• Journal of Korea Trade
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• v.25 no.2
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• pp.178-195
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• 2021

Purpose - This study aims to analyze consumer in the multidimensional aspect of a combination of corporate image and brand personality in order to identify the structural causal relationship between consumer choice and corporate image and brand personality. Design/methodology - This study combined theoretical literature studies with empirical field studies using questionnaire survey methods. To achieve this objective, a hypothetical causal model consisting of three potential variables and nine measurement variables was created based on prior research, and a structural equation model was used to identify the suitability of the model. Findings - The hypothetical model established by this study was judged to be generally appropriate. In particular, corporate image was shown to have significant static direct effects on consumer choice and brand personality. It was also shown that brand personality had a direct static effect on consumer choice, and that corporate image has an indirect significant impact on consumer choice by moderating brand personality. Originality/value - Previous papers have mainly focused on one-dimensional studies of various images, such as companies and brands. However, this paper used a model that analyzed consumer choice through multi-clue information rather than corporate images as the only clue to consumer choice.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.3
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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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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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.

• Asia Marketing Journal
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• v.22 no.2
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• pp.1-18
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• 2020

We estimate a choice-based aggregate demand model accounting for consumers' consideration sets, and study its implications on market structure. In contrast to past research, we model and estimate consumer demand using aggregate-level consumer browsing data in addition to aggregate-level choice data. The use of consumer browsing data allows us to study consumer demand in a realistic setting in which consumers choose from a subset of products. We calibrate the proposed model on both data sets, avoid biases in parameter estimates, and compute the price elasticity measures. As an empirical application, we estimate consumer demand in the camcorder category and study its implications on market structure. The proposed model predicts a limited consumer price response and offers a more discriminating competitive landscape from the one assuming universal consideration set.

• Journal of Distribution Research
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• v.4 no.1
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• pp.17-29
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• 1999

We investigated the consumer behavior of store choice using consumer panel data. The NBD-Dirichlet model known to be predictive of the consumer's brand choice was also found to be well fitted for the store choice behavior. Understanding the regularity in the store choice will provide both manufacturers and sistributors with the necessary guidelines for their competitive strategies.

• Journal of Distribution Science
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• v.13 no.10
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• pp.135-142
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• 2015

Purpose - Following the speedy development of the smart phone industry, tourism companies started to increase their brand recognition and sales volume by adopting mobile applications. However, applications for tourism industries are still insignificant. This study tries to analyze empirical evidence from Korean and Chinese consumers who have used mobile tour applications. By using an expansion of the technology acceptance model (TAM), this study will find what factors have effects on user intention for mobile tour applications. The findings will be helpful for the development of mobile tour applications and the tourism industries. Research design, data, and methodology - This study uses the TAM, which was presented by Davis in 1989. This study uses consumer acceptance level, consumer choice attitude, and use intention as the basic variables to fit to the TAM, and adopts choice content quality, brand value, and usage motivation as additional variables to analyze. This study has developed several hypotheses and collected data from 620 users who used mobile applications for tourism during April 1 to April 30, 2015. A total of 612 valid questionnaires were collected and used in the data analysis. The data was analyzed with structural equation modeling using SPSS Win/pc and Amos 22.0. Results - The findings can be summarized as follows: First, the content quality affects the consumer acceptance degree and choice attitude. Second, the brand value has a directly positive effect on the consumer acceptance degree and choice attitude. It is clear that the content quality and brand value play important roles in raising consumer acceptance and choice attitude. Third, usage motivation has no effect on the consumer acceptance degree and choice attitude. Fourth, the acceptance degree does not have any effect on the consumer choice attitude. Fifth, the acceptance degree affects the use intention. Last, the consumer choice attitude affects the use intentions. This indicates that consumer acceptance and choice attitude must both be achieved to induce use intention among consumers. Finally, the effects of the mobile tour application content quality and brand value on consumer acceptance degree and choice attitude were confirmed. Additionally, the effects of the consumer acceptance degree and choice attitude on use intentions were analyzed. Conclusion - It is not meaningful for tourism marketing to launch tour applications in the mobile market without understanding tourism consumer characteristics. When developing mobile tour applications, companies should focus on the characters of consumer choice attitudes as high quality, high brand value, usefulness, and ease of mobile tour applications. This study has limitations in that it did not consider negative factors such as perceived risks or analyze whether there are differences between Korean and Chinese consumers. In the future, we will consider equipping the same mobile tour applications commonly used by both Korean and Chinese consumers, and then examine negative factors as well as the differences in mobile tour applications between Korean and Chinese consumers.

• Journal of the Korean Society of Clothing and Textiles
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• v.20 no.6
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• pp.1125-1137
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• 1996

The author reviewed seventy papers on social psychology of clothing and fashion marketing fields, which were published in the Journal of the Korean Society of Clothing and Textiles between 1983 and 1996. The market variables and consumer behavior variables were focused on. This review showed that the market variables had been divided into three groups of variables: 1) product variables (product image and product classification): 2) brand variables (brand image and brand positioning): and 3) store variables (store image, store type, and distribution system) Consumer behavior variables have been studied on the basis of EBM Consumer Behavior Model: 1) purchasing motivation as need recognition: 2) information using as search information: 3) evaluation criteria and choice criteria as alternative evaluatioin : 4) clothing purchase, brand choice and store choice as purchase: 5) degree of wear, satisfaction and dissatisfaction as outcome: and 6) clothing discard. Variables that influence on consumer behavior, including situation variables, clothing attitude variables, personal . social variables were added to develop a variable model of clothing consumer behavior using the EBM Consumer Behavior Model.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.324-334
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• 2016

Manufacturers and retailers are interested in how prices, promotions, discounts and other marketing variables can influence the sales and shares of the products that they produce or sell. Therefore, many models have been developed to predict the brand share. Since the customer choice models are usually used to predict the market share, here we use hybrid model of Probabilistic Neural Network and Artificial Bee colony Algorithm (PNN-ABC) that we have introduced to model consumer choice to predict brand share. The evaluation process is carried out using the same data set that we have used for modeling individual consumer choices in a retail coffee market. Then, to show good performance of this model we compare it with Artificial Neural Network with one hidden layer, Artificial Neural Network with two hidden layer, Artificial Neural Network trained with genetic algorithms (ANN-GA), and Probabilistic Neural Network. The evaluated results show that the offered model is outperforms better than other previous models, so it can be use as an effective tool for modeling consumer choice and predicting market share.

• Korean Journal of Organic Agriculture
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• v.17 no.2
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• pp.135-150
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• 2009

This paper was to use choice experiments in the analysis of consumer choice behavior and preferences for five different attributes(the origin of rice, a quality certificate, a quality control, a traceability system, the price of rice) in Cheongju City. Completed surveys yielded 712 responses which were analyzed using the conditional logit model to analyze the marginal willingness to pay of the four attributes(the origin of rice, a quality certificate, a quality control and a traceability system) per household and estimated the marginal willingness to pay of the set of feasible options. The result of this study can be used as a guide for the rice industry in the design of possible labeling schemes.

• Asia-Pacific Journal of Business
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• v.1 no.2
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• pp.23-46
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• 2010

Despite the explosive growth of no-frill airline industry, very little is known about how consumers make purchase decision in such settings. Today's airline industry requires choice models consistent with consumers' true preference sets. This study used conjoint analysis to identify these ideal choice models. 38 percent of the subjects were found to use compensatory and 62 percent non-compensatory models. Our findings suggest a need to base choice-making promotions on ideal choice models if the promotion is to lead consumers to decisions consistent with true preferences.