• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1057-1065
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• 2010

In this paper we discuss some cautionary notes in using the Pearson chi-squared test statistic for the goodness-of-fit of the ordinal response model. If a model includes continuous type explanatory variables, the resulting table from the t of a model is not a regular one in the sense that the cell boundaries are not fixed but randomly determined by some other criteria. The chi-squared statistic from this kind of table does not have a limiting chi-square distribution in general and we need to be very cautious of the use of a chi-squared type goodness-of-t test. We also study the limiting distribution of the chi-squared type statistic for testing the goodness-of-t of cumulative logit models with ordinal responses. The regularity conditions necessary to the limiting distribution will be reformulated in the framework of the cumulative logit model by modifying those of Moore and Spruill (1975). Due to the complex limiting distribution, a parametric bootstrap testing procedure is a good alternative and we explained the suggested method through a practical example of an ordinal response dataset.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1116-1123
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• 2006

The methodological framework proposed in this paper addresses the strength of the applied Bass model by Mahajan and Muller(1996) that it reflects the substitution of next generations among products. Also this paper is to estimate and analyze the forecast of demand for products that do not exist in the marketplace. We forecast the sales of digital TV using estimated market share and data obtained by the face to face Interview. In this research, we use two methods to analyze the demand for Digital TV that are the forecasting the Demand for the Substitution and binary logit analysis. The logit analysis is to estimate the decisive factor of purchasing digital TV. The decisive factors are composed of purchasing plan, region, gender, TV price, contents, coverage, income, age, and TV program. We apply the model to South Korea's market for digital TV. The results show that (1) Income, region and TV price play a prominent part which is the decisive factor of purchasing digital TV. (2) We forecaste the demand of digital TV that will be demanded about 18 millions TVs in 2015

• Korean Management Science Review
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• v.25 no.1
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• pp.139-147
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• 2008

Conjoint Analysis is marketers' favorite methodology for finding out how buyers make trade-offs among competing products and suppliers. Thousands of applications of conjoint analysis have been carried out over the past three decades. The conjoint analysis has been so popular as a management decision tool due to the availability of a choice simulator. A conjoint simulator enables managers to perform 'what if' question accompanying the output of a conjoint study. Traditionally the First Choice Model (FCM) has been widely used as a choice simulator. The FCM is simple to do, easy to understand. In the FCM, the probability of an alternative is zero until its value is greater than others in the set. Once its value exceeds that threshold, however, it receives 100%. The LOGIT simulation model, which is also called as "Share of Preference", has been used commonly as an alternative of the FCM. In the model part worth utilities aren't required to be positive. Besides, it doesn't require part worth utilities computed under LOGIT model. The simulator can be used based on regression, monotone regression, linear programming, and so on. However, it is not free from the Independent from Irrelevant Alternatives (IIA) problem. This paper proposes the EBA (Elimination-By-Aspects) model as a useful conjoint-like method. One advantage of the EBA model is that it models choice in terms of the actual psychological processes that might be taking place. According to EBA, when choosing from choice objects, a person chooses one of the aspects that are effective for the objects and eliminates all objects which do not have this aspect. This process continues until only one alternative remains.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.15-22
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• 2021

This study aims to obtain a stock investment strategy model based on the industrial sector in Indonesia Stock Exchange (IDX). This study uses IDX data for the period of January 1996 to December 2016. This study uses the Markov Regime Switching Model to identify trends in market conditions that occur in industrial sectors on IDX. Furthermore, by using the Logit Regression Model, we can see the influence of economic factors in determining trends in market conditions sectorally and the probability of trends in market conditions. This probability can be the basis for determining stock investment decisions in certain sectors. The results showed descriptively that the stocks of the consumer goods industry sector had the highest average return and the lowest standard deviation. The trend in sectoral stock market conditions that occur in IDX can be divided into two conditions, namely bullish condition (high returns and low volatility) and bearish condition (low returns and high volatility). Differences in the conditions are mainly due to differences in volatility. The use of a Logit Regression Model to produce probability of market conditions and to estimate the influence of economic factors in determining stock market conditions produces models that have varying predictive abilities.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.873-900
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• 2007

Non-market valuation studies tend to assume that individual households have homogeneous preferences for a non-market good to value. However, since the preferences for non-market goods, especially environmental goods are more likely to be heterogeneous by nature, it may be more appropriate to assume heterogeneous preferences for non-market goods, which may in turn may lead to reduced biases in the WTP estimation. This study investigate the extent to which individual households have heterogeneous preferences for reduced concentrations of radon, a radioactive indoor air pollutant, for road safety, and for nuclear power safety. We also analyze the effect of heterogeneity assumption on the results of model and WTP estimation. Using the choice experiments and mixed logit models, we found that allowing for heterogeneous preferences improved model fitness and that there existed heterogeneous preferences for both reduced radon concentration and road safety, albeit not for nuclear power safety. The mean WTP for reduced radon concentrations and road safety increased by factors of 2.44 and l.74 respectively with the models allowing for heterogeneous preferences.

• Land and Housing Review
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• v.11 no.2
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• pp.1-14
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• 2020

The aim of this study is to empirically identify the differentiating characteristics of determinant factors on sing-person households' commuting mode choice compared to multi-person households' one in order to establish the customized police directions to decrease private car use in commuting. While the study use the 2% sample survey data on the population and housing in 2015, it employ multinomial logit models on relative choice probability of such alternative commuting modes as bus, subway or rail, and walking, rather than driving. As potential determinant factors, the study employs demographic, socio-economic, and housing and residential one for both models of single-person and multi-person households. The study finds that the behavior of commuting mode choice has distinctive difference by gender, marriage status, physical activity constraint, job type, residential period in current housing of the single-person household's workers compared to the multi-person households' ones. Based on the findings, the study deduce ten commuting policy directions customized for the single-person household.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.655-673
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• 2004

This paper is concerned with analysing the bankruptcy prediction power of three models: Multivariate Discriminant Analysis(MDA ), Logit Analysis, Neural Network. The after-crisis bankrupted companies were limited to the research data and the listed companies belonging to manufacturing industry was limited to the research data so as 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 network model 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.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.273-290
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• 2006

This study suggests a frequency matrix technique to predict personal credit rate more efficiently using incomplete data sets. At first this study test on multiple discriminant analysis and logistic regression analysis for predicting personal credit rate with incomplete data sets. Missing values are predicted with mean imputation method and regression imputation method here. An artificial neural network and frequency matrix technique are also tested on their performance in predicting personal credit rating. A data set of 8,234 customers in 2004 on personal credit information of Bank A are collected for the test. The performance of frequency matrix technique is compared with that of other methods. The results from the experiments show that the performance of frequency matrix technique is superior to that of all other models such as MDA-mean, Logit-mean, MDA-regression, Logit-regression, and artificial neural networks.

• Journal of Korea Technology Innovation Society
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• v.10 no.1
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• pp.164-181
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• 2007

This paper empirically analyzes determinants of DTV (Digital Television) adoption in household survey data with IT-related household demand characteristics. To this purpose, we conducted a survey for the adoption of DTV to 1,000 households nationwide. In the questionnaire, various questions asking socio-economics characteristics such as age, education, income were included. Also, status of adoption and usage of IT services such as paid broadcasting, internet, and DVD were asked. To analyze the determinants of intention of purchasing, decision of purchasing, and the timing of purchasing DTV, we adopted the ordered logit, binary logit and multinomial legit models. When there is an order among groups, ordered logit was employed and when there is no orders among groups, multinomial logit was emplyed for the estimation. It is found that when conditions of other explanatory variable are constant, the more educated household heads are, the more probable they become early adopters of DTV. It is also found that other conditions being constant, the income level of households and IT-related household demand characteristics are very important factors affecting DTV adoption. Since the likelihood of purchasing DTV is much higher for those who know the government policy of analog broadcasting termination schedule than others who do not know, dissemination of the Korean government's digital broadcasting policy will affect significantly the adoption of DTV. And policy with various incentives ought to be employed to accelerate DTV adoption, because households with the older TV sets are more likely to purchase DTV. It is suggested that the Korean government should develop policy to connect both DBS (Direct Broadcast Satellite) and DTV since DBS subscribers are more likely to be an early adopter than non-subscribers.

• Journal of Korean Society of Transportation
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• v.8 no.1
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• pp.55-71
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• 1990

The behavioral mechanism underlying the traffic assignment model is a choice, or decision-making process of traveling paths between origins and destinations. The deterministic approach to traffic assignment assumes that travelers choose shortest path from their origin-destination pair. Although this assumption seems reasonable, it presumes that all travelers have perfect information regarding travel time, that they make consistently correct decision, and that they all behave in identical fashion. Stochastic user equilibrium assignment relaxes these presumptions by including a random component in traveler's perception of travel time. The objective of this study is to compare "A Model of Deterministic User Equilibrium Assignment" with "Models of Stochastic User Equilibrium Assignment" in the theoretical and practical aspects. Specifically, SUE models are developed to logit and probit based models according to discrete choice functions. The models were applied to sioux Falls net ork consisting of 24 zones, 24 nodes and 76 links. The distribution of perceived travel time was obtained by using the relationship between speed and traffic flow.