• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.58-69
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• 2022

This study compares and analyses the impacts of holding domestic garden expos that will be fundamental for holding garden expos in the future. Satisfaction with the three sites of the 2013 Suncheon Bay International Gardening Expo, 2015 Seoul Gardening Expo, and 2022 Goyang International Flower Fair, as well as factors affecting the satisfaction in economic, social/cultural, environment/ecology, and operation aspects, were analyzed. As a result of the study, the satisfaction level of all three sites was high, with a value of 3.5 or higher. In particular, satisfaction with the 2013 Suncheon Bay International Gardening Expo was the highest. It was found that there was a difference between the satisfaction level of the 2013 Suncheon Bay International Gardening Expo and the 2015 Seoul Gardening Expo. As a regional festival, the 2013 Suncheon Bay International Garden Expo has acquired a high status due to the 'Suncheon Bay Garden' being designated as the first National Garden. It is thought that great satisfaction was obtained because economic, social, cultural, and environmental revitalization was achieved by matching the values of citizen participation and ecological conservation. As a result of the comparison of perception types affecting the satisfaction by garden fair, satisfaction at the 2013 Suncheon Bay International Gardening Expo and the 2015 Seoul Gardening Expo, it was found that both affected all four aspects. The 2022 Goyang International Flower Fair did not affect satisfaction in the operational aspect. This seems to be because the Goyang International Flower Fair is already a fixed local brand. As a result of analyzing the detailed factors of perception that affect satisfaction, the three target sites were commonly analyzed, including social and cultural factors, which attract cultural events, improve pride and affection for the region, and help educate children. In terms of environmental and ecological factors were analyzed as an inconvenience in life due to traffic congestion. It can be seen that it has the same meaning as the comparative analysis of the difference in factors on the satisfaction of the target site. There is no difference in the effect on satisfaction in terms of social·cultural, and environmental·ecological aspects, but there are differences in terms of economy and operation. Based on the analysis results of this study, to hold a domestic garden expo in the future, it is necessary to properly utilize "environmental" and "ecological" garden aspects that have potential values according to the region's characteristics to develop sustainable, eco-friendly tourism resources. In addition, values will be more apparent when cultural and artistic programs are planned to establish a differentiated identity in the host area and are appropriately used as a marketing means for a local fair. A well-planned local festival through communication with local residents can affect the image of the region and lead to the revitalization of the local communities by securing urban competitiveness along with the establishment of urban brands, so it can be said that local residents' participation and national or local organizations' cooperation is essential.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Korean Ophthalmic Optics Society
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• v.19 no.3
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• pp.323-329
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• 2014

Purpose: To understand the pattern of prescribing contact lenses in Korea from 2010 to 2013. Methods: Four hundred survey questionnaires were randomly posted to Korean Optometric clinics for 4 years. The questionnaire was the same form as a form used for International Contact Lens Prescribing Trend. It was also designed to collect information about the contact lenses prescribed to the first 10 patients after its receipt. Results: 1937 fits were used for the analysis among the four hundred survey questionnaires. The average patient age was $26.2{\pm}7.0$ in 2010, $26.1{\pm}7.6$ in 2011, $24.7{\pm}6.6$ in 2012 and $24.8{\pm}7.2$ in 2013. The patients were mainly women (75%). Of all the soft contact lenses, silicon hydrogel lenses were 18% of fits (17% in 2010, 10% in 2011, 20% in 2012, 24% in 2013). By degine, the percentage of toric design lenses accounted for 17% of soft lenses fits and had increased during 4 years (10% in 2010, 18% in 2011, 16% in 2012, 22% in 2013), and cosmetic contact lens made up for 29% (15% in 2010, 20% in 2011, 40% in 2012, 41% in 2013). Conclusions: The contact lenses wearers were mostly women and the average patient age becomes slightly younger. In relation to the increase in the mumber of younger female contact lens wearers,the percentage of cosmetic lenses prescription was much higher (29%) than the global average (7%), and it has gradually increased for last 4 years. This trend could be related to the growth of beauty market in Korea. By emphasizing on toric lens marketing in manufactures, the prescription rate has been gradually increased.

• The Journal of Industrial Distribution & Business
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• v.2 no.2
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• pp.25-38
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• 2011

After the financial crisis, what has been the rapidly growth of large supermarkets, stores, and restaurants linked to concerns that have already reached saturation point, but the new opening large supermarkets is expected to continue into the future. The major supermarkets are continue to grow outward but growth slowed. And that is expected to continue differentiation of the product, acceptance the customer needs, acquiring high margin of sales products. Then the ongoing development of PB brand is to be positioned effective marketing strategy for overcoming the period of slow growth. In addition, big three local supermarkets continue to launch a clothing PB brand, expansion and operation strategy for the situation and based on this study and the success of the domestic large-Mart's PB and PB identifying problem and the need for differentiation and profit for the successful strategy is to discuss in this study. This research looks at the concept of major market's private brand, the strategy, the success example and the prospects, and views the globally rapid-growing private brands, not only having the limited role of distributing the products as retailers, but also having a control of the distribution channel as a manufacturing company. World's major advanced distribution companies, to differentiate their companies' products and increase the profitability, are putting a lot of efforts into private brand products, and there are many good examples that are globalizing, externally expanding, and creating high financial results. In this research, we presented three major domestic discount stores as examples to show that there is a need for a differentiated private brand management strategy in the saturated discount store industry in Korea. Also, we aim to provide a new product strategy for the future that has been saturated with discount stores to the limit, by providing suggestions that private brand products can be used as weapons with the strongest competiveness in the retail industry through pursuing store differentiations from thorough market analysis and product researches, meeting the customers' needs, and obtaining high margins. PB products, particularly clothing design, a thorough market analysis and product development trends and customer needs to reflect the acquisition of High margin differentiated powerful products and sustainable growth through the stores, large supermarkets, congested, a new breakthrough that can give a good opportunity to provide implications discount stores, new product strategy based on ways to limit proposed. This study discount the major three companies studied, the less strain is a generalization. In the future, domestic and local discount store brand PB, SPA brand that the multinational comparative analysis of the value of the PB expansion strategy centered on clothing, additional studies will be needed.

• Journal of Distribution Science
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• v.15 no.5
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• pp.75-83
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• 2017

Purpose - With the rise of the fourth industrial revolution, it has converged with the existing industrial revolution to give shape to increased accessibility of knowledge and information. As a result, it has become easier for scholars to actively persue and compile research in various fields. This current study aims to focus and assess the current standing of KODISA: the Journal of Distribution Science (JDS), International Journal of Industrial Distribution & Business(IJIDB), the East Asian Journal of Business Management (EAJBM), the Journal of Asian Finance, Economics and Business (JAFEB) in a rapidly evolving era. Novel strategies for creating the future vision of KODISA 2020 will also be examined. Research design, data, and methodology - The current research will analyze published journals of KODISA in order to offer a vision for the KODISA 2020 future. In part 1, this paper will observe the current address of the KODISA journal and its overview of past achievements. Next, part 2 will discuss the activities that will be needed for journals of KODISA, JDS, IJIDB, EAJBM, JAFEB to branch out internationally and significant journals will be statistically analyzed in part 3. The last part 4 will offer strategies for the continued growth of KODISA and visions for KODISA 2020. Results - Among the KODISA publications, IJIDB was second, JDS was 23rd (in economic publications of 54 journals), and EAJBM was 22nd (out of 79 publications in management field journals). This shows the high quality of the KODISA publication journals. According to 2016 publication analysis, JDS, IJIDB, etc. each had 157 publications, 15 publications, 16 publications, and 28 publications. In the case of JDS, it showed an increase of 14% compared to last year. Additionally, JAFEB showed a significant increase of 68%. This shows that compared to other journals, it had a higher rate of paper submission. IJIDB and EAJBM did not show any significant increases. In JDS, it showed many studies related to the distribution, management of distribution, and consumer behavior. In order to increase the status of the KODISA journal to a SCI status, many more international conferences will open to increase its international recognition levels. Second, the systematic functions of the journal will be developed further to increase its stability. Third, future graduate schools will open to foster future potential leaders in this field and build a platform for innovators and leaders. Conclusions - In KODISA, JDS was first published in 1999, and has been registered in SCOPUS February 2017. Other sister publications within the KODISA are preparing for SCOPUS registration as well. KODISA journals will prepare to be an innovative journal for 2020 and the future beyond.

• Cartoon and Animation Studies
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• s.20
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• pp.75-86
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• 2010

Recently, as the number of female players has increased rapidly, the electronic gaming industry has begun to look at ways to appeal to the largely untapped female market. According to the latest game market investigative report by China Internet Network Information Center (CNNIC), the total number of game players in China increased by 24.8% in 2009, reached 69,130,000 people, and 38.9% of them are female players. This growth in the number of female player is corroborated by a series of investigative reports from IResearch Company in Shanghai, China: from 2003 to 2009, the number of female players grew from 8% to more than 49%. Therefore, no matter how much attention the game production companies have given to male players or how they have ignored the female players before, the companies would be sensible to face up this reality and adjust their marketing policy a bit more. This article analyzes gender preferences in video games which shows that male players are more likely to be attracted to elements of aggression, violence, competition and fast action in electronic game-playing, while female players are drawn to emotional and social aspects of the games such as an understanding of character relationships. The literatures cited indicates that female players also show apparent preference for games with familiar environments, games that allow players to work together, games that have more than one way to win, and games in which characters do not die. It also discusses the characteristics of female-friendly games from the aspect of emotion, pointing out that the simulation games involving pet, dressing-up, and social simulation games are very popular with female players. Because these are the most suitable game types to fill with emotions of love, share, jealousy, superiority, mystery, these are absolutely attractive to female players. Finally, in accord with the above, I propose some principles of designing female-oriented games, including presenting a good-looking leading character, making the story interesting with "live" NPCs(Non-Playing Characters), and finding ways to satisfy female nature instincts such as taking care of others and the inborn interest of classifying and selecting.

• Science of Emotion and Sensibility
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• v.19 no.4
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• pp.21-32
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• 2016

Studies have observed various phenomena regarding the effect of the interaction between type, price, and brand image of a product on consumers' purchase intent and product quality perception. Yet, few have studied the effect of the interaction between product type and manufacturing method on these factors. However, the advent of three-dimensional (3D) printers added a new manufacturing method, 3D printing, to the traditional methods of handicraft and automated machine-based production, and research is necessary since this new framework might affect consumers' purchase intent and product quality perception. Therefore, this study aimed to verify the effects of the interaction between product type and manufacturing method on purchase intent and product quality perception. To achieve this, in our experiment 1, we selected product types with different characteristics (drone vs. violin vs. cup), and measured whether consumers preferred different manufacturing methods for each product type. The results showed that consumers preferred the 3D printing method for technologically advanced products such as drones, the handmade method for violins, and the automated machine-based manufacturing method, which allows mass production, for cups. Experiment 2 attempted to verify the effects of the differences in manufacturing method preferences for each product type on consumers' purchase intent and product quality perception. Our findings are as follows: for drones, the purchase intent was highest when 3D printing was used; for violins, the purchase intent was highest when the violins were handmade; for cups, the purchase intent was highest when machine-based manufacturing was used. Moreover, whereas the product quality perception for drones did not differ across different manufacturing methods, consumers perceived that handmade violins had the highest quality and that cups manufactured with 3D printing had the lowest quality (the purchase intent for cups was also lowest when 3D printing was used). This study is anticipated to provide a wide range of implications in various areas, including consumer psychology, marketing, and advertising.

• The Korean Journal of Community Living Science
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• v.16 no.4
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• pp.47-57
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• 2005

To investigate the characteristics of edible flowers as a food material, we have examined the kinds, colors, sizes, fresh weights, pigments and shipping periods of edible flowers marketed on the cropping farms, selling agencies and Internet shopping malls from February through September, 2005. Thirty six kinds of edible flowers were marketed in Korea, and all but the chrysanthemum were introduced species. The characteristics of edible flowers were shown differently by the varieties following the same kinds of flowers. Those colors were yellow (twenty five kinds), red (twenty three), pink (twenty), white (eighteen), and orange (sixteen). Flower diameters were measured and showed that seven kinds of edible flowers were 1.0 to 2.0cm, fourteen 2.0 to 3.0cm, sixteen 3.0 to 4.0cm, eight 4.0 to 5.0cm, and nine over 5.0cm. Flower fresh weights were measured as follows: twenty one kinds of edible flowers were under 0.5g ($58.3\%$), eight were $0.6\∼1.0g(22.2\%$), and six were $1.1{\∼}1.5g(16.7\%$). The taste of edible flowers was often bitter (twenty one kinds), sweet and sour (seven), somewhat fragrant (six), fishy (three), and others (nine). The pigments of edible flowers were anthoxanthin (twenty seven kinds), flavonoid (twenty three), carotenoid (seventeen), and betanidin (four).