• Journal of Korea Port Economic Association
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• v.25 no.1
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• pp.15-28
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• 2009

The purpose of this paper is to show the empirical extraction way of benchmarking ports for overcoming the shortcoming which the traditional DEA method has by using 20 Korean ports in 2003 for 2 inputs (birthing capacity, cargo handling capacity) and 2 outputs(Export and Import Quantity, Number of Ship Calls). Because DEA method has produced the limited set of efficient units which are reference to inefficient units respective of their differences in efficiency scores, it is necessary to adopt the more feasible benchmarking information according to the path analysis(tier or stratification). The core empirical results of this paper are as follows. Benchmarking ports against inefficient ports according to the tier analysis are that Masan Port(Janghang$\rightarrow$Jeju$\rightarrow$Seogoipo$\rightarrow$Yeosu), Jinhae Port(Janghang$\rightarrow$Mogpo$\rightarrow$Seogoipo$\rightarrow$Wando), Pohang&DonghaePort(Janghang$\rightarrow$Samcheonpo$\rightarrow$Pyungtag$\rightarrow$Samcheog), and Sogcho Port(Janghang$\rightarrow$Mogpo$\rightarrow$Seogoipo$\rightarrow$Wando). The policy implication to the Korean seaports and planners is that Korean seaports should introduce the new methods like Tier analysis of this paper for evaluating the port performance and enhancing the efficiency in short term, mid term, and long term according to the tier 3 stage, the tier 2 stage, and the tier 1 stage with original DEA stage.

• Korean Journal of Ecology and Environment
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• v.55 no.3
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• pp.201-211
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• 2022

The macroinvertebrate community in the Singal reservoir, Yedang and Juam lake was investigated three times from April 2021 to October 2021. Each lake was investigated by dividing it into inflow, middle-flow, and outflow. Additionally, sampling was conducted again by dividing it into the edge and center parts at each inflow, middle-flow, and outflow. Eight families of benthic macroinvertebrates were collected except for chironomids in the sampling sites. Dominant macroinvertebrates were investigated as chironomids, and Tubificidae was sub-dominant organisms. The density of macroinvertebrate community was higher in the edge area than in the center bottom of the lakes. The density of chironomids was low when the water level was high but was high when the water level was low. In the edge area of the middle-flow in Singal reservoir, the density of chironomids was 1,208 ind. m^-2 in April when the water level was high, but it increased to 1,401 ind. m^-2 in July when the water level was low. Similarly, the density of chironomids at the outflow of Yedang lake was high (1,990 ind. m^-2) in July when the water level was low. The density of chironomids also decreased along with the increasing water level at all edge areas of Juam lake. These results indicated that it will be necessary to consider the water level when studying macroinvertebrate communities in the lake.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.79-105
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• 2023

Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.93-112
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• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.