• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.

• Journal of the Korea Furniture Society
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• v.27 no.3
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• pp.237-245
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• 2016

Single households currently account for 26.5% of all households and their number is expected to continue to rise, reaching 34.5% by 2035. An analysis of the consumption trends and needs of single households shows that they are rising as a new consumer group with a focus on investment on the individual and favouring: small but high-tech products: efficient use of limited resources: safety and peace of mind: self-improvement and leisure. Products which meet such demands are having an impact on the growth of home-furnishing market. An analysis of companies in Korea's home-furnishing market, with examples like the lifestyle company IKEA, shows a variety of brands such as SPA brand, furniture specialist, distributor and character products. And yet most are OEM products which lack differentiated product lines and compete with similar display and distribution structure. We needs the Single household consumption tendency of home-furnishing market and differentiation strategy through product analysis. In order to increase the value of companies in the home-furnishing market, in addition to differentiated design, product competitiveness must aspire to higher customer satisfaction with easy assembly, innovation in logistics, innovative sales methods such as virtual-reality simulation for products and space, individually-tailored furniture for the needs of single household and products which combine smart technology. For home-grown home-furnishing brands to have competitiveness, they must leverage on the strengths of the industry, offering differentiated and competitive products in a wider range of areas with convergence functions as well as differentiation in consumer interface and application of advancing technology; in-depth product research is called for.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Asia Marketing Journal
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• v.11 no.1
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• pp.1-27
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• 2009

The research compared the motivational network of traits predictive of complaint attitudes across consumers in the U.S. and South Korean cultures. Overall, the results revealed a similar pattern of traits predictive of complaint attitudes in the two cultures. The traits of value consciousness, general self-efficacy, emotional instability, and the need for material resources were positively related to attitudes toward complaining. In contrast, conscientiousness was negatively related to complaint attitudes. The only trait predictor of complaining attitude that was significantly different between the Korean and U.S. samples was shopping enjoyment. It was negatively related to complaining attitude in the U.S. sample but unrelated to complaining attitude in the Korean sample. Understanding the personality traits predictive of complaint attitudes has the potential to help marketers develop messages that will encourage the low complaint prone to voice their dissatisfaction. This is important, because when a consumer complains about and unsatisfactory purchase, it gives the firm a chance to take actions to avoid losing a customer.

• Journal of the Korea Society for Simulation
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• v.24 no.3
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• pp.27-35
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• 2015

We analyze an M/G/1/K queueing system with queue-length dependent service and arrival rates. There are a single server and a buffer with finite capacity K including a customer in service. The customers are served by a first-come-first-service basis. We put two thresholds $L_1$ and $L_2$($${\geq_-}L_1$$ ) on the buffer. If the queue length at the service initiation epoch is less than the threshold $L_1$, the service time of customers follows $S_1$ with a mean of ${\mu}_1$ and the arrival of customers follows a Poisson process with a rate of ${\lambda}_1$. When the queue length at the service initiation epoch is equal to or greater than $L_1$ and less than $L_2$, the service time is changed to $S_2$ with a mean of $${\mu}_2{\geq_-}{\mu}_1$$. The arrival rate is still ${\lambda}_1$. Finally, if the queue length at the service initiation epoch is greater than $L_2$, the arrival rate of customers are also changed to a value of $${\lambda}_2({\leq_-}{\lambda}_1)$$ and the mean of the service times is ${\mu}_2$. By using the embedded Markov chain method, we derive queue length distribution at departure epochs. We also obtain the queue length distribution at an arbitrary time by the supplementary variable method. Finally, performance measures such as loss probability and mean waiting time are presented.

• KSBB Journal
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• v.24 no.2
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• pp.156-162
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• 2009

We examined saury, herring, gizzard shad kwamaegi to measure of microbic contamination rate of kwamegi that are sold in the market now. In the total bacteria, staphylococcus, peroxide value, and microorganisms is inhibited that from sample that we treated a substance with chitosan-ascorbate (CA) and other orders deep water (DW), ginseng steamed red and wine (GRW), NT (not treated). When we compared between SGRW and SNT, SCA show us more inhibition effect 0.22-0.49 log cycle in the total aerobacter. When we compared between HDW and HNT, HCA restraint 0.05-0.45log cycle, and when we compared between GDW and GNT, GCA inhibited 0.45 log cycle. In the coliform and E. coli, growths of microorganisms were inhibited followed order by treatment of CA, NT, and DW. GDW, HCA and HNT checked enough amount of water from the moisture measurement; but SGW, GCA, HEW and SCA showed 7-15% lack of moisture, and SNT and GNT have 10% more moisture. Peroxide value is changed to 41-51meq/kg when we did treat CA in there and a side that didn't add antimicrobial expressed the result numerically that 56-58meq/kg. In the sensory evaluation, customer gave preference to followed by Saury kwamaegi, herring, and gizzard shad kwamaegi. We have a point of view when kwamaeki manufactured if we add natural antibiotic and it uses to vacuum drying, we would inhibited of multiplication of microorganism, and of peroxides.

• Journal of Nutrition and Health
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• v.53 no.4
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• pp.431-444
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• 2020

Purpose: The purposes of this study were to understand the health interest of consumers in the United States and Japan and thus understand the motivation of food choices, in order to provide basic data on the country's strategy based on healthy and correct food choices in the future. Methods: A customer survey was conducted in 2019 from October 18 to 31, and it targeted 115 American and 120 Japanese local consumers between the ages of 20- to 64-years-old. Eight questions were formed using General Health Interest. Based on food choice motivation, 27 questions were reconstructed and asked about demographic information. All data were analyzed by SPSS Statistics (ver. 25). Results: Health consciousness was categorized into 2 types: nutrition-seeking type and preference-seeking type. Based on these 2 factors, customers were grouped into 3 clusters: healthy dietary life-seeking group, nutrition balance-seeking group and health indifference group. Food choice motivation was categorized into 4 types: health, efficiency, value, and mood. All 3 groups showed a high tendency for efficiency in common. The results show that consumers want higher satisfaction with their time and money invested in food consumption. It is believed that the focus and investment of market segmentation strategy should be focused on product development, especially for American and Japanese consumers who are interested in health. Conclusion: The results of this study reflect consumer needs that can assist in the selection of healthy and correct foods in the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.27-42
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• 2020

Startup accelerators have emerged as new investment entities that help early startups, which are not easy to survive continuously due to lack of funds, commercialization capabilities, and experiences. As their positive performance on early startups and the ecosystem has been proven, the number of early startups which want to receive their investment is also increasing. However, they are vaguely preparing to attract accelerators' investment because they do not have any information on what factors the accelerators consider important. In addition, researches on startup accelerators are also at an early level, so there are no remarkable prior studies on factors that decide on investment. Therefore, this study aims to help startups prepare for investment attraction by looking at what factors are important for accelerators to invest, and to provide meaningful implications to academia. In the preceding study, we derived five upper level categories, 26 lower level accelerators' investment determinants through the qualitative meta-synthesis method, secondary data analysis, observation on US accelerators and in-depth interviews. In this study, we want to derive important implications by deriving priorities of the accelerators' investment determinants. Therefore, we used AHP that are evaluated as the suitable methodology for deriving importance and priority. The analysis results show that accelerators value market-related factors most. This means that startups that are subject to investment by accelerators are early-stage startups, and many companies have not fully developed their products or services. Therefore, market-related factors that can be evaluated objectively seem to be more important than products (or services) that are still ambiguous. Next, it was found that the factors related to the internal workforce of startups are more important. Since accelerators want to develop their businesses together with start-ups and team members through mentoring, ease of collaboration with them is very important, which seems to be important. The overall priority analysis results of the 26 investment determinants show that 'customer needs' and 'founders and team members' understanding of customers and markets' (0.62) are important and high priority factors. The results also show that startup accelerators consider the customer-centered perspective very important. And among the factors related to startups, the most prominent factor was the founder's openness and execution ability. Therefore, it can be confirmed that accelerators consider the ease of collaboration with these startups very important.

• Asia Marketing Journal
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• v.12 no.2
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• pp.27-52
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• 2010

It is not new that today's business organizations are expected to exhibit ethical and moral management and to carry out social responsibility as a good corporate citizen. Since South Korea emerged as a newly industrialized country during the 1980s, Korean corporations have become active in carrying out their social responsibility as a good corporate citizen to society. In spite of the short history of corporate social responsibility, Korean companies have actively participated in corporate philanthropy. Corporations' significant donations to various social causes, no-lay-off policies, corporate volunteerism and green marketing are evidences of their commitment to corporate citizenship. Corporate social responsibility is now an essential management practice whereby corporation can strengthen its sustainable value creation processes by enhancing the trust assets underlying the relationships between the business and the stakeholders. Much of the conceptual work in the area of corporate social responsibility(CSR) has originated from researches conducted in the management field. Carroll(1979) proposed that corporations have four types of social responsibilities: economic, legal, ethical and philanthropic responsibility. Most past research has investigated CSR and its impact on consumers' attitudes toward the corporations and corporate performances. Although there exists a large body of literature on how consumers perceive and respond to CSR, the majority of past studies were conducted in the United States. The stability and applicability of past findings need to be tested across different national/cultural settings, especially since corporate social responsibility is a reflection of implicit conformation with the expectations and criticism that society may have toward a corporation(Matten and Moon, 2004). In this study, we explored whether people in Korea perceive CSR of Korean corporations in the same four dimensions as done in the United States and what were the measurement items tapping each of these four dimensions. In order to investigate the dimensions of CSR and the measurement items for CSR perceived by Korean people, nine focus group interviews were conducted with several stakeholder groups(two with undergraduate students, two with graduate students, three with general consumers, and two with NGO groups). Scripts from the interviews revealed that the Korean stakeholders perceived four types of CSR which are the same as those proposed by Carroll(1979). However we found CSR issues unique to Korean corporations. For example for the economic responsibility, Korean people mentioned that the corporation needed to contribute to the economic development of the country by generating corporate profits. For the legal responsibility, Koreans included the "corporation need to follow the consumer protection law." For the ethical responsibility, they considered that the corporation needed to not promote false advertisement. In addition, Koreans thought that an ethical company should do transparent management. For the philanthropic responsibility, people in Korea thought that a corporation needed to return parts of its profits to the society for the betterment of society. The 28 items were developed based on the results of the nine focus group interviews, while considering the scale developed by Maignan and Ferrell(2001). Following the procedure proposed by Churchill(1979), we started by developing an item poll consisting of 28 items and purified the initial pool of items through exploratory, confirmatory factor analyses. 176 samples were sued for this analysis. Confirmatory factor analysis was performed on the 28 items in order to verify the underlying four factor structure. Study 1 provided new measurement items for tapping the Korean CSR dimensions, which can be useful for the future studies exploring the effects of CSR on Korean consumers' attitudes toward the corporations and corporate performances. And we found the CSR scale(17 items) has good reliability, discriminant validity and nomological validity. Economic Responsibility: "XYZ company continuously improves the quality of our products", "XYZ company has a procedure in place to respond to customer complaint", "XYZ company contributes to the economic development of our country by generating profits", "XYZ company is eager to hire people". Legal Responsibility: "XYZ company's products meet legal standards", "XYZ company seeks to comply with all laws regulating hiring and employee benefits", "XYZ company honors contractual obligations to its suppliers", "XYZ company's managers try to comply with the law related to the business operation". Ethical Responsibility: "XYZ company has a comprehensive code of conduct", "XYZ company does not promote a false or misleading advertisement", "XYZ company seems to conduct a transparent business", "XYZ company does a fair business with its suppliers or sub-contractors". Philanthropic Responsibility: "XYZ company encourages partnerships with local businesses and schools", "XYZ company supports sports and cultural activities", "XYZ company gives adequate contributions to charities considering its business size", "XYZ company encourages employees to support our community". Study 2 was condusted for comprehensive validity. 655 samples were used for this anlysis. Collected samples were tested by factor analysis and Crnbach's Alpha coefficiednts and were found to be satisfactory in terms of validity and reliability. Furthermore, fitness of the measurement model was tested by using conformatory factor analysis. χ²=880.73(df=160), GFI=0.891, AGFI=0.854, NFI=0.908, NNFI=0.913, RMR=0.059, RMESA=0.070. We hope that CSR scale could greatly facilitate research on Corporate social resposibility, it is by no means the final answer.

• Journal of Distribution Science
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• v.7 no.4
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• pp.47-56
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• 2009

The purpose of this study is to present an alternative improving the efficient and reasonable of the physical distribution system management is influenced by many factors. Therefore, the study depends on the documentary method and survey method to achieve the purpose of this study. The major components of a physical distribution system are refers to as elements, include warehouse·storage system, transportation system, inventory system, physical distribution information system. The factors used in this study are ① factor of product(quality·A/S·added value of product·adaption of product·technical competitive power to other enterprises), ② factor of market(market channel·kinds of customer·physical distribution share), ③ factor of warehouse·storage(warehouse design·size·direction·storage ability·warehouse quality), ④ factor of transportation(promptness·reliability·responsibility·kinds of transportation·cooperation united transportation system·national transportation network), ⑤ factor of packaging (packaging design·material·educating program·pollution degree measure program), ⑥ factor of inventory(ordinary inventory criterion·consistence for inventories record), ⑦ factor of unloaded(unloaded machine·having machine ratio), ⑧ factor of information system (physical distribution quantity analysis·usable computer part), ⑨ factor of physical distribution cost(sales ratio to product) ⑩ factor of physical distribution system(physical distribution center etc). The implication of this study can be summarized as follows: ① In firms that have not adopted a systems integrative approach, physical distribution is a fragmented and often uncoordinated set of activities spread throughout various functions with function having its own set of priorities and measurements. ② The physical distribution is recognized as more an important strategic factor than a simple cost reduction factor, ③ It can be used a strategic competition tool to enterprise.