• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.107-118
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• 2012

The purpose of the study is to analyze the travel characteristics of freight trucks in metropolitan areas, focusing on activity generation, destination choice, and trip chaining behaviors. The results showed that the number of service companies at departure areas has a primary influence on the activity generation pattern and destination choice behavior of trucks in metropolitan areas. The number of trips within a trip chain is largest, in case where the prevailing industry in destination areas is wholesale or retail and the shipment item is food or beverage. These results imply that for the reasonable estimation of truck travel demand both the trip chaining behaviors and the industrial compositions in departure and destination areas should be separately considered for each type of commodity.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.6 no.1
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• pp.83-87
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• 2012

This study is aimed to identify latent classes which are based the change patterns in assistive technology device use among worker with disabilities and to test the effects of independent variables(gender, education, disability type, disability density, activity and participation of ICF: ICF, subjective socioeconomic status: SES, job satisfaction, life satisfaction) on determining latents classes. This study applied Nagin's(1999) semi-parametric group based approach to the panel survey of employment for the disabled. Because dependant variable has dichotomous scale, logit model was used. The results identified three latent classes, which could be defined based on the patterns as follows; assistive device continued use group, assistive device mid-level use group, assistive device sharp decline use group. The effects of the independent variables on the latent classes was tested by multinomial logit analysis. The results showed that education, disability type, ICF, SES, and life satisfaction were significant determinants of the latent classes. Finally, the implications based on analysis results were suggested.

• Journal of Internet Computing and Services
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• v.7 no.1
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• pp.75-89
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• 2006

This paper is concerned with analysing the bankruptcy prediction power of three models: Multivariate Discriminant Analysis(MDA), Logit Analysis, Neural Network. The research targeted the bankrupted companies after the foreign exchange crisis in 1997 to differentiate from previous research efforts, and all participating companies were randomly selected from the KSE listed companies belonging to manufacturing industry to improve prediction accuracy and validity of the model. In order to assure meaningful bankruptcy prediction, training data and testing data were not extracted within the corresponding period. The result is that prediction accuracy of neural networks is more excellent than that of logit analysis and MDA model when considering that execution of testing data was followed by execution of training data.

• Food Science and Preservation
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• v.10 no.3
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• pp.376-380
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• 2003

This aims is to estimate the consumers' preference on the brand rice using factor analysis, completed research on the consumption of brand rice revealed that the household supply in the Seoul area is increasing. An analysis whether housewives' preference in chosing the brand of rice was developed through the consumption experience and re-purchase intention investigation for the brand rice. Also the paper analyzed the consumers' preference using the logit and probit model. Number of respondents who participated in the study(95 ％) totaled 1000 and the sampling method utilized was the multistage stratification and assignment abstraction. Results showed that the preference of housewives' depends on age, education and level of income. Such that as age, education, income level increase so thus their preference for brand rices also increase. Also the re-purchasing of brand rice is high when housewives have a higher educational attainment and prefers to go to work. Conclusively, the long-term sale view for brand rice is closely related to the economic conditions of a household. Hence, with the economic growth, there is a possibility that consumption of brand rice would increase compared to the ordinary rice. We can propose the following political intent from analysis of these results. First, There is a need for continuous public information as reinforcement for brand rice. Second, Marketing operation reinforcement could also be done for customer class security etc.

• Health Policy and Management
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• v.33 no.3
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• pp.295-310
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• 2023

Background: The long-term care (LTC) group has higher rates of chronic disease and disability registration compared to the general older people population. There is a need to provide integrated medical services and care for LTC group. Consequently, this study aimed to identify medical usage patterns based on the ratings of LTC and the characteristics of benefits usage in the LTC group. Methods: This study employed the National Health Insurance Service Database to analyze the effects of demographic and LTC-related characteristics on medical usage from 2015 to 2019 using a repeated measures analysis. A longitudinal logit model was applied to binary data, while a linear mixed model was utilized for continuous data. Results: In the case of LTC ratings, a positive correlation was observed with overall medical usage. In terms of LTC benefit usage characteristics, a higher overall level of medical usage was found in the group using home care benefits. Detailed analysis by medical institution classification revealed a maintained correlation between care ratings and the volume of medical usage. However, medical usage by classification varied based on the characteristics of LTC benefit usage. Conclusion: This study identified a complex interaction between LTC characteristics and medical usage. Predicting the requisite medical services based on the LTC rating presented a challenge. Consequently, it becomes essential for the LTC group to continuously monitor medical and care needs, even after admission into the LTC system. To facilitate this, it is crucial to devise an LTC rating system that accurately reflects medical needs and to broaden the implementation of integrated medical-care policies.

• Journal of Distribution Science
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• v.16 no.11
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• pp.37-45
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• 2018

Purpose - Recently, large quantities of factors have affected the signing of the Free Trade Agreement between two countries. Due to this background, this paper selects South Korea as an example to explore the determinants of Free Trade Agreement from Asian countries. Research design, data, and methodology - A cross sectional data of 2016 will be employed and some variables such as real income and GDP will be used to run an empirical analysis under the linear probability model, probit model and logit model. Results - The findings show that the Asian countries' exchange rate regime, real income, GDP and so forth can increase the probability of signing the Free Trade Agreement with Asian countries. Conversely, the distance can lower the probability of signing the Free Trade Agreement with Asian countries. Meanwhile, although the Asian countries' import, consumer price index and population also can affect the probability of signing the Free Trade Agreement with Asian countries, the estimated coefficients are not statistically significant at 5% level. Conclusions - According to the empirical results, this paper provides a new scope for South Korea's government to sign the Free Trade Agreement with other Asian countries.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.27-34
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• 2000

This study analyzes the price elasticities of airline Passenger demand through the 'Stated Preference' technique which uses survey data. Because the domestic airfare has been regulated by the government. it is not easy to derive Price elasticity through the usual regression analysis with aggregate data and thus a special methodology is required for elasticity estimation. Therefore, in this study we estimated the Price elasticities of domestic air passenger demand and the modal share change rates to the alternative modes with logit model and sample enumeration method, by analyzing the survey data on air Passengers' demand behavior about the mode choice between air-rail. air-bus, and air-car. As the results, the estimated price elasticities are in the range of -0.6~-0.9, and rail is mainly chosen as an alternative mode. bus is chosen Partly, and car is barely used.

• Journal of Korean Society of Transportation
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• v.11 no.2
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• pp.5-26
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• 1993

In order to analyze travel mode choice behavior, behavioral models including logit model, based on revealed preference theory, have been using easily measurable variables such as individual socioeconomic characteristics and physical attributes of travel modes. But some recent attitudinal models of travel choice behavior have implied that the negligence of individual psychological variables and individual choice constraints in travel mode choice might preclude better prediction of individual travel mode choice behavior. In this context, this study was attempted to reconstruct an attitudinal model(AM), especially focused on the decision rules in travel mode choice decision making process, consistent with the conceptual framework relating individual attitude and choice constraints to choice behavior. And to evaluate the strengths of the AM to other comparative models(logit, linear-additive, conjunctive, lexicographic model) in predicting travel mode choice bebavior, an empirical study of the mode choice in work-trip to CBD in Seoul was performed. According to the results the percent of correct prediction(PCP) derived from the AM was higher than those derived from comparative models by at least 7 to 20% in predicting travel mode choice. But each model produced a different prediction accuracy depending on market segmentation by travel modal users, individual socioeconomic characteristics, transportation system characteristics, and satisfaction levels. The finding that different groups divided by a certain criterion employ different decision rules supports the necessity of developing a choice model such as the AM combining compensatory and noncompensatory decision rules, and suggests that a proposed transportation system management plan or policy may have different effects on each group.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.4
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• pp.55-70
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• 2001

Artificial neural network(ANN) models have been widely used for the classification problems in business such as bankruptcy prediction, credit evaluation, etc. Although the application of ANN to classification of consumers＇ choice behavior is a promising research area, there have been only a few researches. In general, most of the researches have reported that the classification performance of the ANN models were better than conventional statistical model Because the survey data on consumer behavior may include much noise and missing data, ANN model will be more robust than conventional statistical models welch need various assumptions. The purpose of this paper is to study the potential of the ANN model for forecasting consumers＇ choice behavior based on survey data. The data was collected by questionnaires to the shoppers of department stores and discount stores. Then the correct classification rates of the ANN models for the training and test sample with that of multiple discriminant analysis(MDA) and logistic regression(Logit) model. The performance of the ANN models were betted than the performance of the MDA and Logit model with respect to correct classification rate. By using input variables identified as significant in the stepwise MDA, the performance of the ANN models were improved.

• Journal of Agricultural Extension & Community Development
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• v.27 no.2
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• pp.75-87
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• 2020

The purpose of this study is to investigate the location characteristics of the rice paddy fields and to predict shrinking areas of them. The study area is in South Korea nationwide, and a 300×300m raster level is adopted as a spatial analysis unit. The binary logit model and spatial simulation model are employed for the analyses. As a result, population, industry, climate and nature, and accessibility play a significant role in determining rice paddy fields' locations. It is predicted that the shrinking rate will be high in Gangwon-do, Gyeongsangbuk-do, and Gyeongsangnam-do until 2027. The hot spots are intensively shaped in the inland of Gangwon-do, eastern parts of Gyeonggi-do, and the borders of Gyeongsangnam-do and Jeollabuk-do between Charyeong and Sobaek mountain ranges. Using Gimcheon-si as an example, the study suggests fundamental policy implications for taking advantage of the simulation results from the lens of local agriculture. Several policy measures are proposed for improving management strategies for the rice paddy fields in the long run.