank test is matched with the average level of group efficiency (57.88 %) and the technology gap ratio (80.93%). The policy implication of this study is that Korean port policy planners should employ meta-frontier DEA, as well as integer models when clustering is needed among Asian container ports for enhancing the efficiency. In addition Korean seaport managers and port authorities should introduce port development and management plans accounting for the reference and clustered seaports after careful analysis.
Keywords
Seaport Efficiency; DEASeaport Clustering; Meta-frontier DEA Model; Integer Programming Model; Comparative and Verification Analysis; Asia Seaports; DEA; Data Envelopment Analysis;
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Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 강상목.김문휘(2010), 메타 프론티어를 이용한 기술효율과 생산성 비교: 한.중 제조업을 대상으로, 한국경제지리학회지, 제3권 제1호, 126-146.
2 강상목.조상규(2009), 한.일 지역 간 초 광역경제권 형성에 따른 제조업의 생산성 변화, 국토연구, 제63권, 225-252.
3 김근섭(2015), 부산항 환적경쟁력 강화를 위한 네트워크 강화방안, 동아시아물류동향, 제85권, 부산발전연구원, 98-103.
4 박노경.Y. Nishimura(1998), An Empirical Study on the Hypothetical Merger between Japanese and Korean Banks -Chiefly on the Application of Integer and DEA Method-, 한국국제경제학회 동계학술발표대회 발표논문집, 한국국제경제학회,743-767.
5 박노경(2013a), 교차효율성 모형을 이용한 컨테이너항만의 효율성 측정방법, 무역연구, 제9권 제4호, 279-294.
6 박노경(2013b), 컨테이너항만의 클러스터링 측정방법 소고: DEA참조집단모형과 교차효율성 모형을 이용, 무역연구, 제9권 제7호, 439-456.
7 박노경(2014), 게임교차효율성 모형을 이용한 컨테이너항만의 효율성 측정방법 소고, 한국항만경제학회지, 제30권 제4호, 279-294.
8 박노경(2015a), 교차효율성 모형과 정수계획법을 이용한 한국주요항만의 클러스터링 및 효율성 변화 측정소고, 무역통상학회지, 제15권 제2호, 1-25.
9 박노경(2015b), 메타프론티어와 교차효율성 모형을 통한 클러스터링의 실증적 검증, 2015 한국무역학회 동계학술대회 발표논문집, 2015년12월18일, 67-77.
10 박노경(2016a), 부트스트랩 DEA모형과 게임교차효율성 모형을 이용한 항만클러스터링 측정에 대한 실증적 비교연구, 한국항만경제학회지, 제31권 제2호, 29-58.
11 박노경(2016b), 메타프론티어와 교차효율성 모형을 통한 클러스터링의 실증적 검증소고, 무역학회지, 제41권 제3호, 27-42.
12 박병인(2015), 광양항과 동북아 주요컨테이너항만간경협 추세분석, 한국항만경제학회지, 제31권 제2호, 85-101.
13 박영태(2016), 글로벌물류시대 항만배후단지 활성화를 위한 실무적 방안, 2016 경제학공동학술대회 한국항만경제학회 분과 학술발표논문집, 2-22.
14 사공일(2009), 동북아항만 환경변화에 따른 수도권 컨테이너항만의 대응방안, 한국무역협회, 1-104.
15 서충원.신연수(2015), 메타프론티어를 이용한 외국관광객을 위한 관광호텔의 권역별 효율성 평가, 무역학회지, 제40권 제4호, 195-215.
16 양동현.장연재(2015), 메타프론티어 맘퀴스트 생산성 지수를 이용한 상급종합병원과 대형 종합병원의 생산성 변화 비교, 산업경제연구, 제26권 제6호, 2705-2730.
17 이선민.박정민(2016), 서해안권 항만의 협력적 경쟁전략과 경쟁구조분석, 산업경제연구, 제29권 제6호, 2435-2453.
18 이수철(2017), 환적유형으로 본 부산항의 안정적 환적화물 유치방안, 아름다운 동행, 제42권, 부산항만공사, 10-15.
19 조승환(2017), 2017년 해양항만정책 방향, 우리나라 해운항만정책 재검토, 2017년 3월 31일 (사)한국국제상학회 정책 Workshop 논문집, 1-41.
20 최건우.김은수.강임호.하태영(2016), 부산항 컨테이너 환적요인에 관한 실증분석, 해양정책연구, 제31권 제2호, 167-189.
21 황준석.홍아름.이대호(2010), 케이블TV 산업의 소유규제 변화와 기업결합 형태별 생산효율성차이의 실증연구, 한국방송학보, 제24권 제2호, 276-313.
22 Amin, G.R. and M. Toloo(2007), Finding the Most Efficient DMUs in DEA: An Improved Integrated Model, Computers & Industrial Engineering , 52, 71-77.   DOI
23 Battese, G.E., and D.S.P. Rao(2002), Technology Gap, Efficiency, and A Stochastic Meta-frontier Function ,ˮ International Journal of Business and Economics, 1(2), 87-93.
24 Battese, G. E., Rao, D. S. P., & O'Donnell, C. J.(2004), "A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies," Journal of Productivity Analysis, 21(1), 91-103.   DOI
25 Chen, C. M. and J. Zhu(2011), Efficient Resource Allocation via Efficiency Bootstraps: Allocation to R&D Project, Operations Research, 59(3), 729-741.   DOI
26 Cook, W. D., and J. Zhu(2007), Classifying Inputs and Outputs in Data Envelopment Analysis, European Journal of Operational Research, 180, 692-699.   DOI
27 Fang, Y., and J. Wang(2012), Selection of the Number of Clusters via the Bootstrap Method, Computational Statistics & Data Analysis , 56(3), 468-477.   DOI
28 Foroughi, A.A.(2011), A New Mixed Integer Linear Model for Selecting the Best Decision Making Units in Data Envelopment Analysis, Computers & Industrial Engineering , 60, 550-554.   DOI
29 Gomory, R.E.(1963), An Algorithm for Integer Solutions to Linear Programs, in R.L. Graves and P.Wolf (Ed.), Recent Advances in Mathematical Programming , McGraw-Hill, New York.
30 Sharma, M.J.,and S.J. Yu(2009), Performance Based Stratification and Clustering for Benchmarking of Container Terminals," Expert Systems with Applications, 36, 5016-5022.   DOI
31 Ulucan, A., and Atici, K.B.(2010), Efficiency Evaluation with Context-dependent and Measure-specific Data Envelopment Approach: An Application in a World Bank Supported Project, OMEGA, 38, 68-83.   DOI
32 Wang, Y.M., and P. Jiang(2012), Alternative Mixed Integer Linear Programming Models for Identifying the Most Efficient Decision Making Unit in Data Envelopment Analysis, Computers & Industrial Engineering , 62, 546-553.   DOI
33 Wang, Q., Z. Zhao, P. Zhou., and D. Zhou.(2013), Energy Efficiency and Production Technology Heterogeneity in China: A Meta-frontier DEA Approach, Economic Modelling, 35, 283-289.   DOI
34 Land, A.H. and A.G. Doig(1969), An Automatic Method of Solving Discrete Programming Problems, Econometrica, 28, 497-520.
35 Hayami, Y.(1969), Sources of Agricultural Productivity Gap among Selected Countries, American Journal of Agricultural Economics, 51, 564-575.   DOI
36 Hayami, Y. and V. W. Ruttan(1970), Agricultural Productivity Differences Among Countries, American Economic Review, 60, 895-911.
37 Hayami, Y. and V. W. Ruttan(1971), Agricultural Development: An International Perspective, Baltimore: John Hopkins University Press.
38 Makani, R., Olfa, B., and Ezzedine, D.(2015), Large Scale Analysis of Islamic Equity Funds Using A Meta-frontier Approach with Data Envelopment Analysis, Research in International Business and Finance, 30, 324-337.
39 Park, Ro Kyung(2008), A Verification of Korean Containerport Efficiency Using the Bootstrap Approach, Journal of Korea Trade,12(2), 1-30.
40 Po, R.W., Guh, Y. Y., and Yang, M.S.(2009), A New Clustering Approach Using Data Envelopment Analysis, European Journal of Operational Research,199, 276-284.   DOI
41 Yu, Y., Y. Choi, and N. Zhang(2014), Strategic Corporate Sustainability Performance of Chinese State-owned Listed Firms: A Meta-frontier Generalized Directional Distance Function Approach, The Social Science Journal, 52(3), 300-310.   DOI
42 Yao, X., H. Zhou, A. Zhang and A. Li(2015), Regional Energy Efficiency, Carbon Emission Performance and Technology Gaps in China: A Meta-frontier Non-radial Directional Distance Function Analysis, Energy Policy, 84, 142-154.   DOI