• The Journal of Industrial Distribution & Business
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• v.9 no.2
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• pp.57-63
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• 2018

Purpose - This research examined the effect of hedonic and utilitarian eating-out motivations on the evaluation of restaurant selection attributes in a fashion premium outlet. Additionally, the influence of experimental and functional attributes on customers' preference for hedonic eating-out motives and utilitarian eating-out motives, and variation of moderating effects through the gender was examined. Research design, data, and methodology - A survey was conducted to verify the established research hypothesis. The questionnaire items for the research were modified to fit the situation of the present study. In order to elaborate the questionnaire, the literature of the previous researchers was reviewed and supplemented. The survey conducted 207 online questionnaires for consumers who have visited domestic fashion premium outlets from July 4, 2017 to July 27, 2017. A total of 207 questionnaires were collected, and a total of 206 questionnaires were used for the empirical analysis after excluding one inappropriate response. In order to verify the reliability and validity of the measured variables, exploratory factor analysis and reliability analysis were performed using SPSS 20.0. Next, the structural equation model (SEM) statistical method was used to test the hypotheses of the study. Results - Hedonic motivation had more influence on experimental attribute importance than the functional attribute importance of the restaurant. However, this result was different depending on the gender. The effects of hedonic motives on empirical attributes were more influenced by female groups, and when influencing functional attributes, male groups were more influenced. However, it was statistically significant (p <0.05) in the female group only when the hedonic eating out motives influenced empirical attributes. Conclusions - This study analyzed the effect of eating-out motivation on the restaurant preference attributes and suggested practical implications. First, customers with hedonic eating-out motivations were evaluating experiential attributes to be more important than functional attributes. Second, for customers who are motivated to use practical eating-out habits, companies should provide services that meet practical and economic needs. In particular, female customers visiting restaurants need differentiated marketing strategies that make them feel new experiences rather than practical ones. In addition, it is necessary to study more complex and integrated studies which will influence restaurant selection attributes of premium outlets customers by adding various eating out motives and selection attributes.

• Korea Journal of Hospital Management
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• v.27 no.3
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• pp.1-14
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• 2022

Purposes: This purpose of this study was to check how much the online word of mouth influences on customer's hospital selection according to Kano's model. Methodology: Kano classified the attributes that affect customer's satisfaction into attractive, one-dimensional, indifferent, must-be, and reverse attributes. Among them, attractive and one-dimensional attributes make up the largest portion in hospital selection. Based on this, the influence of positive or negative online reviews on the selection of hospitals was investigated. Differentiated service was selected as the attractive attributes, and a kind, sufficient explanation was selected as the one-dimensional attributes. Then a questionnaire was conducted how much the positive or negative online reviews influence on hospital selection, respectively. It was conducted from August 7 to September 7, 2021 for medical consumers in their 20s and older who have used medical services for the past 3 years, and the final 142 questionnaires were analyzed. All data was analyzed by chi-square and two-way ANOVA using SPSS ver 25.0. Findings: The results showed that, in one-dimensional attributes, the difference between positive and negative reviews was not statistically significant, but in attractive attributes, positive and negative reviews showed a statistically significant difference. It suggests that positive reviews on attractive attributes had a greater influence on hospital selection. In terms of hospital selection, when the experimental participants were exposed to the positive reviews, the hospital selection ratio did not differ by Kano's attributes, but to the negative reviews it differed. The hospital selection ratio, even after they were exposed to negative reviews, was higher in the attractive attributes than in the one-dimensional attributes. Practical Implication: This study confirmed that hospital selection is influenced differently depending on the Kano's attributes and the direction of the reviews, and suggests that marketers should respond differently to each Kano's attributes when they deal with online reviews of hospitals.

• Archives of design research
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• v.14 no.4
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• pp.99-108
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• 2001

The Charm is composed of various kind of ancient signs, letters and systematic characters so that they delivers messages with many expressions. They, compared with the experimental typography, are more logical and experimental than we generally think. Also, they have meanings and attributes as characters do, in which there are symbols, hieroglyphs, pictures and other similar words. Each attribute diverse from symbolic meaning, associates to deconstruction of letters. It is needed to review the experimental attributes of charms with the view of structural typography for potentialities of expression. The purpose of the study is to analyze and classify the morphologic construction of charms so that we can find the possibilities of applying the attributes to visual languages and typography. Future study seems to be extending the area of expressing of typography fit for our own culture, not for Western

• Journal of Distribution Science
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• v.16 no.1
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• pp.37-46
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• 2018

Purpose - This study is to investigate the effects of consumption motives of restaurant customers on the perception of the importance of restaurant attributes, and to determine the influence of the consumption motives on the empirical and functional attributes between Vietnam and Korea. Research design, data, and methodology - Questionnaire items from previous studies were revised to fit the research purpose of the present study. From August 1 to August 25, 2017, questionnaires were simultaneously administered in Korea and Vietnam using both on-line and off-line survey methods (including SNS and e-mail). With 381 surveyed questionnaires in Vietnam(219) and Korea(162), this study was conducted by using SPSS 22.0 to verify the reliability and validity of the measured variables. Structural equation model (SEM) was employed as a statistical method for the hypotheses test of this study. Results - The results showed that hedonic eating-out motive has more influence on the importance of empirical attribute than that of functional attribute in restaurant. In addition, utilitarian eating-out motive has more influence on functional attributes than empirical attributes. However, these relationships showed the difference between countries in Vietnam and Korea. As for in Korea, consumers' hedonic and utilitarian motives of eating-out were more influential on experimental and functional attributes. Conclusions - This study analyzed the influence on the importance of the eating-out motives of restaurant attributes and how this differed between Vietnamese and Korean.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.589-603
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• 2023

Deep generative models target to infer the underlying true data distribution, and it leads to a huge success in generating fake-but-realistic data. Regarding such a perspective, the data attributes can be a crucial factor in the data generation process since non-existent counterfactual samples can be generated by altering certain factors. For example, we can generate new portrait images by flipping the gender attribute or altering the hair color attributes. This paper proposes counterfactual disentangled variational autoencoder generative adversarial networks (CDVAE-GAN), specialized for data attribute level counterfactual data generation. The structure of the proposed CDVAE-GAN consists of variational autoencoders and generative adversarial networks. Specifically, we adopt a Gaussian variational autoencoder to extract low-dimensional disentangled data features and auxiliary Bernoulli latent variables to model the data attributes separately. Also, we utilize a generative adversarial network to generate data with high fidelity. By enjoying the benefits of the variational autoencoder with the additional Bernoulli latent variables and the generative adversarial network, the proposed CDVAE-GAN can control the data attributes, and it enables producing counterfactual data. Our experimental result on the CelebA dataset qualitatively shows that the generated samples from CDVAE-GAN are realistic. Also, the quantitative results support that the proposed model can produce data that can deceive other machine learning classifiers with the altered data attributes.

• Archives of design research
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• v.19 no.4 s.66
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• pp.187-204
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• 2006

The brand personality of online products and services is know as its e-brand personality. Although, in the competitive conditions of online markets, e-brand personality is agreed to be an important factor, few studies have suggested how to establish e-brand personality through the visual design of web sites. This study identifies and verifies causal relationships between the visual attributes of web pages and e-brand personalities. The first identifies four major dimensions of e-brand personality on diverse web sites. The second uses 52 experimental home pages to identify key visual attributes associated with those four personality dimensions. The third is a confirmatory study with 16 experimental web sites that verifies causal relationships between visual attributes and e-brand personalities. The results show that two visual attributes, 'simplicity' and 'cohesion,' help to establish a 'bold' personality. Three attributes, 'contrast,' 'density,' and 'regularity,' affect whether a site has an 'analytical' personality. 'Contrast,' 'cohesion,' 'density,' and 'regularity' all influence whether a web site is perceived to have a 'friendly' personality. 'Regularity' and 'balance' were expected to affect the 'sophisticated' personality dimension, but no such impact was observed. The paper concludes with a discussion of implications, limitations, and future research directions.

• Journal of Computing Science and Engineering
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• v.8 no.2
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• pp.94-106
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• 2014

Schema matching is widely used in many applications, such as data integration, ontology merging, data warehouse and dataspaces. In this paper, we propose a novel matching technique that is based on the order of attributes appearing in the schema structure of query results. The appearance order embodies the extent of the importance of an attribute for the user examining the query results. The core idea of our approach is to collect statistics about the appearance order of attributes from the query logs, to find correspondences between attributes in the schemas to be matched. As a first step, we employ a matrix to structure the statistics around the appearance order of attributes. Then, two scoring functions are considered to measure the similarity of the collected statistics. Finally, a traditional algorithm is employed to find the mapping with the highest score. Furthermore, our approach can be seen as a complementary member to the family of the existing matchers, and can also be combined with them to obtain more accurate results. We validate our approach with an experimental study, the results of which demonstrate that our approach is effective, and has good performance.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.727-732
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• 2007

Most of previous work on indexing and searching time series focused on the similarity matching and retrieval of one-attribute time series. However, multimedia databases such as music, video need to handle the similarity search in multi-attribute time series. The limitation of the current similarity models for multi-attribute sequences is that there is no consideration for attributes' sequences. The multi-attribute sequences are composed of several attributes' sequences. Since the users may want to find the similar patterns considering attributes's sequences, it is more appropriate to consider the similarity between two multi-attribute sequences in the viewpoint of attributes' sequences. In this paper, we propose the similarity search method based on attributes's sequences in multi-attribute time series databases. The proposed method can efficiently reduce the search space and guarantees no false dismissals. In addition, we give preliminary experimental results to show the effectiveness of the proposed method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.81-89
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• 2019

As the need for the integration of administrative datasets and address information increases, there is also growing interest in POI (Point of Interest) data as a source of location information across applications and platforms. The purpose of this study is to develop an alias database management method for efficient POI searching, based on POI data representing position. First, we determine the attributes of POI alias data as it is used variously by individual users. When classifying aliases of POIs, we excluded POIs in which the typo and names are all in English alphabet. The attributes of POI aliases are classified into four categories, and each category is reclassified into three classes according to the strength of the attributes. We then define the quality of POI aliases classified in this study through experiments. Based on the four attributes of POI defined in this study, we developed a method of managing one POI alias through and integrated method composed of word embedding and a similarity measurement. Experimental results of the proposed POI alias management method show that it is possible to utilize the algorithm developed in this study if there are small numbers of aliases in each POI with appropriate POI attributes defined in this study.

• Korean Journal of Artificial Intelligence
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• v.6 no.2
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• pp.17-22
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• 2018

According to the World Health Organization, the top 10 causes of death worldwide include heart disease. Heart diseases include coronary disease, which induces acute myocardial infarction. Ticagrelor drugs are being used to treat acute alliances, but it has become difficult to breathe due to the drugs. In a related study, Tobias predicted that uric acid causes acute respiratory distress independently of other factors, including BNP. And in the Ahmad study, serum uric acid numbers were related to the left ventricle depending on the level of uric acid. Experimental data are data used after 155 patients who received coronary intervention took ticagrelor. The research methods were leveraged by gradient decent algorithm and linear regression. In order to avoid overfitting in the experiment, training data and test data were separated into 70 and 30 percent respectively. The experimental results lacked the predictability of other attributes except DT in the correlation coefficient and crystal coefficient. However, all attributes related to dyspnea other than DT are determined to be related to causing relaxation of the heart in the left ventricle. Therefore, the attribute causing dyspnea is determined to be an attribute causing relaxation of the heart of the DT and left ventricle.