• Journal of the Korean Geographical Society
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• v.31 no.2
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• pp.160-197
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• 1996

The purpose of this study is to review research trends and issues of economic geography in Korea for the last fifty years by sub-fields of agricultural geography, industrial geography, commercial and service geography, and transportation geography. Research in Korean economic geography has progressed significantly in terms of the scope and the number of papers published during the last a half a century. Agricultural geography was a leading field of economic geography in Korea before mid-1970s. Since the mid-1970s, however, agricultural geography has turned over the leading role in economic geography to industrial geography. Classification and structure of agricultural region has been the most popular research theme in Korea, even though diverse topics has been dealt in the research of agricultulal geography in Korea during the last fifty years. In recent years, emphasis is given to study on the dynamics of agricultural region and regional differentiation of part-time farming. It is suggested that the future issues of research in agricultural geography in Korea are agricultural restructuring and changes in agricultural space under the WTO system, changes in rural area and agricultural region with the progress of informatization, changes in agricultural structures and rural society by the increase of part-time farming, governments agricultulal policy and its impacts, competitive advantages of Korean agricultulal products, and environmental impacts of agricultural restructuring. Research in industrial geography has remarkably progressed since the 1980s. Locational changes, regional industrial structure and formation of industrial region were the major topics of interest in the research of industrial geography in Korea before 1980. Since the early 1980s, in addition to the topics which were interested in before 1980, changes of industrial organization and industrial location, changes of production systems and industrial space development of high technology industries and science parks, industrial restructuring and regional economy, foreign direct investments, industrial linkages and industrial districts, and industrial policy and regional development have been the major research themes of industrial geography in Korea. Considerable number of papers has been published both in Korean journals and in foreign journals during this period. Considering global changes in the organization of industrial space, future research should be more focused on firms strategy for regaining competitive advantages, local and global perspectives of industry, industry and environmental changes, in addition to the topics which have been dealt in recent years. Research in commercial and service geography and transportation geography was negligible in Korea before the late 1970s. These two sub-fields in economic geography have begun to develop since 1980s. Periodic markets, structure of commercial area, and distribution of products were the major topics of interest in the 1980s in the commercial and service geography in Korea. In the 1990s, however reserch in producer services has been active with growth of producer services in Korean economy. It is suggested that regional changes with progress of informatization and technology, changes of international trade and regional changes, development of efficient distribution system, role of producer services in regional development, and network of producer services are the major issues to be studied in the future in the field of commercial and service geography in Korea. Commuting, distribution of products, and transportation networks have been the major topics of research in transportation geography in Korea. Diverse quantitative techniques have been applied in the most of the researches in transportation geography. It is required that future studies in transportation geography should also focus on societal and behavioral issues, policy issues regional impacts of new transportation facilities, an analysis of transportation system at the global or international level. Since the 1980s economic geography in Korea has considerably progressed with publication of papers and books. The progress can be regarded as successful in quantitative aspect, but not in quantitative aspects. For the development of Korean economic geography in both quantitative and qualitative aspects, it is necessary to promote international collaborative researches and interdisciplinary cooperations. Attention should also be given to the research on changes in competitive advantages and economic restructuring, changes of economic space with the development of high technology and the progress of informatization. economic development and culture. and foreign regional studies.

• Progress in Medical Physics
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• v.16 no.1
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• pp.10-15
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• 2005

IAEA's guidance levels have been provided for western people to the end. Guidance levels lower than the IAEA'S will be necessary in view of Korean people's proportions. Therefore, we need to develope the standard doses for Korean people. And we conducted a nationwide survey of patient dose from x-ray examinations in Korea. In this study, the 278 institutions were selected from Members Book of Korean Hospital Association. The valid response rate was approximately 57.9%. Doses were calculated from the questionnaires by NDD method. We obtained the results were as follows; 1) General radiographic equipments were distributed for 42.0%, fluoroscopic equipments 29.4%, dental equipments 13.2%, CT units 8.1 % and mamographic units 7.2%. 2) According to classification by rectification, three-phase equipments were 29.9%, inverter-type generators 29.5%, single-phase equipments 25.5%, constant voltage units 9.0% and unknown units 6.0%. 3) According to classification by receptor system, film-screen types were 46.8%, CR types 26.8%, DR types 17.7% and unknown types 8.9%. 4) The number of examinations were chest 49.2%, spine 16.8% and abdomen 12.7%. 5) Patient doses were head AP 3.44 mGy, abdomen AP 4.25 mGy and chest PA 0.39 mGy.

• Journal of Distribution Science
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• v.8 no.4
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• pp.5-15
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• 2010

This study investigated research trends of JDS that KODISA published and gave implications to elevate quality of scholarly journals. In other words, the study classified scientific system of distribution area to investigate research trends and to compare it with other scholarly journals of distribution and to give implications for higher level of JDS. KODISA published JDS Vol.1 No.1 for the first time in 1999 followed by Vol.8 No.3 in September 2010 to show 109 theses in total. KODISA investigated subjects, research institutions, number of participants, methodology, frequency of theses in both the Korean language and English, frequency of participation of not only the Koreans but also foreigners and use of references, etc. And, the study investigated JDR of KODIA, JKDM(The Journal of Korean Distribution & Management) and JDA that researched distribution, so that it found out development ways. To investigate research trends of JDS that KODISA publishes, main category was made based on the national science and technology standard classification system of MEST (Ministry Of Education, Science And Technology), table of classification of research areas of NRF(National Research Foundation of Korea), research classification system of both KOREADIMA and KLRA(Korea Logistics Research Association) and distribution science and others that KODISA is looking for, and distribution economy area was divided into general distribution, distribution economy, distribution, distribution information and others, and distribution management was divided into distribution management, marketing, MD and purchasing, consumer behavior and others. The findings were as follow: Firstly, main category occupied 47 theses (43.1%) of distribution economy and 62 theses (56.9%) of distribution management among 109 theses in total. Active research area of distribution economy consisted of 14 theses (12.8%) of distribution information and 9 theses (8.3%) of distribution economy to research distribution as well as distribution information positively every year. The distribution management consisted of 25 theses (22.9%) of distribution management and 20 theses (18.3%) of marketing, These days, research on distribution management, marketing, distribution, distribution information and others is increasing. Secondly, researchers published theses as follow: 55 theses (50.5%) by professor by himself or herself, 12 theses (11.0%) of joint research by professors and businesses, Professors/students published 9 theses (8.3%) followed by 5 theses (4.6%) of researchers, 5 theses (4.6%) of businesses, 4 theses (3.7%) of professors, researchers and businesses and 2 theses (1.8%) of students. Professors published theses less, while businesses, research institutions and graduate school students did more continuously. The number of researchers occupied single researcher (43 theses, 39.5%), two researchers (42 theses, 38.5%) and three researchers or more (24 theses, 22.0%). Thirdly, professors published theses the most at most of areas. Researchers of main category of distribution economy consisted of professors (25 theses, 53.2%), professors and businesses (7 theses, 14.9%), professors and businesses (7 theses, 14.9%), professors and researchers (6 theses, 12.8%) and professors and students (3 theses, 6.3%). And, researchers of main category of distribution management consisted of professors (30 theses, 48.4%), professors and businesses (10 theses, 16.1%), and professors and researchers as well as professors and students (6 theses, 9.7%). Researchers of distribution management consisted of professors, professors and businesses, professors and researchers, researchers and businesses, etc to have various types. Professors mainly researched marketing, MD and purchasing, and consumer behavior, etc to demand active participation of businesses and researchers. Fourthly, research methodology was: Literature research occupied 45 theses (41.3%) the most followed by empirical research based on questionnaire survey (44 theses, 40.4%). General distribution, distribution economy, distribution and distribution management, etc mostly adopted literature research, while marketing did empirical research based on questionnaire survey the most. Fifthly, theses in the Korean language occupied 92.7% (101 theses), while those in English did 7.3% (8 theses). No more than one thesis in English was published until 2006, and 7 theses (11.9%) were published after 2007 to increase. The theses in English were published more to be affirmative. Foreigner researcher published one thesis (0.9%) and both Korean researchers and foreigner researchers jointly published two theses (1.8%) to have very much low participation of foreigner researchers. Sixthly, one thesis of JDS had 27.5 references in average that consisted of 11.1 local references and 16.4 foreign references. And, cited times was 0.4 thesis in average to be low. The distribution economy cited 24.2 references in average (9.4 local references and 14.8 foreign references and JDS had 0.6 cited reference. The distribution management had 30.0 references in average (12.1 local references and 17.9 foreign references) and had 0.3 reference of JDS itself. Seventhly, similar type of scholarly journal had theses in the Korean language and English: JDR( Journal of Distribution Research) of KODIA(Korea Distribution Association) published 92 theses in the Korean language (96.8%) and 3 theses in English (3.2%), that is to say, 95 theses in total. JKDM of KOREADIMA published 132 theses in total that consisted of 93 theses in the Korean language (70.5%) and 39 theses in English (29.5%). Since 2008, JKDM has published scholarly journal in English one time every year. JDS published 52 theses in the Korean language (88.1%) and 7 theses in English (11.9%), that is to say, 59 theses in total. Sixthly, similar type of scholarly journals and research methodology were: JDR's research methodology had 65 empirical researches based on questionnaire survey (68.4%), followed by 17 literature researches (17.9%) and 11 quantitative analyses (11.6%). JKDM made use of various kinds of research methodologies to have 60 questionnaire surveys (45.5%), followed by 40 literature researches (30.3%), 21 quantitative analyses (15.9%), 6 system analyses (4.5%) and 5 case studies (3.8%). And, JDS made use of 30 questionnaire surveys (50.8%), followed by 15 literature researches (25.4%), 7 case studies (11.9%) and 6 quantitative analyses (10.2%). Ninthly, similar types of scholarly journals and Korean researchers and foreigner researchers were: JDR published 93 theses (97.8%) by Korean researchers except for 1 thesis by foreigner researcher and 1 thesis by joint research of the Korean researchers and foreigner researchers. And, JKDM had no foreigner research and 13 theses (9.8%) by joint research of the Korean researchers and foreigner researchers to have more foreigner researchers as well as researchers in foreign countries than similar types of scholarly journals had. And, JDS published 56 theses (94.9%) of the Korean researchers, one thesis (1.7%) of foreigner researcher only, and 2 theses (3.4%) of joint research of both the Koreans and foreigners. Tenthly, similar type of scholarly journals and reference had citation: JDR had 42.5 literatures in average that consisted of 10.9 local literatures (25.7%) and 31.6 foreign literatures (74.3%), and cited times accounted for 1.1 thesis to decrease. JKDM cited 10.5 Korean literatures (36.3%) and 18.4 foreign literatures (63.7%), and number of self-cited literature was no more than 1.1. Number of cited times accounted for 2.9 literatures in 2008 and then decreased continuously since then. JDS cited 26,8 references in average that consisted of 10.9 local references (40.7%) and 15.9 foreign references (59.3%), and number of self-cited accounted for 0.2 reference until 2009, and it increased to be 2.1 references in 2010. The author gives implications based on JDS research trends and investigation on similar type of scholarly journals as follow: Firstly, JDS shall actively invite foreign contributors to prepare for SSCI. Secondly, ratio of theses in English shall increase greatly. Thirdly, various kinds of research methodology shall be accepted to elevate quality of scholarly journals. Fourthly, to increase cited times, Google and other web retrievals shall be reinforced to supply scholarly journals to foreign countries more. Local scholarly journals can be worldwide scholarly journal enough to be acknowledged even in foreign countries by improving the implications above.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2015.05a
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• pp.545-570
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• 2015

Korea is among the ten countries with the largest R&D budget and the highest R&D investment-to-GDP ratio, yet the subject of security and protection of R&D results remains relatively unexplored in the country. Countries have implemented in their legal systems measures to properly protect cutting-edge industrial technologies that would adversely affect national security and economy if leaked to other countries. While Korea has a generally stable legal framework as provided in the Regulation on the National R&D Program Management (the "Regulation") and the Act on Industrial Technology Protection, many difficulties follow in practice when determining details on security management and obligations and setting standards in carrying out national R&D projects. This paper proposes to modify and improve security level classification standards in the Regulation. The Regulation provides a dual security level decision-making system for R&D projects: the security level can be determined either by researcher or by the central agency in charge of the project. Unification of such a dual system can avoid unnecessary confusions. To prevent a leakage, it is crucial that research projects be carried out in compliance with their assigned security levels and standards and results be effectively managed. The paper examines from a practitioner's perspective relevant legal provisions on leakage of confidential R&D projects, infringement, injunction, punishment, attempt and conspiracy, dual liability, duty of report to the National Intelligence Service (the "NIS") of security management process and other security issues arising from national R&D projects, and manual drafting in case of a breach. The paper recommends to train security and technological experts such as industrial security experts to properly amend laws on security level classification standards and relevant technological contents. A quarterly policy development committee must also be set up by the NIS in cooperation with relevant organizations. The committee shall provide a project management manual that provides step-by-step guidance for organizations that carry out national R&D projects as a preventive measure against possible leakage. In the short term, the NIS National Industrial Security Center's duties should be expanded to incorporate national R&D projects' security. In the long term, a security task force must be set up to protect, support and manage the projects whose responsibilities should include research, policy development, PR and training of security-related issues. Through these means, a social consensus must be reached on the need for protecting national R&D projects. The most efficient way to implement these measures is to facilitate security training programs and meetings that provide opportunities for communication among industrial security experts and researchers. Furthermore, the Regulation's security provisions must be examined and improved.

• The Korean Journal of Air & Space Law and Policy
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• v.28 no.1
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• pp.3-54
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• 2013

Nowadays, major advanced countries in aviation technology are putting their effort to develop commercial and civil Unmanned Aircraft System(UAS) due to its highly promising market demand in the future. The market scale of commercial and civil UAS is expected to increase up to approximately 8.8 billon U.S. dollars by the year 2020. The usage of commercial and civil UAS covers various areas such as remote sensing, relaying communications, pollution monitoring, fire detection, aerial reconnaissance and photography, coastline monitoring, traffic monitoring and control, disaster control, search and rescue, etc. With the introduction of UAS, changes need to be made on current Air Traffic Management Systems which are focused mainly manned aircrafts to support the operation of UAS. Accordingly, the legislation for the UAS operation should be followed. Currently, ICAO's Unmanned Aircraft System Study Group(UASSG) is leading the standardization process of legislation for UAS operation internationally. However, some advanced countries such as United States, United Kingdom, Australia have adopted its own legislation. Among these countries, United States is most forth going with President Obama signing a bill to integrate UAS into U.S. national airspace by 2015. In case of Korea, legislation for the unmanned aircraft system is just in the beginning stage. There are no regulations regarding the operation of unmanned aircraft in Korea's domestic aviation law except some clauses regarding definition and permission of the unmanned aircraft flight. However, the unmanned aircrafts are currently being used in military and under development for commercial use. In addition, the Ministry of Land, Infrastructure and Transport has a ambitious plan to develop commercial and civil UAS as Korea's most competitive area in aircraft production and export. Thus, Korea is in need of the legislation for the UAS operation domestically. In this regards, I personally think that Korea's domestic legislation for UAS operation will be enacted focusing on following 12 areas : (1)use of airspace, (2)licenses of personnel, (3)certification of airworthiness, (4)definition, (5)classification, (6)equipments and documents, (7)communication, (8)rules of air, (9)training, (10)security, (11)insurance, (12)others. Im parallel with enacting domestic legislation, korea should contribute to the development of international standards for UAS operation by actively participating ICAO's UASSG.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.1092-1099
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• 2022

Research on exhaust aftertreatment devices to reduce air pollutants and greenhouse gas emissions is being actively conducted. However, in the case of the particulate matters/nitrogen oxides (PM/NOx) simultaneous reduction device for ships, the problem of back pressure on the diesel engine and replacement of the filter carrier is occurring. In this study, for the optimal design of the integrated device that can simultaneously reduce PM/NOx, an appropriate standard was presented by studying the flow inside the device and change in back pressure through the inlet/outlet pressure. Ansys Fluent was used to apply porous media conditions to a diesel particulate filter (DPF) and selective catalytic reduction (SCR) by setting porosity to 30%, 40%, 50%, 60%, and 70%. In addition, the ef ect on back pressure was analyzed by applying the inlet velocity according to the engine load to 7.4 m/s, 10.3 m/s, 13.1 m/s, and 26.2 m/s as boundary conditions. As a result of a computational fluid dynamics analysis, the rate of change for back pressure by changing the inlet velocity was greater than when inlet temperature was changed, and the maximum rate of change was 27.4 mbar. This was evaluated as a suitable device for ships of 1800kW because the back pressure in all boundary conditions did not exceed the classification standard of 68mbar.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.201-220
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• 2019

Fake news has emerged as a significant issue over the last few years, igniting discussions and research on how to solve this problem. In particular, studies on automated fact-checking and fake news detection using artificial intelligence and text analysis techniques have drawn attention. Fake news detection research entails a form of document classification; thus, document classification techniques have been widely used in this type of research. However, document summarization techniques have been inconspicuous in this field. At the same time, automatic news summarization services have become popular, and a recent study found that the use of news summarized through abstractive summarization has strengthened the predictive performance of fake news detection models. Therefore, the need to study the integration of document summarization technology in the domestic news data environment has become evident. In order to examine the effect of extractive summarization on the fake news detection model, we first summarized news articles through extractive summarization. Second, we created a summarized news-based detection model. Finally, we compared our model with the full-text-based detection model. The study found that BPN(Back Propagation Neural Network) and SVM(Support Vector Machine) did not exhibit a large difference in performance; however, for DT(Decision Tree), the full-text-based model demonstrated a somewhat better performance. In the case of LR(Logistic Regression), our model exhibited the superior performance. Nonetheless, the results did not show a statistically significant difference between our model and the full-text-based model. Therefore, when the summary is applied, at least the core information of the fake news is preserved, and the LR-based model can confirm the possibility of performance improvement. This study features an experimental application of extractive summarization in fake news detection research by employing various machine-learning algorithms. The study's limitations are, essentially, the relatively small amount of data and the lack of comparison between various summarization technologies. Therefore, an in-depth analysis that applies various analytical techniques to a larger data volume would be helpful in the future.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.41-61
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• 2023

The universal form of life in the era of the 4th industrial revolution can probably be summarized as the keyword "non-face-to-face". In particular, in terms of consumption activities, face-to-face contact is gradually changing to a system that minimizes, and offline stores are rapidly changing to non-contact services through kiosks and robots. The social structure is also changing with the passage of time, and most fundamentally, our dietary consumption patterns are changing. In particular, the increase in single-person households and the aging population are having a great impact on changes in the food service industry, which is closely related to dietary life. The HMR (Home Meal Replacement) market has grown significantly as the labor of cooking at home has decreased and the use of substitute foods has increased. As the size of the market has grown, the types of businesses that provide products have also diversified. The development of technology, non-face-to-face culture, and corporate management efficiency are intertwined, and unmanned stores are spreading recently. In this study, service quality attributes of HMR unmanned stores, where competition is gradually intensifying, are classified, and service quality classification using the Kano model and Timko's customer satisfaction coefficient are calculated to provide implications for service management based on customer satisfaction. As a result of the analysis, 'products with short cooking time' and 'variety of products (menu)' were classified as attractive qualities, and 'cleanliness inside/outside of the store' and 'products at reasonable prices' were classified as unified quality. In addition, 'convenience of self-checkout process' was classified as a natural quality, and 'convenience of in-store passage' was classified as an indifferent quality. Furthermore, when the service factor was satisfied within the HMR unmanned store, the factor with the highest satisfaction coefficient was 'product (menu) variety', and the factor with the highest dissatisfaction factor was 'convenience of self-checkout process'. Through the results of this study, it is intended to derive priorities in service quality management of HMR unmanned stores and provide strategic implications for related businesses.