The terminology "human body" simply means a physical body but also more often, as an object in art works, carries symbolic concepts incorporating the whole history of human lives. Human body has been employed as an artistic object capturing physical body, delivering artist's idea expressing life indicators from different standpoints of times and places. This point of view about human body in art works has in fact rather short history since 1960's when modern thinking paradigm focusing upon rationality and reasoning has begun declining and on the contrary when the body used to be the servant of the mind and soul for a long time has begun attracting artist's attention as a real entity from the viewpoint of dichotomy. During the 1960's, frequent performances in Pop art and of Fluxus showed that the human body has been an important media for artistic communication after importance of body performances had been raised in Action painting in 1940's. The human body became a more determined media in body art works that had got into stride after Yves Kline's conceptual works applying body and its traces. These kinds of art works have continued and consolidated into the Feminism came into blossom in 1980's and into fragmentated and disembodied body art trend in 1990's. Through development of trends in body works, human body now might well be regarded as a clue provide from individual identity with implication over the world. This thesis is to analyse in semiotic way main works of Kiki Smith who is a representative artist devoting to Feminism and proposing extended significance of human body. In the analysis process of works done by two great artists with histrorical background of art trend in order to find and open an significance horizon of human body, semiotics and bodism are therefore perceived as pertinent and applied as basic tools. The first stage of analysis is to get the significances emerged in between expression part and contextual parts, which are separated structually from the most basic level. The study deals with body works furthermore in the way of structual cohesion of the expression and the context from the view of A J. Greimas' Structural Semantics and tried to build up a basic frame for the extended significances of human body. This thesis is, on the other hand, to attempt to contribute for extension of disembodied and fragmentated body discussed in the structural semantic frame earlier by Julia Kriesteva who delivers abjection concepts and phenomenology of Maurice Merleau-Ponty who enables to overview relationship between the body and the world from the viewpoint of Bodism, further into interpretation level. The other works are Kiki smith's that showed epics about death in mid-1980's, detailed humbleness of vulnerable human body exposed to dichotomy and fragmentation in 1990's and religion and mythology incorporating wouln healing in 2000's and henceforth. Through the analysis of Kiki Smith's representative work 'Pee body', it is verified and confirmed that fragmentated body showed beyond boundary gap of the human body and ultimately tends to imply human healing owing to divine maternity. Bodily symbols in Kiki Smith's are extended to the universal world to imply human life and death on the one hand and religion and mythology of human wound and divine healing one the other hand. This thesis through these process and results of analysis is in a broad context, to emphasize that human body as objectified text has a key indicator role to understand world as well as semiotic extension in art works in late 20th century so that we might confirm bodily symbol as a cultural context constitutes a section of contemporary visual arts.
After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.
Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.
Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.
With the growth of social networks, various forms of SNS have emerged. Based on various motivations for use such as interactivity, information exchange, and entertainment, SNS users are also on the fast-growing trend. Facebook is the main SNS channel, and companies have started using Facebook pages as a public relations channel. To this end, in the early stages of operation, companies began to secure a number of fans, and as a result, the number of corporate Facebook fans has recently increased to as many as millions. from a corporate perspective, Facebook is attracting attention because it makes it easier for you to meet the customers you want. Facebook provides an efficient advertising platform based on the numerous data it has. Advertising targeting can be conducted using their demographic characteristics, behavior, or contact information. It is optimized for advertisements that can expose information to a desired target, so that results can be obtained more effectively. it rethink and communicate corporate brand image to customers through contents. The study was conducted through Facebook advertising data, and could be of great help to business people working in the online advertising industry. For this reason, the independent variables used in the research were selected based on the characteristics of the content that the actual business is concerned with. Recently, the company's Facebook page operation goal is to go beyond securing the number of fan pages, branding to promote its brand, and further aiming to communicate with major customers. the main figures for this assessment are Facebook's 'OK', 'Attachment', 'Share', and 'Number of Click' which are the dependent variables of this study. in order to measure the outcome of the target, the consumer's response is set as a key measurable key performance indicator (KPI), and a strategy is set and executed to achieve this. Here, KPI uses Facebook's ad numbers 'reach', 'exposure', 'like', 'share', 'comment', 'clicks', and 'CPC' depending on the situation. in order to achieve the corresponding figures, the consideration of content production must be prior, and in this study, the independent variables were organized by dividing into three considerations for content production into three. The effects of content material, content structure, and message styles on Facebook's user behavior were analyzed using regression analysis. Content materials are related to the content's difficulty, company relevance, and daily involvement. According to existing research, it was very important how the content would attract users' interest. Content could be divided into informative content and interesting content. Informational content is content related to the brand, and information exchange with users is important. Interesting content is defined as posts that are not related to brands related to interesting movies or anecdotes. Based on this, this study started with the assumption that the difficulty, company relevance, and daily involvement have an effect on the dependent variable. In addition, previous studies have found that content types affect Facebook user activity. I think it depends on the combination of photos and text used in the content. Based on this study, the actual photos were used and the hashtag and independent variables were also examined. Finally, we focused on the advertising message. In the previous studies, the effect of advertising messages on users was different depending on whether they were narrative or non-narrative, and furthermore, the influence on message intimacy was different. In this study, we conducted research on the behavior that Facebook users' behavior would be different depending on the language and formality. For dependent variables, 'OK' and 'Full Click Count' are set by every user's action on the content. In this study, we defined each independent variable in the existing study literature and analyzed the effect on the dependent variable, and found that 'good' factors such as 'self association', 'actual use', and 'hidden' are important. Could. Material difficulties', 'actual participation' and 'large scale * difficulties'. In addition, variables such as 'Self Connect', 'Actual Engagement' and 'Sexual Sexual Attention' have been shown to have a significant impact on 'Full Click'. It is expected that through research results, it is possible to contribute to the operation and production strategy of company Facebook operators and content creators by presenting a content strategy optimized for the purpose of the content. In this study, we defined each independent variable in the existing research literature and analyzed its effect on the dependent variable, and we could see that factors on 'good' were significant such as 'self-association', 'reality use', 'concernal material difficulty', 'real-life involvement' and 'massive*difficulty'. In addition, variables such as 'self-connection', 'real-life involvement' and 'formative*attention' were shown to have significant effects for 'full-click'. Through the research results, it is expected that by presenting an optimized content strategy for content purposes, it can contribute to the operation and production strategy of corporate Facebook operators and content producers.
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.
Currently, Social Media, it has widely a renown keyword and its related social trends and businesses have been fastly applied into various contexts. Social media has become an important research area for scholars interested in online technologies and cyber space and their social impacts. Social media is not only including web-based services but also mobile-based application services that allow people to share various style information and knowledge through online connection. Social media users have tendency to common identity- and bond-attachment through interactions such as 'thumbs up', 'reply note', 'forwarding', which may have driven from various factors and may result in delivering information, sharing knowledge, and specific experiences et al. Even further, almost of all social media sites provide and connect unknown strangers depending on shared interests, political views, or enjoyable activities, and other stuffs incorporating the creation of contents, which provides benefits to users. As fast developing digital devices including smartphone, tablet PC, internet based blogging, and photo and video clips, scholars desperately have began to study regarding diverse issues connecting human beings' motivations and the behavioral results which may be articulated by the format of antecedents as well as consequences related to contents that people create via social media. Social media such as Facebook, Twitter, or Cyworld users are more and more getting close each other and build up their relationships by a different style. In this sense, people use social media as tools for maintain pre-existing network, creating new people socially, and at the same time, explicitly find some business opportunities using personal and unlimited public networks. In terms of theory in explaining this phenomenon, social capital is a concept that describes the benefits one receives from one's relationship with others. Thereby, social media use is closely related to the form and connected of people, which is a bridge that can be able to achieve informational benefits of a heterogeneous network of people and common identity- and bonding-attachment which emphasizes emotional benefits from community members or friend group. Social capital would be resources accumulated through the relationships among people, which can be considered as an investment in social relations with expected returns and may achieve benefits from the greater access to and use of resources embedded in social networks. Social media using for their social capital has vastly been adopted in a cyber world, however, there has been little explaining the phenomenon theoretically how people may take advantages or opportunities through interaction among people, why people may interactively give willingness to help or their answers. The individual consciously express themselves in an online space, so called, common identity- or bonding-attachments. Common-identity attachment is the focus of the weak ties, which are loose connections between individuals who may provide useful information or new perspectives for one another but typically not emotional support, whereas common-bonding attachment is explained that between individuals in tightly-knit, emotionally close relationship such as family and close friends. The common identify- and bonding-attachment are mainly studying on-offline setting, which individual convey an impression to others that are expressed to own interest to others. Thus, individuals expect to meet other people and are trying to behave self-presentation engaging in opposite partners accordingly. As developing social media, individuals are motivated to disclose self-disclosures of open and honest using diverse cues such as verbal and nonverbal and pictorial and video files to their friends as well as passing strangers. Social media context, common identity- and bond-attachment for self-presentation seems different compared with face-to-face context. In the realm of social media, social users look for self-impression by posting text messages, pictures, video files. Under the digital environments, people interact to work, shop, learn, entertain, and be played. Social media provides increasingly the kinds of intention and behavior in online. Typically, identity and bond social capital through self-presentation is the intentional and tangible component of identity. At social media, people try to engage in others via a desired impression, which can maintain through performing coherent and complementary communications including displaying signs, symbols, brands made of digital stuffs(information, interest, pictures, etc,). In marketing area, consumers traditionally show common-identity as they select clothes, hairstyles, automobiles, logos, and so on, to impress others in any given context in a shopping mall or opera. To examine these social capital and attachment, we combined a social capital theory with an attachment theory into our research model. Our research model focuses on the common identity- and bond-attachment how they are formulated through social capitals: cognitive capital, structural capital, relational capital, and individual characteristics. Thus, we examined that individual online kindness, self-rated expertise, and social relation influence to build common identity- and bond-attachment, and the attachment effects make an impact on both the willingness to help, however, common bond seems not to show directly impact on information sharing. As a result, we discover that the social capital and attachment theories are mainly applicable to the context of social media and usage in the individual networks. We collected sample data of 256 who are using social media such as Facebook, Twitter, and Cyworld and analyzed the suggested hypotheses through the Structural Equation Model by AMOS. This study analyzes the direct and indirect relationship between the social network service usage and outcomes. Antecedents of kindness, confidence of knowledge, social relations are significantly affected to the mediators common identity-and bond attachments, however, interestingly, network externality does not impact, which we assumed that a size of network was a negative because group members would not significantly contribute if the members do not intend to actively interact with each other. The mediating variables had a positive effect on toward willingness to help. Further, common identity attachment has stronger significant on shared information.
1. Introduction: Contrast to the offline purchasing environment, online store cannot offer the sense of touch or direct visual information of its product to the consumers. So the builder of the online shopping mall should provide more concrete and detailed product information(Kim 2008), and Alba (1997) also predicted that the quality of the offered information is determined by the post-purchase consumer satisfaction. In practice, many fashion and apparel online shopping malls offer the picture information with the product on the real person model to enhance the usefulness of product information. On the other virtual product experience has been suggested to the ways of overcoming the online consumers' limited perceptual capability (Jiang & Benbasat 2005). However, the adoption and the facilitation of the virtual reality tools requires high investment and technical specialty compared to the text/picture product information offerings (Shaffer 2006). This could make the entry barrier to the online shopping to the small retailers and sometimes it could be demanding high level of consumers' perceptual efforts. So the expensive technological solution could affects negatively to the consumer decision making processes. Nevertheless, most of the previous research on the online product information provision suggests the VR be the more effective tools. 2. Research Model and Hypothesis: Presented in
The outline and characteristics of the important doctors of the 'Zhe Zhong Pai'(折衷派) are as follows. Part 1. In the late Edo(江戶) period The 'Zhe Zhong Pai', which tried to take the theory and clinical treatment of the 'Hou Shi Pai (後世派)' and the 'Gu Fang Pai(古方派)' and get their strong points to make treatments perfect, appeared. Their point was 'The main part is the art of the ancients, The latter prescriptions are to be used'(以古法爲主, 後世方爲用) and the "Shang Han Lun(傷寒論)" was revered for its treatments but in actual use it was not kept at that. As mentioned above The 'Zhe Zhong Pai' viewed treatments as the base, which was the view of most doctors in the Edo period. However, the reason the 'Zhe Zhong Pai' is not valued as much as the 'Gu Fang Pai' by medical history books in Japan is because the 'Zhe Zhong Pai' does not have the substantiation or uniqueness of the 'Gu Fang Pai', and also because the view of 'gather as well as store up'(兼收並蓄) was the same as the 'Kao Zheng Pai'. Moreover, the 'compromise'(折衷) point of view was from taking in both Chinese and western medical knowledge systems(漢蘭折衷). Generally the pioneer of the 'Zhe Zhong Pai' is seen as Mochizuki Rokumon(望月鹿門) and after that was Fukui Futei(福井楓亭), Wadato Kaku(和田東郭), Yamada Seichin(山田正珍) and Taki Motohiro(多紀元簡). Part 2. The lives of Wada Tokaku(和田東郭), Nakagame Kinkei(中神琴溪), Nei Teng Xi Zhe(內藤希哲), the important doctors of the 'Zhe Zhong Pai', are as follows. First Wada Tokaku(和田東郭, 1743-1803) was born when the 'Hou Shi Pai' was already declining and the 'Gu Fang Pai' was flourishing and learned medicine from a 'Hou Shi Pai' doctor, Hu Tian Xu Shan(戶田旭山) and a 'Gu Fang Pai' doctor, Yoshimasu Todo(吉益東洞). He was not hindered by 'the old ways(古方)' and did not lean towards 'the new ways(後世方)' and formed a way of compromise that 'looked at hardness and softness as the same'(剛柔相摩) by setting 'the cure of the disease' as the base, and said that to cure diseases 'the old way' must be used, but 'the new way' was necessary to supplement its shortcomings. His works include "Dao Shui Suo Yan(導水瑣言)", "Jiao Chiang Fang Yi Je(蕉窗方意解)" and "Yi Xue Sho(醫學說)". Second. Nakagame Kinkei(中神琴溪, 1744-1833) was famous for leaving Yoshimasu Todo(吉益東洞) and changing to the 'Zhe Zhong Pai', and in his early years used qing fen(輕粉) to cure geisha(妓女) of syphilis. His argument was "the "Shang Han Lun" must be revered but needs to be adapted", "Zhong Jing can be made into a follower but I cannot become his follower", "the later medical texts such as "Ru Men Shi Qin(儒門事親)" should only be used for its prescriptions and not its theories". His works include "Shang Han Lun Yue Yan(傷寒論約言)". Third, Nei Teng Xi Zhe(內藤希哲, 1701-1735) learned medicine from Qing Shui Xian Sheng(淸水先生) and went out to Edo. In his book "Yi Jing Jie Huo Lun(醫經解惑論)" he tells of how he went from 'learning'(學) to 'skepticism'(惑) and how skepticism made him learn in 'the six skepticisms'(六惑). In the latter years Xi Zhe(希哲) combines the "Shen Nong Ben Cao Jing(神農本草經)", the main text for herbal medicine, "Ming Tang Jing(明堂經)" of accupuncture, basic theory texts "Huang Dui Nei Jing(皇帝內經)" and "Nan Jing(難經)" with the "Shang Han Za Bing Lun", a book that the 'Gu Fang Pai' saw as opposing to the rest, and became 'an expert of five scriptures'(五經一貫). Part 3. Asada Showhaku(淺田宗伯, 1815-1894) started medicine at Zhong Cun Zhong Zong(中村中倧) and learned 'the old way'(古方) from Yoshimasu Todo and got experience through Ouan Yue(川越) and Fu Jing(福井) and received teachings in texts, history and Wang Yangmin's principles(陽明學) fmm famous teachers. Showhaku(倧伯) meets a medical official of the makufu(幕府), Ben Kang Zong Yuan(本康宗圓), and receives help from the 3 great doctors of the Edo period, Taki Motokato(多紀元堅), Xiao Dao Xue Gu(小島學古) and Xi Duo Cun Kao(喜多村栲窻) and further develops his arts. At 47 he diagnoses the general Jia Mao(家茂) with 'heart failure from beriberi'(脚氣衡心) and becomes a Zheng Shi(徵土), at 51 he cures a minister from France and received a present from Napoleon, at 65 he becomes the court physician and saves Ming Gong(明宮) Jia Ren Qn Wang(嘉仁親王, later the 大正天皇) from bodily convulsions and becomes 'the vassal of merit who saved the national polity(國體)' At the 7th year of the Meiji(明治) he becomes the 2nd owner of Wen Zhi She(溫知社) and takes part in the 'kampo continuation movement'. In his latter years he saw 14000 patients a year, so we can estimate the qualjty and quantity of his clinical skills. Showhaku(宗伯) wrote over 80 books including the "Ju Chuang Shu Ying(橘窻書影)", "Wu Wu Yao Shi Fang Han(勿誤藥室方函)", "Shang Han Biang Shu(傷寒辨術)", "Jing Qi Shen Lun(精氣神論)", "Hunag Guo Ming Yi Chuan(皇國名醫傳)" and the "Xian Jhe Yi Hua(先哲醫話)". Especially in the "Ju Chuang Shu Ying(橘窻書影) he says "the old theories are the main, and the new prescriptions are to be used"(以古法爲主, 後世方爲用), stating the 'Zhe Zhong Pai' way of thinking, In the first volume of "Shang Han Biang Shu(傷寒辨術)" and "Za Bing Lun Shi(雜病論識)", 'Zong Ping'(總評), He discerns the parts that are not Zhang Zhong Jing's writings and emphasizes his theories and practical uses.
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.
, research model suggests VR effect could be moderated by the product types by the usage situations. Product types could be defined as the portable product and installed product, and the information offering type as still picture of the product, picture of the product with the real-person model and VR. 3. Methods and Results: 3.1. Experimental design and measured variables We designed the 2(product types) X 3(product information types) experimental setting and measured dependent variables such as information usefulness, attitude toward the shopping mall, overall product quality, purchase intention and the revisiting intention. In the case of information usefulness and attitude toward the shopping mall were measured by multi-item scale. As a result of reliability test, Cronbach's Alpha value of each variable shows more than 0.6. Thus, we ensured that the internal consistency of items. 3.2. Manipulation check The main concern of this study is to verify the moderate effect by the product type of usage situation. indicates that our experimental manipulation of the moderate effect of the product type was successful. 3.3. Results As
indicates, there was a significant main effect on the only one dependent variable(attitude toward the shopping mall) by the information types. As predicted, VR has highest mean value compared to other information types. Thus, H1 was partially supported. However, main effect by the product types was not found. To evaluate H2 and H3, a two-way ANOVA was conducted. As
indicates, there exist the interaction effects on the three dependent variables(information usefulness, overall product quality and purchase intention) by the information types and the product types. As predicted, picture of the product with the real-person model has highest mean among the information types in the case of portable product. On the other hand, VR has highest mean among the information types in the case of installed product. Thus, H2 and H3 was supported. 4. Implications: The present study found the moderate effect by the product type of usage situation. Based on the findings the following managerial implications are asserted. First, it was found that information types are affect only the attitude toward the shopping mall. The meaning of this finding is that VR effects are not enough to understand the product itself. Therefore, we must consider when and how to use this VR tools. Second, it was found that there exist the interaction effects on the information usefulness, overall product quality and purchase intention. This finding suggests that consideration of usage situation helps consumer's understanding of product and promotes their purchase intention. In conclusion, not only product attributes but also product usage situations must be fully considered by the online retailers when they want to meet the needs of consumers.
A Study on the ' Zhe Zhong Pai'(折衷派) of the Traditional Medicine of Japan
(일본(日本) 의학(醫學)의 '절충파(折衷派)'에 관(關)한 연구(硏究))
If This Brand Were a Person, or Anthropomorphism of Brands Through Packaging Stories
(가설품패시인(假设品牌是人), 혹통과고사포장장품패의인화(或通过故事包装将品牌拟人化))
이메일무단수집거부
이용약관
제 1 장 총칙
제 2 장 이용계약의 체결
제 3 장 계약 당사자의 의무
제 4 장 서비스의 이용
제 5 장 계약 해지 및 이용 제한
제 6 장 손해배상 및 기타사항
Detail Search
Image Search
(β)