• Journal of Global Scholars of Marketing Science
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• v.15 no.2
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• pp.1-25
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• 2005

Unlike the traditional bricks-and-mortar marketplace, the online environment includes several distinct factors that influence Web site trust. As consumers become more savvy about the Internet, the author contends they will insist on doing business with web companies they trust. This study examines 1) how Web site trust is affected by the following web purchase-related factors: security, privacy, brand name, word-of-mouth, good online experience, and quality of information, and 2) how it influences outcomes. Unlike Urban and colleagues' study (2000), the author argues that not all e-trust bUilding programs guarantee success in building Web site trust. In addition to the mechanism depending on a program, building e-brand trust requires a systematic relationship between a consumer and a particular web site. The findings show that Web site trust does not build one or two components but are established by the interrelationships of complex components. By carefully investigating these variables in formulating marketing strategies, marketers can cultivate brand loyalty and gain a formidable competitive edge.

• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.100-107
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• 2008

The aim of this paper is to design an intelligent character manipulation system suitable for the wireless broadband network environment named as Wibro and for the recent social networking service (SNS). The main feature of our proposed system is an automatic synthesis of a character utilizing the meta data which is attached to each component stored in a character database. It is the second advantageous feature that a user can make or modify his or her own character by modifying the component animation clip of its character. Once the character database is created, it can be represented and utilized in several ways by utilizing the meta data which is related to personal properties including emotion, life style, favorite things, and so on. The system can be evolved to a more powerful one by adopting the more user-related information and the more intelligent synthesis module.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.89-115
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• 2019

This study was conducted to present the stylistic differences between Arthur Conan Doyle and Agatha Christie, famous as writers of classical mystery novels, through data analysis, and further to present the analytical methodology of the study of style based on text mining. The reason why we chose mystery novels for our research is because the unique devices that exist in classical mystery novels have strong stylistic characteristics, and furthermore, by choosing Arthur Conan Doyle and Agatha Christie, who are also famous to the general reader, as subjects of analysis, so that people who are unfamiliar with the research can be familiar with them. The primary objective of this study is to identify how the differences exist within the text and to interpret the effects of these differences on the reader. Accordingly, in addition to events and characters, which are key elements of mystery novels, the writer's grammatical style of writing was defined in style and attempted to analyze it. Two series and four books were selected by each writer, and the text was divided into sentences to secure data. After measuring and granting the emotional score according to each sentence, the emotions of the page progress were visualized as a graph, and the trend of the event progress in the novel was identified under eight themes by applying Topic modeling according to the page. By organizing co-occurrence matrices and performing network analysis, we were able to visually see changes in relationships between people as events progressed. In addition, the entire sentence was divided into a grammatical system based on a total of six types of writing style to identify differences between writers and between works. This enabled us to identify not only the general grammatical writing style of the author, but also the inherent stylistic characteristics in their unconsciousness, and to interpret the effects of these characteristics on the reader. This series of research processes can help to understand the context of the entire text based on a defined understanding of the style, and furthermore, by integrating previously individually conducted stylistic studies. This prior understanding can also contribute to discovering and clarifying the existence of text in unstructured data, including online text. This could help enable more accurate recognition of emotions and delivery of commands on an interactive artificial intelligence platform that currently converts voice into natural language. In the face of increasing attempts to analyze online texts, including New Media, in many ways and discover social phenomena and managerial values, it is expected to contribute to more meaningful online text analysis and semantic interpretation through the links to these studies. However, the fact that the analysis data used in this study are two or four books by author can be considered as a limitation in that the data analysis was not attempted in sufficient quantities. The application of the writing characteristics applied to the Korean text even though it was an English text also could be limitation. The more diverse stylistic characteristics were limited to six, and the less likely interpretation was also considered as a limitation. In addition, it is also regrettable that the research was conducted by analyzing classical mystery novels rather than text that is commonly used today, and that various classical mystery novel writers were not compared. Subsequent research will attempt to increase the diversity of interpretations by taking into account a wider variety of grammatical systems and stylistic structures and will also be applied to the current frequently used online text analysis to assess the potential for interpretation. It is expected that this will enable the interpretation and definition of the specific structure of the style and that various usability can be considered.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.165-178
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• 2017

O2O platforms are developing in a business area of daily life with evolution of IT technology. The aim of this research is to identify any quality factor of online and offline which affects the satisfaction of O2O service by business characteristic and to varify the relationship between service satisfaction and reuse intention. In this study, information quality, system quality and service quality are defined as factors for online quality and perceived quality and perceived price defined as offline quality. This study was conducted on 199 users who use O2O service. The results showed that online quality system and perceived price of offline quality had a positive effect on user satisfaction and that user satisfaction had a positive effect on Intention to Reuse. These results will provide guidelines for O2O service providers to improve their online services and to select an offline vendor for the O2O platform. It would provide customized O2O service according to personal property of a customer, in case that further research by types of business or service, which are not covered this paper.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11c
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• pp.1819-1822
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• 2002

OLAP(On-line Analytical Processing)은 데이터를 다차원적으로 집계하여 그 결과를 온라인으로 사용자에게 제공함으로써 고부가가치 창출에 사용되는 비즈니스 인텔리젼스 기술 중의 하나이다. 질의 처리 시간 제약 조건을 만족하기 위해 OLAP 시스템들은 다차원적 집계 결과를 미리 계산하여 저장해 둔다. 이 때 저장되는 데이터를 OLAP 큐브(cube)라고 하며, 데이터의 분석은 주로 큐브를 브라우징하면서 이루어진다. 본 연구에서는 웹 서비스를 통해 큐브를 브라우징할 수 있는 ‘웹 OLAP 큐브 브라우저(WOCB)'를 개발하였다. WOCB는 본 연구팀이 개발한 웹 서비스 기반의 OLAP API인 XMLMD를 사용하여 개발되었으며, 웹 서비스를 통해 전송되는 OLAP 큐브 데이터를 XML, HTML, 엑셀, 그래프 등의 다양한 형태로 검색할 수 있는 기능을 제공한다. 본 연구 결과는 이기종 플랫폼 환경에 분산되어 있는 OLAP 서버들을 통합할 때 하나의 컴포넌트로 사용될 수 있다는 장점을 갖는다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.373-375
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• 2000

B2B, B2C, B2G, C2C로 구체화된 전자 상거래는 관련 국제 컨소시엄이 구축되고 그 유형에 있어서도 경매, 교환, 직구매, 입찰 등으로 다양해지는 등 이미 차세대 기업 비즈니스 모델로서의 위치를 확고히 하고 있고, 나아가 차별화 된 솔루션으로서 점원이 있는 시장, 실시간 인터넷 대금 납부 등의 서비스들이 국내외적으로 많이 모색되고 있는 실정이다. 본 논문에서는 비교쇼핑 에이전트를 지원하는 B2C 솔루션(ISPA:mIn Seon comparison Agent)을 제안하고 있는데, 비교 쇼핑 에이전트 역시 그러한 노력의 일례로서 이는 동종의 상품을 취급하는 여러 몰 간에도 그 제시 가격이 서로 다른 것에 착안하여 최저가격을 제시하는 사이트를 안내하는 기능을 한다. ISPA는 현 업계에서 웹 기반 시스템의 솔루션으로서 각광 받고 있는 EJB를 플랫폼으로 하며, 각 정보소스에 대한 정보 추출 규칙을 활용해서 온라인으로 비교 정보를 제공하는 종래의 인공지능의 접근과는 달리 J2EE 웹 개발 기술을 이용하여 오프라인으로 비교 정보를 구축하는 웹 기반 시스템으로써 에이전트를 지원한다. 나아가 핵심 클래스인 상품 클래스를 메타 데이터의 부분집합으로써 정의하는 기법을 적용하였는데 이는 개체 지향 패러다임의 시스템 구축 시에 전략적으로 응용될 수 있다.

• Distribution Business Review
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• no.3
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• pp.3-23
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• 2003

미국은 이테일링(E-tailing)이 발달된 국가이며 특히 의류 분야는 초반의 부진을 딛고 꾸준히 성장하여 온라인쇼핑분야에서 커다란 품목 중의 하나로 자리잡고 있다. 한국도 의류 분야의 이태일링이 최근 눈에 띄는 성장을 거두고 있는데 마케팅방향이나 내부적인 운영시스템등에서 미국과는 다른 모습을 보이고 있다. 이는 각자 다른 환경 속에서 다른 산업 기반을 토대로 정장하였기 때문이며 미국의 경우는 여러 면에서 이테일링이 성공할만한 조건과 토대를 이미 가지고 있었다고 볼 수 있다. 한국은 소비자와의 직접적인 거래 자체에 초점을 맞추고 있는 반면 미국은 판매 이외에 넓은 땅덩어리에 산재해 있는 단위들을 효율적으로 운영하는 후방부의 투자 및 연구가 활발히 진행 중에 있다. 넓은 시장 운영에 유리한 시스템을 갖추고 있는 미국의 현황을 살펴봄으로써 앞으로 세계화가 절실히 요구되는 의류 산업환경에 능동적으로 대처 할 수 있도록 제언을 제시하였다.

• Distribution Business Review
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• no.3
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• pp.121-139
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• 2003

최근 내수경기의 불황에도 불구하고 지속적인 고성장세를 보이고 있는 TV홈쇼핑 시장에 대한 산업 전체적인 측면에서 경쟁요인을 분석하였다. 그 결과로써 정부와 업계에 향후 TV 홈쇼핑 시장의 발전 방향을 제시하고 국내 유통시장의 발전추세와 구조적 특성을 파악함으로써 정책적인 제언을 하고자 한다. 이를 위해 TV홈쇼핑 시장의 경쟁요인을 외부경쟁요인과 내부경쟁요인으로 분류하였다. 구체적으로 외부경쟁요인은 업태 특징에 의한 경쟁요인과 국내ㆍ외적 유통산업 변화추세에 따른 경쟁요인으로, 내부경쟁요인은 CATV 시청자구수의 변화, 신규사업자 진출, 시장집중도, 수익률 향상 전략, SO채널확보 및 투자 인터넷쇼핑몰 운영 등으로 분류하여 분석하였다. 이러한 TV 홈쇼핑 시장의 내부ㆍ외부경쟁요인의 도출을 통해 업계에는 효율적인 전략의 일환으로 인터넷쇼핑몰의 매출비중확대, M-Commerce와 B2B 전자상거래 부분으로의 사업확대, 온라인과 오프라인의 연계방안 강구를 통한 틈새시장개발, 고객정보 확보를 통한 CRM, SCM 활용 및 개발 등을 제시하고, 정부에는 업체간 경쟁유발을 통한 소비자의 편익증대, 경쟁확대로 인한 소비자 피해최소화, 유통 인프라에 대한 투자확대 및 제도 보완 등을 정책방향으로 제시하고자 한다.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.353-367
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• 2003

본 연구에서는 중소기업들이 중견기업으로 성장할 때까지 필요로 하는 경영, 자금, 기술, 마케팅, 물류 등 Total Solution 차원의 중소기업지원시스템 중 마케팅ㆍ유통과 관련 협력상거래(collaborative commerce)라는 개념을 도입하여 오프라인과 온라인이 결합되어 대전ㆍ충남 중소기업간의 협력, 제휴를 지원하고, 나아가 대기업, 학계, 벤처캐피탈들이 참여하여 교류할 수 있는 정보공유와 만남의 장을 제공함으로써, 협력상거래 포탈 사이트를 구축하기 위한 이론적 모형을 제시ㆍ구축하고자 한다. 협력상거래 포탈의 기술적 정의는 중소기업간에 인터넷을 통하여 마케팅ㆍ유통과 관련한 기업핵심정보와 비즈니스 프로세스를 공유함으로써 효율적인 협업 전자상거래를 가능하게 하는 모든 기술적 요소의 집합이라 할 수 있다. 협력상거래 포탈의 협업적 프레임워크 기능 요구사항은 \circled1Integration of product ＆ process information, \circled2Extensibility and flexibility of framework, \circled3Platform independence, \circled4Interdependence and modularity of services, \circled5Interoperability among services, \circled6Accessibility of legacy system(ERP, SCM, CRM) 등이다.