• Journal of the Korean Society of Clothing and Textiles
• /
• v.46 no.5
• /
• pp.868-889
• /
• 2022

Fashion companies are using a big data approach as a key strategic analysis to predict and forecast sales. This study investigated the effectiveness of the past sales, web search volume, information amount, brand promotion, and the advertising endorser on the sales forecasting model. The study conducted the autoregressive distributed lag (ARDL) time series model using the internal and external social big data of a national fashion brand. Results indicated that the brand's past sales, search volume, promotion, and amount of advertising endorser information amount significantly affected the sales forecast, whereas the brand's advertising endorser search volume and information amount did not significantly influence the sales forecast. Moreover, the brand's promotion had the highest correlation with sales forecasting. This study adds to information-searching behavior theory by measuring consumers' brand involvement. Last, this study provides digital marketers with implications for developing profitable marketing strategies on the basis of consumers' interest in the brand and advertising endorser.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.46 no.4
• /
• pp.638-656
• /
• 2022

This study aimed to identify characteristics of Generation MZ's consumer purchase decision journey to develop the new fashion CDJ model. The initial stage was affected by habit, online community, social media, aesthetics, circumstantial need, and proxy. In the search and consideration stage, mobile channels were used actively. In the active search and evaluation stage, online media, experiential data, and personal information were employed. In the purchase stage, zoomers took plenty of time in search and evaluation before spending, contrary to millennials who made their purchases more quickly. In the post-purchase experience stage, zoomers actively displayed follow-up behaviors depending on their satisfaction, such as retaining or deleting the app. While, millennials did not turn away from the store or brand, but followed up on their purchases even when they had an unsatisfactory experience. Based on the characteristics of CDJ, iterative cycle CDJ models were developed. Zoomers CDJ model was presented as a search loop that consists of the search and evaluation process, in which information accumulates, and a purchase loop in which the actual purchase occurs. The iterative cycle CDJ model was presented connected to the loyalty loop as the main section, which is accelerated in millennials' CDJ model.

• Korean Journal of Social Welfare
• /
• v.62 no.2
• /
• pp.209-233
• /
• 2010

The purpose of this study is to understand the 'search' experiences of adoptive families. To understand their experiences in searching for birth families, the researchers made contacts with adoptive families who had tried the search before, got informed consents from them, and took in-depth interview with each family. The qualitative case study approach was taken to analyze the data collected. Data collected from five adoptive families were employed for within-case analysis and cross-case analysis. The themes emerged from cross-case analysis were 'the awareness of being adopted', 'curiosity explosion', 'the anxious waiting', 'the moment the truth was found', 'Indeed, I'm a real mom', and 'Then, there was a silence'. Based on the results of the study, the policy and practical guidelines to support the search of adoptive families were suggested. Also, the suggestions for the following studies were made to obtain more abundant information beyond the limitations of the study.

• Health Policy and Management
• /
• v.27 no.3
• /
• pp.241-246
• /
• 2017

Background: The purpose of this study is to investigate the trends on the induced abortion in Korea using social big-data and confirm whether there was time series trends and seasonal characteristics in induced abortion. Methods: From October 1, 2007 to October 24, 2016, we used Naver's data lab query, and the search word was 'induced abortion' in Korean. The average trend of each year was analyzed and the seasonality was analyzed using the cosinor model. Results: There was no significant changes in search volume of abortion during that period. Monthly search volume was the highest in May followed by the order of June and April. On the other hand, the lowest month was December followed by the order of January, and September. The cosinor analysis showed statistically significant seasonal variations (amplitude, 4.46; confidence interval, 1.46-7.47; p< 0.0036). The search volume for induced abortion gradually increased to the lowest point at the end of November and was the highest at the end of May and declined again from June. Conclusion: There has been no significant changes in induced abortion for the past nine years, and seasonal changes in induced abortion have been identified. Therefore, considering the seasonality of the intervention program for the prevention of induced abortion, it will be effective to concentrate on the induced abortion from March to May.

• Korean Journal of Social Welfare Studies
• /
• v.41 no.4
• /
• pp.369-393
• /
• 2010

This study examines the factors influencing Korean international adoptee's search for their birthparents. Considering that the search for birthparents is general needs for adoptees, Korean government should support their searching activities and, first of all, understand their characteristics. The research model was constructed based on the results of previous studies, and the data set of conducted by ministry of health and welfare was reanalyzed for this study. The subjects of the survey were Korean-born adoptees (who are more than 16 years old) in North America, Europe, and Australia. The research questionnaire was translated to English and French, and the survey was conducted on line. A total of 290 questionnaires were included in the analysis. Since survey was conducted on line, the missing rate of the data was relatively high. So, multiply imputed five data sets were used for analysis. Among the variables included in research model, the age group of adoptees, experience of identity crisis in their life, the first time when they became actively interested in Korean roots, the age at the time of adoption, and the attitudes of adoptive parents toward their search were significantly related to their search for birthparents. Adoptees in the age group of 30~34 had more actively participated in search compared to their reference group (which is the age group of more than 35 years old). The earlier they became actively interested in Korean roots, they tended to be more active in searching activities. Also, the experience of identity crisis in life and the age at the time of adoption were positively related to their search. Although most of adoptive parents have supported their search, the adoptees who reported that they didn't know their adoptive parents' attitude toward search, or their parents deceased had more actively participated in search for their birthparents. Some implications for adoption policy and practice were discussed based on the results of the study.

• Journal of information and communication convergence engineering
• /
• v.9 no.3
• /
• pp.325-330
• /
• 2011

Due to the wide growth and popularity of social network website, large numbers of users discover these social network sites are a place where they can be able to spend their leisure time sharing interests, sharing ideas freely, sharing personal experience, and also to search for new friends or partners. These websites give an opportunity for its users to socialize with new people and to keep in touch or reconnect with current or old friends and families across disperse continents, which traditionally replace the common traditional methods. These social network websites need accurate and careful investigations and findings on the usability issues for effective interactivity and more usability. However, little research might have previously invested on the usability of these social network websites. Therefore, we propose a new framework to study and test the usability of these social network sites. We namely call our framework "Interactivity". This framework will enable developers to assess the usability of the social network sites. It will provide an overview of the user's behavior while interacting in these social network websites. Performance of the framework will be performed using Camtasia software. This software will entirely capture the interactivity of users including the screen and the movements, which the screen and the motion of the user action will undergo to analysis at the end of our research.

• Asian Journal of Business Environment
• /
• v.8 no.4
• /
• pp.17-27
• /
• 2018

Purpose - Current study aimed at investigating the symbolic and evaluation relevance to global luxury brands as the causes of inducing social identity verification, and also explored whether the social identity verification will affect the attitude toward the brands. Research design, data, and methodology - 323 questionaries from Chinese consumers were used to test hypotheses by structural equation model of AMOS 22.0. Results - First, social identity verification positively affected on the brand attitude. Second, both the symbolic relevance and the evaluation relevance positively affected on social identity verification. Third, the mediation roles of social identity verification were identified. Social identity verification played a full mediation role in the effect of the symbolic relevance on the brand attitude, and played a partial mediation role in the effect of the evaluation relevance on the brand attitude. Conclusions - This study could contribute to the advancement of theory concerned with the roles of consumers' social identity verification which induces positive attitude toward the global luxury brands. Global brand managers in China should try to search ways by which consumers can feel both the symbolic relevance and evaluation relevance to their luxury brands, and should make efforts to improve the symbolic relevance and evaluation relevance to their brand.

• Journal of Digital Convergence
• /
• v.17 no.12
• /
• pp.255-260
• /
• 2019

Real-time search keywords are not only limited to search keywords that are rapidly increasing interest in real-time, but also have a limitation that they are difficult to determine the sustainability as there is a difference in ranking between portal sites. Estimating sustainability for real-time search keywords is significant in terms of overcoming these limitations and providing some predictability. In particular, long-term search keywords that last for more than a month are of high value as long-lasting social issues. Therefore, in this paper, we analyze the interest based on the ranking of the real-time search keywords and the duration based on sustained weeks, days and hours of real-time search keywords by each portal site and the integrated portal site, and then estimating sustainability based on high level of interest and duration, and present a method to derive real-time search issues with high long-term sustainability.

• Journal of Intelligence and Information Systems
• /
• v.14 no.1
• /
• pp.67-84
• /
• 2008

This paper proposes a design and realization for the semantic search system. The proposed model includes three Architecture Layers of a Semantic Search System ; (they are conceptually named as) the Knowledge Acquisition, the Knowledge Representation and the Knowledge Utilization. Each of these three Layers are designed to interactively work together, so as to maximize the users' information needs. The Knowledge Acquisition Layer includes index and storage of Semantic Metadata from various source of web contents(eg : text, image, multimedia and so on). The Knowledge Representation Layer includes the ontology schema and instance, through the process of semantic search by ontology based query expansion. Finally, the Knowledge Utilization Layer includes the users to search query intuitively, and get its results without the users'knowledge of semantic web language or ontology. So far as the design and the realization of the semantic search site is concerned, the proposedsemantic search system will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.93-111
• /
• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.