• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4229-4236
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• 2014

This study discusses the customer satisfaction as a result of the attributes of menu choice that can meet the needs of foreign visitors. Furthermore, it discusses the possibility that Korean food can be recognized internationally and the research data be available in advance for the people who are going to visit Korea. This study is based on documentary records and empirical studies to analyze and appreciate the effects of customer satisfaction in restaurants that foreigners usually visit. The documentary records are rooted in the related books, papers published in domestic and international associations, academic journals, and various periodicals. According to this research, the attributes of the menu choice in relation to the differences in their purposes has a meaningful influence on the customer satisfaction, so the menu choice of foreign tourists drives their gratification of Korean food. In short, the explanations and ingredients list about items in Korean restaurants need to be improved and explained to increase the number of potential foreign tourists.

• Journal of Distribution Science
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• v.3 no.2
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• pp.29-55
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• 2005

Since discount stores should be operated mostly by the non-human resources regarding the natural characteristics of the business, it is possibly said that their physical environments have been extremely significant. This study attempts to develop the measurement items and construct factors which are especially relevant to the physical environments of the discount stores and examine how the customer satisfaction and intention influence on these construct factors. These provide a useful framework for understanding the problems of measuring and evaluating the physical environments of discount stores. The final factor analysis for each construct factors resulted as four factors, and two categories(amenity and convenience) represented the characteristics of same construct such as the visibility. Then convenience is eliminated, and an attempt was made to add the new variable what is called the visibility. As a result, final construct factors that would be used in this study are made of four items; amenity, accessibility, POP and visibility. This study utilizes the LISREL 8.12 to evaluate the validity of factor structures and measurement model involving the physical environment in discount store. Finally, for the success of the projects, I think that it is necessary to provide comprehensive efforts continuously.

• Management & Information Systems Review
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• v.33 no.3
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• pp.59-76
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• 2014

This research tries to present the role of Jung, which is well known as Koreans' traditional emotional attachment in service recovery process. Prior research on the service recovery have focused on relationship among perceived justice, recovery satisfaction and forgiveness. Especially perceived justice including distributive, procedural, and interactional justice has addressed as most important antecedents of recovery satisfaction. Although the pivotal role of emotional factors for successful service recovery has agreed by many researchers, relatively little attention has been paid to this issue. During the service recovery process, even if customer perceived recovery effort from service provider as justice one, they might feel displeasure or dissatisfaction. It means prior researches have underestimated the importance of emotional aspect, especially for Korean perspectives. In this study, we examined customer reactions to service failure and recovery process in restaurant service settings. Specifically, we focused on the moderating effect of 'Jung' on the paths between perceived justice and outcome variables such as forgiveness and recovery satisfaction.

• Convergence Security Journal
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• v.14 no.3_2
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• pp.23-35
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• 2014

This study aims to verify the relationship between customer orientation and job stress due to the degree of emotional labor on security agents. Objects of study are from 10 security companies, randomly selected from those registered on the Regional Police Agencies in Daejeon and Chungnam, from November 10th to 20th, 2013; thirty agents from each company, or three-hundred in total, were selected as research subjects by random sampling method. Twenty-five subjects were excluded for poor response contents and/or low reliability. Thus, only 275 subjects were included in actual analysis. The research tool was the questionnaire which was re-composed on the basis of domestic/overseas preliminary studies, while the data was processed through the frequency analysis, the reliability analysis, the confirmatory factor analysis and structure model analysis, using SPSS version 19.0 and AMOS 17.0 statistics package. Through the data analysis following the research methods above, the conclusion was acquired as follows. First, as job stress of security agents decreased, customer orientation increased. Second, the group of security agents with lower level of emotional labor positively affected job stress and customer orientation.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.123-132
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• 2016

This study starts from the research question that "Why some companies decide to keep working in partnership even when they are not satisfied with the partner companies simply because they are old business partners." The authors try to find the answer in terms of customer value considering the phases of B2B transaction spectrum: transaction value, relationship value and appraisal value implementing empirical research. The result shows that the intension to retain the relation with an existing partner is formed by the trade-off between the benefit and cost of both contract value and relationship value and not the sole value was dominant. The unique point of the study is that current study is considering these two factors as dependent variables which affect the relationship continuity which is not the case in existing researches.

• Journal of the Korean Applied Science and Technology
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• v.40 no.3
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• pp.579-588
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• 2023

This study attempted to reveal the causal relationship (SEM) focusing on communication style on the impact of lapo formation between personal trainers and customers on motor performance. Accordingly, the following results were derived through the mobile program "Survey Monkey" for 187 PT customers according to the sample plan from October 1 to April 28, 2022. First, it was found that communication style had an effect (+) on lapo formation. Second, communication style partially affects (+) mobility performance, and the control type has no influence relationship. Third, lapo formation was found to have an effect on motor performance. Therefore, since PT is a human service, not a general service, its importance should be emphasized more. In addition, the dominance in the fierce PT market is expected to have both athletic performance and management performance if the verbal and non-verbal aspects of expression methods that customers can respond to are properly reflected.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.157-170
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• 2014

Professional coffee shops are trying to increase customers' satisfaction and to invite more customers by providing the differentiated services. The existing researches show that the effects which the physical environment in shops has on customers' satisfaction and word of mouth intention are appealing to people's attention. In comprehensively examining the studies related to the physical environment, they can be summarized into two main perspectives, that is, the direct effect that the physical environment has on customers' satisfaction, quality perception, and other customers' responses (purchase desire, revisit intention, etc.) and the indirect effect that the physical environment has on customers' responses by means of customers' emotion or value perception. This research established 4 hypotheses by sampling 321 customers of those who have visited professional coffee shops, and empirically analyzed them. The empirical analysis carried out the structure analysis of covariance by using SPSS 17.0 statistics package and AMOS 17.0. As a result of the hypothesis qualification, the other hypotheses excluding one little hypothesis were adopted. The one refused hypothesis is that the only symbolism of the environmental elements in shops doesn't influence the customers' emotion positively (+). This is considered as a very unexpected result, and yet many customers who visit coffee shops express the symbols of professional coffee shops using the expressions such as 'bean coffee shop' or 'star coffee shop', but these expressions seem not to influence customers' mind positively in practice.

• Culinary science and hospitality research
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• v.18 no.5
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• pp.45-62
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• 2012

The purpose of this study is to secure the basic data for the physical environment of an eco-friendly restaurant by surveying and analyzing customer perceptions of the servicescape of an eco-friendly restaurant and to verify the organic causation of the servicescape of an eco-friendly restaurant and customer perceived value, attitude and behavior intention. The samples for empirical analysis were selected from the customers over 20 years who lives in Seoul and Kyung-gi suburbs have experienced visiting eco-friendly restaurant or green restaurant more than once a month. Total 300 copies of questionnaire were distributed for the survey from the second day to the fifteenth day of April for 14 days, and total 264 (88.0%) copies of survey questionnaire except for some questionnaires that had much strong lean tendency or the missing value was discovered. The research results are as follows; when a customer recognizes an eco-friendly restaurant favorably, he or she considers that servicescape plays an important role in deciding perceived value through tangible and intangible perceived values. Since, customer perceived value has a positive effect on attitude and behavior intention, the customer considers as affected on his/her behavior intention when satisfied with the eco-friendly restaurant, which is considered that positive customer attitude will have an effect on behavior intention. Thus, it is considered based on this in-depth analysis result that maintaining and providing servicescape of high standard in the manager's perspective will have a direct effect on ensuring tangible outcomes.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.