• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4328-4336
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• 2011

The aim of this study is to find changes of the attributes that influence the purchase of cut roses during recent five years(2007~2011) and suggest some implications on ways to promote cut roses marketing. For this purpose, a survey was conducted through the Internet among 1,100 randomly chosen people living in Seoul, Inchon and Gyeonggi Province in 2011. A total of 1,023 valid replies were received for the analysis of the survey which was carried out by the subsidiary consulting firm. The survey panels and estimation models to analyze changes of consumers' preference attributes during recent five years are same to them of Kim, et al.(2007). That is, empirical analysis tools such as ordered probit model, multinomial logit model, and conjoint analysis were used according to Kim, et al.(2007). This paper suggests several policy implications to set up the target market of cut roses and marketing mix strategy to specify the best 4P(product, price, place and promotion).

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.967-975
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• 2010

Since the least squares estimation is not appropriate when multicollinearity exists among the regressors of the linear regression model, the principal components regression is used to deal with the multicollinearity problem. This article suggests a new procedure for the selection of suitable principal components. The procedure is based on the condition index instead of the eigenvalue. The principal components corresponding to the indices are removed from the model if any condition indices are larger than the upper limit of the cutoff value. On the other hand, the corresponding principal components are included if any condition indices are smaller than the lower limit. The forward inclusion method is employed to select proper principal components if any condition indices are between the upper limit and the lower limit. The limits are obtained from the linear model which is constructed on the basis of the conjoint analysis. The procedure is evaluated by Monte Carlo simulation in terms of the mean square error of estimator. The simulation results indicate that the proposed procedure is superior to the existing methods.

• Journal of Global Scholars of Marketing Science
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• v.16 no.2
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• pp.77-94
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• 2006

The purpose of this study was to identify the consumers who use the level of price as the indicator of the product quality and calibrate the price response function with price-dependent quality evaluation. In order to implement the purpose of this study, Home theater market in China had been segmented by the mixture regression model, and price response function was calibrated at segment level. Based on the types of price response function, segments were allocated into one of two groups; the group using the level of price as the quality indicator or the group not using the level of price as that. Then, characteristics of both groups were compared in terms of product attributes and demographic variables.

• Korean small business review
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• v.43 no.1
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• pp.35-50
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• 2021

The youth job problem is becoming more serious due to COVID-19. To solve this problem, a "good job platform" was proposed that allows young job seekers to easily and conveniently find excellent SMEs they want to work for. This study developed a "good job self-assessment model" that grasps the preferred jobs of young job seekers and evaluates SMEs and applied them in the platform. In this process, the characteristics of good jobs from the viewpoint of job seekers were identified through conjoint analysis from the viewpoint of salary level, performance compensation, working environment, corporate soundness, and organizational culture. Next, the importance of 13 detailed evaluation items was reflected through AHP for industry, academia, and research experts. The self-assessment model of this study can be used as a tool to improve awareness that changes the SME environment into a job favored by young job seekers. As a result, it could provide an opportunity to change the job problem from providing cost-oriented support to a qualitative solution.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.219-243
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• 2004

Generally, electricity market has monopoly market structure because of need of enormous investment for infrastructure. However, the introduction of competition in network industry as electricity is a tendency of the world with decreasing the effects of economy of scale due to the advancement of technology. Now, electricity industry restructuring is in progress but the competition in electricity retail market is not in force yet in Korea. Whether a effective competition exist or not is very important to policy decision maker who drive restructuring, but there are small numbers of quantitative researches on that. In this study, we estimated the effectiveness of competition in the electricity retail market through switching costs. If switching costs are high, consumers actually can be locked in incumbent firm in spite of introduction of competition. Therefore switching is a critical factor to determine effectiveness of competition and to estimate the size of switching costs quantitatively can proffer the information about whether the competition in the electricity retail market is effective or not in the future. We estimated switching costs using consumer' stated-preference data by conjoint analysis. In according to estimation results, the cost of switching process is not so high, but the relative brand loyalty of an incumbent company is significantly high. And the price is considered as the most important factor choosing an electric service commodity. Based on the empirical results, it is possible to analyze the relationship between suppliers' competitiveness resulted from management efficiency and customers' switching possibilities. The paper therefore provides guidance for suppliers in deciding to enter into retail competition and for policy makers in introducing retail competition. And it has a significance of estimating the switching costs directly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.5260-5267
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• 2013

In order to create a successful regional development model, there should be an effort to foster a strategic industry which boosts a geographical features of rural areas. Because, It must be clear that the strategic industry chosen between choice and concentration of the development of the local industry development which boosts the local economy revitalization. The local government should have continual concern and roles to fulfil political subjects and keep estimating about the possibility that there could be the sustainable development by Task Ahead of the local industry. This study's indicators were established for the adequacy evaluation of the industrial policy by focusing on domestic regional development's success example. Next, Conjoint analysis was conducted on the Experts. On the basis of this analysis, the weights of indicators are derived. And this study suggest the reasonable evaluation system to take Sustainable industry plan of regional strategic. Consequently, 'Regional development' sector separate 3 categories which are 'Local economy', 'Human Resource Development', 'local marketing' and 9 indicators were derived. 'Industrial development' sector derived 9 indicators about 'Construction of infrastructure', 'Technical development' and 'business support'. Looking through the implications of this study. First, the problem needed to be supplemented based on the Diversity and concreteness of Evaluation system when government assesses regional industry development policy. Second, local government have to strategically consider the possibility of convergence between industries and easiness of network in a broad region. Finally, Foundation and support of the professional manpower and companies for the regional industries must be established.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.6
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• pp.1-11
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• 2010

The purpose of this research is to identify satisfaction levels of the arboretum which will be provided in the Multifunctional Administrative City and to estimate the economic value of using choice experiments. The attributes were "Preservation", "Education", "Recreation", "Facility", "Accessibility" and the entrance fee. The main effects model was utilized to construct hypothetical alternatives. Calibration of the conjoint choice model revealed that 'wetlands' and 'forest trails' in "Preservation" and the "Recreation", respectively, were significant variables. This result indicates that respondents are willing to pay more for these if they are provided in the arboretum. Also, 'variety seeking' tendency, age, and income level positively influenced the provision of the arboretum. Involvement in preservation of natural environment, however, had a negative influence on the establishment of the arboretum. Because this study is the first attempt to estimate the economic valuation of an urban arboretum using choice experiment, there are several suggestions for future research in terms of determining the base level and inclusion of salient attribute levels.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.531-539
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• 2009

Logistic regression is widely used as a datamining technique for the customer relationship management. The maximum likelihood estimator has highly inflated variance when multicollinearity exists among the regressors, and it is not robust against outliers. Thus we propose the robust principal components logistic regression to deal with both multicollinearity and outlier problem. A procedure is suggested for the selection of principal components, which is based on the condition index. When a condition index is larger than the cutoff value obtained from the model constructed on the basis of the conjoint analysis, the corresponding principal component is removed from the logistic model. In addition, we employ an algorithm for the robust estimation, which strives to dampen the effect of outliers by applying the appropriate weights and factors to the leverage points and vertical outliers identified by the V-mask type criterion. The Monte Carlo simulation results indicate that the proposed procedure yields higher rate of correct classification than the existing method.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.583-583
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• 2016

다양한 평가지표가 반영된 복합 지수(Composite Index)는 물관리 정책의 우선순위 결정 및 정책성과의 모니터링에 유용한 도구로 사용되고 있다. 각 지표별 중요도를 나타내는 가중치는 최종 지수의 산정에 영향을 미칠 수 있으며, 그 결정방법도 Data Envelopment Analysis(DEA), Benefit of doubt Approach(BOD), Unobserved Component Model(UCM), Budget Allocation Process(BAP), Analytic Hierarchy Process(AHP), Conjoint Analysis(CA) 등 다양하다. 본 연구에서는 여러 가지 가중치 결정방법 중 통계적 방법인 주성분 분석(Principal Component Analysis, PCA)을 사용하여 Park et al.(2016)이 제시한 물관리 탄력성 지수(Water Management Resilience Index, WMRI)에 대한 가중치를 산정하여 동일 가중치를 적용한 기존 결과와 비교하였다. 물관리 탄력성 지수는 자연조건상 물관리 취약성(Vulnerability), 기존 수자원 인프라의 견고성(Robustness), 물위기 적응전략의 다양성(Redundancy)의 3가지 부지수(sub-index)는 각각 13개, 11개, 7개의 지표(Indicator)로 구성되어 있으며, 117개 중권역을 다목적댐 하류 본류유역(범주 1), 용수공급 및 유량조절이 불가능한 지류(범주 2)와 가능한 지류(범주 3)로 분류하여 적용되었다. 각 부지수별로 추출된 3개, 5개, 3개의 주성분이 전체 자료의 76.4%, 71.2%, 63.2%를 설명하는 것으로 분석되었으며 부지수별 주성분의 고유벡터(Eigenvector)와 고유값(Eigenvalue)를 계산하고 각 지표의 가중치를 산정하였다. 주성분 분석에 의한 가중치와 동일 가중치를 적용하였을 경우와 비교해보면 취약성 부지수 1.9%, 견고성 부지수 1.9%, 다양성 부지수 2.1%의 차이가 나타나며 물관리 탄력성 지수는 0.4%의 차이를 보임에 따라 Park et al.이 제시한 연구결과의 적정성을 확인할 수 있었다. 주성분 분석은 객관적인 가중치 설정을 위한 통계적 접근방법의 하나로써 다양한 물관리 정책지수 산정시 활용될 수 있을 것이며, 향후 다른 가중치 산정방법을 적용함으로써 각 방법에 따른 지수 결과의 민감도 및 장단점을 분석할 수 있을 것으로 판단된다.

• Journal of the Korea Fashion and Costume Design Association
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• v.24 no.2
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• pp.59-72
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• 2022

The online fashion market in the 21st century has shown rapid growth. Against this backdrop, using consumer activity data to provide customized customer services has emerged as a viable business model that draws attention. Algorithm-based personalized recommendation services are a good example. But their application in fashion products has clear limitations. It is not easy to identify consumers' perceptions of the attributes of fashion, which are various, hard to define, and very sensitive to trends. So there is a need to compile data on consumers' underlying awareness and to carry out defined research to increase the utilization of such services in the fashion industry and further engage consumers. This research aims to classify the attributes and types of fashion products and to identify consumers' perceptions of a given situation where a recommendation service is offered. To find out consumers' perceptions of and satisfaction with recommendation services, an online and mobile survey was conducted on women in their 20s and 30s, a group that uses recommendation services frequently. A total of 455 responses were used for analysis. SPSS 28.0 was used, combined with Conjoint Analysis and multiple regression, to analyze data. The study results could provide insights into a better understanding of recommendation services and be used as basic data for companies to identify consumers' preferences and draw up a detailed strategy for market segmentation.