• Korean Management Science Review
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• v.19 no.2
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• pp.125-137
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• 2002

The telecommunications market is expanding rapidly and becoming more substitutive. In this environment, demand forecasting is very difficult, yet important for both practitioners and researchers. in this paper, we adopt the modeling approach proposed dy Jun and Park ［6］. The basic premise is that demand patterns result from choice behavior, where customers choose a product to maximize their utility. We apply a choice-based substitutive diffusion model to the Korean mobile telecommunication service market where digital service has completely replaced analog service. In comparison with Bass-type multigeneration models. our model provides superior fitting and forecasting performance. The choice-based model is useful in that it enables the description of such complicated environments and provides the flexibility to include marketing mix variables such as price and advertising in the regression analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.81-89
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• 1996

A design method of fuzzy modeling is presented for the model identification of route choice of traffic problems.The proposed fuzzy modeling implements system structure and parameter identification in the eficient form of""IF..., THEN-.."", using the theories of optimization theory, linguistic fuzzy implication rules. Three kinds ofmethod for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 21,and proposed modified-linear inference (type 3). The fuzzy inference method are utilized to develop the routechoice model in terms of accurate estimation and precise description of human travel behavior. In order to identifypremise structure and parameter of fuzzy implication rules, improved complex method is used and the least squaremethod is utilized for the identification of optimum consequence parameters. Data for route choice of trafficproblems are used to evaluate the performance of the proposed fuzzy modeling. The results show that the proposedmethod can produce the fuzzy model with higher accuracy than previous other studies -BL(binary logic) model,B(production system) model, FL(fuzzy logic) model, NN(neura1 network) model, and FNNs (fuzzy-neuralnetworks) model -.fuzzy-neural networks) model -.

• Asia Marketing Journal
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• v.11 no.1
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• pp.73-92
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• 2009

Consumers influence other consumers' brand choice behavior by delivering a variety of objective or subjective information on a particular product, which is called WOM (Word-Of-Mouth) activities. For WOM activities, WOM senders should choose messages to deliver to other consumers. We classify the contents of the messages a consumer chooses for WOM delivery into two categories: Subjective (positive or negative) evaluation and objective information on products. In our study, we regard WOM senders' activities as a choice behavior and introduce a choice model to study the relationship between the choice of different WOM information (WOM with positive or negative subjective evaluation and WOM with objective information) and its influencing factors (information sources and consumer characteristics) by developing two bivariate Probit models. In order to consider the mediating effects of WOM senders' product involvement, product attitude, and their characteristics (gender and age), we develop three second-level models for the propagation of positive evaluations, of negative evaluations, and of objective information on products in an hierarchical Bayesian modeling framework. Our empirical results show that WOM senders' information choice behavior differs according to the types of information sources. The effects of information sources on WOM activities differ according to the types of WOM messages (subjective evaluation (positive or negative) and objective information). Therefore, our study concludes that WOM activities can be partially managed with effective communication plans influencing on consumers' WOM message choice behavior. The empirical results provide some guidelines for consumers' propagation of information on products companies want.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.44-57
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• 2019

It is crucial to understand how people make decisions on mode choice and to accurately predict their behaviors in transportation planning. One of avenues for advancing modeling is, in particular, taking into account for taste heterogeneity in modeling that can incorporate different decision-making processes across group. In this study, we hypothesize that how people make decisions on mode choice would differ by destination in that land use characteristics are heterogeneous by zone even if zones are all in the same area. To this end, we apply Latent Class Modeling (LCM) to commute trips in Seoul by using 2010 household travel diary survey, investigate types of latent classes with the aid of characteristics of destination, and analyze how those classes differently response to factors. The LCM identifies two classes: in the first one, modal split of auto and public transit (bus and metro) is almost half-and-half and the trip destinations are characterized by relatively more residence facilities and less business/commercial facilities; in the second one, public transit has a notably high share and trip destinations are characterized by relatively more business/commercial facilities. In addition, it turns out that demographic and socio-economic variables affect mode choice differently by class.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.2
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• pp.77-86
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• 2000

Consumers facing a large number of brands to choose from are known to use simplified heuristic to screen a set of relevant brands called the consideration set from the whole alternatives, Purchase decisions are then made from the brands in the consideration set, Two approaches have been suggested to model the two-stage choice process., One is to treat the con-sideration set as a crisp set (e.g Roberts and Lattin 1991) The other is to treat the set as a fuzzy set (e.g. Fortheringham 1988) The paper empirically compares the two types of models using data for soft drinks sneakers and departments. The results show that a model employing the crisp set approach fits the data better than that with the fuzzy set approach and better than a single-stage choice logit model.

• Knowledge Management Research
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• v.20 no.2
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• pp.1-24
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• 2019

This tutorial introduces procedures and methods for performing structural equation modeling using R. To do this, we present advanced analysis methods based on structural equation model such as mediation effect analysis, moderation effect analysis, moderated mediation effect analysis, and multiple-group analysis with R program code using R lavaan package that supports structural equation modeling. R is flexible and scalable, unlike traditional commercial statistical packages. Therefore, new analytical techniques are likely to be implemented ahead of any other statistical package. From this point of view, R will be a very appropriate choice for applying new analytical techniques or advanced techniques that researchers need. Considering that various studies in the social sciences are applying structural equations modeling techniques and increasing interest in open source R, this tutorial is expected to be useful for researchers who are looking for alternatives to existing commercial statistical packages.

• Journal of Korean Society of Transportation
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• v.1 no.1
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• pp.28-42
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• 1983

In recent years, significant advances have been made enabling travel demand analysis and network design methods to be used as increasingly realistic evaluation tools. What has been lacking is the integration of travel demand analysis with network design models. This paper reviews some of advanced (integrated) modeling approaches and presents future research directions of integrated modeling system. To design urban transportation networks, it is argued that the travelers' free choice of mode, destination and route should be introduced into transportation network design procedure instead of assuming that trips from a zone to a workplace are fixed or deriving them in a normative procedure to achieve hypothetical system optima.

• Journal of Applied Reliability
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• v.4 no.1
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• pp.39-64
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• 2004

Taguchi's multi-characteristic experiments seek proper choice of levels of contollable factors which satisfy that all reponses of characteristics in a desirable range simultaneously. This aim can be achieved by response surface techniques that allow more flexible in modeling than traditional Taguchi's parameter design. In this article, a multi-response surface modeling and analysis techniques is proposed to deal with the multi-characteristic optimization problem in experimentation with Taguchi's controllable and noise factors.

• Journal of Korean Society for Quality Management
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• v.27 no.1
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• pp.165-194
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• 1999

Taguchi's parameter design seeks proper choice of levels of controllable factors (Parameters in Taguchi's terminology) that makes the qualify characteristic of a product optimal while making its variability small. This aim can be achieved by response surface techniques that allow flexibility in modeling and analysis. In this article, a collection of response surface modeling and analysis techniques is proposed to deal with the multiresponse optimization problem in experimentation with Taguchi's signal and noise factors.

• Journal of Korean Home Economics Education Association
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• v.23 no.4
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• pp.19-34
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• 2011

The purpose of this study were to investigate relations among family resilience, self-determination(autonomy, perceived competence, relatedness) and commitment to career choice and to examine the meditating effects of self-determination(autonomy, perceived competence, relatedness) in the process by which family resilience affected commitment to career choice. Subjects of the study were 277 college students in the Chungbuk and Kyungpook province. AMOS 7.0 was employed to analyze the data. The results were as follows: First, college students' family resilience had a direct impact on college students' self-determination(autonomy, perceived competence, relatedness) and commitment to career choice. Second, students' self-determination(autonomy, perceived competence, relatedness) had a direct impact on students' commitment to career choice. Third, it was found students' self-determination(autonomy, perceived competence, relatedness) was a meditating factor in the relationship between students' family resilience, and commitment to career choice.