• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.557-563
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• 2012

The purpose of this study is to analyze the spatial structure of Mega-Economic Region particularly in Daegu using Freight Origin-Destination (O/D) Data which comes from KTDB. To diagnose the appropriate separation of Regions, the mean of three standardized indices was calculated. The indicates measured are Freight Occupancy Ratio (FOR), Freight Dependancy Ratio (FDR), Scale Parameter (SP), respectively. The result of analysis showed that FOR FDR SP indicators gave effective explanation about characteristic of Regions depending on Freight moving patterns. Especially, Gyeongsan and Gumi had high correlation Regions with FOR FDR indicator. Also, the major industries of Daegu Metropolitan based on the SP indicator are Chemical and Metal machinery industry.

• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.137-148
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• 2017

Port service level is a metric of competitiveness among ports for the operating/managing bodies such as the terminal operation company (TOC), Port Authority, or the government, and is used as an important indicator for shipping companies and freight haulers when selecting a port. Considering the importance of metrics, we developed software to objectively define and manage six important service indicators exclusive to container and bulk terminals including: berth occupancy rate, ship's waiting ratio, berth throughput, number of berths, average number of vessels waiting, and average waiting time. We computed the six service indicators utilizing berth 1 through berth 5 in the container terminals and berth 1 through berth 4 in the bulk terminals. The software model allows easy computation of expected ship's waiting ratio over berth occupancy rate, berth throughput, counts of berth, average number of vessels waiting and average waiting time. Further, the software allows prediction of yearly throughput by utilizing a ship's waiting ratio and other productivity indicators and making calculations based on arrival patterns of ship traffic. As a result, a TOC is able to make strategic decisions on the trade-offs in the optimal operating level of the facility with better predictors of the service factors (ship's waiting ratio) and productivity factors (yearly throughput). Successful implementation of the software would attract more shipping companies and shippers and maximize TOC profits.