Browse > Article
http://dx.doi.org/10.14400/JDC.2019.17.2.101

An analysis of the Factors of Moving in and Activation Strategies for Incheon Cold-Chain Cluster using LNG cold energy  

Ahn, kil-Seob (Department of Logistics Management, Incheon National University)
Oh, Jae-Gyun (Department of Logistics Management, Incheon National University)
Yang, Tae-Hyeon (Department of Logistics Management, Incheon National University)
Yeo, Gi-Tae (Department of Logistics Management, Incheon National University)
Publication Information
Journal of Digital Convergence / v.17, no.2, 2019 , pp. 101-111 More about this Journal
Abstract
The construction of a "cold-chain cluster," which is a complex of cold-storage warehouses is emerging as an issue in the logistics industry. The Incheon Port Authority, in partnership with Korea Gas Corporation, is carrying out a project to build a cold-storage cluster using cold energy generated in the Songdo LNG receiving terminal. This study proposes a method of activating the cold-storage cluster using the CFPR methodology. An analysis of major factors showed that the most important factor was stability and profitability, which scored 0.281. For sub-factors, sustainable trade volume was the highest in importance, followed by rent level, the sustainability of LNG cold energy utilization technology, competition with general cold-storage warehouses, and exclusion of duplicate investments in facilities. For the future study, the evaluation of complex of cold-storage warehouses using major factors drawn out from this study is needed.
Keywords
Incheon port; Cold-storage cluster; Factors of moving in; Activation plan; CFPR(Consistent Fuzzy Preference Relation);
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 D. B. Han, Y. J. Kim, K. I. Yeom, J. R. Shin & Y. S. Baek. (2017). A Study of Simulation on the Refrigerated Warehouse System Based on the Cold Energy of Lng Using the Pro-Ii Simulator. Journal of Hydrogen and New Energy Institute in Korea, 28(4), 401-406.
2 J. I. Yoon. (2001). Trends of Research and Development for LNG Cold. Journal of the Korea Society for Power System Engineering, 5(4), 5-10.
3 S. H. Lee. (2015). Construction of LNG cold-water logistics center at the rear of Incheon New Port. Korean Journal of Air-Conditioning and Refrigeration Engineering, 44(2), 16-23.
4 Y. Y. Kim. (2008). Efficiency Analysis of Resident Companies in Industrial Cluster Complex. Journal of Korean National Economy, 26(4), 157-181.
5 L. S. Woo. (2007). Strategy of Logistics Innovation Cluster for Korea Port Logistics Park. the Journal of Maritime Affairs and Fisheries, 269, 4-18.
6 K. Y. Seok. (2004). Strategies for Creating Innovative Clusters for Regional Development: Daedeok Research Park. Korean Public Management Review, 7, 121-151.
7 R. B. Seo, J. S Sung & H. E. Yoon. (2012). The Effects of Collaborative R&D Network and Entrepreneurship on Technological Innovation Activity and Performance of Venture Business in Industrial Clusters. Journal of Entrepreneurship and Venture Studies, 15(3), 43-68.
8 B. D. Kye. (2003). Network Structure of Successful Industrial Clusters - Cases of Silicon Valley and Toyota City. Journal of regional studies, 11(1), 63-83.
9 M. Kai, G. Hu & J. S. Costas. (2015). A Cooperative Demand Response Scheme Using Punishment Mechanism and Application to Industrial Refrigerated Warehouses. IEEE Transactions on Industrial Informatics, 11(6), 1520-1531.   DOI
10 Y. Y. Nam, Y. C. Jo & C. H. Lee. (2008). A Study on Establishment of integrated Logistics Centers through Clustering Strategy for Incheon Port Warehousing. Korean journal of Business Administration, 10(3), 127-135.
11 S. G. Kim, S. B. Kim & C. H. Lee. (2008). Site Selection using Port and Industry Clusters. Journal of Korea Port Economic Association, 24(4), 237-255.
12 F. R. L. Junior, L. Osiro & L. C. R. Carpinetti. (2014). A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection. Applied Soft Computing, 21, 194-209.   DOI
13 T. Y. Pham & G. T. Yeo. (2018). A Comparative Analysis Selecting the Transport Routes of Electronics Components from China to Vietnam. Sustainability, 10(7), 1-18.   DOI
14 Z. Xu & J. Chen. (2006). Some models for deriving the priority weights from interval fuzzy perference relations. European Journal of Operational Research, 186(1), 166-280.
15 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.   DOI
16 Y. H. Chen & R. J. Chao. (2012). Supplier selection using consistent fuzzy preference relations. Expert systems with applications, 39(3), 3233-3240.   DOI
17 T. L. Satty. (2005). Making and validating complex decisions with the AHP/ANP. Journal of Systems Science and Systems Engineering, 14, 1-36.   DOI
18 H. Y. Kim & C. M. Kim. (2010), Supply Plan of LNG Cold Energy for a Cryogenic Warehouse, The Korean Society of Mechanical Engineers, 953-954.
19 O. B. Kweon. (2015), Cold Storage Distribution Center of LNG Cfyogenic Technology, The Korean Society of Mechanical Engineers, 7-15.
20 C. K. Kim & S. C. Kim. (2010). A Study on the District Community Cooling System using LNG Cold Energy. Journal of the Korean Institute for gas, 14(6), 27-30.
21 H. Y. Ki & C. M. Kim. (2015). Supply Plan of LNG Cold Energy for a Cryogenic Warehouse . Journal of Mechanical Science and Technology, 11, 953-954.
22 S. H. Lee. (2015). Construction of LNG cold heat utilization logistics center in Incheon New Port, The Magazine of the Society of Air -Conditioning and Refrigerating Engineers of Korea, 44(2), 16-23.
23 A. G. M. Rodrigo, A. C. E. Alexander & D. H. Jose. (2016). Picking Routing Problem with K homogenous material handling equipment for a refrigerated warehouse. Universidad de Antioquia, 80, 9-20.
24 B. E. Farnsworth & E. Benjamin. (2015). A Production Model to Measure Technical Efficiency in the Refrigerated Warehouse Industry. Texas A & M University.
25 Markets and Markets. (2017). Cold Chain Monitoring Market by Component (Hardware (Sensors and Data Loggers) and Software), Application (Pharmaceuticals & Healthcare, Food & Beverages, and Chemicals), Logistics (Storage and Transportation), and Region - Global Forecast to 2023, Markets and Markets. https://www.marketsandmarkets.com/