• Journal of Global Scholars of Marketing Science
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• v.16 no.4
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• pp.39-54
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• 2006

Marketing managers hope to maximize the success rate of new products by satisfying various needs of consumers. For this, an analysis called 'conjoint analysis' has been frequently applied in the process of new product development. This study was performed to compare the predictability of diverse conjoint analyses in choice of general hospitals. The comparison was performed among four models of traditional conjoint analysis and choice-based conjoint analysis. Results show that the hybrid conjoint analysis, which combined the traditional conjoint analysis and the choice-based conjoint model showed the highest predictive accuracy. Still two models show similar estimates of utility.

• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.681-691
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• 2014

Ranking-based conjoint analysis(RBCA) and choice-based conjoint analysis(CBCA) have attracted significant interest in various fields such as marketing research. When conducting research, the researcher has to select one suitable approach in consideration of strengths and weaknesses. This article performs an empirical comparison of the predictability of RBCA and CBCA in order to provide criterion for the selection. A new concept of measurement set is developed by combining the ranking set and choice set. The measurement set enables us to apply two approaches separately on the same consumer group that allows a fair comparison of predictability. RBCA and CBCA are conducted on consumer preferences for RTD-coffee; subsequently, the predicted values of market shares and hit rates are compared. The study result reveals that their predictabilities are not significantly different. Further, the result indicates that RBCA is recommended if the researcher wants to improve data quality by filtering out poor responses or to implement the market segmentation. In contrast, CBCA is recommended if the researcher wants to lessen the burden on the respondents or to measure preferences under similar conditions with the actual marketplace.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.205-218
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• 2004

Conjoint analysis is employed to decompose the consumer's preference judgements into the importance of attributes, and to predict the degree of preference for each profile of the products, services, or ideas. It has been widely used in industrial marketing, particularly in the areas of product positioning and new product development. This paper is mainly concerned with the conjoint analysis based on the Chebyshev estimation since the efficiency of the least squares estimator is lower than that of the Chebyshev estimator when the preferences are measured as the rank-order. A case study is performed on the preference for cellular phones. And it is shown that conjoint analysis based on the Chebyshev estimation is superior, in terms of the predictive validity, to one which is based on the least squares estimation.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.441-447
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• 2007

The conjoint analysis is widely accepted in the field of marketing as a way to understand and incorporate the structure of customer preferences into the new product design process. We apply the conjoint analysis for understanding preferences about after school computer courses in elementary schools. We show that the artificial neural network analysis in addition to the conjoint analysis is very useful to understand the needs of elementary school students about after school computer courses.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.921-933
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• 2016

In this paper, we consider the comparisons of the personal preferences of analytic hierarchy process (AHP) and conjoint analysis (CA) which contain very relatively small number of alternatives. However, a direct performance comparison is not easy because these two methods have a much different process to achieve the final decision. Therefore, we adopt a validity and reference method with empirical case study for cosmetics preference of female college students. In case study, conjoint analysis has the merit of measuring internal validity; however, AHP has the merit of measuring predictive validity.

• Journal of Korea Game Society
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• v.3 no.1
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• pp.37-48
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• 2003

Although the user needs for computer game have been complicated and fragmented, new game development of Korean computer game developers are carried out from the developer's perspective. In the light of this limitation. This study introduces conjoint that designs an optimal new product for game users. We applied the conjoint analysis to Koran game market and found several important issues regarding Koran game users. Our results show that, regardless of game types, Korean game useis' preference mainly center on "variety of game."

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.11a
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• pp.171-177
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• 2000

본 연구는 ‘문화적 미래형 감성디자인 개발’을 위한 Car AV시스템 개발 프로젝트의 일환으로서 기존 제품의 사용성 평가와 사용자 관찰 방법 등을 통해 사용 환경과 사용자의 이용 행태에 관해 조사하고, 특히 컨조인트 분석을 통해 사용자의 선호도에 주요한 영향을 미친 신뢰성 있는 속성을 규명하고자 하는데 목적이 있다. 컨조인트 분석 프로세스에서 추출된 독립적인 각각의 속성과 수준들의 조합안을 바탕으로 사용자 선호도 조사를 함으로써 궁극적으로는 최적의 속성과 수준의 조합안을 제시하고자 한다. 또한 컨조인트 분석을 위해서 인터넷을 이용한 조사 시스템 구축과 활용 과정에 대해 살펴봄으로써 이의 실질적인 활용과 문제점에 관해 고찰하고자 한다.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.695-703
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• 2009

Currently, various cellular phone products with multiple functions and diverse designs are coming out in the cellular phone market. Companies have been developing their products for profit maximization, considering preferences of customers. In this article, we have created 18 profiles using the SPSS program and executed a survey to analyze preferences of college students. Also, we have grasped the relative importance of each attribute using conjoint analysis and executed clustering analysis to make market segmentation by binding the respondents who have similar partial value utilities. Lastly, by choice simulation, we have predicted market shares of 18 virtual products.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.205-214
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• 2011

With the success of Kindle, an electronic book reader developed by Amazon.com, there has been a growing interest in both electronic books and readers in Korea. In this paper, we analyze electronic book user needs through fuzzy analytic hierarchy process (AHP) and conjoint analysis. First, we select the important factors which can affect the intention to purchase electronic book readers by applying the fuzzy AHP with the help of electronic book experts. Next, we perform conjoint analysis to reveal the detailed needs of electronic book users for each of the selected factors. Some useful implications and research limitations are also presented with future research directions.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.7-16
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• 2019

As fierce competition is expected in the wearable devices marekt, it is needed to develop a technology planning that can increase consumer acceptance. This study aims to provide implications for technology planning of wearable devices by examining consumer preferences for the devices. For this purpose we employed a conjoint analysis. In the process of the analysis, we considered the trend of anticipatory standardization for wearable devices in an attempt to improve objectivity of analysis whilst many previous studies relied on focus group interview. For the anticipatory standardization information, we utilized liaisons and projects of wearable devices at International Electrotechnical Commission, and we designed a conjoint survey on the basis of the information. We conducted an online survey, and a total of 229 individuals responded to our survey. The result of conjoint analysis shows that main use and enhanced features were more important attributes than the others were. However, consumer preferences for detailed levels of each attribute were different by gender and age groups. This result implies that technology planning of wearable devices require distinct approaches by consumer segments.