This study aims at providing comprehensive data which would be helpful to establish a web shopping mall by analyzing the structure of web fashion star shops which have recently emerged as a result of advances in digital technology and communication. For the purpose of analyzing VMD strategy used in web fashion star shop, we adopt both of the documental and empirical research methods, based on which we examine the concept of E-commerce and current business situation of web fashion star shop industry, and then analyze the main page, product category page and product detail page in a star shop featured by a male pop star within a web shopping mall. According to our analysis of the structure of web fashion star shop, in case of open market, a banner with star's image on it leads to star shop when people click on the link of the banner, and in case of independent mall, they show each star's unique style in the main page. Product category page is linked to each product detail page which presents items of various fashion coordinates, satisfying needs of consumers to follow star's trendy fashion sense.
The purpose of this study is to examine the current situation of IMC strategies of Korean fashion brands which enter into Chinese market and to propose the efficient IMC strategies. Twenty Korean fashion brands which enter into Chinese market were selected and in-depth interviews with the managers were conducted. First, advertising is focused on magazines, and outdoor advertising, advertising in departments' magazines, distributing catalogs, and star marketing are performed in some cases. Brands often execute sales promotion activities such as price deduction, offering coupons, and presenting gifts. PR activities like events and sponsorship marketing which targets uncertain public or loyal customers are performed. PPL is conducted passively though it can be very effective. CRM is not operated systematically and customer management is conducted through tele-marketing and direct mail by shop managers. Web sites of brands have insufficient contents and are operated ineffectively. VMD follows brand's basic policy, but in cases of agents whose copyrights are transferred or branches which are place in areas where managing them is hard, shop managers operate their stores by themselves. Finally, because of socialistic consciousness, the perception about service of sales people is lacked.
Purpose: The hotel industry needs a leader who can actively demonstrate leadership to respond to and accept changes in the organization in a highly competitive and fast-changing environment. Therefore, the role of leaders who instill clear vision and goals of the organization in their members, listen to their opinions, and empathize is paramount. Leaders should encourage successful organizational activities based on active participation by employees and create the best environment for working with a sense of mission and responsibility. This study aims to identify the relationship between empathy leadership and job engagement as a result variable of team cohesion in the hotel culinary department and conduct empirical studies on the role of empathy leadership and job engagement. Research design, data, and methodology: The data were collected from employees who work in culinary department at a five-star franchise hotel located in the Seoul metropolitan area. Because it is difficult to conduct a survey through face-to-face contact with employees due to the COVID-19 pandemic, the online survey was conducted from February 1 to February 28, 2020. A total of 330 questionnaires through online were distributed and 268 employees completed the survey, yielding a response rate of 81%. Of the 268 returned responses, 27 responses were not usable due to missing information. Thus, a total of 241 responses were used for analysis. Results: The study results are as follows. First, it has been shown that the empathy leadership of culinary department in hotel companies has a significant positive impact on the job engagement. Second, it has been shown that job engagement has a significant positive effect on members' team cohesiveness. Third, empathy leadership of hotel companies' culinary department has a significant positive impact on members' team cohesiveness. Fourth, job engagement has a significant positive (+) mediating effect in the relationship between empathy leadership and team cohesiveness in culinary department. Conclusion: This study supports the theory that an emotional and empathic leader's behavior or ability can change the effectiveness or atmosphere of a rapidly changing hotel culinary team organization by presenting a research model on the effect of empathic leadership on job engagement and team cohesiveness. And hotel chefs should be more aware of the importance of empathic leadership and make them a human resource of the organization through formal and informal communication with culinary employees.
The purpose of this study is to find trends in new media fashion content by analyzing the fashion content of the official Instagram accounts of domestic fashion magazines that are being transformed by digital media. The framework for these analysis of fashion content type and methods of production is based on one used in an earlier research project. Empirical analysis is conducted on Vogue Korea's official Instagram accounts, using the highest number of major views as the secondary measure of interest. After screening for fashion content in posts on the Vogue Korea account for four months, 291 short video postings were extracted to analyze the number of views the postings received. The results were categorized as 'star', 'show/exhibition', 'product', 'shop', 'fashion film', 'designer', or 'event', included in the data are the number of postings by type and the number of views by post. Based on the characteristics of the creator and the editing, the posts were classified into 'professional production highlight', 'professional production private', 'UCC' or 'GIF' videos, the number of views per post were also collected. The research results show different levels of interest depending on the type of fashion content, and also on the way the videos were produced. The study also investigated how the combination of these two factors affects interest. When producing a new media fashion content, combining a 'star' type post with 'professional production private' video content was most popular. The selection of production method is therefore important even given the same type of content.
Journal of The Korean Association of Information Education
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v.9
no.2
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pp.177-185
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2005
The latest BLOG is highlighted both freely writing about the personal life and the tool which is maintaining friendly relations with many people by trackback. In this study, this BLOG system is designed for improving self-esteem in the class by using these characteristic of BLOG. the internet activity of students and their normal activity in the classroom connects with The Star-Gift-Shop module. This module induces students to an active BLOG, activity with interest. as a result of this activity in the class BLOG system, students improves their computer application ability and confidence of them. Which is effected teacher's efficient classroom management.
This research worked on the cooperative case by Marc Jacobs, who was involved in innovative collaboration in the field of fashion, and the analysis on imbedded values. With assessment of it, this paper aims at providing the theoretical ground on prevalence of fashion collaboration for creative innovation and presenting the basic material in establishing the design and marketing in the fashion industry. In methodology, the review was followed up about literature regarding Marc Jacobs and collaboration and his cases in 2001 through 2012. Results showed that his collaboration cases could be divided into those with modern artist, those with fashion brand or designer, those with other field brand than fashion, and those with the public star. They were processed into such a form as development of new product and collection, shop display, and exhibition event. The value could be drawn from this case examination of Marc Jacobs' fashion collaboration, which includes the design innovation through reinterpretation of tradition, innovation of maximized brand value, and transboundary innovation toward a vast extension of realm. Namely, the collaboration of Marc Jacobs would be the driving force for design innovation and the creative process for both parties concerned through endless cooperation and would generate the innovative value for fashion field.
Professional coffee shops are trying to increase customers' satisfaction and to invite more customers by providing the differentiated services. The existing researches show that the effects which the physical environment in shops has on customers' satisfaction and word of mouth intention are appealing to people's attention. In comprehensively examining the studies related to the physical environment, they can be summarized into two main perspectives, that is, the direct effect that the physical environment has on customers' satisfaction, quality perception, and other customers' responses (purchase desire, revisit intention, etc.) and the indirect effect that the physical environment has on customers' responses by means of customers' emotion or value perception. This research established 4 hypotheses by sampling 321 customers of those who have visited professional coffee shops, and empirically analyzed them. The empirical analysis carried out the structure analysis of covariance by using SPSS 17.0 statistics package and AMOS 17.0. As a result of the hypothesis qualification, the other hypotheses excluding one little hypothesis were adopted. The one refused hypothesis is that the only symbolism of the environmental elements in shops doesn't influence the customers' emotion positively (+). This is considered as a very unexpected result, and yet many customers who visit coffee shops express the symbols of professional coffee shops using the expressions such as 'bean coffee shop' or 'star coffee shop', but these expressions seem not to influence customers' mind positively in practice.
Journal of the Korea Academia-Industrial cooperation Society
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v.18
no.2
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pp.456-464
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2017
These days, the sports industry and related industries are growing very fast due to active sports participation. Recently, tourism products that integrate tourism with sport have already appeared. The products include tourism behavior, such as sports activities, sports spectating, and visiting sports memorial halls and museums, etc. This study examined the relationship among the tourist behavior, sports spectating factors, and team association components. Based on the theoretical study, a field survey was performed by questionnaires. The sports spectating factors and team association components have a slight influence on the tourist behavior after analysis using the SPSS program. The implications are as follows. First, sports teams should make efforts not only on the team's win at the sports game, but also to develop marketing strategies about the sports complex, and star players of their team. Second, sports teams have to develop tourist products that collaborate with the local tourism industry linked to tourist attractions, accommodations, souvenir shop, and entertainment facilities for sports spectators.
Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used
. Past studies to improve CF performance typically used additional information other than users' evaluations such as demographic data. Some studies applied SNA techniques as a new similarity metric. This study is novel in that it used SNA to separate dataset. This study shows that performance of CF can be improved, without any additional information, when SNA techniques are used as proposed. This study has several theoretical and practical implications. This study empirically shows that the characteristics of dataset can affect the performance of CF recommender systems. This helps researchers understand factors affecting performance of CF. This study also opens a door for future studies in the area of applying SNA to CF to analyze characteristics of dataset. In practice, this study provides guidelines to improve performance of CF recommender systems with a simple modification.
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