• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.413-416
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• 2014

최근 전 세계적으로 사회적 여건 변화와 소비자의 욕구 변화에 따라 여가 중심으로의 가치관이 변화하면서 다양한 레저스포츠의 수요가 점차 증가하고 있다. 특히 여름철 수상 레포츠에 대한 관심과 참여율이 증가하고 있는 실정이며, 정형화되어있는 수상레저용 보트의 다양한 선체 디자인에 대한 욕구도 증가하고 있다. 따라서 본 논문에서는 소비자들의 선체 디자인에 대한 다양한 욕구의 변화에 적극적으로 대응할 수 있도록 협력적 필터링 기법을 이용한 수상레저용 보트 디자인 설계를 위한 추천시스템을 개발하고자 한다. 이를 위하여 소비자 설문조사를 통해 보트 디자인 관련 감성을 선정하고, 요인분석과 평가로 감성을 도출하여 고객 감성 선호측면에서의 보트 디자인 배열을 제시하였다. 또한 사용자의 선호도를 반영한 보트 디자인에 따른 감성 어휘 선정을 위해서 보트의 선체, 바디, 추진 장치 등의 요소에 따라 분석하여 사용자의 선호도에 맞는 수상레저용 보트 모델을 제시하였다.

• The Journal of Asian Finance, Economics and Business
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• 제7권8호
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• pp.383-393
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• 2020

The purpose of this research is to identify factors affecting consumer's brand preference toward environment-friendly products like electric vehicles in Bangkok, Thailand. The researcher conducted the study based on a quantitative approach and adapted a nonprobability sampling as a convenience sampling method. The data were collected from 400 respondents living in Bangkok, who are 18 years old and above, with significant knowledge of electric vehicles. This study adapted the Structural Equation Model (SEM) and Confirmatory Factor Analysis (CFA) to examine the model accuracy, reliability and verification influence of various variables. The results revealed that social influence has significant effect on environment concern as well as a positive effect on attitude. The initial significance of environment concern leads to a positive effect on fuel efficiency, followed by brand preference. Lastly, attitude has a significant effect on brand preference as attitude of consumers toward environment-friendly products affects the encouragement of brand preference, which largely depends on individual opinion. From an environmental concern, the researchers identified fuel efficiency and attitude having a positive and significant effect on brand preference toward environment-friendly products for electric vehicles. The authors also found that environmental concern and social influences on green purchasing behavior were significantly interrelated.

• 제어로봇시스템학회논문지
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• 제10권11호
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• pp.1107-1111
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• 2004

As an information technology is developed, more intelligent system considering emotional factor for implementing the personality is required. In this paper, Reactive Learning Inference System considering emotional factor is proposed. Emotional Facter(E) is defined for a criterion for representing the personal preference. This system is designed to have functions of Reactive filtering by Emotional factor, Incremental learning, perception & inference and knowledge retrieval. This system is applied to the area for analysis of customer's tastes and its performance is analyzed and compared.

• 한국경영과학회지
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• 제33권3호
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• pp.59-76
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• 2008

Studies of recommender systems have focused on improving their performance in terms of error rates between the actual and predicted preference values. Also, many studies have been conducted to investigate the relationships between customer information processing and the characteristics of recommender systems via surveys and web-based experiments. However, the actual impact of recommendation on product pages for customer browsing behavior and decision-making in the commercial environment has not, to the best of our knowledge, been investigated with actual clickstream data. The principal objective of this research is to assess the effects of product recommendation on customer behavior in e-Commerce, using actual clickstream data. For this purpose, we utilized an online bookstore's clickstream data prior to and after the web site renovation of the store. We compared the recommendation effects on customer behavior with the data. From these comparisons, we determined that the relevant recommendations in product pages have positive relationships with the acquisition of customer attention and elaboration. Additionally, the placing of recommended items in shopping cart is positively related to suggesting the relevant recommendations. However, the frequencies at which the recommended items were purchased did not differ prior to and after the renovation of the site.

• 한국조리학회지
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• 제14권4호
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• pp.203-216
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• 2008

The purpose of this study is to investigate the preference of Korean traditional food and kimchi among different age groups in order to find a way to increase kimchi consumption. For this study, data from 15 male respondents(5.2%) and 271 female respondents(94.8%) was used. Age distribution of total respondents were in their 20's(21.8%), 30's(32.7%), 40's(32.7%) and 50's(11.6%), which showed the rate of 40's was very high. Most of the groups showed similar rates over the question on "have to eat kimchi" and "don't need to eat kimchi", but the elders' preference was high while the youngers' was relatively low. Therefore, the preference of kimchi has a small gap between the age groups, but all of them like kimchi in general.

• 한국통신학회논문지
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• 제28권9B호
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• pp.806-812
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• 2003

본 논문에서는 고객의 다양한 감성에 기반한 웹 디자인을 통해 사용자들로 하여금 새로운 경험을 체험하도록 정적과 동적 요소에 따른 16개의 감성 차원을 모델링하고 페이지 레이아웃, 배경색, 움직임 좌표 등의 감성 데이터베이스를 활용하여 고객의 선호 감성에 따라서 웹 페이지가 재구성되는 유무선 인터넷 서비스 시스템을 제안한다. 실험 결과 기존 시스템보다 세대별 감성 만족도 및 웹 사이트의 평균체류시간이 증가되었음을 모의 실험을 통해서 확인하였다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.548-555
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• 2003

Customer satisfaction level is usually measured in terms of price, quality, customization, after-sale-service, product variety etc. Each finn sets up a distinctive production/marketing strategy to gain competitive advantage by prioritizing the customer satisfaction measures. The market differentiation strategy directly results in supply chain performance such as lead time, inventory, customer fill rate and market share. Product proliferation desirable in customization sense often conflicts the economies of scale effect in production side. This paper focuses the relationship between product variety and market share. Specifically, we investigate how introduction of new product affects the current market share, i.e.,) formation of customer preference and provide some insight into the optimal range of product variety.

• 한국경영과학회지
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• 제29권1호
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• pp.101-112
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• 2004

Customer satisfaction level is usually measured in terms of price, qualify, customization, after-sale-service, product variety etc. Each firm sets up a distinctive production/marketing strategy to gain competitive advantage by Prioritizing the customer satisfaction measures. The market differentiation strategy directly results in supply chain performance such as lead time, inventory, customer fill rate and market share. Product proliferation desirable in customization sense often conflicts the economies of scale effect in production side. This paper focuses the relationship between product variety and market share. Specifically, we investigate how introduction of new product affects the current market share, i.e., formation of customer preference and provide some insight into the optimal range of product variety.

• 한국IT서비스학회지
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• 제7권2호
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• pp.13-23
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• 2008

This research is to study the core factors for knowledge information database service and very important database service quality factors to improve customer satisfaction. The database service quality has been critical issue rather than just information service in these days, because the qualitative aspect is becoming more important factors rather than quantitative aspect. As database service quality has been influenced by satisfaction of database user, it needs to try to get excellent results by enhancing ability to obtain information. In order to satisfy this condition, it needs to measure database service quality more accurately first. In this study, we apply conjoint analysis to measure how much to give quality condition to achieve customer satisfaction.

• Journal of Information Technology Applications and Management
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• 제24권1호
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• pp.111-128
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• 2017

Existing studies for recommender have focused on recommending an appropriate item based on the customer preference. However, it has not yet been studied actively to recommend purchase timing for the repurchase product despite of its importance. This study aims to propose MLP and RNN models based on the only simple purchase history data to predict the timing of customer repurchase and compare performances in the perspective of prediction accuracy and quality. As an experiment result, RNN model showed outstanding performance compared to MLP model. The proposed model can be used to develop CRM system which can offer SMS or app based promotion to the customer at the right time. This model also can be used to increase sales for repurchase product business by balancing the level of order as well as inducing repurchase of customer.