• Journal of The Geomorphological Association of Korea
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• v.23 no.2
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• pp.109-125
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• 2016

This study aims to identify the landslide susceptible zones of Boeun area and provide reliable landslide susceptibility maps by applying different modeling methods. Aerial photographs and field survey on the Boeun area identified landslide inventory map that consists of 388 landslide locations. A total ofseven landslide causative factors (elevation, slope angle, slope aspect, geology, soil, forest and land-use) were extracted from the database and then converted into raster. Landslide causative factors were provided to investigate about the spatial relationship between each factor and landslide occurrence by using fuzzy set and logistic regression model. Fuzzy membership value and logistic regression coefficient were employed to determine each factor's rating for landslide susceptibility mapping. Then, the landslide susceptibility maps were compared and validated by cross validation technique. In the cross validation process, 50% of observed landslides were selected randomly by Excel and two success rate curves (SRC) were generated for each landslide susceptibility map. The result demonstrates the 84.34% and 83.29% accuracy ratio for logistic regression model and fuzzy set model respectively. It means that both models were very reliable and reasonable methods for landslide susceptibility analysis.

• Structural Engineering and Mechanics
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• v.34 no.1
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• pp.39-60
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• 2010

In Turkey, majority of industrial facilities are composed of precast buildings. However, precast buildings have suffered extensive damage during Kocaeli and Duzce (1999) and Adana-Ceyhan (1998) earthquakes. Therefore, in this study, fragilities of existing building stock and damage probabilities of precast buildings were studied. For this purpose, building inventories were prepared and variation of structural parameters was determined by investigating the design project of 65 precast buildings constructed in Denizli, Turkey. Twelve analysis models which reflect the stiffness, strength and ductility properties of building inventory were constructed. After the definition of strain based displacement limits and corresponding damage states for buildings, displacement demands were calculated by using non linear time history analysis. During the analyses 360 strong ground motion records were used. Exceedence ratios of concerned damage limits was calculated by checking the displacement demands and then PGV based fragility curves were constructed. Efficiency of strength, stiffness and ductility properties of existing precast buildings were investigated by comparing the fragility curves. The results have shown that the most effective parameters that govern the damage probabilities of precast buildings are stiffness and ductility. It was also stated that the results of fragility analysis and damage and failure observations performed after Kocaeli and Duzce Earthquakes are compatible.

• Journal of Distribution Science
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• v.19 no.8
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• pp.5-12
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• 2021

Purpose: The purpose of this paper is to analyze and examine the issues that are directly associated with the United States COVID-19 vaccine distribution and its strategies so that other countries may learn from it and develop sound distribution strategies. Research design, data and methodology: This paper has applied both historical and narrative models to review, identify, and analyze existing literatures to assess the United States' vaccine distribution strategy. Results: Distribution strategy developed by the United States seems to have focused heavily on the basic tenets of physical distribution, i.e., transportation, warehousing, inventory, and large-venue mass-vaccination sites, and the strategy seems to have been successful when looking only at the physical tenets of distribution. However, the analysis indicates that the distribution strategy has not either focused on or included the major activities of distribution, such as inward and outward communication, information, and customer satisfaction. Conclusions: The countries that are currently developing or implementing COVID-19 vaccine distribution strategy should review and learn from the United States' vaccine distribution strategy and its implementation. The countries should include and address all the activities of distribution, including inward and outward communication, information, and customer satisfaction to achieve their vaccination goals, minimize confusion, reduce wasting of doses and vaccine desserts, and improve vaccination rates.

• Journal of Distribution Science
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• v.20 no.12
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• pp.13-22
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• 2022

Purpose: The paper contributes to the existing literature on Vietnamese corporate governance and firm performance with a focus on listed family firms and the use of a more suitable econometric framework to analyze firm performance. The study investigates how family firm performance is affected by corporate governance under the standpoint of stewardship theory in Vietnam. Research design, data and methodology: With the use of different measures for firm performance (Tobin's Q, ROA, and ROE), regression models were estimated using Generalized Least Square (GLS) method on a panel data of a total of 113 listed companies during the five-year period from 2015 to 2019. Results: We found that family ownership as the main characteristic of the stewardship theory affects family firms positively. In addition, several other characteristics in corporate governance as board composition (board independence, board audits, and board committees), CEO (age and tenure) and firm characteristics (size, age, expansion, and annual sales) showed significant impacts on firm performance. Our findings also suggest that family firm performance can be either positively or negatively affected based on the characteristics of corporate governance. The findings can help companies evaluate the significance of corporate governance through deciding board structure and the selection of CEOs to match family firm characteristics. It also gives insights for investors, rating agencies, and policymakers for relevant purposes.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.229-235
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• 2021

The ability of entrepreneurs to arrange working capital is the key to maximizing the profitability of small- and medium-sized enterprises and the wealth of entrepreneurs. The study investigates the correlation between entrepreneurs' working capital management and the profitability of SMEs listed on six Gulf Cooperation Council (GCC) stock exchanges between 2019 and 2020. The secondary data is collected from the financial statements of SMEs listed on the six GCC stock exchanges. Actual sample for the research study was a total of 136 small- and medium-sized enterprises selected using purposive sampling methods. Four research models were considered in this analysis, all ending up affecting gross profits. The selected entrepreneurial SMEs were listed on six different Gulf Cooperation Council stock exchanges during 2019-2020. The fixed financial assets ratio, financial debt ratio, and company size are used as control variables and data were analyzed using multiple regression. The research results demonstrate that there is a statistically significant negative correlation between profitability measured by gross profit and cash cycle and the components of the cash cycle (including days of accounts receivable and days of inventory). The study further reveals that there is no significant correlation between gross profit and days of accounts payable.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.181-194
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• 2017

This study aims to develop a regression model for forest volume estimation using field-collected forest inventory information and airborne LiDAR data. The response variable of the model is forest stem volume, was measured by random sampling from each individual plot of the 30 circular sample plots collected in Bonghwa-gun, Gyeong sangbuk-do, while the predictor variables for the model are Height Percentiles(HP) and Height Bin(HB), which are metrics extracted from raw LiDAR data. In order to find the most appropriate model, the candidate models are constructed from simple linear regression, quadratic polynomial regression and multiple regression analysis and the cross-validation tests were conducted for verification purposes. As a result, $R^2$ of the multiple regression models of $HB_{5-10}$, $HB_{15-20}$, $HB_{20-25}$, and $HBgt_{25}$ among the estimated models was the highest at 0.509, and the PRESS statistic of the simple linear regression model of $HP_{25}$ was the lowest at 122.352. $HB_{5-10}$, $HB_{15-20}$, $HB_{20-25}$, and $HBgt_{25}-based$ models, thus, are comparatively considered more appropriate for Korean forests with complicated vertical structures.

• Journal of the Korean Society of Safety
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• v.30 no.1
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• pp.72-78
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• 2015

According to the report of the WHO, workers have been exposed to much job strain such as job load, responsibility, role, interpersonal conflict etc. In Korea, studies on job strain started to become active from 1990s and now hundreds of studies are actively under going or publishing so that the studies are contributing to development and improvement of job strain. Representative measurement models of job strain are Job Strain Model of Karasek, Job Stress Model of NOISH, Korea Occupational Stress Scale, JSQ(Job Stress Questionnaire), K-OSI(Korea Version of Occupational Stress Inventory) etc. (Lee Kwan-Suk, 2012 ; KOSHA, 2003). Among them, Job Strain Model of Karasek had been loved by many researchers of job strain before Korea Occupational Stress Scale was developed. Job Strain Model of Karasek had been fitted to Korean style and then, used to analyze job strain of Korean people so that this Scale highly contributed to seeking relationship with cardiovascular disease, musculoskeletal disease caused by job, smoking, drug, alcohol poisoning, and pulse(Lee Kwan-Suk, 2012). But as this Model was studied and developed based on foreign culture and life pattern, a model fit to Korea was developed to measure job strain for Korean people, which is Korea Occupational Stress Scale now most frequently used in measuring job strain. Accordingly, after this study made questionnaire survey about same population using the two methods used most frequently in measuring job strain, the study investigated what features appeared, what correlations appear between two models, and comparatively analyzed characteristics each independent and dependent variable. Based on this, the study aimed to exactly express job strain of Korean people. The subjects of the study were a population of 233, and Karasek's Questionnaire and KOSS's Questionnaire were surveyed at the same time. The results were analyzed by statistical program to obtain significant difference between two models. Four particular groups were divided with Job Strain Model of Karasek and the four particular groups were measured with Korea Occupational Stress Scale. And job strain come from combination of two models was measured, with which new comparative analysis method was suggested.

• 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.

• Journal of Distribution Research
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• v.6 no.2
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• pp.1-17
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• 2002

The recent dot-com craze has been one of the main causes that accelerated the growth of internet-related companies in diversity as well as in size. Meanwhile, the domestic market of supplies and equipment for internet businesses has been dominated by major foreign companies. To regain their market positions, the domestic manufacturers had to find the way to build up their competitive advantages, such as meeting their customers needs and reducing overall costs. In this study, one domestic PC server manufacturer, which competes fiercely with foreign manufacturers for the top place, has been chosen as a model to evaluate its current supply chain and to find an area that can be improved for a better performance. System Dynamics is used throughout the study. The central concept to system dynamics is understanding how all the objects in a system interact with one another. It focuses on feedback and secondary effects to think through how a strategy might or might not work, depending on how organizational changes are received, and what kinds of consequences emerge. Then, computerized models were built for simulations, each with different conditions, and, finally, the results were evaluated based on some criteria which are considered to be important and meaningful. The inefficiency that exists in the supply chain was proved to be a thirty-day long purchasing order leadtime, and it was expected that more effective supply chain could be formed if the leadtme were reduced to 14 days or 7 days. The results of simulations showed that the overall expected costs in supply chain was the least with the purchasing leadtime being 7 days. The lower average number of parts held as inventory, along with the reduced lost sales, acted as the factor reducing the expected overall costs. Although there was a slight increase in the average number of final products held as inventory and the total ordering cost, the benefits from lower parts inventory and reduced lost sales were large enough to justify the overall cost reduction.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.