• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.211-221
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• 2008

This dissertation studied the psychological cost, which converted the mental pain suffered by the victim of a traffic accident and his/her family, friends and people around him/her into social costs. Three methodologies - Choice Experiments, Direct Question and Dichotomous Choice Question - were used to design questionnaires, and models were built for each questionnaire design method. When building models, a logit model was used, which is used most frequently in probabilistic choice model. And the tobitmodel was used to make direct questionnaires. When verifying these models, although there were some differences in each model, suitability of most models and credibility of each coefficient were meaningful around the credibility level of 95%. According to the analysis, domestic psychological cost produced through the assessment model of psychological cost was 15.63 million won per person or 5.1 trillion in total, assuming 37.1% of total traffic accident cost.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.111-121
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• 2007

A transit assignment model can forecast the behaviors of transit users. thereby playing an important role In the evaluation of transit policies. Most existing transit assignment models are based on the models for passenger cars; therefore they cannot reflect the specific characteristics of transit modes. In addition most of the existing models are based on a single transit mode (bus or rail), and they cannot forecast the behaviors of transit users in a changing mass transportation system. The goal of this study is to overcome these problems with the exiting models and to develop a more realistic model. The newly developed model is based on mixed transit modes and is a stochastic model that can reflect the different preferences of each transit user for travel time and transfering. Data gathered from the Seoul metropolitan area's smart card are used to calibrate this model. This study is expected to be used for the evaluation of transportation policies and to attribute the development of transit revitalization strategies.

• Environmental and Resource Economics Review
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• v.16 no.3
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• pp.701-721
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• 2007

A key issue in the development and application of stated preference nonmarket valuation is the incorporation of unobserved heterogeneity in utility models. Two approaches to this task have dominated. The first is to include individual-specific characteristics into the estimated indirect utility functions. These characteristics are usually socioeconomic or demographic variables. The second employs generalized models such as random parameter logit or probit models to allow model parameters to vary across individuals. This paper examines a third approach: the inclusion of psychological or 'latent' variables such as general attitudes and behaviour-specific attitudes to account for heterogeneity in models of stated preferences. Attitudinal indicators are used as explanatory variables and as segmentation criteria in a choice modelling application. Results show that both the model significance and parameter estimates are influenced by the inclusion of the latent variables, and that attitudinal variables are significant factors for WTP estimates.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of Korean Society of Rural Planning
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• v.18 no.2
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• pp.39-45
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• 2012

The objective of this study was to analyze the determinant factors in the new agricultural technology acceptance targeted to the automatic switchgear for heat-retaining mulching used on the oriental melons farms. The probit and the logit models were estimated using survey data. The result indicated that the level of income, innovativeness, and reliability are important factors of the new agricultural technology acceptance. Therefore, it is considered the level of income, innovativeness, and reliability in advance to extend the new agricultural technology quickly.

• Journal of Agricultural Extension & Community Development
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• v.16 no.3
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• pp.643-668
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• 2009

The purpose of this study is to estimate the value of the sociocultural multifunctionality of rural areas in Korea. The sociocultural multifunctionality of rural areas consists of emotional comfort, green landscape, cultural heritage, and rural viability values. The value of the sociocultural multifunctionality was assessed by contingent valuation method incoporating preference uncertainty. The log-logit models indicated that households were willing to pay 14,027~26,757 won per month and the model with preference uncertainty gave the highest WTP. WTP was affected by respondent's sex, location, awareness of relation with multifunctionality and others. The total value of sociocultural multifunctionality of rural areas in Korea estimated to 2,691~5,134 billion won per year.

• Journal of the Korean Operations Research and Management Science Society
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• v.8 no.2
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• pp.45-56
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• 1983

This paper presents a generalized fuel choice model in which restrictive constraints on cross-price coefficients as Baughman-Joskow-FEA Logit Model need not be imposed, but all demand elasticities are uniquely determined. The model is applied to estimating aggregate energy demand and fuel choices for the residential and commercial sector. The structural equations are estimated by a generalized least squares procedure using national-level EPB, KDI, BK, KRIS, MOER data for 1965 and 1980, and other related reports. The econometric results support the argument that “third-price” and “fourth-price” coefficients should not be constrained in estimating relative market share models. Furthermore, by using this fuel choice model, it has forecasted energy demands by fuel sources in, the residential and commercial sector until 1991. The results are turned out good estimates to compare with existing demands forecasted from other institutes.

• Management Science and Financial Engineering
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• v.12 no.2
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• pp.19-35
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• 2006

We use the hierarchical Bayesian approach to describe the transition probabilities of a binary nonhomogeneous Markov chain. The Markov chain is used for describing the transition behavior of emotionally disturbed children in a treatment program. The effects of covariates on transition probabilities are assessed using a logit link function. To describe the time evolution of transition probabilities, we consider two modeling strategies. The first strategy is based on the concept of exchangeabiligy, whereas the second one is based on a first order Markov property. The deviance information criterion (DIC) measure is used to compare models with two different time dependent structures. The inferences are made using the Markov chain Monte Carlo technique. The developed methodology is applied to some real data.

• Korean Management Science Review
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• v.13 no.3
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• pp.91-104
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• 1996

The basic idea of Quality Function Deployment(QFD) is to deploy the voice of customers into the final product through product planning, part planning, process planning, and manufacturing. In the product planning stage, which is the first stage of product development, customer attributes(CAs) are translated into engineering characteristics(ECs). Then, based on the relationship between CAs and ECs, the target values of ECs are determined. In the previous research, the process of analyzing these relationships is mostly subjective in nature. In this article, we formulate the process of determining the target values of ECs as an optimization model. That is, we first determine the relationship between CAs and ECs as cumulative logit models and construct constraints into which the company strategy as well as the needs of customers can be incorprated. Next, cost functions of ECs are developed, which are summed into an objective function. An algorithm to solve the formulated optimization problem is developed and illustrated with an example.

• Journal of Korean Society of Transportation
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• v.14 no.4
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• pp.31-48
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• 1996

This paper develops a disaggregate model system for travel behavior of workers in a metropolitan area. We attempt to develop a set of models for predicting trip generation type, trip purpose, destination, mode choices in each trip on the way from work to home by using the concept of utility maximization of base-to-base tour. The model incorporates the concept that decisions of a trip in a trip in a travel tour depend on decisions of the trips having been made before and decisions of trip planned after of this trip, as well as on current trip conditions. As the structure of the model, the nested logit model is used to avoid a simultaneous model's complexity. The data to be used for estimating the model system are from the person trip survey which was carried out in 1981 in Nagoya metropolitan. Empirical tests of the model for Nagoya metropolitan area show encouraging results and prove the validity of the assumption of this model.