• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.59-88
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• 2008

Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.

• The korean journal of orthodontics
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• v.37 no.5
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• pp.351-363
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• 2007

The aim of this study was to evaluate pulp and periodontal changes following rapid tooth retraction by periodontal distraction after bone undermining surgery in young adult dogs. Methods: Alter extraction of second premolars, the interseptal bone mesial to the upper 3rd premolar was undermined. After activating the distraction appliance at 0.5 mm/day for six days, the dogs were sacrificed at 0, 1, 3, 5, 7, and 9 weeks during the consolidation period. Tissue changes of periodontium and pulp were evaluated radiologically, histologically, and immunohistochemically. Results: Digital subtraction radiography showed active bone formation in the stretched periodontal ligament from 0 - 4 weeks. Resorption of the alveolar bone, appearance of osteoclasts, and infiltration of inflammatory cells were observed just after the activation period at the pressure side, and distinctive bone formation was seen in the tension side of the periodontal ligament from 1 week. New bone formation was active at 1 - 3 weeks. The expression of calcitonin gene-related peptide in the experimental group was increased at the alveolar bone and pulp, and periodontal ligament at the pressure side from 0 - 1 week, and it decreased after 5 weeks to become similar to that of the control group. Conclusions: The results showed that rapid tooth movement using periodontal distraction can be new form of orthodontic tooth movement for accelerating normal bone formation.

• Journal of the HCI Society of Korea
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• v.11 no.2
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• pp.15-22
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• 2016

The ways to interact with digital appliances are becoming more diverse. Users can control appliances using a remote control and a touch-screen, and appliances can send users feedback through various ways such as sound, voice, and visual signals. However, there is little research on how to define which output method to use for providing feedback according to the user' input method. In this study, we designed an experimental study that seeks to identify how to appropriately match the output method - voice and sound - based on the user input - voice and button. We made four types of interaction with two kinds input methods and two kinds of output methods. For the four interaction types, we compared the usability, perceived satisfaction, preference and suitability. Results reveals that the output method affects the ease of use and perceived satisfaction of the input method. The voice input method with sound feedback was evaluated more satisfying than with the voice feedback. However, the keying input method with voice feedback was evaluated more satisfying than with sound feedback. The keying input method was more dependent on the output method than the voice input method. We also found that the feedback method of appliances determines the perceived appropriateness of the interaction.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.92-100
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• 2010

Due to the development of digital appliance, role of TV causes both-way by introducing IPTV, and SNS service causes big change of watching environment and residence environment. There are good conditions on the role of integrated control because it is arranged in the living room which secures movement most effectively and because family members can easily use, and the degree of use is high. Therefore, we infer user's needs by analyzing user scenario and current role of TV in home network environment. Primarily, we collect surveys of development scenario and technology which companies suggest TV applied by home network service, and secondly, we comparatively study scenario which the companies mentioned above suggest through observing user scenario, and study the role of IPTV in the future through actual scenario-based experiment by ethnography. After analyzing user scenario through case study and experiment, there are integrated device studies mainly in company study because it can be made up inside home, security and entertainment. On the other hand, there are patterns of user behavior by scenario experiment mainly in auto-tainment, security, and it showed that it is insufficient for interaction between TV and home media peripheral. Through this paper, we analyze context of home user, and based on this, we could suggest effective use of service development. Also after analyzing user form, we could know it also should be considered of ratio between activity inside home and activity outside home.

• Journal of the Korean Society of Food Science and Nutrition
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• v.32 no.3
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• pp.393-399
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• 2003

The purpose of this study was to investigate the preferred methods for making summer kimchi as a basic research of making commercial kimchi. Questionnaire were collected from 590 housewives nationwide in Korea, and the data were analyzed by SPSS program. The results were as follows: (1) The average salting time of Chinese cabbage was 3~5 hrs when the combined method of dry and brine salting was used, regardless of the region. (2) Seven jeotkals (salt-fermented fishes) including anchovy, anchovy juice, shrimp, northern sand lance juice, hair-tail viscera, flatfish and yellow corvenia were mainly used in kimchi. Among them, anchovy and anchovy juice jeotkals were preferred to all others in Southern area (Busan, Gwangju, Gyeongnam, Gyeongbuk, Jeonnam), while shrimp jeotkal in Seoul, Gwangju, Jeonbuk, Chungnam and Jeju, and northern sand lance juice jeotkal in Daegu, Daejeon and Gyeonggi, respectively. In most regions, however, blending type of 2 jeotkals was used in kimchi. (3) Eleven ingredients such as red pepper, garlic, ginger, green onion, radish, leek, onion, carrot, sugar, sesame and MSG were used as basic components for making kimchi. In particular, MSG was used as a basic ingredient regardless of region and age. However, a standard taste for making kimchi was depended on housewife in this study.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.6
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• pp.947-958
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• 2008

To study the effect of a washing machine with silver nano technology on its detergency, the discoloring of the dyed clothes and the staining of standards adjacent fabrics were examined. As the laundry specimen, cotton fabric dyed with reactive dyes and Polyester fabric dyed with disperse dyes were chosen; and as the adjacent fabrics, undyed cotton. polyester and nylon fabrics were chosen. The colorfastness was evaluated after washing under conditions that those washing temperature, liquor ratio, detergency concentration and the type of water were varied. When the clothes were washed with the tap water contains silver ion, the deposition of silver compounds into the washed clothes was measured. As a results, after the washing in the various conditions, discoloring of the dyed clothes was not intense. The higher the washing temperature and the lower the liquor ratio, the larger the staining appeared on the white fabrics; especially for the white nylon fabrics. The concentration of detergent and the type of water affected hardly the colorfastness. After the repeated washing with the water contains silver, whiteness of the cotton and the nylon fabrics were lower than the result after the washing with the tap water, and a quantity of silver ions was found on the washed clothes.

• Journal of Broadcast Engineering
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• v.6 no.3
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• pp.246-259
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• 2001

Due to recent rapid deployment of Internet streaming service and digital broadcasting service, the issue of how to efficiently support streaming workload in so called "Internet Home Appliance" receives prime interests from industry as well as academia. The underlying dilemma is that it may not be feasible to put cutting edge CPU, boards, disks and other peripherals into that type of device. The primary reason is its cost. Usually, Internet Home Appliances has its dedicated usage, e.g. Internet Radio, and thus it does not require high-end CPU nor high-end Va subsystem. The same reasoning applies to I/O subsystem. In Internet Home Appliances dedicated to handle compressed moving picture, it is not equipped with high end SCSI disk with fast rotational speed. Thus, it is mandatory to devise elaborate software algorithm to exploit the available hardware resources and maximize the efficiency of the system. This paper presents our experiences in the design and implementation of a new multimedia file system which can efficiently deliver the required disk bandwidth for a periodic I/O workload. We have implemented the file system on the Linux operating system, and examined itsperformance under streaming I/O workload. The results of the study show that the proposed file system exhibits superior performance than the Linux Ext2 file system under streaming I/O workload. The result of this work not only contribute to advance the state f art file system technology for multimedia streaming but also put forth the software which is readily available and can be deployed. deployed.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.101-116
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• 2015

Recently, due to the development of smart devices and social media, vast amounts of information with the various forms were accumulated. Particularly, considerable research efforts are being directed towards analyzing unstructured big data to resolve various social problems. Accordingly, focus of data-driven decision-making is being moved from structured data analysis to unstructured one. Also, in the field of recommendation system, which is the typical area of data-driven decision-making, the need of using unstructured data has been steadily increased to improve system performance. Approaches to improve the performance of recommendation systems can be found in two aspects- improving algorithms and acquiring useful data with high quality. Traditionally, most efforts to improve the performance of recommendation system were made by the former approach, while the latter approach has not attracted much attention relatively. In this sense, efforts to utilize unstructured data from variable sources are very timely and necessary. Particularly, as the interests of users are directly connected with their needs, identifying the interests of the user through unstructured big data analysis can be a crew for improving performance of recommendation systems. In this sense, this study proposes the methodology of improving recommendation system by measuring interests of the user. Specially, this study proposes the method to quantify interests of the user by analyzing user's internet usage patterns, and to predict user's repurchase based upon the discovered preferences. There are two important modules in this study. The first module predicts repurchase probability of each category through analyzing users' purchase history. We include the first module to our research scope for comparing the accuracy of traditional purchase-based prediction model to our new model presented in the second module. This procedure extracts purchase history of users. The core part of our methodology is in the second module. This module extracts users' interests by analyzing news articles the users have read. The second module constructs a correspondence matrix between topics and news articles by performing topic modeling on real world news articles. And then, the module analyzes users' news access patterns and then constructs a correspondence matrix between articles and users. After that, by merging the results of the previous processes in the second module, we can obtain a correspondence matrix between users and topics. This matrix describes users' interests in a structured manner. Finally, by using the matrix, the second module builds a model for predicting repurchase probability of each category. In this paper, we also provide experimental results of our performance evaluation. The outline of data used our experiments is as follows. We acquired web transaction data of 5,000 panels from a company that is specialized to analyzing ranks of internet sites. At first we extracted 15,000 URLs of news articles published from July 2012 to June 2013 from the original data and we crawled main contents of the news articles. After that we selected 2,615 users who have read at least one of the extracted news articles. Among the 2,615 users, we discovered that the number of target users who purchase at least one items from our target shopping mall 'G' is 359. In the experiments, we analyzed purchase history and news access records of the 359 internet users. From the performance evaluation, we found that our prediction model using both users' interests and purchase history outperforms a prediction model using only users' purchase history from a view point of misclassification ratio. In detail, our model outperformed the traditional one in appliance, beauty, computer, culture, digital, fashion, and sports categories when artificial neural network based models were used. Similarly, our model outperformed the traditional one in beauty, computer, digital, fashion, food, and furniture categories when decision tree based models were used although the improvement is very small.