• Journal of the Korea Society of Computer and Information
• /
• v.29 no.6
• /
• pp.223-233
• /
• 2024

This study investigates the impact of personalization recommendation systems on customer loyalty in e-commerce, focusing on the role of information presentation, system interaction, and social community functions. It examines how these elements influence flow state, word of mouth (WOM), and repurchase intention (RPI). Using structural equation modeling (SEM) and data collected from 500 respondents in SPSS and AMOS, the study finds that all three personalization aspects significantly enhance flow state, which, in turn, positively affects WOM and RPI. System interaction directly boosts both WOM and RPI, while information presentation and social community functions influence only one of these loyalty measures. Flow state mediates the relationship between personalization factors and loyalty outcomes. These findings suggest e-commerce platforms should enhance system interaction and embed social community features to foster customer loyalty.

• International Journal of Advanced Culture Technology
• /
• v.8 no.4
• /
• pp.263-270
• /
• 2020

The growth of the mobile app markets has made it popular among people who recommend relevant information about restaurants. The recommendation service app based on AI Chatbot is that it can efficiently manage time and finances by making it easy for restaurant consumers to easily access the information they want anytime, anywhere. Eating out consumers use smartphone applications for finding restaurants, making reservations, and getting reviews and how to use them. In addition, social attention has recently been focused on the research of AI chatbot. The Chatbot is combined with the mobile messenger platform and enabling various services due to the text-type interactive service. It also helps users to find the services and data that they need information tersely. Applying this to restaurant recommendation services will increase the reliability of the information in providing personal information. In this paper, an artificial intelligence chatbot-based smartphone restaurant recommendation app using personalization information is proposed. The recommendation service app utilizes personalization information such as gender, age, interests, occupation, search records, visit records, wish lists, reviews, and real-time location information. Users can get recommendations for restaurants that fir their purpose through chatting using AI chatbot. Furthermore, it is possible to check real-time information about restaurants, make reservations, and write reviews. The proposed app uses a collaborative filtering recommendation system, and users receive information on dining out using artificial intelligence chatbots. Through chatbots, users can receive customized services using personal information while minimizing time and space limitations.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2011.01a
• /
• pp.75-79
• /
• 2011

본 논문에서는 센서를 활용하여 개인의 위치 및 상황 정보를 수집하고 패턴을 분석하여 이에 따라 동적으로 서비스를 제공하는 상황인식 TV 프로그램 추천 및 제어 시스템(CAPUS)을 제안하였다. 상황인식기반 TV 응용서비스를 위하여 개인화(Personalization)기술에 적용을 할 수 있는 사례로 TV채널 추천을 예로 실험하였다. CAPUS는 유비쿼터스의 큰 축이라 할 수 있는 개인화기술을 구현할 수 있는 시스템으로 그 규모가 무척 크며 방대하다 할 수 있다. 본문에서 제안한 CAPUS는 사용자의 정보를 수집하는 에이전트, 분석하는 에이전트, 필터링하는 에이전트 등 다양한 소프트웨어와 알고리즘이 필요하다. 사용자의 정보를 동적으로 수집 및 분석하고 생성한 후에 이를 활용하여 사용자에게 다시 서비스를 제공하는 기술이 CAPUS의 핵심이라 할 수 있다. 데이터의 분석을 통해 비슷한 행동이나 상황을 파악할 수 있으며 사용자에게 맞는 서비스를 제공할 수 있게 된다.

• Journal of Information Technology Services
• /
• v.9 no.2
• /
• pp.21-42
• /
• 2010

As digital convergence and mobile services evolve, personalization becomes one of the most important factors attracting customers. Personalization means functions offering individually customized services with relevant contents using information on individual preferences. This sort of personalized services has attracted great attention of a large part of online firms. One of representative services of such personalized services is a mobile widget service. In this study, we identified seven antecedents affecting the quality of personalized mobile widget services and empirically investigated which antecedent has a significant effect of the quality of personalized mobile widget services. In addition we carried out empirical investigation into the effect of the quality of personalized mobile widget service on user satisfaction and trust. As a result of this research, we revealed that seven variables including information services affected components of personalized services, and usefulness and perceived benefit as components of personalized services affected user trust and satisfaction for personalized services.

• Journal of the Korean Society for information Management
• /
• v.20 no.4 s.50
• /
• pp.113-134
• /
• 2003

With SDI service provided in libraries and information centers traditionally, this paper studies component technologies and structure of system platform in PIS(personalization information service based on the customized information service served currently in some institutions. The PIS system should provide relevant information as an output through the learning system analyzing user information searching behavior as an input value with personal profile information. To do it, this paper studies requirements and algorithms to develop PIS, and proposes learning system and recommendation system as core components in PIS.

• The Journal of Society for e-Business Studies
• /
• v.3 no.2
• /
• pp.95-112
• /
• 1998

With the advent and proliferation of the Internet, Electronic Commerce(EC) on the Internet has become one of the most rapidly growing area and has been the subject of much research lately. EC is commercial transactions using computers in virtual environment through computer networks. The computer system deals with various ranges of things such as products, services, and information on EC. In this paper we describe the construction methods of web site based on the personalization, Also, we present the personalization technology and architecture of the P-Commerce proposed in this paper. Finally, we describe the methods constructing EC site using P-Commerce solution.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.3 s.35
• /
• pp.101-110
• /
• 2005

A virtual locator is a logical locator based on the contents of a physical locator. These contents can be existing member properties in the physical locator. Using virtual locator, we can accomplish personalization which is the technology area associated most often with CRM. In this study, however, what are called virtual locators in many OLAP models would be treated as physical locators for many unique aggregation levels. By using physical locators, we can bring a successful e-business.

• Asia pacific journal of information systems
• /
• v.30 no.2
• /
• pp.252-283
• /
• 2020

Online retail is a growing opportunity for retailers and consumers. Cross-buying provides companies with an opportunity to increase their revenue contributions from existing consumers. In many fields, especially in the service sector, cross-selling is an easier strategy to use relative to increasing revenue rather than acquiring new consumers. Website personalization has been a powerful indispensable tool for web-based companies and end users. Using the Mehrabian and Russell's Stimulus-Organism-Response framework, we experimentally examined how an online retailing merchant's environmental stimuli (S) arouses internal affective and cognitive states (O), that affect consumers' approach-avoidance behavior (R) in cross-buying and shopping cart abandonment in online transactions.

• Science of Emotion and Sensibility
• /
• v.20 no.2
• /
• pp.59-72
• /
• 2017

In the flood of information, many consumers want to choose the style that is suitable for their sensibility, which is usefulness and need for personalized services have been steadily increasing. This study made a video of personalized internet shopping mall and then university students (N=170) who have been using the internet shopping mall were asked to experience this and the change in consumer response was measured. According to level of personalization, this study found difference of web-site evaluation, satisfaction/internet behavior and quality evaluations of products. With regard to preferred types of internet shopping malls and the number of access, the difference was investigated. The results are as follows. First, subjects who experienced internet shopping mall of active personalization showed higher level of active personalization. Level of passive personalization differed depending on preferred types of internet shopping malls, for example, people who prefer online apparel shopping mall were low but people who prefer complex big shopping mall and social commerce were high. Second, after experiencing internet shopping mall of active personalization, satisfaction/internet behavior and quality evaluations of products did not change but passive personalization decreased and active personalization and web-site evaluation increased. Third, the number of access to internet shopping mall positively correlated with satisfaction/internet behavior and web-site evaluation, on the other hand, active personalization negatively correlated with satisfaction/internet behavior and web-site evaluation.

• Convergence Security Journal
• /
• v.8 no.4
• /
• pp.167-179
• /
• 2008

As ubiquitous technology develops, there are many studies to provide various contents proper to users through a mobile device. However, there is a limit of information provision due to a small user interface of a mobile device. This study proposes a system that can solve a problem and provide an intelligent agent model appropriate to a mobile environment and job information positively that an individual user is interested. It is composed of a personalization engine to monitor users' behavior patterns and a learning algorithm to provide information to a mobile device. Analysis shows that preferred job items are different by sex, age and education, while a region affects job searching significantly.