• Journal of Distribution Science
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• v.4 no.2
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• pp.5-20
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• 2006

Retail is called location business because it is one of the most important factors to estimate management of stores for retailers who are going to sell products directly to customers. Retailers' management achievements are shown in sale in general. Therefore, retailers tend to focus on ways to increase the numbers of customers in order to raise sales. First of all, in this research, I am going to examine the most fundamental models such as Reilly's retail gravitation, converse model, huff probability model and multiful losit model in selecting stores. Secondly, I am going to provide the process and analyzing ways to predict estimated sales amount with the previous theory model. Also I am going to predict estimated sales amount of the department store L which is located in D metorpolitan city. Lastly, I am going to argue about the problem of this research and the next research subject. Our main goal is to provide ways to complement and inspect sales estimation models, which can be used in fields after taking characters of high class structure of Korea into consideration on the base of previous researches. According to the result of the research, my conclusion is that if the process of analysis and changing factors are complemented, revise model, which can reflect reality of Korea, will be provided. Therefore, in the future study, we have to build up theory models to suit for our retail market through critic reviews about the existing high class structure of Korea.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.117-130
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• 2005

In both deteministic user Optimal Traffic Assignment Model (UOTAM) and stochastic UOTAM, travel time, which is a major ccriterion for traffic loading over transportation network, is defined by the sum of link travel time and turn delay at intersections. In this assignment method, drivers actual route perception processes and choice behaviors, which can become main explanatory factors, are not sufficiently considered: therefore may result in biased traffic loading. Even though there have been some efforts in Stochastic UOTAM for reflecting drivers' route perception cost by assuming cumulative distribution function of link travel time, it has not been fundamental fruitions, but some trials based on the unreasonable assumptions of Probit model of truncated travel time distribution function and Logit model of independency of inter-link congestion. The critical reason why deterministic UOTAM have not been able to reflect route perception cost is that the route perception cost has each different value according to each origin, destination, and path connection the origin and destination. Therefore in order to find the optimum route between OD pair, route enumeration problem that all routes connecting an OD pair must be compared is encountered, and it is the critical reason causing computational failure because uncountable number of path may be enumerated as the scale of transportation network become bigger. The purpose of this study is to propose a method to enable UOTAM to reflect route perception cost without route enumeration between an O-D pair. For this purpose, this study defines a link as a least definition of path. Thus since each link can be treated as a path, in two links searching process of the link label based optimum path algorithm, the route enumeration between OD pair can be reduced the scale of finding optimum path to all links. The computational burden of this method is no more than link label based optimum path algorithm. Each different perception cost is embedded as a quantitative value generated by comparing the sub-path from the origin to the searching link and the searched link.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.157-167
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• 2005

Seoul metropolitan public transport reform results in the introduction of the semi-public operation and distance-based fare policies. With implementation of these policies, public transport revenue allocation has been (will be) evolved very complicated because the existing revenue allocation issues have not only been clearly solved, which is generated by the combined relationship among Korea Railroad Corporation (KRC). Seoul Metropolitan Subway Corporation (SMSC). Seoul Metropolitan Rapid Transit Corporation (SMRTC), and Incheon Rapid Transit Corporation (IRTC), but also the revenue allocation problem between bus and urban railroad-related organizations need to be considered in this combined framework. On top of that. based on the future plans such as the private sector's railroad construction plan(s), the light rail transit construction plans of several local governments and the join of remained bus lines of Seoul metropolitan areas, it is understood that the revenue allocation among public transport operating organization will become one of main issues of operation organization as well as local and central governments. As a basic approach for revenue allocation of public transport operation organizations, the purpose of this paper is to propose an integrated model applicable to estimate degree of service contribution in passenger carriage in the combined public transport network. With a hypothesis that the complete electronic card system is deployed, this paper supposes every passenger's loading and alighting stations is recordable. Thereby, this paper limits research scope as to Seoul metropolitan railroad area since used route(s) between origin and destination stations can not be traceded because transfer stations each passenger path through is not recorded. Each model proposed in the paper is as follows: 1. a generalized cost reflecting passenger's transfer behavior; 2.a K path model for determining similar routes between O-D; 3.an assignment model for loading O-D trips onto the detected similar routes using Logit Model.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.121-133
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• 2017

The propose of study is to examine the characteristics of companies with high possibility to form an internal control weakness using forecasting model. This study use the actual listed/unlisted companies' data from K_financial institution. The first conclusion is that discriminant model is more valid than logit model to predict internal control weak companies. A discriminant model for predicting the vulnerability of internal control has high classification accuracy and has low the Type II error that is incorrectly classifying vulnerable companies to normal companies. The second conclusion is that the characteristic of weak internal control companies have a low credit rating, low asset soundness assessment, high delinquency rates, lower operating cash flow, high debt ratios, and minus operating profit to the net sales ratio. As not only a case of listed companies but unlisted companies which did not occur in previous studies are extended in this study, research results including the forecasting model can be used as a predictive tool of financial institutions predicting companies with high potential internal control weakness to prevent asset losses.

• The Korean Journal of Financial Management
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• v.23 no.2
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• pp.209-237
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• 2006

Since previous default forecasting models for the firms evaluate the probability of default based upon the accounting data from book values, they cannot reflect the changes in markets sensitively and they seem to lack theoretical background. The market-information based models, however, not only make use of market data for the default prediction, but also have strong theoretical background like Black-Scholes (1973) option theory. So, many firms recently use such market based model as KMV to forecast their default probabilities and to manage their credit risks. Korean firms also widely use the KMV model in which default point is defined by liquid debt plus 50% of fixed debt. Since the debt structures between Korean and American firms are significantly different, Korean firms should carefully use KMV model. In this study, we empirically investigate the importance of debt structure. In particular, we find the following facts: First, in Korea, fixed debts are more important than liquid debts in accurate prediction of default. Second, the percentage of fixed debt must be less than 20% when default point is calculated for Korean firms, which is different from the KMV. These facts give Korean firms some valuable implication about default forecasting and management of credit risk.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.667-677
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• 2013

The introduction of a new transit facility affects mode share of travel alternatives. The multinomial logit model, which has been the most commonly used for estimating mode share, has difficulty in reflecting heterogeneity of travelers' choices, and it has a limitation on grasping their characteristics of mode choice. The limitation may lead to over- or under-estimation of the new transit facility and bring about significant social costs. This paper aims to find a methodology to overcome the problem of preference homogeneity. It also applies market segmentation structure of separating the whole population into direct and indirect beneficiary to consider their preference heterogeneity. A mode choice model is estimated on data from Jeju Province and statistically tested. The results show that mode transfer rate of direct beneficiaries that inhabit in downtown areas increases as the new transit facility provides more advanced services with higher costs. The results and the model suggested in this study can contribute to improving the accuracy of demand forecasting of new transit facilities by reflecting heterogeneity of mode-transfer patterns.

• 한국사회정책
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• v.24 no.4
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• pp.63-87
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• 2017

Self-employed women are highly vulnerable to social risks like unemployment and poverty as job instability has increased in recent decades. Despite this, the Korean public policy focus has been on employees, not the self-employed. This may be closely linked to the legacy of the East Asian welfare model policy logic. Therefore, this study explores social risk levels by gender and employment status and examines the relation between social risks of self-employed women and the East Asian welfare model policy logic, through comparing-means analysis and ordered logit regression analysis using the 9th wave data of the Korea Welfare Panel Study Korea. The study yields evidence of divisions in social risk levels according to gender and employment status: that is, a gender difference, and a substantial gap between self-employed workers and regular employees. Furthermore, the findings of the study indicate that self-employed women — especially in small businesses — are more vulnerable to social risks than are self-employed men. This strongly supports the conclusion that the higher social risks of self-employed women in Korea are closely linked to the legacy of East Asian welfare model policy logic, which focuses on social protection for core workers and largely neglects women.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.347-364
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• 2022

Fraudulent companies or sellers strategically manipulate reviews to influence customers' purchase decisions; therefore, the reliability of reviews has become crucial for customer decision-making. Since customers increasingly rely on online reviews to search for more detailed information about products or services before purchasing, many researchers focus on detecting manipulated reviews. However, the main problem in detecting manipulated reviews is the difficulties with obtaining data with manipulated reviews to utilize machine learning techniques with sufficient data. Also, the number of manipulated reviews is insufficient compared with the number of non-manipulated reviews, so the class imbalance problem occurs. The class with fewer examples is under-represented and can hamper a model's accuracy, so machine learning methods suffer from the class imbalance problem and solving the class imbalance problem is important to build an accurate model for detecting manipulated reviews. Thus, we propose an OpenAI-based reviews generation model to solve the manipulated reviews imbalance problem, thereby enhancing the accuracy of manipulated reviews detection. In this research, we applied the novel autoregressive language model - GPT-3 to generate reviews based on manipulated reviews. Moreover, we found that applying GPT-3 model for oversampling manipulated reviews can recover a satisfactory portion of performance losses and shows better performance in classification (logit, decision tree, neural networks) than traditional oversampling models such as random oversampling and SMOTE.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.1-14
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• 2022

In this study, in order to analyze the preference for UAM of public transportation users following the introduction of urban air transportation(UAM), A preference consciousness(SP) survey was conducted on 840 users of Incheon public transportation using the Incheon International Airport-Incheon Gil Hospital route, which is the urban air traffic(UAM) demonstration route section. In addition, the means selection model was estimated based on the results of conducting a preference consciousness (SP) survey. As a result of analyzing the time value for travel using the established means selection model, it was found to be 56,428 won/hour, As a result of verifying the elasticity of travel cost (won), in-vehicle time (minutes), and out-of-vehicle time (minutes) in the model, the effect on the urban air traffic (UAM) share in this model was found that travel cost (won), in-vehicle time (minutes), and out-of-vehicle time (minutes) were in order, and the effect was greater when the travel cost (won) decreased than when it increased.

• Information Systems Review
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• v.25 no.3
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• pp.59-81
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• 2023

Elderly suicide problem has become worse in South Korea. With a rapid aging of the population, the trend of suicide among the elderly is expected to accelerate, preventing elderly suicide has been considered an important societal problem. Thus, we aim to investigate various factors that explain suicidal ideation and to develop a predictive model for suicidal ideation in the context of elderly people in South Korea. To this end, this study contributes to addressing the elderly suicide problem. By using seven-year panel data from the Korea Welfare Panel Survey, we extract various potential causal factors for elderly suicidal ideation based on interpersonal theory of suicide and social disorganization theory. Then a panel logit model was employed to assess the impacts of potential factors on suicidal ideation and deep learning and machine learning algorithms were used to develop a predictive model for suicidal ideation of elderly people. The results of our study provide practical implications for preventing elderly suicide by identifying causal factors of suicidal ideation and a high suicidal risk group of the elderly. This study sheds light on synergy of mixed methodology and provides various academic implications.