• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.571-576
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• 2007

Advanced online environment and communication technology have made the e-commerce environments evolved rapidly. In the e-commerce area, one of the most important concepts regarding the relationship between seller and buyer is the "trust." Considering the purpose of purchase and satisfaction of website, the users may face problems such as consumer's transaction security or personal information sharing when they make transactions over web sites. It could be difficult to pursue the goal for the users to purchase product or service over online if the seller or service provider cannot establish trust to the customers. In this paper, through multi-dimensional viewpoints of trust, satisfaction can be accounted for by cue-based trust and experienced trust. The purchase intention mediates the experienced trust when online users purchase products or use online service.

• Journal of Korean Society for Quality Management
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• v.28 no.3
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• pp.133-144
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• 2000

Many organizations have developed their own information systems not only for internal efficiency but also for effectiveness of external customer services. One of the most effective service tools for their customers is the use of information technology. The web technology is rapidly becoming one of the most effective tools for online customer services. In order to gain competitive edge, organizations must have effective web site planning methods for their customer service. A study on traditional information systems planning methodologies has been conducted and they are compared with web site planning techniques. Cases of web sites in order to Improve customer relationship are analyzed. finally, a new conceptual framework for web site planning strategy for e-CRM is proposed in this paper. In order to support effective web site planning, online customer contact points and online service activities are defined and classified as several stages. And, web site strategies corresponding to each customer service activities are developed and proposed, With this framework, organizations can build competitive web strategies for improving their online customer relationships, thereby increasing customer satisfaction.

• The Journal of Information Systems
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• v.20 no.2
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• pp.21-36
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• 2011

The Web has become an excellent source for gathering consumer opinions. There are now numerous Web sites containing such opinions, e.g., customer reviews of products, forums, discussion groups, and blogs. This paper focuses on online customer reviews of products. It makes some contributions. Especially it proposes minimalism and chunking framework for analyzing and comparing consumer opinions of competing products. Users are able to clearly see the strengths and weaknesses of each product in the minds of consumers in terms of various product features. This comparison is useful to both potential customers and product manufacturers. For a product manufacturer, the comparison enables it to easily gather marketing intelligence and product benchmarking information. In this paper, we only focus on mining opinion/product features that the reviewers have commented on. Five types of online review presentations are presented to mine such features. Our experimental results show that these techniques are useful to identify customers' opinions and trends.

• Asia pacific journal of information systems
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• v.21 no.3
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• pp.1-18
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• 2011

Blog have become very popular with Internet users as one of the latest forms of online communication as well as knowledge sharing tools. However, blogs generate growing concerns regarding information privacy issues. This study, based on social exchange theory, presents results about bloggers' information sharing behavior. The 157 surveys are collected from a large university in the eastern U.S. The survey results indicate that trust which has four second order factors: economy based trust, trust in reciprocity, trust in other bloggers and trust in social interaction positively affects bloggers' information sharing behavior. However, online information privacy concerns have a negative impact on the relationship between trust and bloggers' information sharing behavior.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.1-21
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• 2015

This paper aims to assess the feasibility of a new and less-focused type of online sociability (the watching network) as a useful information source for personalized recommendations. In this paper, we recommend scientific articles of interests by using the shared interests between target users and their watching connections. Our recommendations are based on one typical social bookmarking system, CiteULike. The watching network-based recommendations, which use a much smaller size of user data, produces suggestions that are as good as the conventional Collaborative Filtering technique. The results demonstrate that the watching network is a useful information source and a feasible foundation for information personalization. Furthermore, the watching network is substitutable for anonymous peers of the Collaborative Filtering recommendations. This study shows the expandability of social network-based recommendations to the new type of online social networks.

• Management & Information Systems Review
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• v.26
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• pp.153-180
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• 2008

Most previous electronic commerce studies have focused on a single product or similar products. The effects of different product types have been relatively neglected. and so previous studies have limited the generalization. The purpose of this study was to explore the effects of different product types. The Internet product and service classification grid proposed by Peterson et al.(1997). A survey-based approach was employed to investigate the research questions. Regression analysis demonstrated that the determinants of online shopping acceptance differ among product or service types. As a result of analysis, personal innovativeness of information technology, perceived Web security, personal privacy concerns, and product involvement can influence consumer acceptance of online shopping, but their influence varies according to product or service types.

• The Journal of Information Systems
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• v.29 no.2
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• pp.173-195
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• 2020

Purpose The purpose of this study is to verify the effect of reviewer's attributes on review usefulness while exploring the variables that can moderate the relationship between reviewer's attributes and review usefulness through empirical analysis. Design/methodology/approach To understand the impact of online reviewer profiles on review usefulness and how these impacts change, this study collected more than 30,000 online reviews of restaurants through TripAdvisor.com, that is a representative OTA shares tourism information. We analyze the moderating effects of four variables such as review length, review equivocality, review uncertainty, and review readability. Findings According to the empirical analysis result, this study reveals that the reviewer's profile attribute can significantly improve the review usefulness of the reviewer, and confirmed the moderating effect of the review's attribute(Review length, Equivocality, Uncertainty, Readability).

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.145-152
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• 2015

We consider an online selective-sample learning problem for sequence classification, where the goal is to learn a predictive model using a stream of data samples whose class labels can be selectively queried by the algorithm. Given that there is a limit to the total number of queries permitted, the key issue is choosing the most informative and salient samples for their class labels to be queried. Recently, several aggressive selective-sample algorithms have been proposed under a linear model for static (non-sequential) binary classification. We extend the idea to hidden Markov models for multi-class sequence classification by introducing reasonable measures for the novelty and prediction confidence of the incoming sample with respect to the current model, on which the query decision is based. For several sequence classification datasets/tasks in online learning setups, we demonstrate the effectiveness of the proposed approach.

• Asia pacific journal of information systems
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• v.32 no.3
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• pp.514-536
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• 2022

Online reviews offer valuable information to businesses by reflecting consumer experiences about their products and services. Two crucial aspects of online reviews are the topics consumers choose to address, and the sentiments expressed in their reviews. Building upon previous literature that shows online reviews are context-dependent, we employ the Expectation-Confirmation Theory (ECT) to examine the impact of topic distribution on review sentiment in South Korea and the U.S. during pre- and post-pandemic periods. After applying a topic modeling to Airbnb app review data, we measure the contribution of each topic on review sentiment using SHAP values. Our results indicate variations in topic distribution trends between 2018 and 2021. In addition, the order and magnitude of topics' impact on review sentiment change between pre- and post-pandemic periods for both countries. This study can help businesses understand how topics and sentiments associated with their products and services changed after the pandemic and thus identify areas of improvement.

• Asia pacific journal of information systems
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• v.27 no.4
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• pp.216-232
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• 2017

This study's objective is to use the construal-level theory (CLT) to explore the effect of the utility of online travel reviews on tourists' perception. To accomplish this goal, online travel reviews are divided into two different categories based on concreteness, and the usefulness of each review is compared with the temporal dimension of psychological distance. The results show that close future tourists are more influenced by concrete reviews than abstract reviews; however, the far future tourists are more influenced by abstract reviews than concrete reviews. Based on these results, theoretical and practical implications are discussed, and suggestions are made for future research.