디지털융복합연구 (Journal of Digital Convergence)

  • 제18권10호
  • /
  • Pages.181-194
  • /
  • 2020
  • /
  • 2713-6434(pISSN)
  • /
  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
권호 표지
DOI QR코드

DOI QR Code

수도권 콜드체인 클러스터 경쟁력 평가에 관한 연구

An Evaluation of Cold Chain Cluster Competitiveness in the Metropolitan Area

  • 안길섭 (인천대학교 동북아 물류대학원) ;
  • 박성훈 (인천대학교 동북아 물류대학원) ;
  • 이해찬 (인천대학교 동북아 물류대학원) ;
  • 여기태 (인천대학교 동북아 물류대학원)
  • Ahn, Kil-Seob (Graduate School of Logistics, Incheon National University) ;
  • Park, Sung-Hoon (Graduate School of Logistics, Incheon National University) ;
  • Lee, Hae-Chan (Graduate School of Logistics, Incheon National University) ;
  • Yeo, Gi-Tae (Graduate School of Logistics, Incheon National University)
  • 투고 : 2020.09.14
  • 심사 : 2020.10.20
  • 발행 : 2020.10.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

유통시장의 변화에 따라 농·수·축산물의 보관과 유통 그리고 가공식품 및 신선식품의 보관과 운송에 대한 이슈가 급부상하고 있으며, 이에 따라 콜드체인이 물류 서비스의 한축으로 자연스럽게 주목을 받고 있다. 본 연구는 최근 들어 활기를 띠고 있는 냉동냉장 식품 등 콜드체인 유통과 관련하여 관심을 끌고 있는 수도권 지역 콜드체인 클러스터 구축에 대한 입지 경쟁력 평가를 목적으로 한다. 이를 위해 본 연구는 전문가의 지식을 효율적으로 추출하여 계량화할 수 있는 CFPR(Consistent Fuzzy Preference Relations) 분석기법을 활용하여 수도권 콜드체인 클러스터 후보지에 대한 경쟁력을 평가하였다. 연구 결과, 입지 경쟁력은 인천신항 배후부지, 경기 남부권(용인), 경기 서부권(김포 물류단지), 평택오성물류단지 순으로 우수한 것으로 나타났다. 특히 본 연구는 냉동·냉장 물류창고 운영 전문가의 지식을 추출하여, 수도권 콜드체인 클러스터 후보지에 대한 세부적인 경쟁력 평가를 실시하고, 최적의 클러스터 후보지를 제시하였다는 점에서 기존 연구들과 차별성을 가진다. 향후 연구에서는 설문 대상을 신선식품 물류센터의 소유권을 확보하기 위한 구매 및 구축 결정권을 가진 기업경영자, 대기업군, 공공기업 군 등으로 구분하여 조사할 필요가 있다.

Due to the changes in the distribution market, issues related to storage and distribution of agricultural, aquatic and livestock products, and storage and transportation of processed and fresh food are rapidly emerging, and as a result, Cold Chain is naturally receiving attention as one of the logistics services. The purpose of this study is to evaluate the competitiveness of location in the construction of a cold chain cluster centered on the metropolitan area, which has attracted attention in relation to the distribution of cold chains, such as recently refrigerated frozen foods. To this end, this study evaluated the competitiveness of cold chain cluster candidates in the metropolitan area by utilizing the CFPR (Consistent Fuzzy Preference Relations) method that can efficiently extract and quantify expert knowledge. As a result, the location competitiveness was found to be superior to Incheon New Port's hinterland, Gyeonggi South Area (Yongin), Gyeonggi West Area (Gimpo Logistics Complex), and Pyeongtaek Oseong Logistics Complex. In particular, this study extracted the knowledge of refrigerated and refrigerated logistics warehouse operation experts, and conducted detailed competitiveness assessments for cold chain cluster candidates in the metropolitan area, and suggested the optimal cluster candidates. In the future research, it is necessary to classify the questionnaire into the owner, large business group, and public business group, etc., who have the right to purchase and build to secure ownership of the fresh food distribution center.

키워드

참고문헌

  1. J. Y. Jung (2019). Busan Cold chain industry status and logistics hub planning, BISTEP.
  2. S. U. Lee, H. S. Jang, J. M. Song & H. N. Park (2013). A Study on Measures to Enter the Chinese Cold Chain Market, KMI, 1-233.
  3. S. Y. Choi (2015). Current Status and Challenges of the Korean Cold Chain Industry. Logistics Newspaper (www.klnews.co.kr, 2015.7.31.)
  4. Markets and Markets(2020). Cold Chain Market Trends Global Forecast to 2023, https://www.marketsandmarkets.com/
  5. 360marketupdates(2020). Global Cold Chain Logistics Market Trend 2020, http://www.360marketupdates.com
  6. Ministry of Land, Infrastructure and Transport (2015). Overseas construction and fresh food logistics operation status survey and support plan research, 1-97.
  7. Korea Agro-Fisheries and Food Distribution Corporation(aT) (2019), Major Food and Food Industry Statistics in 2019 (Based on 2017, 2018)
  8. Korea Logistics News (2015). Current status and challenges of the domestic cold chain industry, www.klnews.co.kr
  9. CBRE(2019). ASIA PACIFIC Real Estate Market OUTLOOK 2019, 22-27.
  10. Ministry of Trade, Inoustry & Energy (2015). Free Chain Area Cold Chain Hub Construction and Linkage Research, 1-113.
  11. H. S. Kim & S. B Sang (2019). A Study on the Activation Plan of Cold Chain Logistics System in Incheon Port. Journal of Korea Port Economic Association 35(3), 19-40. https://doi.org/10.38121/kpea.2019.09.35.3.19
  12. Y. S. Chun & J. S. Park (2017). A Study on the Factors for Selecting Location of Global Cold Chain Logistics Hub Using AHP Technique: Focusing on Fresh Food. Journal of Logistics Society 27(6), 59-70.
  13. Y. M. Koo & D. J. Kim (2018). Analysis of Importance for Activation of Fresh Food Transport in Domestic Cold Chain. Logistics Research 26(4), 23-38.
  14. K. S. Ahn, J. G. Oh, T. H. Yang & G. T. Yeo(2019). An analysis of the Factors of Moving in and Activation Strategies for Incheon Cold-Chain Cluster using LNG cold energy, Journal of Digital Convergence, 17(2), 101-111. https://doi.org/10.14400/JDC.2019.17.2.101
  15. S. G. Kang, S. B. Ahn & C. H. Lee (2008). A study on the port cluster selection model in the manufacturing industry. Journal of Korean Port Economics 24(4), 237-255.
  16. G. J. Yun & S. W. Seo (2019). A Study on the Development of a Marine Industrial Cluster in Seosan-Daesan Port, Korean Institute of Navigation and Port Research, 35(1), 19-38.
  17. J. J. K & K. S. Kim (2009). An Analysis on Locational Factors of Urban Industrial Cluster-The Case of Seoul Digtal Vally, Journal of Koera Planning Association, 44(7), 85-96.
  18. X.. Zhang, J. S. L. Lam & C. Iris (2020). Cold chain shipping mode choice with environmental and financial perspectives. Transportation Research Part D: Transport and Environment, 87, 102537. https://doi.org/10.1016/j.trd.2020.102537
  19. Zhao, Y., Zhang, X., Xu, X., & Zhang, S. (2020). Research progress of phase change cold storage materials used in cold chain transportation and their different cold storage packaging structures. Journal of Molecular Liquids, 114360. https://doi.org/10.1016/j.molliq.2020.114360
  20. F. Vivaldi, B. Melai, A. Bonini, N. Poma, P. Salvo, A. Kirchhain & F. Di Francesco (2020). A temperature-sensitive RFID tag for the identification of cold chain failures. Sensors and Actuators A: Physical, 313, 112182. https://doi.org/10.1016/j.sna.2020.112182
  21. Falcon, V. C., Porras, Y. V. V., Altamirano, C. M. G., & Kartoglu, U. (2020). A vaccine cold chain temperature monitoring study in the United Mexican States. Vaccine, 38(33), 5202-5211. https://doi.org/10.1016/j.vaccine.2020.06.014
  22. G. Liu, J. Hu, Y. Yang, S. Xia & M. K. Lim (2020). Vehicle routing problem in cold Chain logistics: A joint distribution model with carbon trading mechanisms. Resources, Conservation and Recycling, 156, 104715. https://doi.org/10.1016/j.resconrec.2020.104715
  23. J. S. Jeong & M. J. Lee (2015). Strategies for Entry into Emerging Markets of the Korean Automotive Industry. Korean International Trade Association, 20(2), 119-153.
  24. I. G. Hyun & S. J. Park (2011). The Analysis of Chinese Consumer's Automoblie Attribute Selection, Korea Research Academy of Distribution and Management, 14(4), 187-204. https://doi.org/10.17961/jdmr.14.4.201109.187
  25. M. Sasaki, A. Suzuki & Z. Drezner (1999). On the selection of hub airports for an airline hub-and-spoke system. Computers & Operations Research, 26(14), 1411-1422. https://doi.org/10.1016/S0305-0548(99)00043-X
  26. R. Doganis & A. Graham (1987). AIRPORT MANAGEMENT: THE ROLE OF PERFORMANCE INDICATORS. Polytechnic of Central London, England, 13(1), pp.243.
  27. Y. Yoshida & H. Fujimoto (2004). Japanese-airport benchmarking with the DEA and endogenous-weight TFP methods: testing the criticism of overinvestment in Japanese regional airports. Transportation Research Part E: Logistics and Transportation Review, 40(6), 533-546. https://doi.org/10.1016/j.tre.2004.08.003
  28. T. H. Oum, C. Yu & X Fu (2003). A comparative analysis of productivity performance of the worlds major airports: summary report of the ATRS global airport benchmarking research report-2002. Journal of Air Transport Management, 9(5), 285-297. https://doi.org/10.1016/S0969-6997(03)00037-1
  29. E. Herrera-Viedma, S. Alonso, F. Chiclana & F. Herrera. (2007). A Consensus Model for Group Decision Making With Incomplete Fuzzy Preference Relations. IEEE transactions on fuzzy systems, 15(5), 863-877. https://doi.org/10.1109/TFUZZ.2006.889952
  30. T. C. Wang & Y. L. Lin (2009). Applying the consistent fuzzy preference relations to select merger strategy for commercial banks in new financial environments. Expert Systems with Applications, 36(3), 7019-7026. https://doi.org/10.1016/j.eswa.2008.08.023
  31. Korea International Trade Association, Korea International Logistics Council (2007). National Sales Logistics Center Survey Report, 1-163
  32. K. W. Choi (2017). A study on the location selection of a domestic cold chain distribution center. A master's thesis from Korea Maritime University.
  33. J. W. Jeon & C. G. Choi (2019). Analysis of the rent-determining factors of distribution centers: focusing on the metropolitan area. Real estate research 29(2), 27-38.