• Journal of Korean Society on Water Environment
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• v.20 no.6
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• pp.555-562
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• 2004

This paper presents the development and application of a riparian buffer zone design model(RBZDM). The model was developed as a decision-making tool for watershed management, by integrating geographic information system(GIS) and analytical hierarchy process(AHP) theory. Several factors for watershed management, such as pollution removal capacity, land aquisition cost, distribution of point and non-point pollution sources, and possibility of new pollution source location, were analyzed based on AHP theory. The vegetated buffer zone width was designed using GIS-based riparian buffer analysis. The developed model was applied to the Kyoungan Stream watershed, which is an important part of Paldang lake catchment area. The Kyoungan stream watershed was divided into sixteen subbasins. Six of them belong to the main stem, where the model was applied. Ten alternatives of buffer zone width and five hierarchial levels were designed. The relative importance and the relative preference were computed by pair-wise comparison of evaluation criteria given in hierarchial levels. The buffer zone width was determined by linear function of the given alternatives and relative preferences. From this study, it was determined that the six buffer zone widths of Kyoungan main stems would be 1,594, 1,744, 1,856, 1,782, 1,338, 1,780 meter, from upstream to downstream.

• The Journal of Fisheries Business Administration
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• v.40 no.3
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• pp.127-146
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• 2009

This study is to estimate the factor weights of the reasons for decreases in marine fishery resources using the Analytical Hierarchy Process. Furthermore, it classifies 20 fishes under a fishery resource recovery plan into various groups of fishes according to these factor weights using the non-hierarchial cluster analysis. The factors of decreases in marine fishery resources are identified as bio-ecological, technology-system, economic-business, and fishing village-society factors. Two of the most important factors of decreases in resource are turned out to be the economic-business and bio-ecological factors, estimated as 31% and 30% respectively. The technology-system and fishing village-society factors are estimated as 21% and 18% respectively. The study utilizes non-hierarchical cluster analysis in order to classify 20 fishes into 2, 3, and 4 groups. K-means cluster analysis is applied for grouping in conjunction with ANOVA to identify statistical differences in factors. Once again, the economic-business and bio-economic factors play main role in grouping 2-groups of fishes case. The third group of fishes in addition to the previous 2 groups of fishes appears as those 4 factors of decrease evenly play about the same role at a 3-groups of fishes case. Finally, the economic-business and bio-economic factors are turned out to be evenly important in the 4th group once there are 4-groups of fishes.

• Journal of Korea Port Economic Association
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• v.34 no.4
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• pp.17-38
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• 2018

The purpose of this study is to establish shipping companies' selection factors related to a classification society and to explore the relative importance of each factor using the analytical hierarchy process(AHP) technique. Insufficient research exists on the hierarchial structure of shipping companies' factors of selecting a classification society. The factors are identified and classified into two tiers of major and detailed factors, by referring to the related industrial linkages, prior research related to the determinants, and the process and service delivery of the classification society's activities. The empirical analysis of this study is based on the relative importance of determinants when selecting a classification society, and experts engaged with shipping companies were surveyed using questionnaires. The results of the AHP methodology on the main factors of shipping companies in selecting a classification society are as follows. The relative importance of the main factors was 0.373 for technical and survey services, 0.284 for recognized organizations(RO) functions, 0.177 for cost and 0.167 for market(related industry) expectations. The relative importance of the detailed factors is 0.144 for the ability to respond to a port state control(PSC) inspection, 0.143 for technical services, 0.090 for the requirements of financial institutions/ shippers/shipyards, 0.087 for class maintenance costs, 0.086 for the survey network, 0.085 for surveyor competency, 0.072 for cooperation with IMO and government authorities, 0.067 for recognition for RO, 0.058 for the business power of the classification society, 0.052 for the initial inspection costs, 0.040 for reputation and trustworthiness, 0.038 for the costs related to the class, and 0.037 for connections to related industries.