• 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.

• 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.

• Culinary science and hospitality research
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• v.14 no.2
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• pp.215-224
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• 2008

The objective for this research was to clarify the preference for alternative restaurants with different combinations of factor levels: local specialty food, non-local specialty food, very attentive service, moderately attentive service, not attentive service, traditional decoration, modern decoration, \10,000, \15,000, and \20,000. Total 230 copies of questionnaire were completed. Conjoint experiment method was used to develop full restaurant profiles. Ordinal probit model was used to measure the effects of factor levels on the preference. Results of the study demonstrated that the ordinal probit model analysis result for the data also indicated a good model fit. The effects of factor levels on the preference were statistically significant. As expected, the estimates of implicit price to pay were statistically significant. Moreover, the customers were more willing to pay for local specialty than other factor levels. The customers also considered the food factor as a very important factor. This research suggested that the customer's decision-making process for restaurants was best modeled as a conjoint experiment method that combines various factor levels. And it showed the results could be used as good data for understanding the relationships between the factors and preference in choosing food and restaurants in tourist areas.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.3
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• pp.270-280
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• 2014

The objective of this research is to quantitatively valuate the economic value of analysis model related to climate change mitigation and adaptation. Due to the fact that the subject of this research, which is the Korean climate change mitigation and adaptation model, has not been actualized, a conjoint analysis applying stated preference data has utilized. As results, among the many attributes considered in this research, the value of the attribute related to reflecting Korea's current situation is analyzed to be largest in both greenhouse gas (GHG) mitigation model and climate change adaptation model. Additionally, if all the considered functional aspects are assumed to be feasible, the economic value of the Korean GHG mitigation model is assumed to be 60.3 billion Korean won(KRW) and the Korean climate change adaptation model is assumed to be 51 billion KRW.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2003.11a
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• pp.87-100
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• 2003

본 연구는 마케팅 분야에서 주로 사용되는 신제품확산모델(new product diffusion model)들이 기본적인 배스 모형(Bass model)에 기반하여 개별 소비자의 이질성(heterogeneity)을 반영하지 못하고, 제품이 시장에 출시되기 이전 단계에 시장수요를 예측하지 못하는 한계를 극복하기 위한 방법론을 제시하기 위해 진행되었다. 연구에 사용된 방법론을 살펴보면, 먼저 컨조인트(Conjoint) 분석을 통해 제품의 개별 속성들에 대한 소비자의 선호 구조를 파악하고, 이를 통해 추정된 정적(static)인 소비자 효용함수를 시장 및 기술 환경의 변화에 대한 적절한 예측자료와 결합하여 동적(dynamic)인 효용함수로 전환함으로써 시간에 따른 동적(dynamic) 시장 점유율(market share)을 예측하고, 그 결과를 신제품확산모델로부터 도출된 잠재시장(market potential) 추정치와 결합함으로써 신제품의 판매량을 예측한다. 또한 본 연구에서 제시하는 모델을 한국의 30인치 이상 대형TV 시장에 대해 실증적으로 분석하였으며, CRT TV, Projection TV, LCD TV, PDP TV에 대한 시장수요를 예측하였다. 분석 결과, 소비자들은 TV 선택시 화질과 가격에 민감한 반응을 보이는 것을 알 수 있으며, 이를 바탕으로 한 시장 예측 결과, 단기적으로는 가격 경쟁력이 있는 Projection TV가 높은 시장 점유율을 보이지만, 50인치 이상 LCD TV가 상용화될 경우, LCD TV가 다른 TV들보다 상대적으로 많은 판매량을 보일 것으로 예측되었다. 또한 TV 크기에 따른 소비자들의 선택을 살펴본 결과 50∼60인치대에 비해 40인치대 크기의 TV가 많이 판매될 것으로 예상된다.

• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.27-38
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• 2018

Purpose: A large number of attributes with mixed levels are often considered in the conjoint analysis. In the cases where attributes have two or three levels, we research on the efficient design of survey questionnaire to estimate all the main effect and two factor interaction effects with a reasonable size of it. Methods: To reduce the number of questions in a questionnaire, the balanced incomplete block mixed level factorial design with minimum aberration was proposed by Lim and Chung (2016). Based on the number of questions and that of the respondents in that design, D-optimality criterion is adopted to find efficient designs where the main effect and two factor interaction effects are estimated. Results: The list of the number of questions and that of the respondents in efficient designs for survey questionnaire are recommended based on the D-efficiency of each design and the proposed selection criteria for the number of both questions and the respondents. By analyzing all the respondents survey data generated by the simulation study, we find the proper model. Conclusion: The proposed methods of designing survey questionnaires seem to perform well in the sense that how often the proper model is found in a simulation study where all the respondents survey data are generated by the simulation model.

• Journal of Korean Society for Quality Management
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• v.47 no.2
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• pp.345-365
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• 2019

Purpose: We consider export of Korea for Muslim population of Cairo residents in Egypt. Product instant cup noodle and yuzu tea are mainly focused on Kano model and Timko's customer satisfaction factor (CS - Coefficient) analysis and conjoint analysis. Methods: Based on the evaluation and conjoint analysis, cluster analysis was additionally applied to further exploratory research as to what kind of population the target customer has. A total of 120 people, each 60 people each, were prosecuted for Muslim women, middle middle class who had over 3,000 Korean won annual income for that study, and in Cairo in August 18. Results: The Kano analysis result Instant cup noodles act as attractive elements for packaging state, cooking method, smell and convenience, and Yuzu tea acted as an attractive element of taste, eating method, raw materials, efficacy, packaging form. Customer satisfaction factor, instant cup noodles, capacity and noodle thickness was a factor of indifference in Kano analysis, but acted as an attractive factor, the way to eat citron tea was classified as a factor of indifference. Conclusion: In the case of instant cup noodles, we first set up the taste of chicken-based soup with high appreciation as a whole, a group that likes chicken-based soup taste and oil noodles for each market segment, a taste of beef based soup And popular group that likes raw noodles Appears that diversification is necessary, and it has been found that it is necessary to develop a product type by hierarchy and marketing with different size priority from group packaging container. In the case of Yuzu tea, it is indispensable to emphasize the efficacy, in particular, energy recovery preference appears high, appealing point matching the needs of energy recovery is necessary, release the citrus fruit as a product without buckwheat in Bisson Ho, the packaging container, The group that likes cups and sticks is different and we found that it is necessary to prepare all two types.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.93-115
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• 2017

The ability of smartphones to facilitate various services like mobile banking, e-commerce and mobile payments has made them part of consumers' lives. Conjoint analysis (CA) is a marketing research approach used to assess how consumers' preferences for products or services develop. The potential applications of CA are numerous in consumer electronics, banking and insurance services, job selection and workplace loyalty, consumer packaged goods, and travel and tourism. Choice-Based Conjoint (CBC) analysis is the most commonly used CA approach in marketing research. The purpose of this study is to utilise CBC analysis to investigate the relative importance of smartphone attributes that influence consumer smartphone preference. An experiment was designed using Sawtooth CBC Software. 326 students attempted the online survey. Utility values were derived by Hierarchical Bayes (HB) estimation and used to explain consumers' smartphone preferences. All the six attributes used for the study were found to significantly influence smartphone preference. Smartphone brand was the most important, followed by the price, camera, RAM, battery life, and storage. This study is one of the first to use Sawtooth CBC analysis to assess consumer smartphone preference based on the six attributes. We provide implications for the development of new smartphones based on attributes.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.5
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• pp.606-617
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• 2002

The purpose of this study is to develop a decision model that helps manufacturers and retailers determine the optimal timing of markdown in order to maximize their profit. An optimal timing decision model was developed based on three steps; conjoint measurement, scenario analysis and simulation. Data were collected from the sample of 149 out of 170 undergraduate and graduate students in Seoul in 1997. From the Jeans market, 8 brands; Levi's, lee, Guess, Calvin Klein, Pintos, Get used, MFG, and Basic, were selected as competitors for this study. In the conjoint measurement, respondents estimated the level of preference, from 1 to 100, for each item in which brand, price, style, and colors were used to explain product characteristics. Then, in order to reflect competitive situation in Jeans market, four types of scenarios were developed. In each scenario, simulations were applied to decide optimal timing of markdowns that leads to maximal profitability and sales volume. The profit was calculated based on the equation; Profit = Jean's market volume x market share of each brand - cost, where market volume was obtained by integral calculus for market utility function, and market share by logit value of part-worth from the conjoint analysis. For the purpose of the parsimony of the research, costs and the level of markdown were fixed to 30% of the regular price. In results, the optimal timing decision model identified 3 different types of brands. The brands that do not need to take markdown were Ievi's, MFG, and Basic Jeans characterized by the highest brand power and the highest price zone. The brands that needed to take early markdowns were Guess, Lee, Calvin Klein, and Get Used with the intermediate level of brand power and price. The brand that need late markdown was Pintos with the weakest brand power among the competitors and the lowest price. The optimal range of markdown remains for further research.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.73-78
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• 2002

In this paper, we propose a constrained optimization model for conjoint analysis (a preference decomposition technique) to improve parameter estimation by restricting the relative importance of the attributes to an extent as decided by the respondents. Quite simply, respondents are asked to provide some pairwise attribute comparisons that are then incorporated as additional constraints in a linear programming model that estimates the partial preference values. This data collection method is typical in the analytic hierarchy process. Results of a simulation study show the new model can improve the predictive accuracy in partial value estimation by ordinal east squares (OLS) regression.