• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.3
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• pp.125-146
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• 2013

Nowadays, the performance of the mobile game sales is influencing the ranking of game companies listed on KOSDAQ. In the meantime, venture capital companies had focused on online game. Recently, however, they have great interest in mobile games and mobile game companies. In addition, angel investors and accelerators are increasing investment for the mobile game companies. The most important issues for mobile game investor is how to evaluate the mobile game companies and their contents. Therefore, this study derived the evaluation factors for the mobile game company. And research method converged of the opinions of both supply side and demand side of the game industry. Ten professionals who are responsible for the supply of the game industry and CEO group & development experts of game development company were selected for survey in this study. Also ten professionals who are responsible for the demand of the game industry and the investment company were selected for survey in this study. And Delphi technique was performed according to the survey. Management skills, development capabilities, game play, feasibility, operational capabilities has emerged as five evaluation factors to evaluate the mobile game company. And the 20 sub-factors including CEO's reliability were derived. AHP(Analytic Hierarchy Process) theory is applied to analyze the importance of the qualitative elements which were derived by Delphi technique. As a result, the analysis hierarchy of evaluation factors for the mobile game company was created. Pair-wise comparison for each element was performed to analyze the importance. As a result, 'Core fun of the game' (12,2%), 'Involvement of the game' (10.3%), 'Security Reliability' (8.9%), 'Core developers' ability' (7.6%) appeared in order of importance. The significance of this study is offering more objective methodology for realistic assessment and importance of elements to evaluate mobile game company.

• Culinary science and hospitality research
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• v.17 no.1
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• pp.124-141
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• 2011

The domestic food culture in Korea has gone through great changes, among which dining out is considered most prominent. These changes are caused by a number of factors: development of several related industries, increase in dining out chances, diversification of consumer needs, change in consumption awareness and quality, increase in disposable income, women's advance into the society, etc. Under these circumstances, the fast food industry has been experiencing slow growth, whereas family restaurants and take out coffee franchises are consistently increasing the number of restaurants and shops as a part of aggressive management to increase sales. This study aims, first, to examine the effects of consumer's brand individuality and satisfaction on brand trust, brand emotion, brand identification, and brand loyalty of specialty coffee shops. Subsequently, this study observes how consumer's brand individuality and satisfaction affect the formation of brand trust, brand emotion, brand identification, and brand loyalty in accordance with preferred type of specialty coffee shops, frequency of experience, and life style in order to establish relevant strategies. The results of this study are as follows. First, brand individuality had a positive effect on customer satisfaction. Second, customer satisfaction had a positive effect on brand trust. Third, customer satisfaction had a positive effect on brand loyalty. Fourth, customer satisfaction had a positive effect on brand emotion. Fifth, brand trust had a positive effect on brand loyalty. Sixth, brand emotion had a positive effect on brand loyalty. These results have the following implications. First, the dimensions of brand individuality are presented as a means to form brand loyalty, thereby demonstrating the significance of the effect. Accordingly, developing a proper brand individuality in forming brand loyalty is imperative. Second, consumers using specialty coffee shops had the greatest effect on the relation between dimensions of brand individuality and customer satisfaction in this study, while the interrelation between customer satisfaction and brand loyalty was not concretely supported in the preceding studies.

• Journal of Distribution Science
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• v.9 no.3
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• pp.73-82
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• 2011

This study presents an effective and distinctive marketing strategy through the implementation of the aesthetic art marketing communication technique of storytelling. The reason applying art to marketing is effective is that it gives "class" and aesthetic beauty to the brand's image, which will lead to an increase in revenue and loyalty of consumers. The story stands in for the brand's subject of "desire." Luxury brand customers not only consume high-quality products, require the utmost in service, and value of the brand, they also appreciate the story the brand is telling. The story, combined with art, is called art marketing communication; it makes the brand more unique through its enhanced visual elements. The study discusses art collaboration, art exhibition, a transforming architecture project, art advertisement, a flagship store, and a human resource training center. Based on the "desire," I adopted the element and principle of storytelling. By visualizing the brand with a symbol, the company is able to relate to consumers' sentimentality. Through storytelling art marketing communication, and the strategy using relevance of brand and artist's popularity, the research shows efficient art marketing influences to the brand's image. The results of the research indicate that by using adequate art marketing communication that best reflects the identity and story of the luxury brand, it produces great results; the research also demonstrated, in various ways, that art marketing will succeed. The case showed the following outcomes. First, consumers have a tendency to choose a brand that is associated with an empathizing story. World renowned brands see through the market's "desires" for unique stories, and they also provide the ability to amuse consumers. The story in a product will become an important competitive element in future markets. Second, the art marketing communication applying a story rendered a brand with distinction. The most effective art marketing communications are art collaboration, art exhibition, locomotive architecture project, and others that are adopted as various means. Third, the brand's products were considered as an art piece, which led to not only strengthening the loyalty of consumers but also an increase in sales. In addition, the company could sustain a premium price for the goods sold. By adapting art to a brand's tradition, an innovative and creative new product provides consumer satisfaction, and producing goods in limited editions creates enthusiastic collectors. Fourth, this study suggests an abridged report, implication, limitation of the study, and directions for further research. Referring to the case for the adaptation of luxury brands, efficient art marketing strategies considering Korean company brand and efficiently study preceding Korean company brand art marketing strategy could be proposed.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.29-56
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• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.

• Asia Marketing Journal
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• v.15 no.1
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• pp.1-22
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• 2013

This case focuses on Shanghai Tang, the first truly Chinese luxury brand that appeals to both Westerners and, more recently, to Chinese consumers worldwide. A visionary and wealthy businessman Sir David Tang created this company from scratch in 1994 in Hong Kong. Its story, spanned over almost two decades, has been fascinating. It went from what best a Chinese brand could be in the eyes of Westerners who love the Chinese culture, to a nearly-bankrupted company in 1998, before being acquired by Richemont, the second largest luxury group in the world. Since then, its turnaround has been spectacular with a growing appeal among Chinese luxury consumers who represent the core segment of the luxury industry today. The main objective of this case study is to formally examine how Shanghai Tang overcame its downfall and re-emerged as one the very few well- known Chinese luxury brands. More specifically, this case highlights the ways with which Shanghai Tang made a transitional change from a brand for Westerners who love the Chinese culture, to a brand for both, Westerners who love the Chinese culture and Chinese who love luxury. A close examination reveals that Shanghai Tang has followed the brand identity concept that consists of two major components: functional and emotional. The functional component for developing a luxury brand concerns all product characteristics that will make a product 'luxurious' in the eyes of the consumer, such as premium quality of cachemire from Mongolia, Chinese silk, lacquer, finest leather, porcelain, and jade in the case of Shanghai Tang. The emotional component consists of non-functional symbolic meanings of a brand. The symbolic meaning marks the major difference between a premium and a luxury brand. In the case of Shanghai Tang, its symbolic meaning refers to the Chinese culture and the brand aims to represent the best of Chinese traditions and establish itself as "the ambassador of modern Chinese style". It touches the Chinese heritage and emotions. Shanghai Tang has reinvented the modern Chinese chic by drawing back to the stylish decadence of Shanghai in the 1930s, which was then called the "Paris of the East", and this is where the brand finds inspiration to create its own myth. Once the functional and emotional components assured, Shanghai Tang has gone through a four-stage development to become the first global Chinese luxury brand: introduction, deepening, expansion, and revitalization. Introduction: David Tang discovered a market gap and had a vision to launch the first Chinese luxury brand to the world. The key success drivers for the introduction and management of a Chinese luxury brand are a solid brand identity and, above all, a creative mind, an inspired person. This was David Tang then, and this is now Raphael Le Masne de Chermont, the current Executive Chairman. Shanghai Tang combines Chinese and Western elements, which it finds to be the most sustainable platform for drawing consumers. Deepening: A major objective of the next phase is to become recognized as a luxury brand and a fashion or design authority. For this purpose, Shanghai Tang has cooperated with other well-regarded luxury and lifestyle brands such as Puma and Swarovski. It also expanded its product lines from high-end custom-made garments to music CDs and restaurant. Expansion: After the opening of his first store in Hong Kong in 1994, David Tang went on to open his second store in New York City three years later. However this New York retail operation was a financial disaster. Barely nineteen months after the opening, the store was shut down and quietly relocated to a cheaper location of Madison Avenue. Despite this failure, Shanghai Tang products found numerous followers especially among Western tourists and became "souvenir-like" must-haves. However, despite its strong brand DNA, the brand did not generate enough repeated sales and over the years the company cumulated heavy debts and became unprofitable. Revitalizing: After its purchase by Richemont in 1998, Le Masne de Chermont was appointed to lead the company, reposition the brand and undertake some major strategic changes such as revising the "Shanghai Tang" designs to appeal not only to Westerners but also to Chinese consumers, and to open new stores around the world. Since then, Shanghai Tang has become synonymous to a modern Chinese luxury lifestyle brand.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.5
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• pp.13-29
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• 2023

Urban parks are social infrastructure supporting citizens' health, quality of life, and community formation. As the proportion of urban parks that have been established for more than 20 years is increasing, the need for refurbishment to improve the physical space environment and enhance the functions of aging urban parks is increasing. Since the government's refurbishment of aging urban parks has limitations in securing financial resources and promoting attractiveness, they must be promoted through public-private partnerships. Japan, which suffered from the problem of aging urban parks, has successfully promoted several park refurbishment projects by introducing the Park-PFI through the revision of the 「Urban Park Act」 in 2017. This study examines and analyzes the characteristics of the Japan Park-PFI as an alternative to improving the quality of aging domestic urban park services through public-private partnerships and the validity of the aging urban park refurbishment projects through Park-PFI. The main findings are as follows. First, it is necessary to start discussions on introducing Japan's Park-PFI according to the domestic conditions as a means of public-private partnership to improve the service quality and diversify the functions of aging urban parks. In order to introduce Park-PFI social discussions and follow-up studies on the deterioration of urban parks. Must be conducted. The installation of private capital and profit facilities and improvements of related regulations, such as the 「Parks and Green Spaces Act」 and the 「Public Property Act」, is required. Second, it is judged that the Park-PFI project is a policy alternative that can enhance the benefits to citizens, local governments, and private operators under the premise that the need to refurbish aging urban parks is high and the location is suitable for promoting the project. As a result of a pilot application of the Park-PFI project to Seyeong Park, an aging urban park located in Bupyeong-gu, Incheon, it was analyzed to be profitable in terms of the profitability index (PI), net present value (FNPV), and internal rate of return (FIRR). It is considered possible to participate in the business sector. At the local government level, private capital is used to improve the physical space environment of aging urban parks, as well as the refurbishment of the urban parks by utilizing financial resources generated by returning a portion of the facility usage fees and profits (0.5% of annual sales) of private operators. It was found that management budgets could be secured.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Asia pacific journal of information systems
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• v.22 no.1
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• pp.29-52
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• 2012

Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

• Journal of Distribution Science
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• v.8 no.3
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• pp.49-56
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• 2010

At the initial stage of Internet advertising, banner advertising came into fashion. As the Internet developed into a central part of daily lives and the competition in the on-line advertising market was getting fierce, there was not enough space for banner advertising, which rushed to portal sites only. All these factors was responsible for an upsurge in advertising prices. Consequently, the high-cost and low-efficiency problems with banner advertising were raised, which led to an emergence of keyword advertising as a new type of Internet advertising to replace its predecessor. In the beginning of 2000s, when Internet advertising came to be activated, display advertisement including banner advertising dominated the Net. However, display advertising showed signs of gradual decline, and registered minus growth in the year 2009, whereas keyword advertising showed rapid growth and started to outdo display advertising as of the year 2005. Keyword advertising refers to the advertising technique that exposes relevant advertisements on the top of research sites when one searches for a keyword. Instead of exposing advertisements to unspecified individuals like banner advertising, keyword advertising, or targeted advertising technique, shows advertisements only when customers search for a desired keyword so that only highly prospective customers are given a chance to see them. In this context, it is also referred to as search advertising. It is regarded as more aggressive advertising with a high hit rate than previous advertising in that, instead of the seller discovering customers and running an advertisement for them like TV, radios or banner advertising, it exposes advertisements to visiting customers. Keyword advertising makes it possible for a company to seek publicity on line simply by making use of a single word and to achieve a maximum of efficiency at a minimum cost. The strong point of keyword advertising is that customers are allowed to directly contact the products in question through its more efficient advertising when compared to the advertisements of mass media such as TV and radio, etc. The weak point of keyword advertising is that a company should have its advertisement registered on each and every portal site and finds it hard to exercise substantial supervision over its advertisement, there being a possibility of its advertising expenses exceeding its profits. Keyword advertising severs as the most appropriate methods of advertising for the sales and publicity of small and medium enterprises which are in need of a maximum of advertising effect at a low advertising cost. At present, keyword advertising is divided into CPC advertising and CPM advertising. The former is known as the most efficient technique, which is also referred to as advertising based on the meter rate system; A company is supposed to pay for the number of clicks on a searched keyword which users have searched. This is representatively adopted by Overture, Google's Adwords, Naver's Clickchoice, and Daum's Clicks, etc. CPM advertising is dependent upon the flat rate payment system, making a company pay for its advertisement on the basis of the number of exposure, not on the basis of the number of clicks. This method fixes a price for advertisement on the basis of 1,000-time exposure, and is mainly adopted by Naver's Timechoice, Daum's Speciallink, and Nate's Speedup, etc, At present, the CPC method is most frequently adopted. The weak point of the CPC method is that advertising cost can rise through constant clicks from the same IP. If a company makes good use of strategies for maximizing the strong points of keyword advertising and complementing its weak points, it is highly likely to turn its visitors into prospective customers. Accordingly, an advertiser should make an analysis of customers' behavior and approach them in a variety of ways, trying hard to find out what they want. With this in mind, her or she has to put multiple keywords into use when running for ads. When he or she first runs an ad, he or she should first give priority to which keyword to select. The advertiser should consider how many individuals using a search engine will click the keyword in question and how much money he or she has to pay for the advertisement. As the popular keywords that the users of search engines are frequently using are expensive in terms of a unit cost per click, the advertisers without much money for advertising at the initial phrase should pay attention to detailed keywords suitable to their budget. Detailed keywords are also referred to as peripheral keywords or extension keywords, which can be called a combination of major keywords. Most keywords are in the form of texts. The biggest strong point of text-based advertising is that it looks like search results, causing little antipathy to it. But it fails to attract much attention because of the fact that most keyword advertising is in the form of texts. Image-embedded advertising is easy to notice due to images, but it is exposed on the lower part of a web page and regarded as an advertisement, which leads to a low click through rate. However, its strong point is that its prices are lower than those of text-based advertising. If a company owns a logo or a product that is easy enough for people to recognize, the company is well advised to make good use of image-embedded advertising so as to attract Internet users' attention. Advertisers should make an analysis of their logos and examine customers' responses based on the events of sites in question and the composition of products as a vehicle for monitoring their behavior in detail. Besides, keyword advertising allows them to analyze the advertising effects of exposed keywords through the analysis of logos. The logo analysis refers to a close analysis of the current situation of a site by making an analysis of information about visitors on the basis of the analysis of the number of visitors and page view, and that of cookie values. It is in the log files generated through each Web server that a user's IP, used pages, the time when he or she uses it, and cookie values are stored. The log files contain a huge amount of data. As it is almost impossible to make a direct analysis of these log files, one is supposed to make an analysis of them by using solutions for a log analysis. The generic information that can be extracted from tools for each logo analysis includes the number of viewing the total pages, the number of average page view per day, the number of basic page view, the number of page view per visit, the total number of hits, the number of average hits per day, the number of hits per visit, the number of visits, the number of average visits per day, the net number of visitors, average visitors per day, one-time visitors, visitors who have come more than twice, and average using hours, etc. These sites are deemed to be useful for utilizing data for the analysis of the situation and current status of rival companies as well as benchmarking. As keyword advertising exposes advertisements exclusively on search-result pages, competition among advertisers attempting to preoccupy popular keywords is very fierce. Some portal sites keep on giving priority to the existing advertisers, whereas others provide chances to purchase keywords in question to all the advertisers after the advertising contract is over. If an advertiser tries to rely on keywords sensitive to seasons and timeliness in case of sites providing priority to the established advertisers, he or she may as well make a purchase of a vacant place for advertising lest he or she should miss appropriate timing for advertising. However, Naver doesn't provide priority to the existing advertisers as far as all the keyword advertisements are concerned. In this case, one can preoccupy keywords if he or she enters into a contract after confirming the contract period for advertising. This study is designed to take a look at marketing for keyword advertising and to present effective strategies for keyword advertising marketing. At present, the Korean CPC advertising market is virtually monopolized by Overture. Its strong points are that Overture is based on the CPC charging model and that advertisements are registered on the top of the most representative portal sites in Korea. These advantages serve as the most appropriate medium for small and medium enterprises to use. However, the CPC method of Overture has its weak points, too. That is, the CPC method is not the only perfect advertising model among the search advertisements in the on-line market. So it is absolutely necessary that small and medium enterprises including independent shopping malls should complement the weaknesses of the CPC method and make good use of strategies for maximizing its strengths so as to increase their sales and to create a point of contact with customers.