• 대한교통학회지
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• 제28권5호
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• pp.65-75
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• 2010

본 연구에서는 조건부 선택법을 이용하여 여러 속성들과 다양한 수준으로 구성된 가상의 택배 서비스 프로그램에 대한 소비자의 선택 행동을 체계적으로 분석함으로써 개별 속성들의 수준변화에 따른 소비자들의 평균 지불의사액을 측정함과 동시에 응답자의 성, 연령, 소득 등 사회 경제적 특성에 의한 택배 서비스 선택 결정요인을 분석하였다. 실증분석결과, 공변량을 포함하지 않은 모형을 기준으로 할 때 개별 속성 수준이 1단위 개선될 경우 응답자들의 평균적 지불의사액은 안정성 변수의 경우 2,349.6원으로 가장 크고, 이어서 정확성 변수의 경우 829.3원, 신속성 변수의 경우 588.5원, 마지막으로 친절성 및 사후 서비스 변수의 경우 358.8원으로 분석되었다. 이러한 결과를 토대로 할 때, 응답자들은 택배 서비스 속성들 중 안정성을 가장 중요시하며, 이어서 정확성, 신속성, 친절성 및 사후 서비스 등의 순으로 중요시함을 알 수 있다. 본 연구에서 도출된 택배 서비스의 개별 속성에 대한 정량적 가치들은 향후 바람직한 택배 서비스 가격정책 수립에 있어 유용한 정보를 제공할 것으로 판단된다.

• 한국의류학회지
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• 제33권7호
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• pp.1086-1097
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• 2009

Consumers have more choices for apparel products as e-shopping grows. This study examines the importance of apparel product attributes and classifies online apparel buyers into groups based on product attribute evaluation in various choice sets. For the empirical research, the online survey was conducted and Latent Gold Choice 4.0 was used for the choice-based conjoint analysis. Five consumer segments are found based on the choice selection of product attributes. The importance of product attributes (online shopping mall, brand, price, and style) and the preference of each product attribute level were different across segments. This research improves the knowledge of the purchasing behavior of online apparel buyers and provides proper attribute combinations of apparel e-shopping for each consumer segment.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2004년도 제5회 정기학술발표대회 논문집
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• pp.362-365
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• 2004

본 연구에서는 EVM체계의 정보화 활용성 확보를 위해, 각 성과 정보들에 대한 그래픽 정보의 제공과 공정 및 공사비 정보의 효율적 통합을 위하여 필요로 하는 EVM 속성코드의 연계모형구성을 제안하고 있다. EVM 속성코드는 EVM관련 각종 정보들을 유형화하여 EVM정보관리의 활용성을 높일 수 있도록 제안하는 것이며, EVM정보를 구성하는 일반적 데이터들을 속성코드로 구성하였다. 본 속성코드 연계모형을 통해 EVM시스템 구축 시, EVM 관련 상세정보들의 추출, 정렬 및 그룹화가 가능하며 이로써 공사관리자로 하여금 보다 효율적인 실적정보관리가 가능할 것으로 기대된다.

• 한국유기농업학회지
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• 제28권2호
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• pp.189-208
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• 2020

The purpose of this study aims to estimate consumption selection attribute, part-worth of organic instant rice through the use of conjoint analysis method. The conjoint analysis is to trace the development of consumer preference among multi-attribute alternatives. The selection attribute was including 4 factors preferred Type of rice, Capacity, Brand and payment price. For this research, a total of 192 questionnaires was collected of which 200 were completed. The research design was a full profile method by orthogonal design then 9 main profiles, 3 holdout sets were created. The results of this research were as follows. Consumers of organic instant rice are consider their importance of selection attributes was in order to price (25.87%), Type of rice (27.231%), Brand/Purchase channel (24.013%) and Capacity (18.494%). The findings of this study have identified 3 clusters for each experience visitors. Each cluster has a different and showed the relative importance or preference values for each accessible attribute of the segmentation.

• 한국시뮬레이션학회논문지
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• 제9권3호
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• pp.77-89
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• 2000

This paper suggests a multi-attribute dispatching rule for an automated guided vehicle(AGV). The attributes to be considered are the number of queues in outgoing buffers of workstations, distance between an idle AGV and a workstation with a job waiting for the service of vehicle, and the number of queues in input buffers of the destination workstation of a job. The suggested rule is based on the simple additive weighting method using a normalized score for each attribute. A neural network approach is applied to obtain an appropriate weight vector of attributes based on the current status of the manufacturing system. Backpropagation algorithm is used to train the neural network model. The proposed dispatching rules and some single attribute rules are compared and analyzed by simulation technique. A number of simulation runs are executed under different experimental conditions to compare the several performance measures of the suggested rules and some existing single attribute dispatching rules each other.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2011년도 추계학술대회
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• pp.695-716
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• 2011

In the future, smartphone convergences are not only based on the on/offline integration, but also with the integration between mobile communications and broadcasts. Therefore, there is a need to search for new direction of mobile device that enables variety user applications that are different from the existing size and application issue. The aim of this reserch is to improve user interface of smartphone's functional attribute. The survey results in this paper showed that the most preferable attribute of smartphone among the 8 was the wireless internet 25.3%, followed by messaging 20% and application 19.8%, which totaled to 62.5%. But the samples used were mostly limited to those aged 20 through 30. So the results are not considered as a representative preference of all smartphone users, and should be considered otherwise before materializing them to a product. Therefore, for the more liable results the further research should be conducted to gather data from a variety of users of all ages, and the functional attribute should be analysed through QFD.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.86-88
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• 2014

나이브 베이스가 가지는 가정은 실세계 데이터를 분류함에 있어 해로운 효과를 보이곤 한다. 이러한 가정을 완화하기 위해, 우리는 Naive Bayes Mutual Information Attribute Weighting with Smooth Kernel Density Estimation (NBMIKDE) 접근 방법을 소개한다. NBMIKDE는 애트리뷰트를 위한 스무드 커널과 상호 정보량 측정값을 기반으로 하는 어트리뷰트 가중치 기법을 조합한 것이다.

• 반도체디스플레이기술학회지
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• 제22권2호
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• pp.128-132
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• 2023

Recently, with the development of deep learning technology, research on pedestrian attribute recognition technology using deep neural networks has been actively conducted. Existing pedestrian attribute recognition techniques can be obtained in such a way as global-based, regional-area-based, visual attention-based, sequential prediction-based, and newly designed loss function-based, depending on how pedestrian attributes are detected. It is known that the performance of these pedestrian attribute recognition technologies varies greatly depending on the type of backbone network that constitutes the deep neural networks model. Therefore, in this paper, several backbone networks are applied to the baseline pedestrian attribute recognition model and the performance changes of the model are analyzed. In this paper, the analysis is conducted using Resnet34, Resnet50, Resnet101, Swin-tiny, and Swinv2-tiny, which are representative backbone networks used in the fields of image classification, object detection, etc. Furthermore, this paper analyzes the change in time complexity when inferencing each backbone network using a CPU and a GPU.

• 동아시아식생활학회지
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• 제18권2호
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• pp.165-171
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• 2008

The purpose of this study was to measure tourists' preference for alternative restaurants with different combinations of attribute levels: grown area logo, origin description, traditional food, fusion food, national food, and price. A total of 210 questionnaires were completed. A conjoint experimental method was used to develop hypothetical restaurants, and an ordinal probit model was used to measure the effects of the attribute levels on tourists' preference. The ordinal probit model analysis results for the data indicated an excellent model fit. The effects of the attribute levels on tourists' preferences were statistically significant. As expected, estimates of the marginal willingness to pay were statistically significant Moreover, the tourists were more willing to pay for grown area logo as compared to the other attribute levels. The tourists also considered the grown area logo as a very important attribute. Withe regard to developing and testing conjoint models in the design of choice experiments involving multifactor alternatives, this study may approach a deeper understanding of the conjoint experiment. Greater understanding of the conjoint experiment can improve the managerial diagnoses of the problems as well as the opportunities for different marketing strategies including local branding programs and menu development and marketing communications.

• 한국의류학회지
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• 제24권8호
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• pp.1197-1208
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• 2000

The purpose of this study was to find out the effects of the accord between consumers benefit factors and attribute factors of brand image on brand attitude. This study was based on Kellers conceptualizing model of brand image. The subjects were 605 working women in their twenties living in Seoul, Korea. The data were analyzed by Euclidian distance model, ANOVA of repeated measures, regression, F-test by Extra Sum of Squares Principle. The results were as follows. 1. There were significant differences among the brands and among the segmented groups in the accord between benefit factors and attribute factors of brand image and in the brand preference. Moreover there were significant interactions between the brands and the segmented groups in the accord between benefit factors and attribute factors of brand image and in the brand preference. 2. There were significant effects of the accord between benefit factors and attribute factor of brand image on brand attitude. 3. There were significantly different effects of the accord between benefit factors and attribute factors of brand image on brand attitude among the segmented groups.