• Culinary science and hospitality research
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• v.9 no.3
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• pp.37-54
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• 2003

As the life style of modern people is gradually being more scientific, up-to-date and specialized, food habit and food culture are a measure of cultural level of a country. Studies on consumer behavioral model show that food habit is closely related to consumer preference, changing life pattern and increasing family income. The purpose of this study was, accordingly, to define the impact of menu characteristics on customer menu selection. For that purpose, some attempts were made: First, discuss the theories on Italian food and customer purchasing behavior as a standard of analysis. Second, find out if there are any differences in customer menu-selection factors in hotel Italian restaurant. Third, make an empirical analysis of menu-selection factors in hotel Italian restaurant to suggest in which direction it should move forward. Fourth, analyze the relationship of demographic characteristics to menu-selection factors.

• Journal of the Korean Home Economics Association
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• v.40 no.12
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• pp.49-61
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• 2002

The purpose of this study was to investigate the effect of clothing involvement on the perceived risk in internet shopping and store selection criteria. The subjects used for the study were 210 male and 338 female college students. The clothing involvement consisted of pleasure, symbolism, and selection difficulty factors. The perceived risk consisted of size/defect risk, social psychological risk, privacy risk, delivery risk, and price risk. The store selection criteria had security/service, entertainment/variety, price/convenience factors. The results showed that consumers were segmented by four groups based on clothing involvement factors: clothing pleasure group, symbolism group, confidence group, and low clothing involvement group. The four segmented groups differed in regard to the perceived risk, store selection criteria, and demographics. For example, clothing pleasure group perceived the size/defect risk and social psychological risk higher than did the other groups. Also, the clothing pleasure group considered entertainment/variety more important and had younger female consumers.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.15-25
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• 2002

This paper considers supplier selection process for e-business & ISO 9001 quality management system environments. Determining suitable suppliers in the electronic commerce has become a key strategic consideration. However, the nature of these decisions is usually complex and unstructured. In this paper, a Quality Estimated Supplier Selection (QESS) model is proposed to deal with the supplier selection problems in the e-business(Business to Business: B to B). In the supplier selection, quality management factors will be considered for the first time, and then price, and delivery etc. In the first level, we deal with the quality management factors such as quality management audit, product test, engineering man-power, capability index and training time etc., based on the five point scale. In the second level, a QESS model determines the final solution by considering factors such as price, production lead-time and delivery time.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.217-228
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• 2020

The selection factors of service companies have changed in accordance with intensifying competition in the marine transportation service market and environment changes of transportation services. To explore the important factors of customer choice to marine transportation service, this study empirically examines the influence of these selection factors; service provision area, price competitiveness, corporate image, service expertise, and sales support, on transaction continuity through customers' perceived service value and satisfaction. Based on an online survey with those in the Korean marine transportation industry, this study conducted statistical analyses using structural equation modeling. Based on relevant previous studies, the current study constructed a total of 55 survey questions. Finally, 213 questionnaires were collected. Among the five selection factors, corporate image did not affect perceived service value, and price competitiveness was still the most important factor. However, service expertise and sales support were found to be more important factors than regional factors. In order to maintain transaction continuity, shipping companies should also strive to improve their service quality to their customers. In particular, service quality strategies focused on time and regional factors should develop to strategies with the key factors for the changed business environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.153-172
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• 2022

In this study, the authors intend to analyze factors contributing to research performance using Backpropagation Neural Network and Support Vector Machine. The analyzing factors contributing to lecturer research performance start from defining the features. The next stage is to collect datasets based on defining features. Then transform the raw dataset into data ready to be processed. After the data is transformed, the next stage is the selection of features. Before the selection of features, the target feature is determined, namely research performance. The selection of features consists of Chi-Square selection (U), and Pearson correlation coefficient (CM). The selection of features produces eight factors contributing to lecturer research performance are Scientific Papers (U: 154.38, CM: 0.79), Number of Citation (U: 95.86, CM: 0.70), Conference (U: 68.67, CM: 0.57), Grade (U: 10.13, CM: 0.29), Grant (U: 35.40, CM: 0.36), IPR (U: 19.81, CM: 0.27), Qualification (U: 2.57, CM: 0.26), and Grant Awardee (U: 2.66, CM: 0.26). To analyze the factors, two data mining classifiers were involved, Backpropagation Neural Networks (BPNN) and Support Vector Machine (SVM). Evaluation of the data mining classifier with an accuracy score for BPNN of 95 percent, and SVM of 92 percent. The essence of this analysis is not to find the highest accuracy score, but rather whether the factors can pass the test phase with the expected results. The findings of this study reveal the factors that have a significant impact on research performance and vice versa.

• The Korean Journal of Health Service Management
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• v.3 no.1
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• pp.47-58
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• 2009

This study is to grasp selection factors and habits of information searching of customers of ophthalmic service and to verify the differences in them and to investigate how they affect in selecting medical institute by demographic sociological characters, selection factors by classification and habits of information searching, how many times they used and the type of medical treatment. The result of analysis of importance of selection factors of medical institute, it showed that doctors' career were evaluated high by classification and it showed in order of university hospital, hospital, clinic in facilities and equipment and in order of university hospital, clinic, hospital in distance transportation Analysis of importance of selection factors by sex distinction, it showed that doctors' career were high for both male and female and according to the result of analysis of selection factors by an age, doctors' career variable was measured high and it showed in order of facilities, equipment, distance and convenient transportation. The result of analysis by the form of medical treatment, doctors' career were measured high in all diseases. Facilities and equipment were measured high in case of a corrective operation of eyesight and distance transportation variable showed high in simple eye diseases. According to the result of analysis of habits of searching information by utility frequency, one's own experience in the past(direct visits) was the highest over all and it showed in order of introduction of other ophthalmic department in case of people who go to the institutes many times.

• Geomechanics and Engineering
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• v.25 no.1
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• pp.1-16
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• 2021

Machine learning models have been widely used for landslide susceptibility assessment (LSA) in recent years. The large number of inputs or conditioning factors for these models, however, can reduce the computation efficiency and increase the difficulty in collecting data. Feature selection is a good tool to address this problem by selecting the most important features among all factors to reduce the size of the input variables. However, two important questions need to be solved: (1) how do feature selection methods affect the performance of machine learning models? and (2) which feature selection method is the most suitable for a given machine learning model? This paper aims to address these two questions by comparing the predictive performance of 13 feature selection-based machine learning (FS-ML) models and 5 ordinary machine learning models on LSA. First, five commonly used machine learning models (i.e., logistic regression, support vector machine, artificial neural network, Gaussian process and random forest) and six typical feature selection methods in the literature are adopted to constitute the proposed models. Then, fifteen conditioning factors are chosen as input variables and 1,017 landslides are used as recorded data. Next, feature selection methods are used to obtain the importance of the conditioning factors to create feature subsets, based on which 13 FS-ML models are constructed. For each of the machine learning models, a best optimized FS-ML model is selected according to the area under curve value. Finally, five optimal FS-ML models are obtained and applied to the LSA of the studied area. The predictive abilities of the FS-ML models on LSA are verified and compared through the receive operating characteristic curve and statistical indicators such as sensitivity, specificity and accuracy. The results showed that different feature selection methods have different effects on the performance of LSA machine learning models. FS-ML models generally outperform the ordinary machine learning models. The best FS-ML model is the recursive feature elimination (RFE) optimized RF, and RFE is an optimal method for feature selection.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.169-177
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• 2007

Competitive international business environment has forced many firms to focus on supply chain management to cope with highly increasing competition. Hence the supplier selection is the most important decision of a company. Because it has a direct effect on cost reduction and quality, profitability and flexibility improvement of a company, so the right supplier selection significantly affect on the organization's efficiency and effectiveness and competitiveness. The primary research objects of this study is to evaluate an importance of supplier selection factors as an index and to present the evaluation model for supplier selection. For this purpose, this study adopts the AHP method to calculate the importance of supplier selection factors. In this study, 16 factors which affect on the supplier selection decision making are classified into three factors-product supply related factor, product related factor, management ability related factor.

• Journal of the Korean Society of Clothing and Textiles
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• v.7 no.1
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• pp.27-35
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• 1983

The purpose of this study is to find out the relationship between needs and factors of clothing Selection. 400 women students from 4 universities and colleges in Seoul were selected and tested. And Hwang Jeongkyu's Needs inventory test sheets for need inventory test and the questionnaire based on Lee Eunju's study for factors of clothing selection were given to the sample. The test data was computerized to get the relationship. The results are as follows: (I) Behavior of clothing selection according to expression of individuality correlated significantly with achievement, aggression, dominance, emotionality, exhibitionism, sex, and autonomy at the .01 level. (2) Behavior of clothing selection according to utility correlated significantly with abasement, and affiliation at the .01 level. and with emotionality at the .05 level, (3) Behavior of clothing selection according to economy correlated significantly with abasement, affiliation, dominance, emotionality, and exhibitionism at the .05 level, and with achievement at the .01 level. (4) Behavior of clothing selection according to modesty correlated significantly with abasement, exhibitionism, and sex at the .01 level. (5) Behavior of clothing selection according to conformity correlated significantly with abasement, emotionality, and autonomy at the .01 level, and with dominance at the .05 level.

• Journal of the Korean Home Economics Association
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• v.23 no.4
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• pp.1-7
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• 1985

The aim of this study is to find out the relation-ship between personality and te factors for clothing selection. For the test, 396 high school girl students in Seoul were selected, respectively. The general personality test sheets by Kim Giseok and the questionnaire besed on Park Eunju's study on the factors for clothing selection were given to the sample group. RESULTS : 1. Behavior of clothing selection according to expression of individuality is sign ificantly correlated with ascendancy and sociability at the level of .001, and with emotional stability at .50. 2. Behavior of clothing selection according to utility is significantly correlated with resopnsibility and emotional stability at the level of .01. 3. Behavior of clothing selection according to economy is significantly correlated with ascendancy and self-confidence at the level of .01, and with responsibility and sociablity at .05. 4. Behavior of clothing selection according to modesty is significantly correlated with ascendancy and sociability at level of .001, and with self-confidence at .01. 5. Behavior of clothing selection according to conformity is significantly correlated with ascendancy, emothional stability, and self-confidence at the level of .001, and with sociability at .05.