• Title/Summary/Keyword: DB marketing

Search Result 45, Processing Time 0.023 seconds

A Study on Analyzing out the Key Tasks and Developing the Professional Type of National Librarians through Job Analysis (직무분석을 통한 국립중앙도서관사서의 핵심업무 및 전문사서 유형 개발에 관한 연구)

  • Ahn, In-Ja;Hoang, Gum-Sook;Noh, Young-Hee
    • Journal of the Korean Society for information Management
    • /
    • v.25 no.1
    • /
    • pp.129-148
    • /
    • 2008
  • Analyzing out the Key Tasks and Developing the Professional Type of National Librarians through Job Analysis was made, because improving the professionalism of librarians is the strategy of survival in the competency based society. It is composed of 22 duties, 216 tasks of national librarian job and 96 key tasks is extracted among them. As the results, 12 types of professional librarian which is composed 10 function oriented types, and 2 user oriented types, is suggested: collection development librarian, cataloger taxonomist, information service librarian, reading coach, research librarian of international standards, database & system manager, international work librarian, national support librarian, marketing librarian, library literacy librarian, children' librarian, handicapped service librarian.

Current CRM Adoption in Korean Apparel Industry (국내 의류업체의 CRM 도입현황)

  • Ko, Eun-Ju
    • Journal of the Korean Society of Clothing and Textiles
    • /
    • v.30 no.1 s.149
    • /
    • pp.1-11
    • /
    • 2006
  • The purpose of this study was to analyze the current CRM situation in Korean apparel industry. Specifically, research purposes were 1) to examine the concepts and benefits of CRM, 2) to examine CRM strategies, 3) to analyze CRM system(i.e., customer relationship management service, customer segmentation criteria, DB management system), and 4) to analyze the potential problems and CRM adoption plan. The subjects for this research were thirty CRM managers in Korean apparel firms classified by the company type(woman's wear, man's wear, casual wear, children's wear, retailer) interviewed from December 2003 to March 1004. The results of this study were as follows: First, the concept of CRM represented the prime customer relationship, continuous consideration, and customer management system. The benefits of CRM reflected re-sales, improvement of profit share, and acquisition of customer's data base. Second, concerning the CRM strategies, most companies focused on persistent customer management through mileage program, membership cards and also implemented product strategies such as demand forecasting, customization based on customer data analysis. We also found that industry preferred to use pricing strategies, for example, segmentation of customer through discrepancies of price in which customers are provided by discount and gift voucher services. Regarding distribution strategy, channel diversification, localized service, and convenient delivery system were used. As promotion strategies, they chose celebrating customers' personal events and promoting cultural events and issuing coupons. Third, regarding CRM system, information service was the most frequently adopted, important and highly beneficial category. Also POS/web-POS, homepage were main sources of information. RFM is the mostly commonly used customer segmentation criteria. Fourth, potential problems in CRM adoption were lack of CRM knowledge and performance measurement of CRM. Future CRM adoption plan included CRM education and development of CRM performance measures.

A Study of the Curriculum Operating Model and Standard Courses for Library & Information Science in Korea (한국문헌정보학 교과과정 운영모형 및 표준교과목 개발에 관한 연구)

  • Noh, Young-Hee;Ahn, in-Ja;Choi, Sang-Ki
    • Journal of the Korean Society for Library and Information Science
    • /
    • v.46 no.2
    • /
    • pp.55-82
    • /
    • 2012
  • This study seeks to develop a curriculum operating model for Korean Library and Information Science, based on investigations into LIS curricula at home and abroad. Standard courses that can be applied to this model were also proposed. This study comprehensively analyzed the contents of domestic and foreign curricula and surveyed current librarians in all types of library fields. As a result, this study proposed required courses, core courses, and elective courses. Six required LIS courses are: Introduction to Library and Information Science, Information Organization, Information Services, Library and Information Center Management, Information Retrieval, and Field Work. Six core LIS courses are: Classification & Cataloging Practice, Subject Information Resources, Collection Development, Digital Library, Introduction to Bibliography, and Introduction to Archive Management. Twenty selective LIS courses include: the General Library and Information Science area (Cultural History of Information, Information Society and Library, Library and Copyright, Research Methods in Library and Information Science), the Information Organization area (Metadata Fundamentals, KORMARC Practice), the Information Services area (Information Literacy Instruction, Reading Guidance, Information User Study), the Library and Information Center Management area (Library Management, including management for different kinds of libraries, Library Information Cooperator, Library Marketing, Non-book Material and Multimedia Management (Contents Management), the Information Science area (Database Management, including Web DB Management, Indexing and Abstracting, Introduction to Information Science, Understanding Information Science, Automated System of Library, Library Information Network), and the Archival Science area (Preservation Management).

Research Direction for Functional Foods Safety (건강기능식품 안전관리 연구방향)

  • Jung, Ki-Hwa
    • Journal of Food Hygiene and Safety
    • /
    • v.25 no.4
    • /
    • pp.410-417
    • /
    • 2010
  • Various functional foods, marketing health and functional effects, have been distributed in the market. These products, being in forms of foods, tablets, and capsules, are likely to be mistaken as drugs. In addition, non-experts may sell these as foods, or use these for therapy. Efforts for creating health food regulations or building regulatory system for improving the current status of functional foods have been made, but these have not been communicated to consumers yet. As a result, problems of circulating functional foods for therapy or adding illegal medical to such products have persisted, which has become worse by internet media. The cause of this problem can be categorized into (1) product itself and (2) its use, but in either case, one possible cause is lack of communications with consumers. Potential problems that can be caused by functional foods include illegal substances, hazardous substances, allergic reactions, considerations when administered to patients, drug interactions, ingredients with purity or concentrations too low to be detected, products with metabolic activations, health risks from over- or under-dose of vitamin and minerals, and products with alkaloids. (Journal of Health Science, 56, Supplement (2010)). The reason why side effects related to functional foods have been increasing is that under-qualified functional food companies are exaggerating the functionality for marketing purposes. KFDA has been informing consumers, through its web pages, to address the above mentioned issues related to functional foods, but there still is room for improvement, to promote proper use of functional foods and avoid drug interactions. Specifically, to address these issues, institutionalizing to collect information on approved products and their side effects, settling reevaluation systems, and standardizing preclinical tests and clinical tests are becoming urgent. Also to provide crucial information, unified database systems, seamlessly aggregating heterogeneous data in different domains, with user interfaces enabling effective one-stop search, are crucial.

Visualizing the Results of Opinion Mining from Social Media Contents: Case Study of a Noodle Company (소셜미디어 콘텐츠의 오피니언 마이닝결과 시각화: N라면 사례 분석 연구)

  • Kim, Yoosin;Kwon, Do Young;Jeong, Seung Ryul
    • Journal of Intelligence and Information Systems
    • /
    • v.20 no.4
    • /
    • pp.89-105
    • /
    • 2014
  • After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.