• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.2
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• pp.1-13
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• 2002

In this paper, we compares the business failure prediction accuracy among Linear Programming Discriminant Analysis(LPDA) model, Multivariate Discriminant Analysis (MDA) model and logit analysis model. The Data for 417 companies analyzed were gathered from KIS-FAS Published by Korea Information Service in 1999. The result of comparison for four time horizons shows that LPDA Is advantageous in prediction accuracy over the other two models when over all tilt ratio and business failure accuracy are considered simultaneously.

• IE interfaces
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• v.15 no.2
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• pp.209-217
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• 2002

Quality of Service(QoS) in the telecommunications can be evaluated by analyzing the opinion data which result from the surveyed opinions of respondents and quantify subjective satisfaction on the QoS from the customers' viewpoints. For analyzing the opinion data, MOS(mean opinion score) method and Cumulative Probability Curve method are often used. The methods are based on the scoring method, and therefore, have the intrinsic deficiency due to the assignment of arbitrary scores. In this paper, we propose an analysis method of the opinion data using logit models which can be used to analyze the ordinal categorical data without assigning arbitrary scores to customers' opinion, and develop an analysis procedure considering the usage of procedures provided by SAS(Statistical Analysis System) statistical package. By the proposed method, we can estimate the relationship between customer satisfaction and network performance parameters, and provide guidelines for network planning. In addition, the proposed method is compared with Cumulative Probability Curve method with respect to prediction errors.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.203-206
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• 1996

Prediction of firm bankruptcy have been extensively studied in accounting, as all stockholders in a firm have a vested interest in monitoring its financial performance. The objective of this paper is to develop the hybrid models for bankruptcy prediction. The proposed hybrid models are two phase. Phase one are (a) DA-assisted neural network, (b) Logit-assisted neural network, and (c) Genetic-assisted neural network. And, phase two are (a) DA-assisted Case based reasoning, and (b) Genetic-assisted Case based reasoning. In the variables selection, We are focusing on three alternative methods - linear discriminant analysis, logit analysis and genetic algorithms - that can be used empirically select predictors for hybrid model in bankruptcy prediction. Empirical results using Korean medium-sized firms data show that hybrid models are very promising neural network models and case based reasoning for bankruptcy prediction in terms of predictive accuracy and adaptability.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.61-77
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• 1995

The main objective of this research is the development of a logit model of urban workers' auto ownership choice. For the utility specification. a variety of behavioral hypotheses about the factors which affect the urban workers' auto ownership choice are considered. Based on the behavioral hypotheses, a binary logit model of auto ownership is estimated. Empirical estimation is based on a sample of workers taken in Daegu City(1994). The binary logit model of auto ownership development in this paper provides reasonable results in terms of behavioral and statistical considerations. Furthermore, this paper develops several submarket models of auto ownership choice. Market segmentation was made using age, sex, income, home-to-work time distance. It is found that the estimated results with market segmentation are also reasonable. Finally future directions of model development are suggested.

• Journal of Sericultural and Entomological Science
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• v.20 no.2
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• pp.36-39
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• 1978

With the current advances in insect toxicant bioassay, the need for easy methods of estimating the dosage-mortality regression equation has become vital. The Probit analysis seems to be not convenient for estimating the dosage-mortality regression equation and median lethal dose(LD50) because of its complexity in calculation. This study presents a comparision between Probit and Losit transformation for the estimation from bioassay results. Validation of the two methods is presented for the pathogenecity of nuclear polyhedrosis virus to the larva of fall web worm, Hyphantria cunea D.

• Knowledge Management Research
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• v.14 no.1
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• pp.73-94
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• 2013

Customer's purchase state consists of purchase inertia and variety-seeking. As the growing brand familiarity triggers the increase of brand attractiveness, customers purchase state will be of inertia. However the excessively growing brand familiarity ignites the decrease of brand attractiveness. Followingly the purchase state will be tend to plunge into the variety-seeking state. The main topic of this study is to validate the asymmetric formation of customer's purchase states between inertia and variety-seeking. In order to follow up the main topic, this article introduces a model to freely describe the velocity of value changes depending upon the purchase states. This model will help overcome the limitation of the past studies having been based on the symmetric value changes. Based on this approach marketer will be able to decide the timing of sales promotions. This research utilized local telecommunication carrier's database of smartphone application purchase/download records. This database was collected from two years (2009 and 2010) span, the time when the smartphones started commodifying in Korea whilst most of the past studies had used purchase data of maturity stage products. From this approach utilizing the introduction stage data in the product life cycle, the probability of brand choice depending upon the purchase state on the early-stage can be probed. Moreover, this study tries to expand the research methodology from the other areas of research by knowledge sharing. Here this study introduces the methodology of section-aggregated multinomial logit to simultaneously estimate the parameters that were included in the plural multinomial logit functions while the plural functions were inter-connected. This adoption of section-aggregated multinomial logit model procedures from the computerized statistics areas is expected to nourish the marketing research for more precise analysis and estimation of effects of marketing activities.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.768-777
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• 2006

The purpose of this study lies in formulating the landscape preference model using a conditional logit that involves the effect of visual elements as well as landscape itself on landscape preferences. To measure landscape preferences, a photo-questionnaire composed of paired photographs of the Cairngorms National Park of Scotland and the Jirisan National Park of Korea was distributed to visitors to the Jirisan National Park of Korea. Visual elements of landscape quantitatively measured by photogrammetry were reduced to orthogonal principal components that were subsequently used as explanatory variables in a conditional logit. As a result, the mixed conditional logit including the effect of landscape itself satisfied the Independence of Irrelevant Alternatives (IIA) property and showed reliable goodness of fit (${\rho}^2=0.25$). It was concluded that the mixed conditional logit including the effect of landscape itself was appropriate for landscape preference model rather than usual conditional logit excluding the effect.

• Journal of Distribution Research
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• v.4 no.3
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• pp.47-64
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• 2000

This study introduces the mother logit model to predict consumer's store choices. The model is not based on the IIA assumptions and thus accounts for substitution among similar alternatives. The choice data as an input to the model is obtained through the conjoint-type choice experiment. The model is applied to consumer's choice of fastfood stores in the context where new store enters the market. The analysis shows that the substitution effects are significant and therefore the mother logit model predicts better than the IIA model. The mother logit model will be useful as well for the market structure analysis in capturing cannibalization among several brands.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.151-161
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• 1997

An easy Monte Carlo Gibbs sampling approach is suggested for Bayesian analysis of cumulative logit models for ordinal polytomous data. Because in the cumulative logit model the posterior conditional distributions of parameters are not given in convenient forms for random sample generation, appropriate latent variables are introduced into the model so that in the new model all the conditional distributions are given in very convenient forms for implementation of the Gibbs sampler.

• Journal of the Korean Institute of Landscape Architecture
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• v.24 no.4
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• pp.96-111
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• 1997

This study was carried out to identify users' choice behavior of theme parks. overland. Lotte World, Seoul Land, Dreamland and Children's Grand Park were selected as study areas. Both multinomial logic model(MNL), nested logic model(NMNL) and joint logit model wet$.$e test using a choice-based sample collected on study areas. Hausman-McFadden test showed that the MNL is not appropriate because the IIA assumption is violated. To avoid the problematic IIA assumption, the NMNL was tested. It splits similar alternatives into groups and nests separate decisions into hierarchical order to avoid the IIA assumption. Cluster analysis and discriminant analysis were conducted to find applicable nest structures. The inclusive value coefficient was 0.7788. It meant that sufficient condition of this model is met and users' choice behavior can be better understood by NMNL than MNL. The $\rho$2 value and accuracy of prediction of this model were 0.402 and 46.33% , respectively. Several comments were suggested to make the NMNL to be more reliable for future research on users' choice behavior of theme park.