• 대한교통학회지
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• 제11권2호
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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.

• 한국경영과학회지
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• 제34권3호
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• pp.29-41
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• 2009

The purpose of this paper is to develop a new classification method for predicting consumer choice based on genetic algorithm, and to validate Its prediction power over existing methods. To serve this purpose, we propose a hybrid model, and discuss Its methodological characteristics in comparison with other existing classification methods. Also, we conduct a series of experiments employing survey data of consumer choices of MP3 players to assess the prediction power of the model. The results show that the suggested model in this paper is statistically superior to the existing methods such as logistic regression model, artificial neural network model and decision tree model in terms of prediction accuracy. The model is also shown to have an advantage of providing several strategic information of practical use for consumer choice.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2008년도 추계학술대회 및 정기총회
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• pp.1-7
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• 2008

The purpose of this paper is to develop a new classification method for predicting consumer choice based on genetic algorithm, and to validate its prediction power over existing methods. To serve this purpose, we propose a hybrid model, and discuss its methodological characteristics in comparison with other existing classification methods. Also, to assess the prediction power of the model, we conduct a series of experiments employing survey data of consumer choices of MP3 players. The results show that the suggested model in this paper is statistically superior to the existing methods such as logistic regression model, artificial neural network model and decision tree model in terms of prediction accuracy. The model is also shown to have an advantage of providing several strategic information of practical use for consumer choice.

• The Journal of Asian Finance, Economics and Business
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• 제7권2호
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• pp.221-228
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• 2020

This study suggests an alternative to the conventional collaborative filtering method for predicting consumer choice, using case-based reasoning. The algorithm of case-based reasoning determines the similarity between the alternative sets that each subject chooses. Case-based reasoning uses the inverse of the normalized Euclidian distance as a similarity measurement. This normalized distance is calculated by the ratio of difference between each attribute level relative to the maximum range between the lowest and highest level. The alternative case-based reasoning based on similarity predicts a target subject's choice by applying the utility values of the subjects most similar to the target subject to calculate the utility of the profiles that the target subject chooses. This approach assumes that subjects who deliberate in a similar alternative set may have similar preferences for each attribute level in decision making. The result shows the similarity between comparable alternatives the consumers consider buying is a significant factor to predict the consumer choice. Also the interaction effect has a positive influence on the predictive accuracy. This implies the consumers who looked into the same alternatives can probably pick up the same product at the end. The suggested alternative requires fewer predictors than conjoint analysis for predicting customer choices.

• 한국ITS학회 논문지
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• 제22권6호
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• pp.157-167
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• 2023

본 연구에서는 분산 컴퓨팅 및 개별 디바이스 활용을 통해 개인 정보 보호에 특화된 학습방법인 연합학습 방법론을 기반으로, 모바일 내비게이션 애플리케이션에서 수집된 대규모의 운전자 데이터를 이용하여 경로 선택 예측 모델을 수립하는 방법에 대해 고찰한다. 경로 선택 모델링에서 활용될 수 있는 운전자 데이터의 전처리 및 분석 방법을 수립하고, 서포트벡터머신(SVM) 및 다층 퍼셉트론(MLP)과 같이 기존에 널리 활용되는 학습 방법과 연합학습 방법의 성능과 특성을 비교한다. 분석 결과 연합학습을 통한 모델 성능은 중앙 서버 기반의 모델과의 비교에서 예측 정확도 측면의 차이가 거의 없는 것으로 나타났으나, 개별 데이터가 충분히 확보되는 경우 연합학습 모델과 같은 개인화 모델의 성능이 개선될 수 있다는 점을 확인하였다. 연합학습 모델은 본 연구의 경로 선택 모델링 사례와 같이 모빌리티 부문의 데이터 프라이버시 문제가 중요한 분야에서 대규모 데이터 처리를 필요로 하는 경우에 그 활용 가치가 매우 높을 것으로 기대된다.

• 대한가정학회지
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• 제46권5호
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• pp.63-71
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• 2008

The purposes of this study were (1) to analyze the absolute and relative importance of tourists' choice attributes of restaurants and (2) to compare tourists' choice patterns with the prediction of restaurant operators in the tourism provinces of Gangwon-do, Empirical data for this study were collected from the 77 tourists and 66 restaurants operators. The attributes and attribute levels for the hypothetical profiles were decided from a focus group interview and 15 profiles were selected from fractional factorial designs. The SPSS/WIN 12,0 conjoint procedure was used to calculate the utility scores and simulate the profiles, According to the analysis on the relative importance of tourists' choice attributes of restaurants, food taste was the most important attribute(36.9%), followed by facility cleanliness(28.5%), dishes cleanliness(24.5%), price(19.3%) and service(18.3%). The tourists' ratings of the importance of the individual attributes differed from the ranking of the relative importance of the same attributes as derived from the conjoint analysis. The operators rated dishes cleanliness(27.6%) as also important, followed by food taste(27.7%), in choosing a restaurant Tourists' preference and operators' prediction of hypothetical profiles showed significant difference in L(p < .05), O(p < .01), M(p < .05), and H(p < .01) restaurants. Operators who want to differentiate themselves from their competitors should make decisions based on an increased understanding of tourists' restaurant choice decision process and measure the latent needs of tourists in the tourism provinces.

• 한국조경학회지
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• 제24권4호
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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.

• Communications for Statistical Applications and Methods
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• 제17권6호
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• pp.811-827
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• 2010

본 논문에서는 통계적 역문제로서 이항 선택모형에서의 밀도추정 방법에 대하여 연구하였다. 밀도함수의 추정을 위하여 직교열 기저를 이용하였으며, 모형의 복잡성과 예측의 정확성을 반영한 적절한 절단모수의 선택에 대하여 고려하였다. 이항 선택 모형에서 데이터에 의존하는 절단모수를 선택하는 방법에 대해 제안하고 모의실험, 실자료를 통해 제안한 방법의 성능을 규명하였다.

• 한국조경학회지
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• 제28권2호
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• pp.18-27
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• 2000

The importance of constraints has been one of major issues in recreation for prediction of choice behavior; however, traditional conjoint choice model did not consider the effects of these variables or fail to integrate them into choice model adequately. The purposes of this research are (a) to estimate the effects of constraints in theme park choice behavior by the constraints-induced conjoint choice model, and (b) to test additional explanatory power of the additional constraints in this suggested model against the more parsimonious traditional model. A leading polling agency was employed to select respondents. Both alternative generating and choice set generating fractional factorial design were conducted to meet the necessary and sufficient conditions for calibration of the constraints-induced conjoint choice model. Th alternative-specific model was calibrated. The log-likelihood ratio test revealed that suggested model was accepted in the favor of the traditional model, and the goodness-of-fit($\rho$$^2$) of suggested and traditional model was 0.48427 and 0.47950, respectively. There was no difference between traditional and suggested model in estimates of attribute levels of car and shuttle bus because alternatives were created to estimate the effects of constraints independently from mode related variables. Most parameters values of constraints had the expected sign and magnitude: the results reflected the characteristics of the theme parks, such as abundance of natural attractions and poor accessibility in Everland, location of major fun rides indoor in Lotte World, city park like characteristics of Dream Land, and traffic jams in Seoul. Instead of the multinomial logit model, the nested logit model is recommended for future researches because this model more reasonably reflects the real decision-making process in park choice. Development of new methodology too integrate this hierarchical decision-making into choice model is anticipated.

• 지역연구
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• 제11권1호
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• pp.31-60
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• 1995

The distribution of economic activity over a mutually exclusive and exhaustive categorical industry-region matrix is modeled as a composition of two random components: the probability-like share distribution of jobs and the dynamic evolution of absolute aggregates. The former describes the individual activity location choice by comparing the predicted profitability of the current industry-region pair against that of all other alternatives based on the available information on industry-specific, region specific, or activity specific attributes. The latter describes the time evolution of macro-level aggregates using a dynamic reduced from model. With the seperation of micro choice behavior and macro dynamic aggregate constraint, the usual independence and identicality assumptions become consistent with the activity share distribution, hence multi-regional industrial migration can be represented by a set of probability evolution equations in a conservative Markovian from. We call this a Micro-Macro Composition Approach since the product of the aggregate prediction and the predicted activity share distribution gives the predicted activity distribution gives the predicted activity distribution which explicitly considers the underlying individual choice behavior. The model can be applied to interesting practical problems such as the plant location choice of multinational enterprise, the government industrial ploicy to attract international firms, and the optimal tax-transfer mix to influence activity location choice. We consider the latter as an example.