• Journal of Distribution Science
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• v.9 no.3
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• pp.5-14
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• 2011

One of the new roles of modern retail stores is to supply consumers with a memorable experience. In Korea, enhancing a store's environment so that customers remember a unique shopping experience is recognized as a sound strategy for strengthening the store's competitiveness. Motivated by this incentive, awareness of the experience-store concept is starting to increase in various categories of the retail industry. However, many experience stores, except in a few cases, have yet to derive a significant profit, explaining why Korean consumers are somewhat unfamiliar with, yet fascinated by, the experience stores that now exist in the country. Consumer satisfaction directly, and indirectly, affects a company's future profit and potential financial gain; customer satisfaction also affects loyalty. Therefore, knowing the significant factors that increase satisfaction and loyalty is essential for any company, in any field, to be able to effectively differentiate itself from the competition. Intrigued by increased competition opportunities, most Korean companies have adopted experience-store marketing strategies. When establishing the most effective processes for increasing sales and achieving a sustainable competitive advantage of a new concept, companies should consider certain factors that influence consumers' ability to accept new concepts and ideas. The Technology Acceptance Model (TAM) is a theory that models how people accept new concepts. TAM proposes the following two factors that influence a person's decisions about how, and when, he or she will use a new product: "perceived usefulness" and "perceived ease of use." Much of the existing research has suggested that a person's character also affects the process for accepting new ideas. Such personal character attributes as individual preferences, self-confidence, and a person's values, traits, and/or skills affect the process for willingly consenting to try something new. It will be meaningful to establish how the TAM theory's components, as well as personal character, affect individuals accepting the experience-store concept. To that end, as it pertains to an experience store, the first goal of the study is to examine the influence of innovative factors (perceived usefulness and perceived ease of use) on satisfaction and loyalty. The second objective is to define the moderate effect of consumers' personal characteristics on the model. The proposed model was tested on 149 respondents who were engaged in leisure sports activities and bought sports outdoor garments and equipment. According to the study's findings, the satisfaction and loyalty of an experience store can be explained by perceived usefulness and perceived ease of use, with the study's results demonstrating the stronger of the two factors being "perceived ease of use." The study failed to explain the effects of a person's character on the model. In conclusion, when the companies that operate the experience stores execute their marketing and promotion strategies, they should stress the stores' "ease of use" product components. Additionally, it can be extrapolated from the study data that since the experience-store idea is still relatively unfamiliar to Korean consumers, most customers are not yet able to evaluate, nor take a position regarding, their respective attitudes toward experience stores.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• Cartoon and Animation Studies
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• s.41
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• pp.511-531
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• 2015

The underlying impetus of the birth of animated film is attraction about a moving image. And the animation image occurs from the process of performative relationship between an animator and apparatus. Therefore, analysing the method how the moving image is constructed will be the focal starting point to deal with an animated film as a text. In this context, that conveys the theme in more sensuous way will be examined in a dimension of the material, technique and image-making method. KIM Jin-man's is a Stop Motion Animated Film with Noodlescreen about a journey of a fish that wishes to go outside of the water. KIM created original and friendly images out of plain thin noodle which is a common ingredient in Korea, and dealt with the ontological introspection based of the concept of Nondualism. Nondualism based on the interconnected and cyclical eastern philosophy which is different from the western dualistic theory points to the idea that the universe and all its multiplicity are ultimately expressions or appearances of one essential reality. This paper focuses on KIM's recent work and sees how Nondualism is applied throughout the animated film by analysing the performative method of mediums, technique, and structure. First of all, the form of Noodlescreen will be reviewed in Chapter Two. Pinscreen Animation which was invented by Alexander Alexeieff and Claire Parker will be also compared with Noodlescreen in the aesthetic viewpoint here. In Chapter Three, it will be analysed how the description of the image of binary opposition itself provides expanded sense and rich metaphor. Lastly, the format of Mise-en-abyme going constantly towards outer space will be dealt how it exposes the cinematic illusion and spatiality in Chapter Four. Throughout the whole chapters, it will reviewed how the concept of Nondualism relates the images of and deactivate the boundary of binary opposition in terms of both the story development and the visualization method. By this methodology, it will be confirmed that image of animated film not only explains the narrative but also activates the perception about the theme and provides integrated sensory experiences in the independent and expanded dimension.

• Journal of radiological science and technology
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• v.39 no.1
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• pp.51-57
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• 2016

Acoustic noise during magnetic resonance imaging (MRI) is the main source for patient discomfort. we report our preliminary experience with this technique in neuroimaging with regard to subjective and objective noise levels and image quality. 60 patients(29 males, 31 females, average age of 60.1) underwent routine brain MRI with 3.0 Tesla (MAGNETOM Tim Trio; Siemens, Germany) system and 12-channel head coil. Q-$T_2$ and $T_2$ sequence were performed. Measurement of sound pressure levels (SPL) and heart rate on Q-$T_2$ and $T_2$ was performed respectively. Quantitative analysis was carried out by measuring the SNR, CNR, and SIR values of Q-$T_2$, $T_2$ and a statistical analysis was performed using independent sample T-test. Qualitative analysis was evaluated by the eyes for the overall quality image of Q-$T_2$ and $T_2$. A 5-point evaluation scale was used, including excellent(5), good(4), fair(3), poor(2), and unacceptable(1). The average noise and peak noise decreased by $15dB_A$ and $10dB_A$ on $T_2$ and Q-$T_2$ test. Also, the average value of heartbeat rate was lower in Q-$T_2$ for 120 seconds in each test, but there was no statistical significance. The quantitative analysis showed that there was no significant difference between CNR and SIR, and there was a significant difference (p<0.05) as SNR had a lower average value on Q-$T_2$. According to the qualitative analysis, the overall quality image of 59 case $T_2$ and Q-$T_2$ was evaluated as excellent at 5 points, and 1 case was evaluated as good at 4 points due to a motion artifact. Q-$T_2$ is a promising technique for acoustic noise reduction and improved patient comfort.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.1-15
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• 2024

This study aims to elucidate the characteristics of big tech platform companies' sports content business in an environment of rapid digital transformation. Specifically, this study examines the market structure of big tech platform companies with a focus on Amazon, revealing the role of sports content within this structure through an analysis of Amazon's sports marketing business and provides an outlook on the sports content business of big tech platform companies. Based on two-sided market platform business models, big tech platform companies incorporate sports content as a strategy to enhance the value of their platforms. Therefore, sports content is used as a tool to enhance the value of their platforms and to consolidate their monopoly position by maximizing profits by increasing the synergy of platform ecosystems such as infrastructure. Amazon acquires popular live sports broadcasting rights on a continental or national basis and supplies them to its platforms, which not only increases the number of new customers and purchasing effects, but also provides IT solution services to sports organizations and teams while planning and supplying various promotional contents, thus creates synergy across Amazon's platforms including its advertising business. Amazon also expands its business opportunities and increases its overall value by supplying live sports contents to Amazon Prime Video and Amazon Prime, providing technical services to various stakeholders through Amazon Web Services, and offering Amazon Marketing Cloud services for analyzing and predicting advertisers' advertising and marketing performance. This gives rise to a new paradigm in the sports marketing business in the digital era, stemming from the difference in market structure between big tech companies based on two-sided market platforms and legacy global companies based on one-sided markets. The core of this new model is a business through the development of various contents based on live sports streaming rights, and sports content marketing will become a major field of sports marketing along with traditional broadcasting rights and sponsorship. Big tech platform global companies such as Amazon, Apple, and Google have the potential to become new global sports marketing companies, and the current sports marketing and advertising companies, as well as teams and leagues, are facing both crises and opportunities.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.