• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.417-425
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• 2021

This study was conducted to evaluate the characteristics of major selection of college students majoring in culinary. By conducting an Importance-Performance Analysis(IPA) through students who are currently majoring in a culinary major, it is intended to increase student satisfaction, student loyalty, the enrollment rate and to present the direction the college should pursue. The questionnaire was conducted for 4 weeks from June 22, 2020 to July 19, 2020, the results are as follows. As a result of the t-test (paired sample t-test) for 23 attributes, the average value of importance was 4.0765, the average value of satisfaction was 3.5091, showing high importance, the attributes considered important by item were 'educational facilities (4.50)', 'school welfare (4.50)', the attributes having the highest satisfaction with experience after selecting a major were 'aptitude and conformity (3.94)', 'future hope and concordance (3.91)'. The IPA analysis results on the major selection attributes of college students majoring in culinary are as follows. First, In the first quadrant, 11 attributes including 'aptitude and conformity' appeared, Second, In the second quadrant, 5 attributes including 'employment support' appeared. Third, In the third quadrant, 5 attributes including 'college scholastic ability score' appeared, Finally, In the fourth quadrant, 2 attributes including 'experience in major field' appeared.

• Information Systems Review
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• v.25 no.4
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• pp.89-112
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• 2023

In March 2020, as it was declared a COVID-19 pandemic, various quarantine measures were taken. Accordingly, many changes have occurred in the tourism and hospitality industries. In particular, quarantine guidelines, such as the introduction of non-face-to-face services and social distancing, were implemented in the restaurant industry. For decades, research on restaurant attributes has emphasized the importance of three attributes: atmosphere, service quality, and food quality. Nevertheless, to the best of our knowledge, research on restaurant attributes considering the COVID-19 situation is insufficient. To respond to this call, this study attempted an exploratory approach to classify new restaurant attributes based on understanding environmental changes. This study considered 31,115 online reviews registered in Naverplace as an analysis unit, with 475 general restaurants located in Euljiro, Seoul. Further, we attempted to classify restaurant attributes by clustering words within online reviews through TF-IDF and LDA topic modeling techniques. As a result of the analysis, the factors of "prevention of infectious diseases" were derived as new attributes of restaurants in the context of COVID-19 situations, along with the atmosphere, service quality, and food quality. This study is of academic significance by expanding the literature of existing restaurant attributes in that it categorized the three attributes presented by existing restaurant attributes and further presented new attributes. Moreover, the analysis results have led to the formulation of practical recommendations, considering both the operational aspects of restaurants and policy implications.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.145-153
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• 2008

Existing shortest-path algorithms mainly consider a single attribute. But traveler actually chooses a route considering not single attribute but various attributes which are synthesized travel time, route length, personal preference, etc. Therefore, to search the optimal path, these attributes are considered synthetically. In this study route searching algorithm which selects the maximum utility route using discrete choice model has developed in order to consider various attributes. Six elements which affect route choice are chosen for the route choice model and parameters of the models are estimated using survey data. A multinomial logit models are developed to design the function of route choice model. As a result, the model which has route length, delay time, the number of turning as parameter is selected based on the significance test. We use existing shortest path algorithm, which can reflect urban transportation network such as u-turn or p-turn, and apply it to the real network.

• Journal of Korea Port Economic Association
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• v.33 no.4
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• pp.37-58
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• 2017

The implicit assumption of port selection studies based on survey and respondents' perceptions is that the preference of the port selection attributes is proportional to the selection behavior. Further, the straight lines of the port selection attributes could also have non-linear properties. This study confirms nonlinear characteristics of selection attributes by using Kano model. The findings of this study showed that several properties of carriers were evaluated as nonlinear characteristics, such as the intermodal links and network accessibility, and size of port and terminal. Hence, port service providers such as port authorities and terminal operating companiesl, should construct a port operation strategy that reflects the non-linear port selection characteristics of shipping companies. Since this study aimed at exploring the forms of port selection characteristics, long-term additional verification studies on ports and stakeholders at domestics and abroad were needed. The Kano model and importance-selection analysis method used for analysis and strategy establishment also need to be improved to capture evident characteristics and to present strategic guidelines.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.444-455
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• 2013

The purpose of this study is to explore the selection attributes for parents of children with language disability when choosing a clinic. The data collection was carried out in 3 steps: the preliminary survey, first open survey and second survey in AHP(Analytic Hierarchy Process). The subjects of were 252 in total. The results were as follows: First, The order of priority attributes in superior categories for parents of children with language disability when selecting a clinic were 'therapist-related attributes', 'program-related attributes' and 'physical-related attributes' in turn. The top 5 priority attributes in subcategories were 'therapist's academic background and major', 'ability to make a rapport', 'clinical experience and qualification of therapist', 'kindness and confidence' and 'counseling program for parents'. Second, The parents of preschoolers age 6 and younger chose 'clinical experience and qualification of therapist', 'counseling program for parents' and 'learning materials' for the most priority attributes, whereas the parents of students age from 7 to 12, considered 'therapist's academic background and major', 'clinical fee' and 'distance transport parking' more importantly to select a clinic. The results of this study provided preliminary data for successful planning of speech and language therapy.

• Information Systems Review
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• v.24 no.1
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• pp.1-19
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• 2022

Social media-based communication has become crucial part of our personal and official lives. Therefore, it is no surprise that social media sentiment analysis has emerged an important way of detecting potential customers' sentiment trends for all kinds of companies. However, social media sentiment analysis suffers from huge number of sentiment features obtained in the process of conducting the sentiment analysis. In this sense, this study proposes a novel method by using Bayesian Network. In this model MBFS (Markov Blanket-based Feature Selection) is used to reduce the number of sentiment features. To show the validity of our proposed model, we utilized online review data from Yelp, a famous social media about restaurant, bars, beauty salons evaluation and recommendation. We used a number of benchmarking feature selection methods like correlation-based feature selection, information gain, and gain ratio. A number of machine learning classifiers were also used for our validation tasks, like TAN, NBN, Sons & Spouses BN (Bayesian Network), Augmented Markov Blanket. Furthermore, we conducted Bayesian Network-based what-if analysis to see how the knowledge map between target node and related explanatory nodes could yield meaningful glimpse into what is going on in sentiments underlying the target dataset.

• Journal of Korean Society for Quality Management
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• v.45 no.1
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• pp.55-64
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• 2017

Purpose: A large number of attributes with mixed levels are often considered in the conjoint analysis. The respondents may have difficulty with scoring their preferences accurately because of many attribute items involved in each survey question. We research on the technique for reducing the number of attribute items. Methods: In order to reduce the number of attribute items in a survey question, we make a new attribute by merging two original attributes. A 'No question' option is also included as a new level in a merged attribute. Results: We propose BIB $6^4$ design in the case where we have four attributes with 2 levels and 3 levels, respectively and then analyze all the respondents survey data generated by the repeated simulation study in order to compare various model selection methods. Conclusion: How to reduce the number of attribute items is proposed and how to design and analyze the survey data are illustrated.

• Journal of Global Scholars of Marketing Science
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• v.15 no.3
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• pp.149-168
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• 2005

The purpose of this paper is to study the impact of brand personality on the choice of tour site. For this purpose, Japanese, Chinese and Korean tourists visiting Jeju-Ireland were sampled and asked to evaluate the personality dimensions and attributes of six major tour sites in Asia. Factor analysis is applied to 42 personality scales of Aaker and 5 personality dimensions are extracted. Then, Multinomial Logit model is applied to estimate the relative impact of personality dimensions and attributes on the choice of tour sites. Results suggest useful implications. The personality of tour sites has meaningful influence on choice of tour sites, in some cases more important than tour site attributes. Among 5 dimensions of personality, sincerity and excitement are found to be important dimensions in the choice process of tour site. Sophistication of the site, expressed as glamorous, charming, handsomeness, uniqueness, and smooth, is also found to be important in determining intention to visit in the future.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.41-50
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• 2020

Sentimental analysis begins with the search for words that determine the sentimentality inherent in data. Managers can understand market sentimentality by analyzing a number of relevant sentiment words which consumers usually tend to use. In this study, we propose exploring performance of feature selection methods embedded with Particle Swarm Optimization Multi Objectives Evolutionary Algorithms. The performance of the feature selection methods was benchmarked with machine learning classifiers such as Decision Tree, Naive Bayesian Network, Support Vector Machine, Random Forest, Bagging, Random Subspace, and Rotation Forest. Our empirical results of opinion mining revealed that the number of features was significantly reduced and the performance was not hurt. In specific, the Support Vector Machine showed the highest accuracy. Random subspace produced the best AUC results.

• Information Systems Review
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• v.25 no.1
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• pp.47-73
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• 2023

Management decision-making based on artificial intelligence(AI) plays an important role in helping decision-makers. Business decision-making centered on AI is evaluated as a driving force for corporate growth. AI-based on accurate analysis techniques could support decision-makers in making high-quality decisions. This study proposes an effective decision-making method with the application of multi-label feature selection. In this regard, We present a CFS-BR (Correlation-based Feature Selection based on Binary Relevance approach) that reduces data sets in high-dimensional space. As a result of analyzing sample data and empirical data, CFS-BR can support efficient decision-making by selecting the best combination of meaningful attributes based on the Best-First algorithm. In addition, compared to the previous multi-label feature selection method, CFS-BR is useful for increasing the effectiveness of decision-making, as its accuracy is higher.