• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• 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.

• Journal of Distribution Research
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• v.16 no.1
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• pp.95-115
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• 2011

Food service is the major part of franchise business in Korea, accounting for 69.9% of the brands in the market. As the food service industry becomes mature, many franchisees have struggled to survive in the market. In general, consumers have higher levels of expectation toward service quality of franchised outlets compared that of (non-franchised) independent ones. They also tend to believe that franchisees deliver standardized service at the uniform food price, regardless of their locations. Such beliefs seem to be important reasons that consumers prefer franchised outlets to independent ones. Nevertheless, few studies examined the impact of qualify features of franchisees on customer satisfaction so far. To this end, this study examined the characteristics of various quality features of franchisees in the food service industry, regarding their relationship with customer satisfaction and dissatisfaction. The quality perception of heavy-users was also compared with that of light-users in order to find insights for developing differentiated marketing strategy for the two segments. Customer satisfaction has been understood as a one-dimensional construct while there are recent studies that insist two-dimensional nature of the construct. In this regard, Kano et al. (1984) suggested to categorize quality features of a product or service into five types, based on their relation to customer satisfaction and dissatisfaction: Must-be quality, Attractive quality, One-dimensional quality, Indifferent quality, and Reverse quality. According to the Kano model, customers are more dissatisfied when Must-be quality(M) are not fulfilled, but their satisfaction does not arise above neutral no matter how fully the quality fulfilled. In comparison, customers are more satisfied with a full provision of Attactive quality(A) but manage to accept its dysfunction. One-dimensional quality(O) results in satisfaction when fulfilled and dissatisfaction when not fulfilled. For Indifferent quality(I), its presence or absence influences neither customer satisfaction nor dissatisfaction. Lastly, Reverse quality(R) refers to the features whose high degree of achievement results in customer dissatisfaction rather than satisfaction. Meanwhile, the basic guidelines of the Kano model have a limitation in that the quality type of each feature is simply determined by calculating the mode statistics. In order to overcome such limitation, the relative importance of each feature on customer satisfaction (Better value; b) and dissatisfaction (Worse value; w) were calculated following the formulas below (Timko, 1993). The Better value indicates how much customer satisfaction is increased by providing the quality feature in question. In contrast, the Worse value indicates how much customer dissatisfaction is decreased by providing the quality feature. Better = (A + O)/(A+O+M+I) Worse = (O+M)/(A+O+M+I)(-1) An on-line survey was performed in order to understand the nature of quality features of franchisees in the food service industry by applying the Kano Model. A total of twenty quality features (refer to the Table 2) were identified as the result of literature review in franchise business and a pre-test with fifty college students in Seoul. The potential respondents of our main survey was limited to the customers who have visited more than two restaurants/stores of the same franchise brand. Survey invitation e-mails were sent out to the panels of a market research company and a total of 257 responses were used for analysis. Following the guidelines of Kano model, each of the twenty quality features was classified into one of the five types based on customers' responses to a set of questions: "(1) how do you feel if the following quality feature is fulfilled in the franchise restaurant that you visit," and "(2) how do you feel if the following quality feature is not fulfilled in the franchise restaurant that you visit." The analyses revealed that customers' dissatisfaction with franchisees is commonly associated with the poor level of cleanliness of the store (w=-0.872), kindness of the staffs(w=-0.890), conveniences such as parking lot and restroom(w=-0.669), and expertise of the staffs(w=-0.492). Such quality features were categorized as Must-be quality in this study. While standardization or uniformity across franchisees has been emphasized in franchise business, this study found that consumers are interested only in uniformity of price across franchisees(w=-0.608), but not interested in standardizations of menu items, interior designs, customer service procedures, and food tastes. Customers appeared to be more satisfied when the franchise brand has promotional events such as giveaways(b=0.767), good accessibility(b=0.699), customer loyalty programs(b=0.659), award winning history(b=0.641), and outlets in the overseas market(b=0.506). The results are summarized in a matrix form in Table 1. Better(b) and Worse(w) index indicate relative importance of each quality feature on customer satisfaction and dissatisfaction, respectively. Meanwhile, there were differences in perceiving the quality features between light users and heavy users of any specific franchise brand in the food service industry. Expertise of the staffs was labeled as Must-be quality for heavy users but Indifferent quality for light users. Light users seemed indifferent to overseas expansion of the brand and offering new menu items on a regular basis, while heavy users appeared to perceive them as Attractive quality. Such difference may come from their different levels of involvement when they eat out. The results are shown in Table 2. The findings of this study help practitioners understand the quality features they need to focus on to strengthen the competitive power in the food service market. Above all, removing the factors that cause customer dissatisfaction seems to be the most critical for franchisees. To retain loyal customers of the franchise brand, it is also recommended for franchisor to invest resources in the development of new menu items as well as training programs for the staffs. Lastly, if resources allow, promotional events, loyalty programs, overseas expansion, award-winning history can be considered as tools for attracting more customers to the business.

• Journal of Global Scholars of Marketing Science
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• v.20 no.3
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• pp.231-238
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• 2010

The anthropomorphism of brands, defined as seeing human beings in brands (Puzakova, Kwak, and Rosereto, 2008) is the focus of this study. Specifically, the research objective is to understand the ways in which brands are rendered humanlike. By analyzing consumer readings of stories found on food product packages we intend to show how marketers and consumers humanize a spectrum of brands and create meanings. Our research question considers the possibility that a single brand may host multiple or single meanings, associations, and personalities for different consumers. We start by highlighting the theoretical and practical significance of our research, explain why we turn our attention to packages as vehicles of brand meaning transfer, then describe our qualitative methodology, discuss findings, and conclude with a discussion of managerial implications and directions for future studies. The study was designed to directly expose consumers to potential vehicles of brand meaning transfer and then engage these consumers in free verbal reflections on their perceived meanings. Specifically, we asked participants to read non-nutritional stories on selected branded food packages, in order to elicit data about received meanings. Packaging has yet to receive due attention in consumer research (Hine, 1995). Until now, attention has focused solely on its utilitarian function and has generated a body of research that has explored the impact of nutritional information and claims on consumer perceptions of products (e.g., Loureiro, McCluskey and Mittelhammer, 2002; Mazis and Raymond, 1997; Nayga, Lipinski and Savur, 1998; Wansik, 2003). An exception is a recent study that turns its attention to non-nutritional packaging narratives and treats them as cultural productions and vehicles for mythologizing the brand (Kniazeva and Belk, 2007). The next step in this stream of research is to explore how such mythologizing activity affects brand personality perception and how these perceptions relate to consumers. These are the questions that our study aimed to address. We used in-depth interviews to help overcome the limitations of quantitative studies. Our convenience sample was formed with the objective of providing demographic and psychographic diversity in order to elicit variations in consumer reflections to food packaging stories. Our informants represent middle-class residents of the US and do not exhibit extreme alternative lifestyles described by Thompson as "cultural creatives" (2004). Nine people were individually interviewed on their food consumption preferences and behavior. Participants were asked to have a look at the twelve displayed food product packages and read all the textual information on the package, after which we continued with questions that focused on the consumer interpretations of the reading material (Scott and Batra, 2003). On average, each participant reflected on 4-5 packages. Our in-depth interviews lasted one to one and a half hours each. The interviews were tape recorded and transcribed, providing 140 pages of text. The products came from local grocery stores on the West Coast of the US and represented a basic range of food product categories, including snacks, canned foods, cereals, baby foods, and tea. The data were analyzed using procedures for developing grounded theory delineated by Strauss and Corbin (1998). As a result, our study does not support the notion of one brand/one personality as assumed by prior work. Thus, we reveal multiple brand personalities peacefully cohabiting in the same brand as seen by different consumers, despite marketer attempts to create more singular brand personalities. We extend Fournier's (1998) proposition, that one's life projects shape the intensity and nature of brand relationships. We find that these life projects also affect perceived brand personifications and meanings. While Fournier provides a conceptual framework that links together consumers’ life themes (Mick and Buhl, 1992) and relational roles assigned to anthropomorphized brands, we find that consumer life projects mold both the ways in which brands are rendered humanlike and the ways in which brands connect to consumers' existential concerns. We find two modes through which brands are anthropomorphized by our participants. First, brand personalities are created by seeing them through perceived demographic, psychographic, and social characteristics that are to some degree shared by consumers. Second, brands in our study further relate to consumers' existential concerns by either being blended with consumer personalities in order to connect to them (the brand as a friend, a family member, a next door neighbor) or by distancing themselves from the brand personalities and estranging them (the brand as a used car salesman, a "bunch of executives.") By focusing on food product packages, we illuminate a very specific, widely-used, but little-researched vehicle of marketing communication: brand storytelling. Recent work that has approached packages as mythmakers, finds it increasingly challenging for marketers to produce textual stories that link the personalities of products to the personalities of those consuming them, and suggests that "a multiplicity of building material for creating desired consumer myths is what a postmodern consumer arguably needs" (Kniazeva and Belk, 2007). Used as vehicles for storytelling, food packages can exploit both rational and emotional approaches, offering consumers either a "lecture" or "drama" (Randazzo, 2006), myths (Kniazeva and Belk, 2007; Holt, 2004; Thompson, 2004), or meanings (McCracken, 2005) as necessary building blocks for anthropomorphizing their brands. The craft of giving birth to brand personalities is in the hands of writers/marketers and in the minds of readers/consumers who individually and sometimes idiosyncratically put a meaningful human face on a brand.

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

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

• Journal of Yeungnam Medical Science
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• v.18 no.2
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• pp.226-238
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• 2001

Background: Anemia in chronic renal failure plays an important role in increasing morbidity of dialysis patients. The causes of the anemia are multifactorial. With using of erythropoietin(EPO) most of uremia-induced anemia can be overcome. However, about 10% of renal failure patients shows EPO-resistant anemia. Hyporesponsiveness to EPO has been related to many factors: iron deficiency, aluminum intoxication, inflammations, malignancies and secondary hyperparathyroidism. So I evaluated the improvement of EPO responsiveness after correction of above several factors. Materials and Methods: Seventy-two patients on hemodialysis over 6 months were treated with intravenous ascorbic acid(IVAA, 300 mg t.i.w. for 12 weeks), After administration of IVAA for 12 weeks, patients were classified into several groups according to iron status, serum aluminum levels and i-PTH levels. Indivisualized treatments were performed: increased iron supplement for absolute iron deficiency, active vitamin D3 for secondary hyperparathyroidism and desferrioxamine(DFO, 5 mg/kg t.i.w.) for aluminum intoxication or hyperferritinemia. Results: 1) Result of IVAA therapy for 12 weeks on all patients(n=72). Hemoglobin levels at 2, 4, 6 week were significantly elevated compared to baseline, but those of hemoglobin at 8, 10, 12 week were not significantly different. 2) Result of IVAA therapy for 20 weeks on patients with 100 ${\mu}g/l$ ${\leq}$ ferritin < 500 ${\mu}g/l$ and transferrin saturation(Tsat) below 30%(n=30). After treatment of IV AA for 12 weeks, patients were evaluated the response of therapy according to iron status. Patients with 100 ${\mu}g/l$ ${\leq}$ ferritin < 500 ${\mu}g/l$ and Tsat below 30% showed the most effective response. These patients were treated further for 8 weeks. Hemoglobin levels at 2, 4 week were significantly increased compared to baseline with significantly reduced doses of EPO at 2, 4, 6, 10, 12, 16, 20 week. Concomitantly significantly improvement of Tsat at 2, 6, 16, 20 week compared to baseline were identified. 3) Result of IVAA therapy for 12 weeks followed by DFO therapy for 8 weeks on patients with serum aluminum above 4 ${\mu}g/l$(n=12) Hemoglobin levels were not significantly increased during IVAA therapy for 12 weeks but dosages of EPO were significantly decreased at 2, 4, 6, 8 week during DFO therapy compared to pre-treatment status. Conclusion: IVAA can be helpful for the treatment of the anemia caused by functional iron deficiency and can reduce the dosage of EPO for anemia correction. And administration of low dose DFO, in cases of increased serum aluminum level, can reduce the requirement of EPO.

• Journal of Global Scholars of Marketing Science
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• v.17 no.2
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• pp.111-131
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• 2007

As a brand becomes a core asset in creating a corporation's value, brand marketing has become one of core strategies that corporations pursue. Recently, for customer relationship management, possession and consumption of goods were centered on brand for the management. Thus, management related to this matter was developed. The main reason of the increased interest on the relationship between the brand and the consumer is due to acquisition of individual consumers and development of relationship with those consumers. Along with the development of relationship, a corporation is able to establish long-term relationships. This has become a competitive advantage for the corporation. All of these processes became the strategic assets of corporations. The importance and the increase of interest of a brand have also become a big issue academically. Brand equity, brand extension, brand identity, brand relationship, and brand community are the results derived from the interest of a brand. More specifically, in marketing, the study of brands has been led to the study of factors related to building of powerful brands and the process of building the brand. Recently, studies concentrated primarily on the consumer-brand relationship. The reason is that brand loyalty can not explain the dynamic quality aspects of loyalty, the consumer-brand relationship building process, and especially interactions between the brands and the consumers. In the studies of consumer-brand relationship, a brand is not just limited to possession or consumption objectives, but rather conceptualized as partners. Most of the studies from the past concentrated on the results of qualitative analysis of consumer-brand relationship to show the depth and width of the performance of consumer-brand relationship. Studies in Korea have been the same. Recently, studies of consumer-brand relationship started to concentrate on quantitative analysis rather than qualitative analysis or even go further with quantitative analysis to show effecting factors of consumer-brand relationship. Studies of new quantitative approaches show the possibilities of using the results as a new concept of viewing consumer-brand relationship and possibilities of applying these new concepts on marketing. Studies of consumer-brand relationship with quantitative approach already exist, but none of them include sub-dimensions of consumer-brand relationship, which presents theoretical proofs for measurement. In other words, most studies add up or average out the sub-dimensions of consumer-brand relationship. However, to do these kind of studies, precondition of sub-dimensions being in identical constructs is necessary. Therefore, most of the studies from the past do not meet conditions of sub-dimensions being as one dimension construct. From this, we question the validity of past studies and their limits. The main purpose of this paper is to overcome the limits shown from the past studies by practical use of previous studies on sub-dimensions in a one-dimensional construct (Naver & Slater, 1990; Cronin & Taylor, 1992; Chang & Chen, 1998). In this study, two arbitrary groups were classified to evaluate reliability of the measurements and reliability analyses were pursued on each group. For convergent validity, correlations, Cronbach's, one-factor solution exploratory analysis were used. For discriminant validity correlation of consumer-brand relationship was compared with that of an involvement, which is a similar concept with consumer-based relationship. It also indicated dependent correlations by Cohen and Cohen (1975, p.35) and results showed that it was different constructs from 6 sub-dimensions of consumer-brand relationship. Through the results of studies mentioned above, we were able to finalize that sub-dimensions of consumer-brand relationship can viewed from one-dimensional constructs. This means that the one-dimensional construct of consumer-brand relationship can be viewed with reliability and validity. The result of this research is theoretically meaningful in that it assumes consumer-brand relationship in a one-dimensional construct and provides the basis of methodologies which are previously preformed. It is thought that this research also provides the possibility of new research on consumer-brand relationship in that it gives root to the fact that it is possible to manipulate one-dimensional constructs consisting of consumer-brand relationship. In the case of previous research on consumer-brand relationship, consumer-brand relationship is classified into several types on the basis of components consisting of consumer-brand relationship and a number of studies have been performed with priority given to the types. However, as we can possibly manipulate a one-dimensional construct through this research, it is expected that various studies which make the level or strength of consumer-brand relationship practical application of construct will be performed, and not research focused on separate types of consumer-brand relationship. Additionally, we have the theoretical basis of probability in which to manipulate the consumer-brand relationship with one-dimensional constructs. It is anticipated that studies using this construct, which is consumer-brand relationship, practical use of dependent variables, parameters, mediators, and so on, will be performed.

• Trans-
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• v.3
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• pp.109-135
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• 2017

The purpose of this thesis is to analyze characteristics of everyday movement showed in performances of Steve Paxton. A work of art has been realized as a special object enjoyed by high class people as high culture for a long time. Therefore, a gap between everyday life and art has been greatly existed, and the emergence of everyday elements in a work of art means that public awareness involving social change is changed. The postmodernism as the period when a boundary between art and everyday life is uncertain was a postwar society after the Second World War and a social situation that rapidly changes into a capitalistic society. Changes in this time made scholars gain access academically concepts related to everyday life, and affected artists as the spirit of the times of pluralistic postmodernism refusing totality. At the same period of the time, modern dance also faced a turning point as post-modern dance. After the Second World War, modern dance started to be evaluated as it reaches the limit, and at this juncture, headed by dancers including the Judson Dance Theatre. Acting as a dancer in a dance company of Merce Cunningham, Steve Paxton, one of founders of the Judson Dance Theatre, had a critical mind of the conditions of dance company with the social structure and the process that movement is made. This thinking is showed in early performances as an at tempt to realize everyday motion it self in performances. His early activity represented by a walking motion attracted attention as a simple motion that excludes all artful elements of existing dance performances and is possible to conduct by a person who is not a dancer. Although starting the use of everyday movement is regarded as an open characteristic of post-modern dance, advanced researches on this were rare, so this study started. In addition, studies related to Steve Paxton are skewed towards Contact Improvisation that he rose as an active practician. As the use of ordinary movement before he focused on Contact Improvisation, this study examines other attempts including Contact Improvisation as attempts after the beginning of his performances. Therefore, the study analyzes Satisfyin' Lover, Contact at 10th & 2nd and Bound that are performances of Steve Paxton, and based on this, draws everyday characteristics. In addition, related books, academic essays, dance articles and reviews are consulted to consider a concept related to everyday life and understand dance historical movement of post-modern dance. Paxton attracted attention because of his activity starting at critical approach of movement of existing modern dance. As walking of performers who are not dancers, a walking motion showed in Satisfyin' Lover gave esthetic meaning to everyday movement. After that, he was affected by Eastern ideas, so developed Contact Improvisation making a motion through energy of the natural laws. In addition, he had everyday things on his performances, and used a method to deliver various images by using mundane movement and impromptu gestures originating from relaxed body. Everyday movement of his performances represents change in awareness of performances of the art of dancing that are traditionally maintained including change of dance genre of an area. His activity with unprecedented attempt and experimentation should be highly evaluated as efforts to overcome the limit of modern dance.

• Journal of Genetic Medicine
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• v.8 no.2
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• pp.89-99
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• 2011

Over the years Korean health care system has improved in delivery of quality care to the general population for many areas of the health problems. The system is now being recognized in the world as the most cost effective one. It is covered by the uniform national health insurance policy for which most people in Korea are mandatory policy holders. Genetic counseling service, however, which is well recognized as an integral part of clinical genetics service deals with diagnosis and management of genetic condition as well as genetic information presentation and family support, is yet to be delivered in comprehensive way for the patients and families in need. Two major obstacles in providing genetic counseling service in korean health care system are identified; One is the lack of recognition for the need for genetic counseling service as necessary service by the national health insurance. Genetic counseling consumes a significant time in delivery and the current very low-fee schedule for physician service makes it very difficult to provide meaningful service. Second is the critical shortage of qualified professionals in the field of medical genetics and genetic counseling who can provide the service of genetic counseling in clinical setting. However, recognition and understanding of the fact that the scope and role of genetic counseling is expanding in post genomic era of personalized medicine for delivery of quality health care, will lead to the efforts to overcome obstacles in providing genetic counseling service in korean health care system. Only concerted efforts from health care policy makers of government on clinical genetics service and genetic counseling for establishing adequate reimbursement coverage and professional communities for developing educational program and certification process for professional genetic counselors, are necessary for the delivery of much needed clinical genetic counseling service in Korea.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.45-58
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• 2014

The Korean Culture Contents spread out to Worldwide, because the Korean wave is sweeping in the world. The contents stand in the middle of the Korean wave that we are used it. Each country is ongoing to keep their Culture industry improve the national brand and High added value. Performing contents is important factor of arousal in the enterprise industry. To improve high arousal confidence of product and positive attitude by populace is one of important factor by advertiser. Culture contents is the same situation. If culture contents have trusted by everyone, they will give information their around to spread word-of-mouth. So, many researcher study to measure for person's arousal analysis by statistical survey, physiological response, body movement and facial expression. First, Statistical survey has a problem that it is not possible to measure each person's arousal real time and we cannot get good survey result after they watched contents. Second, physiological response should be checked with surround because experimenter sets sensors up their chair or space by each of them. Additionally it is difficult to handle provided amount of information with real time from their sensor. Third, body movement is easy to get their movement from camera but it difficult to set up experimental condition, to measure their body language and to get the meaning. Lastly, many researcher study facial expression. They measures facial expression, eye tracking and face posed. Most of previous studies about arousal and interest are mostly limited to reaction of just one person and they have problems with application multi audiences. They have a particular method, for example they need room light surround, but set limits only one person and special environment condition in the laboratory. Also, we need to measure arousal in the contents, but is difficult to define also it is not easy to collect reaction by audiences immediately. Many audience in the theater watch performance. We suggest the system to measure multi-audience's reaction with real-time during performance. We use difference image analysis method for multi-audience but it weaks a dark field. To overcome dark environment during recoding IR camera can get the photo from dark area. In addition we present Multi-Audience Engagement Index (MAEI) to calculate algorithm which sources from sound, audience' movement and eye tracking value. Algorithm calculates audience arousal from the mobile survey, sound value, audience' reaction and audience eye's tracking. It improves accuracy of Multi-Audience Engagement Index, we compare Multi-Audience Engagement Index with mobile survey. And then it send the result to reporting system and proposal an interested persons. Mobile surveys are easy, fast, and visitors' discomfort can be minimized. Also additional information can be provided mobile advantage. Mobile application to communicate with the database, real-time information on visitors' attitudes focused on the content stored. Database can provide different survey every time based on provided information. The example shown in the survey are as follows: Impressive scene, Satisfied, Touched, Interested, Didn't pay attention and so on. The suggested system is combine as 3 parts. The system consist of three parts, External Device, Server and Internal Device. External Device can record multi-Audience in the dark field with IR camera and sound signal. Also we use survey with mobile application and send the data to ERD Server DB. The Server part's contain contents' data, such as each scene's weights value, group audience weights index, camera control program, algorithm and calculate Multi-Audience Engagement Index. Internal Device presents Multi-Audience Engagement Index with Web UI, print and display field monitor. Our system is test-operated by the Mogencelab in the DMC display exhibition hall which is located in the Sangam Dong, Mapo Gu, Seoul. We have still gotten from visitor daily. If we find this system audience arousal factor with this will be very useful to create contents.