• Journal of Intelligence and Information Systems
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• v.12 no.4
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• pp.1-14
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• 2006

This study proposed a customer preference estimation model for production recommendation and a method to enhance the performance of product recommendation using the estimated customer preference information. That is, we suggested customer preference estimation model to estimate exactly customer's product preference with his behavior. This model shows the relationship of customer's behaviors with his preferences. The proposed estimation model is optimized by learning the relative weights of customer's behavior variables to have an effect on his preference and enables to estimate exactly his preference. To validate our proposed models, we collected virtual book store data and then made a comparative analysis of our proposed models and a benchmark model in terms of performance results of collaborative filtering for product recommendation. The benchmark model means a prior preference weighting model. The results of our empirical analysis showed that our proposed model performed better results than the benchmark model.

• Journal of Information Technology Applications and Management
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• v.10 no.3
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• pp.75-92
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• 2003

In order to investigate IS(Information Systems) outsourcing cost estimation model preference of firms, this study reviews previous literatures on outsourcing and firm characteristics. The relationships between firm characteristics and IS outsourcing cost estimation model preference are analysed. Four major factors of firms characteristics are found and classified. IS outsourcing cost estimation model with SLA are found to have a strong relationship with organizational culture. Future research will be needed to verify the result of this exploratory study.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.443-450
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• 2005

In this paper, we propose an intelligent model lot extraction of the web user's preference and present the results of evaluation. For this purpose, we analyze shortcomings of current information retrieval engine being used and reflect preference weights on learner. As it doesn't depend on frequency of each word but intelligently learns patterns of user behavior, the mechanism Provides the appropriate set of results about user's questions. Then, we propose the concept of preference trend and its considerations and present an algorithm for extracting preference with examples. Also, we design an intelligent model for extraction of behavior patterns and propose HTML index and process of intelligent learning for preference decision. Finally, we validate the proposed model by comparing estimated results(after applying the Preference) of document ranking measurement.

• Journal of the Korean Graphic Arts Communication Society
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• v.30 no.2
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• pp.69-78
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• 2012

This research attempts to analyze how attributes of ad model influence on brand familiarity, personality, and preference among consumers. Attributes of ad model was classified into three; attractiveness, professionalism, and reliability. One hundred of consumers who lived in Daejeun City were selected as respondents for this research. The result of hypothesis I showed that attributes of ad model significantly influenced on brand familiarity. it was the result of hypothesis II that both Attractiveness and professionalism of ad model affected brand personality. It was also found that attractiveness and professionalism are significantly brand preference from the result of hypothesis III. In conclusion, findings showed that attractiveness of ad model mostly influenced on brand familiarity, personality, preference.

• Journal of the Korean Society of Costume
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• v.42
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• pp.113-126
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• 1999

The purpose of this study was to identify the differences n preference of advertisement and intention to buy the advertised jeans among the consumer groups which perceived eroticism and attraction of female model in advertising differently. he data were collected using questio-nnaires which contained eleven advertisements of Guess jeans selected form Vogue magazine publ-ished from 1990 to 1996. Female college students (n=270) living in Seoul Korea participated in the study. The data were analyzed by one-way ANOVA. he results of this study were as follows:First there were significant differences in preference of advertisement and intentio to buy the advertised jeans among the consumer groups which had different perceptions of eroticism and attraction of model in the case of eleven advert-isements. Second consumer group which perceived model erotic and attractive highly had the most preference of advertisement and intention to buy the advertised jeans, However consumer group which perceived model low in two aspects had the lowest preference and intention to buy. Third consumer group which perceived model a low erotic but highly attractive women had a higher preference of advertisement and intention to buy the advertised jeans than consumer gorup which perceived model a highly erotic but low attractive women or the former group was similar in prefe-rence and intention to buy to the latter group.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.111-126
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• 2002

This paper presents an interactive decision procedure to aggregate each group member's preferences when each group member articulates his or her preference information incompletely. An index, an indicative for the preference strength between alternatives, is derived to aid each decision maker to articulate preference information about alternatives. We develop a mathematical programming model that can establish dominance relations when the preference information about values of alternatives, attribute weights, and group member's importance weights are provided incompletely. Also, the preference relation between alternatives is to be considered in the model. Based on the preference strength measure and mathematical model, we develop an interactive group decision support procedure.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.1-8
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• 2009

Learning user's preference is a key issue in intelligent system such as personalized service. The study on user preference model has adapted simple user preference model, which determines a set of preferred keywords or topic, and weights to each target. In this paper, we recommend multi-perspective user preference model that factors sentiment information in the model. Based on the topicality and sentimental information processed using natural language processing techniques, it learns a user's preference. To handle timc-variant nature of user preference, user preference is calculated by session, short-term and long term. User evaluation is used to validate the effect of user preference teaming and it shows 86.52%, 86.28%, 87.22% of accuracy for topic interest, keyword interest, and keyword favorableness.

• Proceedings of the Technology Innovation Conference
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• 2006.02a
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• pp.264-297
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• 2006

In this paper, we attempt to analyze consumer preference for the alternative-fuel vehicles based on data from a stated preference using the conjoint analysis. Five possible fuel types (gasoline, diesel, CNG, LPG, Hybrid (electricity+gasoline)) are covered in conjoint cards. To estimate and analyze consumer preference, discrete choice model is used. Specifically, Bayesian mixed logit model is used. Based on estimating results, we discuss the business strategy and policy for the alternative fuel vehicle.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.41-52
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• 1994

Imprecision of evaluation or lack of prior information about preference can be an obstacle for decision maker in representing his strict preference. Therefore, fuzziness of preference can take place, and in addition, intransitivity or incomparability of preference becomes the critical difficulty in making complete preorder of alternatives. In order to get better solution and to improve practical usufulness, MCDM should be established as a pseudo-criterion model that include fuzzy preference. In this paper, we suggest a pseudo-criterion model that can make complete preorder of alternatives by metric distance measure.

• Journal of Korean Critical Care Nursing
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• v.9 no.2
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• pp.36-47
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• 2016

Purpose: The study examined core job characteristics and job preference to explain work performance among critical care nurses. The theoretical model was constructed based on the job characteristics model with core job characteristics as exogenous variables, and work performance and job preference as endogenous variables. Methods: A total of 228 hospital nurses participated in the study from May to September, 2015. Data were collected through structured questionnaires and analyzed using structural equation modeling. Results: The model showed a good fit to the data with $x^2/df=2.90$, goodness of fit index = .91, root mean square residual = .20, comparative fit index = .93, and incremental fit index = .93. The core job characteristics explained 64% of the variance in job preference. The core job characteristics and job preference explained 52% of the variance in work performance. Conclusions: The core job characteristics can explain the work performance among critical care nurses through job preference. Effective strategies to improve the work performance among critical care nurses should focus on the application of the core job characteristic into a productive work environment. Further studies are warranted to explore the role of job preference of critical care nurses in promoting their work performance.