• Journal of Applied Tourism Food and Beverage Management and Research
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• v.16 no.2
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• pp.175-199
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• 2005

Family Restaurant is a service business of a kind. The role of service operator is to improve a sales of service goods through maximizing the service value with customer satisfaction at the moment of MOT(moment of truth). Family Restaurant come to the great growth on the face of it. In future, it will place emphasis more and more on not hardware but software including service quality. The purpose of this study, therefore, is to research the effect on service quality of the job satisfaction of Family Restaurant's service staff. Data was collected from the employee who are working at Family Restaurant located in Taegu. The empirical research has been done over 50days from 1April, 2004 to 20May, 2004. In conclusion of empirical analysis, 4 hypotheses were significant among 7 hypotheses suggested in this study. The research showed as follows : First, the organic trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed positive influence on job satisfaction. Second, the personal trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed positive influence on service quality. Third, the official trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed negative influence on job satisfaction. Fourth, the organic trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed positive influence on service quality. Fifth, the personal trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed negative influence on service quality. Sixth, the organic trait among the effect factor of job satisfaction perceived by Family Restaurant service staff showed negative influence on service quality. Seventh, the job satisfaction of Family Restaurant service staff showed positive influence on service quality. Besides, the critical points of this study are as follows; First, we designated the subject of research to the employee of Family Restaurant only. Second, multi-situations(time, holiday) which can happen as service was offered, wasn't concerned. Third, as service quality was estimated by general service quality, the research in future should subdivide service quality more. I, finally, applied the pervious researches on job satisfaction and service quality in the employee of Family Restaurant. To extend more this research model in future, the variables like customer satisfaction should be added.

• Asia pacific journal of information systems
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• v.23 no.3
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• pp.131-154
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• 2013

New internet technologies have created a revolutionary new platform which allows consumers to make decision about product price and quality quickly and provides information about themselves through the transcript of online reviews. By expressing their feelings toward products or services on virtual opinion platforms, users extend their influence into cyberspace as electronic word-of-mouth (e-WOM). Existing research indicates that an impact of eWOM on the consumer decision process is influential. For both academic researchers and practitioners, investigating this phenomenon of information sharing in online website is essential given the increasing number of consumers using them as sources of purchase decisions. It is worthwhile to examine the extent to which opinion seekers are willing to accept and adopt online reviews and which factors encourage adoption. Discerning the most motivating aspects of information adoption in particular, could help electronic marketers better promote their brand and presence on the internet. The objectives of this study are to investigate how online WOM influences a persons' purchase decision by discovering which factors encourage information adoption. Especially focused on the self-efficacy, this research investigates how self-efficacy affects on information usefulness and adoption of online information. Although people are exposed to same review or comment about product or service, some accept the reviews while others do not. We notice that accepting online reviews mainly depends on the person's preference or personal characteristics. This study empirically examines this issue by using cognitive dissonance theory. Specifically, in the movie industry, we address few questions-is always positive WOM generating positive effect? What if the movie isn't the person's favorite genre? What if the person who is very self-assertive so doesn't take other's opinion easily? In these cases of cognitive dissonance, is always WOM generating same result? While many studies have focused on one direct of WOM which indicates positive (or negative) informative reviews or comments generate positive (or negative) results and more (or less) profits, this study investigates not only directional properties of WOM but also how people change their opinion towards product or service positive to negative, negative to positive through the online WOM. An experiment was conducted quantitatively by using a sample of 168 users who have experience within the online movie review site, 'Naver Movie'. Users were required to complete a survey regarding reviews and comments taken from the real movie page. The data reflected user's perceptions of online WOM information that determined users' adoption level. Analysis results provide empirical support for the proposed theoretical perspective. When user can't agree with the opinion of online WOM information, in other words, when cognitive dissonance between online WOM information and users' preference occurs, perceived self-efficacy significantly decreases customers' perception of usefulness. And this perception of usefulness plays an important role in determining users' intention to adopt online WOM information. Most of researches have been concentrated on characteristics of online WOM itself such as quality or vividness of information, credibility of source and direction of online WOM, etc. for describing effect of online WOM, but our results suggest that users' personal character (e.g., self-efficacy) plays decisive role for acceptance of online WOM information. Higher self-efficacy means lower possibility to accept the information that represents counter opinion because of cognitive dissonance, whereas the people that have lower self-efficacy are willing to accept the online WOM information as true and refer to purchase decision. This study suggests a model for understanding role of direction of online WOM information. Also, our result implicates the importance of online review supervision and personalized information service by confirming switching opinion negative to positive is more difficult than positive to negative through the online WOM information. This implication would help marketers to manage online reviews of their products or services.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.69-85
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• 2016

Successful relationship with loving partners is one of the most important factors in life. In psychology, there have been some previous researches studying the factors influencing romantic relationships. However, most of these researches were performed based on statistical analysis; thus they have limitations in analyzing complex non-linear relationships or rules based reasoning. This research analyzes commitment and persistence in heterosexual involvement according to styles of loving using a datamining technique as well as statistical methods. In this research, we consider six different styles of loving - 'eros', 'ludus', 'stroge', 'pragma', 'mania' and 'agape' which influence romantic relationships between lovers, besides the factors suggested by the previous researches. These six types of love are defined by Lee (1977) as follows: 'eros' is romantic, passionate love; 'ludus' is a game-playing or uncommitted love; 'storge' is a slow developing, friendship-based love; 'pragma' is a pragmatic, practical, mutually beneficial relationship; 'mania' is an obsessive or possessive love and, lastly, 'agape' is a gentle, caring, giving type of love, brotherly love, not concerned with the self. In order to do this research, data from 105 heterosexual couples were collected. Using the data, a linear regression method was first performed to find out the important factors associated with a commitment to partners. The result shows that 'satisfaction', 'eros' and 'agape' are significant factors associated with the commitment level for both male and female. Interestingly, in male cases, 'agape' has a greater effect on commitment than 'eros'. On the other hand, in female cases, 'eros' is a more significant factor than 'agape' to commitment. In addition to that, 'investment' of the male is also crucial factor for male commitment. Next, decision tree analysis was performed to find out the characteristics of high commitment couples and low commitment couples. In order to build decision tree models in this experiment, 'decision tree' operator in the datamining tool, Rapid Miner was used. The experimental result shows that males having a high satisfaction level in relationship show a high commitment level. However, even though a male may not have a high satisfaction level, if he has made a lot of financial or mental investment in relationship, and his partner shows him a certain amount of 'agape', then he also shows a high commitment level to the female. In the case of female, a women having a high 'eros' and 'satisfaction' level shows a high commitment level. Otherwise, even though a female may not have a high satisfaction level, if her partner shows a certain amount of 'mania' then the female also shows a high commitment level. Finally, this research built a prediction model to establish whether the relationship will persist or break up using a decision tree. The result shows that the most important factor influencing to the break up is a 'narcissistic tendency' of the male. In addition to that, 'satisfaction', 'investment' and 'mania' of both male and female also affect a break up. Interestingly, while the 'mania' level of a male works positively to maintain the relationship, that of a female has a negative influence. The contribution of this research is adopting a new technique of analysis using a datamining method for psychology. In addition, the results of this research can provide useful advice to couples for building a harmonious relationship with each other. This research has several limitations. First, the experimental data was sampled based on oversampling technique to balance the size of each classes. Thus, it has a limitation of evaluating performances of the predictive models objectively. Second, the result data, whether the relationship persists of not, was collected relatively in short periods - 6 months after the initial data collection. Lastly, most of the respondents of the survey is in their 20's. In order to get more general results, we would like to extend this research to general populations.

• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.99-108
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• 2008

To extend our detailed knowledge for the Hwasan caldera, we carried out magnetotelluric (MT) survey, which is pretty sensitive to electrical property variation in both horizontal and vertical direction of subsurface, across the Hwasan caldera with the direction of EW. The 2-D inversion results of observed MT data lead to following conclusions. Firstly, the depth of the basin basement inferred by the MT inversion results matches well with that suggested by previous potential studies, but the basement resistivity seems fairly low when compared to that of general case. This feature might be related with the large-scaled, highly conductive layer beneath the Euisung Sub-basin suggested by the previous MT study. Secondly, the high resistivity zones reaching to 4000 $\Omega{\cdot}m$ are imaged around two external ring fault boundaries. These zones are thought of as the response of the rhyolitic dykes intruding along the ring fault, and in the previous gravity data correspond to relatively high density anomalies. Thirdly, low resistivity zone reaching to 200 $\Omega{\cdot}m$ is detected around a depth of 1km beneath the central part of the caldera, which has not been yet reported in korean geophysical literatures. If we take account of the evolution model of the Hwasan caldera, this zone is regarded as the past sedimentary layer that subsided during the period of forming external ring fault system. In addition, the relatively low density anomaly observed in the central part of the caldera may be attributed to this sedimentary layer.

• Economic and Environmental Geology
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• v.31 no.3
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• pp.185-199
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• 1998

Hydrogeochemical and environmental isotope studies were undertaken for various kinds of water samples collected in 1995-1996 from the Bugok geothermal area. Physicochemical data indicate the occurrence of three distinct groups of natural water: Group I ($Na-S0_4$ type water with high temperatures up to $77^{\circ}C$, occurring from the central part of the geothermal area), Group II (warm $Na-HCO_{3}-SO_{4}$ type water, occurring from peripheral sites), Group III ($Ca-HCO_3$ type water, occurring as surface waters and/or shallow cold groundwaters). The Group I waters are further divided into two SUbtypes: Subgroup Ia and Subgroup lb. The general order of increasing degrees of hydrogeochemical evolution (due to the degrees of water-rock interaction) is: Group III$\rightarrow$Group II$\rightarrow$Group I. The Group II and III waters show smaller degrees of interaction with rocks (largely calcite and Na-plagioclase), whereas the Group I waters record the stronger interaction with plagioclase, K-feldspar, mica, chlorite and pyrite. The concentration and sulfur isotope composition of dissolved sulfate appear as a key parameter to understand the origin and evolution of geothermal waters. The sulfate was derived not only from oxidation of sedimentary pyrites in surrounding rocks (especially for the Subgroup Ib waters) but also from magmatic hydrothermal pyrites occurring in restricted fracture channels which extend down to a deep geothermal reservoir (typically for the Subgroup Ia waters). It is shown that the applicability of alkaliion geothermometer calculations for these waters is hampered by several processes (especially the mixing with Mg-rich near-surface waters) that modify the chemical composition. However, the multi-component mineral/water equilibria calculation and available fluid inclusion data indicate that geothermal waters of the Bugok area reach temperatures around $125^{\circ}C$ at deep geothermal reservoir (possibly a cooling pluton). Environmental isotope data (oxygen-18, deuterium and tritium) indicate the origin of all groups of waters from diverse meteoric waters. The Subgroup Ia waters are typically lower in O-H isotope values and tritium content, indicating their derivation from distinct meteoric waters. Combined with tritium isotope data, the Subgroup Ia waters likely represent the older (at least 45 years old) meteoric waters circuated down to the deep geothermal reservoir and record the lesser degrees of mixing with near-surface waters. We propose a model for the genesis and evolution of sulfate-rich geothermal waters.

• Korean Journal of Remote Sensing
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• v.12 no.2
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• pp.139-154
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• 1996

In order to evaluate the sensor`s look direction bias in the Landsat TM image and to estimate trends of primary geological lineaments, we have attempted to systematically compare lineaments in TM image, relief shadowed DEM's, and actual lineaments of geologic and topographic map through the Hough transform technique. Hough transform is known to be very effective to estimate the trend of geological lineaments, and help us to obtain the true trends of lineaments. It is often necessary to compensate the preferential enhancements of terrain lineaments in a TM image occurred by to look direction bias, and that can be achieved by utilizing an auxiliary data. In this study, we have successfully adopted the relief shadowed DEM in which the illuminating azimuth angle is perpendicular to look direction of a TM image for assessing true trends of geological lineaments. The results also show that the sum of four relief shadowed DEM's directional components can possibly be used as an alternative. In Euiseong-gun area where Sindong Group and Mayans Group are mainly distributed, geological lineaments trending $N5^{\circ}$~$10^{\circ}$W are dominant, while those of $N55^{\circ}$~$65^{\circ}$ W are major trends in Cheongsong-gun area where Hayang Group, Yucheon Group and Bulguksa Granite are distributed. Using relief shadowed DEM as an auxiliary data, we found the $N55^{\circ}$~$65^{\circ}$ W lineaments which are not cleanly observed in TM image over Euiseong-gun area. Compared with the trend of Gumchon and Gaum strike-slip faults, these lineaments are considered to be an extension of the faults. Therefore these strike-slip faults possibly extend up to Sindong Group in the northwest parts in the study area.

• Journal of the Daesoon Academy of Sciences
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• v.45
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• pp.37-67
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• 2023

This paper aims to examine the loyalty and filial piety pursued by Taoists, focusing on the concept of loyalty and loyalty shown in Wenchang Filial Piety Classic and General Collection of Jingming on Loyalty and Filial Piety. After the Han Dynasty, the concept of loyalty and filial piety became the representative virtues that led the country and society to follow the ideology of Confucius as the dominant ideology. This applied to everyone from emperor to each individual. Taoism had different reasons for promoting the concept of loyalty and filial piety and these even varied from sect to sect, but generally, Taoism could also be said to emphasize loyalty and filial piety. Depending on the sect of Taoism, filial piety might be valued on its own or filial piety might be valued in conjunction with loyalty. In particular, defining Taoism was criticized for "forgetting the desirable behavior required in the human network of the world and severing relationships with various objects encountered in life." In this respect, the concept of loyalty and filial piety in General Collection of Jingming on Loyalty and Filial Piety, could be observed to emphasize 'filial piety' in conjunction with 'loyalty', and this shows the influence of Confucius' concept of loyalty and filial piety. At the same time, this shows the concept of loyalty and filial piety as reimagined by Taoism. The most fundamental aim of Taoism is to pursue immortality. However, as a prerequisite for becoming such a god, loyalty and filial piety, were practiced alongside 'gentleness' and 'humanity and trustworthiness.' Here, the Taoist emphasis on 'loyalty and filial piety', 'gentleness', and 'humanity and trustworthiness' is essentially the same as in Neo-Confucianism. However, seeking to become an immortal through these values represents a motivation that is different from Neo-Confucians who denied the pursuit of immortality. In this paper, loyalty and filial piety as understood and practiced by Neo-Confucian scholars will be compared with the same concepts in the Taoist context and the findings will be summarized via three categories. First, in the Taoist model longevity and the pursuit of immortality are seen as being closely related to filial piety. The reason why achieving longevity and pursuing immortality was considered closely related to filial piety is because this is a modified and enhanced reimagining of the Neo-Confucianist concept of loyalty and filial piety. The other is that Taoism's concept of loyalty and filial piety is richly supplemented with content about 'interactions between heaven and humankind.' When filial piety is practiced in this context, the principle of responding to the gods of heaven and earth is emphasized. At the same time, Taoism presents consequences for insufficient filial piety to parents or insufficient loyal to the king; disasters will be brought down by heaven. Finally, it is argued that the practice filial piety is necessary and should extend not only to parents to all phenomena in the world without distinguishing based on one's degree of intimacy to those phenomena.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.