• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.6
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• pp.609-616
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• 2016

This paper is proposed a customized market analysis method using SVM and collaborative filtering. The proposed customized market analysis scheme is consists of DC(Data Classification) module, ICF(Improved Collaborative Filtering) module, and CMA(Customized Market Analysis) module. DC module classifies the characteristics of on-line and off-line shopping mall and traditional markets into price, quality, and quantity using SVM. ICF module calculates the similarity by adding age weight and job weight, and generates network using the similarity of purchased item each users, and makes a recommendation list of neighbor nodes. And CMA module provides the result of customized market analysis using the data classification result of DC module and the recommendation list of ICF module. As a result of comparing the proposed customized recommendation list with the existing user based recommendation list, the case of recommendation list using the existing collaborative filtering scheme, precision is 0.53, recall is 0.56, and F-measure is 0.57. But the case of proposed customized recommendation list, precision is 0.78, recall is 0.85, and F-measure is 0.81. That is, the proposed customized recommendation list shows more precision.

• Journal of Distribution Science
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• v.15 no.12
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• pp.21-30
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• 2017

Purpose - This research approaches to the new niche market of medical tourism to investigate how factors of cultural similarity influence the international distribution management. This study also estimates the interaction effects of distribution channel on the relationships of facility attributes and customers' destination choice behavior. Research design, data, and methodology - We collected the sample of 881 potential customers from the more economically developed regions in China. Regression analysis is used to confirm the relationships in the research model. Results - The result shows that cultural similarity plays an important moderating role in the relationships of facility attributes and destination choice intention. For instance, power distance and masculinity interact with the distribution facility characteristics of medical quality and reputation to influence customers' selection of the destination country. Individualism, powder distance, and masculinity play moderating roles when social environment affects destination choice intention. Especially, all the elements of cultural similarity moderate the relationships between travel cost and destination choice intention. This research also proves that depending on distribution channel, determinants of distribution facility are the critical predictors of intention to select the medical service outside of China. Conclusions - The study enables managers to develop the more effective strategies reflecting the interaction effects of cultural similarity and distribution channel on customers' decision-making process.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.31-43
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• 2014

Large number of Android mobile application has been developed and deployed through the Android open market by increasing android-based smart work device users recently. But, it has been discovered security vulnerabilities on malicious applications that are developed and deployed through the open market or 3rd party market. There are issues to leak user's personal and financial information in mobile devices to external server without the user's knowledge in most of malicious application inserted Trojan Horse forms of malicious code. Therefore, in order to minimize the damage caused by malignant constantly increasing malicious application, it is required a proactive detection mechanism development. In this paper, we analyzed the existing techniques' Pros and Cons to detect a malicious application and proposed discrimination and detection result using malicious application discrimination mechanism based on Jaccard similarity after collecting events occur in real-time execution on android-mobile devices.

• Journal of Korea Port Economic Association
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• v.27 no.1
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• pp.155-183
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• 2011

The purpose of this paper is to analyze competition status of Korean and Chinese vessels in the EU market. To achieve this purpose, this study uses Market Share Index, Export Bias Index, Trade Specialization Index, Export Similarity Index, and Market Share Expansion Ratio-Export Similarity Deepening Ratio as analyzing method. The statistical data used in this study are obtained from the trade statistics for 5 years(2005-2009) produced by Korean International Trade Association. The results of this study show that Korean ships are less competitive than Chinese ones in the EU export market in that Korea does not export various kinds of ships but export some restricted kinds of vessels even in the competitive ship, implying that Korea has been gradually losing its competitiveness. These results suggest that Korea should improve the competitiveness of shipbuilding industry by pursuing such differentiated strategies as exporting high value-added vessels while keeping on maintaining Korea's dominance over its competitive ships to overcome China's competitive advantage in the EU region.

• Asia Marketing Journal
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• v.17 no.3
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• pp.73-103
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• 2015

According to Resource Dependence theory, an organization's behavior and strategy is affected by external resources. An organization has diverse resources interacting with environment. Because organization cannot focus on all those resources, it concentrates on its critical resources. In market environment, firm responds to other firms by controlling their internal critical resources or manages interdependency with environment to get market share. Thus Firm should choose best behavior and strategy when internal and external resources are change. When new brand enters, incumbents might change their strategy to protect their market share depending on critical value. More precisely, incumbents sharing market with entrant respond, but incumbents having competitive internal resources do not. In this article, we study incumbent's responses to a new brand entry and long-term effect. We show that how incumbents change their price strategy in reaction to the new brand' entry and also show these responses vary depending on interdependency of internal resources and external environments and ownership.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.2
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• pp.212-223
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• 2004

The purpose of this study is 1) to identify Chinese environment for investment and apparel market, 2) to analyze the current situations of Korean fashion brands＇entry to Chinese market, 3) to analyze the marketing strategies to China according to product category, and 4) to identify merits and problems of Chinese market. For data collection, secondary resources were collected, and the telephone interview with merchandisers were implemented with brand managers. Twenty-one fashion brands were included for the study. Results of the study were as followed： 1) China was a big potential apparel market due to its rapid economic growth. Apparel purchase behavior and clothing preference of Chinese consumers were various by regional groups. 2) The motives of entry to China were to competition in domestic markets, saving raw material cost. The entry modes to China were direct export, license and regional manufacturing system. 3) Marketing strategies were to pursue high quality branding, high pricing and placing strategies with high-class department stores. Also star marketing were used with ＂Han Rue＂. Also various promotion strategies were implemented such as fashion show and unique VMD. 4) The merits of Chinese market were high potential market for export, close proximity, cultural similarity and Han-Ryu syndrome. Problems of Chinese market for export were lack of experts on Chinese market, fierce competition in China, and unstable economic policies.

• Journal of Korea Trade
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• v.26 no.4
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• pp.63-82
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• 2022

Purpose - Drawing on relational institutional theory, we explored how demographic similarity between board members of a firm and newly emerged political elites led to firms' increased financial resource acquisition such as leverage ratio and decreased export intensity amidst the Asian financial crisis. We also studied how a firm's leverage ratio and export intensity can further affect firm profitability and financial credit rating. Design/methodology - We revisited and explored a unique, unprecedented crisis that affected most Korean firms: the Asian financial crisis that coincided with a governmental shift from a conservative to a liberal party. We collected demographic information from 432 listed Korean firms' board members and 43 political elites of the Blue House from 1998-2000 to create a demographic similarity measurement. We collected firms' financial information, built panel data, and used ordinary least squares regression to test our theory. Findings - Our results showed that demographic similarity between a firm's directors and newly emerged politicians had a positive association with a firm's leverage ratio but a negative association with a firm's export intensity. A firm's leverage ratio had a negative relationship with firm performance measured by firm profitability and financial credit rating. A firm's export intensity showed a positive effect on firm performance. Originality/value - We highlighted that during an economic crisis that coincided with a governmental shift and change of leading political actors, firms exerted efforts to survey the environment and build new external stakeholder relationships to cope with the changing landscape. We proposed that in an emerging market like Korea where low levels of trust and favoritism are prevalent across society, one of the relational institutional strategies that firms can employ is the selection of directors with similar demographic characteristics to political elites based on factors including birthplace and school affiliations. We examined the efforts of firms to build political networks with newly empowered political elites during a financial crisis, and the consequences of establishing such networks. We highlighted that during a financial crisis, the demographic similarity between a firm's board members and newly emerged politicians can provide firms with access to financial resources but can also result in poor management and reduced effort to enhance its international competitiveness.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• The Research Journal of the Costume Culture
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• v.25 no.1
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• pp.32-47
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• 2017

As the popularity of Korean drama and celebrities in China, Korean fashion is becoming increasingly popular in the Chinese market. Although the effect of Korean drama on Chinse consumers' attitudes toward Korean products are known, little research has been conducted to understand the mechanisms underlying the impact of Korean drama on the development of consumer attitudes. Thus, this study examines how Chinese consumers' exposure to Korean dramas has influenced their attitudes towards Korean fashion products. Applying the similarity-attraction theory, the study explores the roles Chinese consumers' perceived similarities in appearance and values with Korean characters in TV dramas plays in the process of attitude development. Data was collected via an online survey and the responses of 317 Chinese consumers in their twenties were used for data analysis. The results of structural equation modeling show that exposure to Korean dramas has a direct impact on Chinese consumers' perceived appearance similarity, perceived value similarity, image of Korean people, and attitudes toward Korean fashion products-results that support the theory of mere exposure. In addition, the analysis demonstrates that perceived appearance similarity positively influences the image of Koreans among Chinese people, which, in turn, influences attitudes toward Korean fashion products, supporting the similarity-attraction theory. However, the effect of perceived value similarity on attitude toward Korean fashion products was not significant. The study concludes by describing its practical implications for the Korean fashion industry and presenting ideas for future research.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.4
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• pp.156-162
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• 2006

Transmission zones can be defined based on LMPs. Each zone consists of nodes with similar LMPs, and zonal price is determined by average nodal prices in each zone.[1] Network reduction is still important for the analysis of zonal systems under electricity market environments, even though the computing capability of computer system can deal with entire power systems. The Similarity Index is a good performance measure for the network reduction.[2] It can be applied to the network reduction between zones categorized by the nodal prices. This paper deals with a novel network reduction method between zones based on the similarity Index. Line admittances of reduced network were determined by using the least square method. The proposed method was verified by IEEE 39 bus test system.