• Korean journal of food and cookery science
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• v.29 no.4
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• pp.367-376
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• 2013

The objectives of this study are to provide the food market of internet shopping malls with effective marketing data, to provide basic data for the development of related fields of the study, and ultimately to increase the satisfaction of food consumers of internet shopping malls. To achieve the object of this research, a cluster analysis of the research subjects was carried out based on the following 5 factors of food purchasing attribute that had been deduced by a factor analysis by the types of food purchasers: quality characteristics, informativity, convenience, price and diversity. According to the result of the cluster analysis, the research subjects were classified into the 2 clusters of diversity and informativity. The deduced 2 clusters, together with age and occupation among general characteristics, were used as independent variables to find out food purchasing behaviors and satisfaction at internet shopping malls. The results are as follows: Regarding the frequency of food purchasing experiences at internet shopping malls according to occupation, the highest frequency was shown by those involved in service, sales and self-employed businesses; whereas regarding the frequency according to age, those in their 30s and 40s showed the highest frequency. The total amount of money spent on food purchasing for 1 year at internet shopping malls was shown to increase as age increased. The frequency of the purchasing experiences of agricultural products and fish products was shown to be higher as age increased. However, overall purchase satisfaction was highest among those in their 30s, while lowest among those in their 40s. Regarding satisfaction by the types of food purchased via internet shopping malls, satisfaction was relatively higher with common foods and functional foods, while lower with fish products. Taken together, it was concluded that purchasing behaviors at internet food shopping malls, such as the frequency of purchasing experiences and purchase amount, varied depending on age rather than purchasing attribute. Accordingly, in order to vitalize internet food shopping malls, it would be necessary to provide customized food shopping information for individual age groups.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.392-401
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• 2013

This study was conducted to research the Selection Attribute for Pension which is located in the region of S. Gyeonggi-do. We intended to find the best choice point for reserving the pension using IPA and suggest or provide strategic implications and marketing method for running the pension. The survey was conducted from the early January to the end of March in 2012 with one to one method. A total of 300 questionnaires were distributed and 229 responded questionnaires were reliable to be used as a sample. The result of the survey was analyzed by using SPSS 15.0 version for window with Paired t-test and IPA method. Frequency Analysis was also conducted for the characteristic of samples. Findings are presented and discussed in three areas. First, the cleanliness of rooms, service for customer, heating and cooling system are the key important factors for the choice of pensions. Secondly, all factors are statistically significant level(p<0.01, p<0.001) as a results of performing IPA method. Thirdly, the result has shown that the varity of programs in the pension have significant impact on the customers' choice and satisfaction.

• The Journal of Industrial Distribution & Business
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• v.9 no.3
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• pp.81-87
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• 2018

Purpose - The perception of the quality of the consumer's distributor's brand(PBs) is generally perceived to be lower than that of the manufacturer's brand(NB), although it is a critical factor in determining the success of PBs. Accordingly, this study examines the characteristics of the convenience store PB products and their correlation with brand trust and purchase intent in the consumers who have had experience purchasing the convenience store PBs to expand the sales variables. Further, this research shows that the marketing strategy is to increase the share of PBs by providing an empirical analysis on the effect of the product attribute factors on the sales volume associated with brand trust, purchase intent, and others. Research design, data, and methodology - The survey period of this study was approximately three weeks from December 1, 2017 to December 21, 2017. The study samples that were taken from 100 random people extracted. The statistical analysis was carried out with multiple regression analysis using the SPSS statistical package. Results - The analysis shows that the brand credibility and purchasing intention were statistically significant differences between the private convenience store private brand products. Specifically, brand trust showed a statistically significant relationship the brand images and quality levels, but the perceived value was not affected statistically. Although the intent of the purchase showed a statistically significant relationship the quality level and the perceived value, the brand image was not statistically significant in its relationship. Conclusions - Overall, it has been established that the perception value does not statistically affect brand trust for convenience store PB products, and that the brand image has no statistically significant effect on the purchase intent. These results are analyzed to be due to the influence of brand in convenience stores themselves rather than brand trust and purchase intentions that affect sales performance, which is the property of private brand food and beverage products, the perceived value of their products. Accordingly, the study found that not only did the marketing performance of the convenience store PB products be improved statistically, but also the cause of the product attributes that were not statistically significant was identified.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.27-36
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• 2019

In this study, experiments on the improvement of the emotion classification, analysis and accuracy of EEG data were proceeded, which applied DEAP (a Database for Emotion Analysis using Physiological signals) dataset. In the experiment, total 32 of EEG channel data measured from 32 of subjects were applied. In pre-processing step, 256Hz sampling tasks of the EEG data were conducted, each wave range of the frequency (Hz); Theta, Slow-alpha, Alpha, Beta and Gamma were then extracted by using Finite Impulse Response Filter. After the extracted data were classified through Time-frequency transform, the data were purified through Independent Component Analysis to delete artifacts. The purified data were converted into CSV file format in order to conduct experiments of Machine learning algorithm and Arousal-Valence plane was used in the criteria of the emotion classification. The emotions were categorized into three-sections; 'Positive', 'Negative' and 'Neutral' meaning the tranquil (neutral) emotional condition. Data of 'Neutral' condition were classified by using Cz(Central zero) channel configured as Reference channel. To enhance the accuracy ratio, the experiment was performed by applying the attributes selected by ASC(Attribute Selected Classifier). In "Arousal" sector, the accuracy of this study's experiments was higher at "32.48%" than Koelstra's results. And the result of ASC showed higher accuracy at "8.13%" compare to the Liu's results in "Valence". In the experiment of Random Forest Classifier adapting ASC to improve accuracy, the higher accuracy rate at "2.68%" was confirmed than Total mean as the criterion compare to the existing researches.

• Journal of the Korean housing association
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• v.26 no.4
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• pp.11-21
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• 2015

Due to the mass production of housing in Korea, homogeneous current housing may fail to represent residents' preferences, especially for the elderly. The purpose of this study is to identify the preferred properties of consumers for accessible housing and to examine whether cluster analysis can identify groups of residents with similar accessible housing preferences. Using a conjoint method, prospective users can jointly consider all accessible attributes, with cost attributes suggested by this study. Four categories (accessibility, safety, convenience, cost), 7 attributes (clear width, level difference, installation of grab bars, installation of elevators: only for single house type, non slippery floor materials, safety alarms, service control devices, cost) and 2 levels for each attribute were chosen. A total of 374 questionnaires were collected through a questionnaire survey method. This study employed ratings-based Conjoint analysis and the respondents ranked each card, which consisted of a set of accessible housing attributes. The data were analyzed using SPSS 16.0. The findings of this study have identified 3-4 clusters for each housing sub market. Each cluster has a different combination of socio-demographic characteristics and residential characteristics, and showed the relative importance or preference values for each accessible attribute of the segmentation. For the single housing, one group of people strongly preferred installation of elevator. The results suggested that better customization of housing could be more appealing to the different clusters of residents, providing accessible housing with cost limitations.

• Korean Journal of Food Science and Technology
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• v.44 no.5
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• pp.648-652
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• 2012

The sensory characteristics of nine commercially distilled soju samples were determined by sensory descriptive analysis. Eight aroma attributes, as well as four flavor/taste attributes, and six mouth-feel related attributes were evaluated by 9 judges. The descriptive data set was initially analyzed for a significant overall product effect by employing a three-way mixed model analysis of variance (judges, samples, and replications) as well as two-way interactions, with judges treated as random. In addition, correlations between mean attribute ratings were calculated, and a principal component analysis (PCA) of the mean attribute ratings employing the covariance matrix was conducted. Based on the PCA, distilled soju samples were primarily separated along the first principal component, which accounted for 66% of the total variance between the samples, with high intensities of 'alcohol taste' and 'alcohol aroma' versus 'yeast aroma'. The second principal component accounted for 14% of the total variance. Soju containing high alcohol showed stronger intensities of 'bitterness', 'alcohol taste', 'alcohol aroma', as well as all mouth-feel attributes.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.147-152
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• 2013

Now, plastic surgery has become the industry for beauty. In order to know the characteristics of high-visit web sites that many people have visited, 33 high visit websites of plastic surgery were compared to 60 benchmark sites of same industry. We selected 34 web site attributes that can be measured objectively from existing studies. For analysis, Multiple Discriminant Analysis(MDA) is conducted for searching what attributes divide two group definitely. The result of this study shows the dividing attributes fall into 2 categories like 'Community', 'Up to date'. Thus, we are able to conclude that high-visit plastic surgery web sites are community-centric site but not contents-centric and are maintained with tide up to date. The methodology employed in this study provides an efficient way of improving satisfaction of visitors of plastic surgery website.

• Culinary science and hospitality research
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• v.16 no.3
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• pp.94-113
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• 2010

Despite a number of previous studies about cultural tourism festivals, studies on food menus in the cultural tourism festival setting have often been neglected. Considering the importance of food menus, identifying major selection attributes that satisfy visitors in a festival setting is vital. Using conjoint analysis, this study demonstrated that price was the most influential selection attributes to attract visitors. The time required between ordering and receiving food was found to be the second important selection attribute, followed by menu and place. Cluster analysis identified two distinct segments that take different sets of elements into account when making their selection decision. Conjoint simulation estimated the most preferred foodservice form in cultural tourism festivals setting would have 21.18% potential market share. The implications gained from this study provided an important starting point for determining key selection attributes in establishing strategies to enhance visitors' level of satisfaction.

• Journal of the Korean Society of Clothing and Textiles
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• v.14 no.4 s.36
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• pp.252-261
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• 1990

This study intends to provide a beneficial foundation which can aid our understanding of how a clothing consumer group can be classified according to the clothing buying motives, and what differences are there about the importances of stroe image attribute among them and how consumer's preferences to the store image are shown differently among them and ultimately, some concrete data which can be useful in establishing efficient store image strategies for clothing stores. 413 subjects were gathered through convenience sampling method and, for data analysis, cronbach'$\alpha$, frequency, percentage, mean, $x^{2}-text$, 1-test, ANOVA, Duncan Multiple Range Test, Factor Analysis, Cluster Analysis were conducted. The results are as follows; 1. Three kind of factors in the clothing buying motives were determined for analysis of consumers group and by which it was revealed as to be significant for us to classify them four subdivisions; those of fashion pursuit group, self display group, financial utilitarian group, individual group. 2. Importance on store image attribute was revealed then the middle aged women regarded quality, price, service in order as more important factors than others. 3. Store image preferences show significantly when concerned with quality, price, fashion, impression and age of store personnel, convenience for exchanging and returning goods, credit, delivery and repair, mailing of catalogue and discount coupon, exit from, brightness of store among consumer groups. From these findings, concretely store image strategies are proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.859-876
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• 2010

In this paper, we propose a hierarchical application traffic classification system as an alternative means to overcome the limitations of the port number and payload based methodologies, which are traditionally considered traffic classification methods. The proposed system is a new classification model that hierarchically combines a binary classifier SVM and Support Vector Data Descriptions (SVDDs). The proposed system selects an optimal attribute subset from the bi-directional traffic flows generated by our traffic analysis system (KU-MON) that enables real-time collection and analysis of campus traffic. The system is composed of three layers: The first layer is a binary classifier SVM that performs rapid classification between P2P and non-P2P traffic. The second layer classifies P2P traffic into file-sharing, messenger and TV, based on three SVDDs. The third layer performs specialized classification of all individual application traffic types. Since the proposed system enables both coarse- and fine-grained classification, it can guarantee efficient resource management, such as a stable network environment, seamless bandwidth guarantee and appropriate QoS. Moreover, even when a new application emerges, it can be easily adapted for incremental updating and scaling. Only additional training for the new part of the application traffic is needed instead of retraining the entire system. The performance of the proposed system is validated via experiments which confirm that its recall and precision measures are satisfactory.