• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.193-202
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• 2020

This study was intended to present the magnitude of privacy infringement concerns and their relationship to consumer innovation (functional innovation, hedonistic innovation, social innovation, cognitive innovation), to identify differences among groups and to suggest implications for marketing strategies for the spread of new products. The implications of this study are as follows. First, functional innovation has shown that differences exist between groups. Analysts say that sensitive groups are buying products that can simplify their work immediately after release despite concerns over privacy violations. Second, hedonistic innovation has shown that differences exist between groups. These findings suggest that sensitive groups prefer novel products, products that give excitement and excitement about products, and products that give new enjoyment and fun that they have never known before. Third, social innovation has been shown that there is no difference between groups. These analyses show that the self-esteem of using products that others have never experienced before, and the curiosity that anyone envies, are purchased or used first. Finally, cognitive innovation showed that differences existed between groups. These analyses show that new products are purchased when they meet the functions, design, and innovation that consumers want.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1136-1141
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• 2016

IoT technology has been used as a core technology of convergence service that needs intelligent information processing, and the importance is largely emerging now. And internal network construction thru IoT interaction device can connect with IoT device effectively, provide diverse services by connection with open platform. Especially, beacon that is based on low electric power bluetooth device is receiving attention as one of core technology of IoT. Beacon technology is utilized widly in various fields of industry, and there are lot of demands in the specific environment and conditions beyond the basic function. On this thesis, the authors are proposing the beacon device that utilized acceleration sensor and hole sensor. this beacon device can control the target on specific situation thru sensing of moving target. For the more, we will expect to apply to the various type of factory environments like detachable installation, optimized management using sensor.

• Journal of the Korean Society of Costume
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• v.58 no.4
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• pp.72-85
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• 2008

With the new millennium setting in, our society is plowing its way through more drastically changing currents than ever. Nowadays, many people believe that high tech such as the Internet, digital civilization, the IT revolution, bio-industry, and the genome project, that has brought humans material prosperity, is the right change in direction. However, the more we adopt high tech into our lives, the more we desire high touch in order to achieve a balance. In other words, we need something to act as a ballast to stabilize our minds. As such, the more high tech develops, the more individuals miss and search for tools that appeal to their emotions. Because of this, although high touch is an opposite concept to high tech, it coexists with high tech, and it is defined as "human contact of high sensitivity that stimulates the emotion of humans". High Touch, a term which originated from "High Tech, High Touch", a book written by American futurist John Naisbitt, refers to human contact that makes human life richer, forminga deep impression on individuals and providing comfort. As such, high touch, which is gaining significant attention in modern society, is a phenomenon occurring throughout politics, society, culture, art, and religion, together with high tech. Through high touch, modern people must realize how to understand and accept a modern society that is dominated by the age of technology and in which direction they should head. Under this background, this study has the following objectives: to interpret the concept of high touch in the age of high tech in association with formative art and fashion, and through various media examine the desire for expression that may stimulate emotion in modern people, which is required by the high tech-prevalent modern society. It further analyzes how high touch is reflected in modern fashion and presents the direction future fashion should head in.

• Fashion & Textile Research Journal
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• v.17 no.3
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• pp.315-326
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• 2015

Woman leadership has been remarkably highlighted with women's accelerating entry into society. Domestic and overseas interests about political leaders began with the age of media and they are rapidly spreading worldwide with the development of internet, SNS and blog. Along with this phenomenon, exposure of images has been remarkably increasing and fashion has been also used as a political strategy. However, the research on woman political leaders has been insufficient so this study selected Geunhye Park, Michelle Obama and Hillary Clinton as representative woman leaders for the research. 149 pictures of Geunhye Park, 171 pictures of Michelle Obama and 124 pictures of Hillary Clinton from the articles containing their pictures from Jan. 2002 to Dec. 2013 were analyzed, focusing on their gender. The three woman political leaders' typical images of femininity, masculinity and androgyny were categorized respectively and the period and works in which those images had been expressed were reviewed. Also, fashion styles of the images pursued by each gender were analyzed through their color, material, silhouette, design point, items and accessories. As a result, Geunhye Park had femininity image at the beginning and had masculinity image when she did election campaigns, which led to her current image of androgyny. Michelle Obama uses the image of femininity, masculinity and androgyny simultaneously. It was found that Hillary Clinton emphasized the image of masculinity and androgyny but she emphasizes femininity image these days.

• The Research Journal of the Costume Culture
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• v.18 no.6
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• pp.1090-1111
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• 2010

Thanks to both developments in various media such as the internet and TV and China's economic growth, the fashion market in China has gain a lot of attention by global businesses as a newly-raised spending market. Fashion companies in Korea have entered into the china since the late 1990s. For them to get competitive edges, they have to differentiate their brand by creating new design based on the culture becoming mega-trend in fashion market. So in this research, I try to create fashion designs based on Hallyu Stars' fashion styles and images, who come on as a new culture code in China and other Asian. For this, I conducted theological consideration on what the Hallyu is, and looked into fashion styles in soft dramas which 5 Hallyu Stars started in and street fashion in Shanghai in China. Based on the outcomes of analysis, I figured out those star's fashion style and created products targeting young generation born after 1980s in China. The conclusion of this study is as follows. Firstly, the very definition of Hallyu which can be described as a phenomenon in which Korean movies, soap operas, and pop music have become immensely popular throughout Asia.has been expanding to signify the proliferation of Korean culture as a whole. Secondly, having selected the 5 female stars representing Hallyu, we were able to analyze and categorize their fashion styles on the basis of their music videos, movies, and soap-operas. Thirdly, In order to explore the level of influence of Hallyu fashion industry, we studied the street fashion of Shanghai The result was that we could observe both the slim and feminine cool casual style and the cute and affectionate pretty casual style simultaneously.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.8-19
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• 2020

We see an energy fucused smart city evolution of the UK along with the project of "Smart London Plan (SLP)." A theoretical logic of business model innovation has been discussed and a research framework of evolving energy focused smart city is formulated. The starting point is the silo system. In the second stage, the private investment in smart meters establishes a basement for next stages. As results, the UK's smart energy sector has evolved from smart meter installation through smart grid to new business models such as water-energy nexus and microgrid. Before smart meter installation of the government, the electricity system was centralized. However, after consumer engagement plan has been set to make them understand benefits that they can secure through smart meters, the customer behavior has been changed. The data analytics firm enables greater understanding of consumer behavior and it helps energy industry to be smart via controlling, securing and using that data to improve the energy system. In the third stage, distribution network operators (DNOs)' access to smart meter data has been allowed and the segmentation starts. In the fourth stage, with collaboration of Ofwat and Ofgem, it is possible to eliminate unnecessary duplication of works and reduce interest conflict between water and electricity. In the fifth stage, smart meter and grid has been integrated as an "adaptive" system and a transition from DNO to DSO is accomplished for the integrated operation. Microgrid is a prototype for an "adaptive" smart grid. Previous steps enable London to accomplish a platform leadership to support the increasing electrification of the heating and transport sector and smart home.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.39-54
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• 2018

This study aims to expand K-Wave business. For this, it firstly investigated previous studies and pointed out limitations of the current scope of the K-Wave business. Therefore, as a theoretical background, it attempts to construct an analysis framework based on four types of creativity type model and to redefine the concept of K-Wave business, which refers to a series of business activities that create, utilize the asset, and reuse the originality of intellectual property assets. This study analyzes the business activities of K-Wave's asset creation, utilization, and talent linkage during 2013~2017. The scope of the asset creation covers the highest ranked movies, dramas, and K-pops, while the utilization of those is analyzed in cosmetics, food, and fashion industries. The personal talent is the source of new K-Wave value creation and Webtoon IP is analyzed. As a result, in the case of movies and dramas, the representative market is China, which is the result of the efforts to avoid the continuation of China's regulation and the development of local OTTs. It is confirmed that the product development for Chinese consumers is active as activities of K-Wave utilization in cosmetics, food and fashion. Interesting is that new K-Wave content is circulated in the beauty sector. Finally, it is confirmed that Webtoon IP, which has been structured with a solid story in individual talent, is the origin of new K-Wave asset creation such as movies and dramas.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.21-31
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• 2014

As the protein drug industry is growing, protein informations are indispensable for the protein drug development. NCBI and PDB in the U.S., the EMBL in Europe and the DDBJ in Japan are the representative centers for bio information and each center provides specific data for protein information. To obtain specific protein information, users are to be collect them from the service sites of each center and then combine or analyze for their purpose. To facilitate the accessibility to bio data, various R&D activities are running for development of diverse web services relevant to bio data in major data centers or small-scale projects. With the recognition of protein information as pivotal for the protein drug development, DrugBank in Canada, GDSC in the U.S. start to provide integrated informations between drugs and proteins. However, those service does not meet users' demands due to lack of diversity. In Korea, infra structures for bioinformatics are limited and the current services for protein drug information are providing only basic information of the drug including distribution data. This is a pilot study to construct a specialized service for protein drug information in Korean style breaking through the limitations of current services. This study proposed new fields for protein characterization information which had not been provided by current services and evaluated their effectiveness and usability by comparing them to the existing fields with expert survey. As a result, the newly proposed fields for protein characterization have been proven to be useful data fields for the service of protein drug information.