• Culinary science and hospitality research
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• v.22 no.5
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• pp.252-266
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• 2016

The purpose of this study is to verify a relationship among service quality and customer satisfaction of wedding hall restaurants, and recommendation intention, as well as the moderating effect of image of wedding halls and hotels on the relationship. A hierarchical regression analysis thorugh SPSS was conducted to test the model hypotheses. Research samples were collected from 331 customers of wedding hall restaurants and hotels located in Seoul. The findings and implications of the research can be summarized as follows. First, the employees, facilities and environment service, and convenience of wedding hall restaurants had a positive effect on customer satisfaction of wedding hall restaurants. Second, evidence suggested that service quality of wedding hall restaurants had a positive effect on recommendation intention. Third, while there was a negative moderating effect of image of wedding halls and hotels between food and employee service quality and customer satisfaction, a positive moderation effect of image of wedding halls and hotels was found. Fourth, there was a negative moderating effect between customer satisfaction and recommendation intention.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.31-36
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• 2019

A chatbot is an important area of mobile service, which understands informal data of a user as a conversational form and provides a customized service information for user. However, there is still a lack of a service way to fully understand the user's natural language typed query dialogue. Therefore, in this paper, we extract meaningful words, such a region, a food category, and a restaurant name from user's dialogue sentences for recommending a restaurant. and by comparing the extracted words against the contents of the knowledge database that is built from the hashtag for recommending a restaurant in SNS, and provides user target information having statistically much the word-similarity. In order to evaluate the performance of the restaurant recommendation chatbot system implemented in this paper, we measured the accessibility of various user query information by constructing a web-based mobile environment. As a results by comparing a previous similar system, our chabot is reduced by 37.2% and 73.3% with respect to the touch-count and the cutaway-count respectively.

• Journal of the Korea Organic Resources Recycling Association
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• v.8 no.3
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• pp.73-80
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• 2000

The objective of study was to evaluate the apropriate maturity indices for garbage composting using sawdust as bulking agent. Materials used in this study were the average composition garbage(G20) and garbage conditioned by sawdust(GS30, GS50) and cereals(GSC30). Indices for evaluating maturity were VS, water soluble TOC, polysaccharide, Humification Index(HI), and E4/E6. Experiment results showed that VS reduction was the most desirable index for evaluating compost maturity except for the GS50 which were conditioned with high sawdust Water soluble TOC decreased rapidly during the composting of first one month and then little changed. Therefore, water soluble TOC was recommended as maturity index. Polysaccharide was considered as a maturity index in case of garbage conditioned with sawdust and high cereals. Humification Index(HI) and E4/E6 were available as maturity indices in case of only some garbage composting so additional study was needed to confirm them as maturity indices for all garbage composting. Correlation analysis indicated that indices for evaluating maturity of garbage(about 30 C/N ratio) adding sawdust as bulking agent and high cereals, were VS reduction, water soluble TOC, polysaccharide, and E4/E6.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.176-179
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• 2019

최근 세계적으로 한국에 대한 인식이 좋아짐으로써 한국으로 유학이나 여행을 오는 외국인이 많아지고 있다. 외국은 다양한 문화와 언어를 가지고 있고 그 외국의 문화와 언어에 익숙하지 않은 많은 식당에서 그들은 식사함에 어려움을 겪고 있다. 우리 학교의 경우에서도 마찬가지로 유학 와 있는 한국어가 서툰 학생들이 한국에서 가장 불편한 일 중 하나가 식당에서 음식을 시키는 것이라고 할 정도로 식사가 제한되어 있다. 이를 해결하기 위해 본 논문에서는 QR 코드를 메뉴판에 부착하여 그 QR 코드를 찍기만 하면 바로 원하는 언어를 선택할 수 있고, 그들의 언어로 음식에 대한 설명이 나타나는 시스템을 제안하고 개발하였다. 제안한 시스템은 종교에 따라 먹지 못하거나, 식습관에 따라 먹지 않는 음식이 있는 외국인들 역시 전자 메뉴판을 이용함으로 어려움을 해결 할 수 있다. 제안한 시스템은 그들 주변에 어떤 식당이 있고 어떤 음식이 있는지 쉽게 알 수 있고 그 어플을 사용하는 사람들과 소통할 수 있는 어플리케이션을 제작함으로써 유학생뿐만 아닌 일반 관광객들을 대상으로도 적극적으로 활용 할 수 있을 것으로 기대가 된다.

• Culinary science and hospitality research
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• v.19 no.4
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• pp.268-278
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• 2013

The purpose of this research is to examine the effects of selection attributes of medicinal food on customer satisfaction and purchase attitude in Jinju area. A survey was conducted to 300 people who live in Jinju area, and 252 completed copies of questionnaire was returned. Statistical package 'SPSS WIN 20.0' was used to analyze the sample data, and the result of the analysis is as follows. First, for the hypothesis, 'selection attributes of medicinal food have a significant effect on satisfaction,' food quality, health food and services have a significant effect on customer satisfaction. Second, customer satisfaction with medicinal food has a significant effect on revisit. Third, customer satisfaction leads to recommendation to others. In conclusion, this research shows that medicinal food restaurants in Jinju area should provide healthy food menu, high-quality food and high-class services, which could be effective to promote the specialty of medicinal food restaurants for costumers.

• Culinary science and hospitality research
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• v.15 no.2
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• pp.93-107
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• 2009

The aims of this study concerning tourists travelling in the island of Jeju include: to identify and assess the promotional efforts for traditional Jeju cuisine; and to identify the impacts of those efforts on customers and tourists. The analyses revealed that continuous promotion efforts, along with changes in the cooking methods and the development of new menus, are needed for the items of traditional Jeju cuisine that are relatively unknown to tourists and that fail to satisfy customers. Customers seeking Jeju food reported high satisfaction with such items as grilled meat and fish, steamed meat and fish, and raw fish(hoe), so those cooking methods must also be continually improved. Promotional efforts had impacts on the satisfaction and revisit rates of customers while the recognizability of foods offered had impacts on all areas, including the satisfaction and revisit rates of customers as well as word-of-mouth advertising among them. There needs to be an experience-oriented or educational program that introduces customers to traditional Jeju cuisine. Since customers and tourists gain information on traditional Jeju cuisine from the recommendations and word-of-mouth advertising from the locals they meet on the island, traditional Jeju cuisine should also be advertised to the local residents. The commercial merchandising of Jeju culinary culture and making festivals based on it must, therefore, be preceded by studies on how to increase the locals' awareness of local traditional cuisine.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.31-49
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• 2023

With the growth of the food-catering industry, consumer preferences and the number of dine-in restaurants are gradually increasing. Thus, personalized recommendation services are required to select a restaurant suitable for consumer preferences. Previous studies have used questionnaires and star-rating approaches, which do not effectively depict consumer preferences. Online reviews are the most essential sources of information in this regard. However, previous studies have aggregated online reviews into long documents, and traditional machine-learning methods have been applied to these to extract semantic representations; however, such approaches fail to consider the surrounding word or context. Therefore, this study proposes a novel review textual-based restaurant recommendation model (RT-RRM) that uses deep learning to effectively extract consumer preferences from online reviews. The proposed model concatenates consumer-restaurant interactions with the extracted high-level semantic representations and predicts consumer preferences accurately and effectively. Experiments on real-world datasets show that the proposed model exhibits excellent recommendation performance compared with several baseline models.

• Culinary science and hospitality research
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• v.21 no.1
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• pp.174-190
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• 2015

This study looks at a causal relationships between service quality and behavior intention(re-visiting, recommendation, loyalty) to attract customers and make them loyal customers in the context of Japanese restaurants. The study includes 250 consumers who have experience in Japanese restaurants located in Busan to conduct survey for empirical testing. To achieve the purpose of current study, frequency test, multiple/simple regression analysis, and factor analysis were conducted with SPSS 18.0 statistical program. Structure Equation Model analysis has been employed for hypothesis testing. Results showed that the service of employee has been recognized as an primary factor among elements of Japanese restaurants' service quality to satisfy customer, and employee's service is the strongest affecting factor to consumers' behavioral intention as well. In addition, the food quality identified as an the strongest factor that affects behavior intention, whereas physical environment is the lowest factor. It can be interpreted that the quality of food is very important element to make their consumers revisit or recommend the restaurant to others. In this study, especially, the service of the employee has been identified as an key factor to customer satisfaction and behavioral intention. Therefore, CEO or restaurateurs of Japanese restaurants have to consider the importance of service quality and food quality to make more patrons as well as their business success.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.4
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• pp.633-643
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• 2013

This study investigated the efficiency of university foodservice operations by analyzing the effect of consumer's perception towards university foodservice quality. University students in the Jeonnam area were surveyed and 571 out of 700 surveys were chosen (response rate: 97.0%). SPSS (ver. 20.0) was used to conduct descriptive analysis, factor analysis, reliability analysis, t-test, and multiple regression analysis. The results show that 21.9% of university students have never used the university foodservice, while 48.7% of university students have eaten there 1~2 times per week. The most common reasons reported for avoiding the university foodservice were a limited menu selection (51.5%) and an untasty food (45.8%). The perception of overall service quality at the university foodservice scored relatively low (3.01 points), compared with its importance (3.89 points). The food taste, menu variety, and quality of food ingredients are factors that require improvement for operational strategies by the importance-performance analysis (IPA). The food factors (taste, variety, and quality) among university foodservice qualities had a significantly positive effect on consumers' overall satisfaction (p<0.001), perceived value (p<0.01), intent to recommend (p<0.001), and intent to revisit (p<0.01). These result indicate that the university foodservice management should focus on developing food factors and strive to meet the needs of university students through continuous customer surveys.