• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.1-20
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• 2018

Car Sharing Service is provided with sharing the vehicleas you can use it anywhere and anytime. The paper verified the factors impact between providing infrastructure characteristics such as scarcity, system quality and service quality and user evaluation factors based on DeLone & McLean IS Success Model. User evaluation factors have an influence on net benefit. D&M IS model mainly proved inner organization impact. The research collected experienced car sharing service, we analyzed the 224 respondents. The result of the hypothesis follows. The scarcity of time is negatively related to perceived social support and app trust. Provisional coupon is positively related to perceived social support and app trust. But, scarcity of quantity is not related to user evaluation factors. Most of the system qualities are related to app trust, however, privacy concern isn't related to app trust. the paper's demographic characteristic is lack of experience frequency. User evaluation factors that are perceived social support and app trust are positively related to user satisfaction and WoM intention. User satisfaction is individual impact and WoM intention is organization impact. Two factors are the net benefit in car sharing service. The area of sharing economy should more study about correlation among experimental various factors. Thus, the paper has different significant from antecedent research. because of trying to experimental analysis.

• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.21-37
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• 2007

This research investigates relationships between a company's corporate image and consumer attitudes toward brands in the company. It also examines the fit between a company and its individual products and consumer-company identification as intervening variables between the relationships. Data for this research were collected from 347 undergraduate students through a survey. They were asked to provide their perceptions on two brands for each of 8 large Korean companies. The results indicate that corporate image directly influences brand trust, whereas it does not affect brand trust indirectly, through company-product fit. Also, the results indicate that corporate image does not directly influence brand affect, whereas it does influence brand affect indirectly, through consumer-company identification.

• Asian Journal for Public Opinion Research
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• v.1 no.4
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• pp.234-248
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• 2014

A telephone survey was conducted in a metropolitan city in 2012 to examine people's credibility ratings of different media outlets, in particular, Weibo - one of the most popular social media platforms in China. Our findings suggest: First, people place more trust in traditional news media than in online sources by a significant margin. Second, demographic influences on media trust seem to be minimal. Only age and gender were related to some credibility measures. Third, Weibo use was not related to one's credibility perception toward traditional media but interestingly, Weibo use showed different impacts on people's evaluation of Weibo's credibility. Commenting frequency was negatively related to one's trust in Weibo, while retweeting frequency was positively related to one's trust in Weibo.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.35-45
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• 2014

Due to the spread of unreliable online information on the social network services, the users are faced with a difficult problem for determining if the information is trustworthy or not. At present, the users should make a decision by themselves throughly for the trustworthiness of the information. Therefore, we need a way to systematically evaluate the trustworthiness of information on the social network services. In this paper, we design a trust index, called KTI (Korean Trust Index for SNS), as a criterion for measuring the trust degree of the information on the social network services. Using KTI, the users are readily able to determine whether the information is trustworthy. Consequently, we can estimate the social trust degree based on the variation of KTI. This paper derives the various factors affecting trust from the properties of the social network services, and proposes a model to evaluate the trustworthiness of information that is directly produced and distributed over the online network. Quantifying the trust degree of the information on the social network services allows the users to make efficient use of the social network.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.1-9
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• 2009

In heterogeneous and distributed computing environments, with an increasing number of Web services providing similar functionalities, the reliability of Web services is a critical decision factor. To fulfill the open business model such as cooperation among enterprises, several Web services can be composed into the upper level business transaction. In Web services composition, the reliability of services is more and more critical. Though each unit Web service can be reliable, the reliability of the composed service is not guaranteed. Thus a way to efficiently assess and select composed Web services is needed. In this paper, we define new metrics for measuring the trust value of Web services, and propose an evaluation method to predict the trustworthy degree of the composed services based on the metrics. We also define a conceptual framework to support optimal Web services selection based on the proposed trust evaluation method. By selecting using the quantitative measurement rather than intuitive selection of the service user, it allows the service users to select the high reliable service meeting their quality requirements well.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.57-67
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• 2011

Trust is generally assumed to be an important precondition for people's adoption of e-government services. This study analyzes the direct and indirect impact of information privacy, interactivity, subjective norms and words-of-mouth on perceived trust of e-government services and trust toward government. The Partial Least Square(PLS) was applied to the citizen survey data for hypotheses testing. PLS permits the simultaneous testing of cause-effect hypotheses while also allowing evaluation of the measurement model. Statistical results indicate that interactivity, subjective norms and words-of-mouth positively affects perceived trust of e-government services, which in turn affects the level of political efficacy and the trust toward the government. Interactivity has been found to affect words-of-mouth as well. However, information privacy has no significant effect on the trust of e-government services.

• Korean Journal of Legislative Studies
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• v.27 no.1
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• pp.79-115
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• 2021

Voters' negative evaluations of government performance lower their trust in government, which functions as the reward and punishment for the government. Trust in government thus serves to promote political accountability of the representative government. However, voters build their confidence toward the party government where the ruling party is responsible for the performance. Considering this partisan nature, we empirically examine that the influence of voters' performance evaluations on governmental trust is conditional on their party identifications. While higher perceptions of political/social conflict and increasing negative evaluations of government policies and economic performance are associated with the lower level of confidence in government, the relationship is contrasted between different party identifiers. For supporters of the ruling party in 2020, the negative evaluations of government performance are not likely to reduce trust in government a lot. On the contrary, those who identify with the main opposition party show the most prominent effect of negative evaluations on their distrust in government. This study demonstrates that trust in government is affected by voters' partisan preferences, not entirely by evaluations of government performance. Such a distortion of the reward and sanction function of governmental trust might lead to the weakening of the accountability mechanism in representative democracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1260-1281
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• 2015

As the number of services available on the Web increases, it is vital to be able to identify which services can be trusted. Since there can be an extremely large number of potential services that offer similar functionality, it is challenging to select the right ones. Service requestors have to decide which services closelysatisfy their needs, and theymust worry about the reliability of the service provider. Although an individual service can be trusted, a composed service is not guaranteed to be trustworthy. In this paper, we present a trust model that supports service discovery and composition based on trustworthiness. We define a method to evaluate trust in order to discover trustworthy services. We also provide a method to perform trust estimation for dynamic service composition, and we present results of two experiments. The proposed model allows for service requestors to obtain the most trustworthy services possible. Our mechanism uses direct and indirect user experience to discover the trustworthiness of the services and service providers. Moreover, composing services based on quantitative trust measurements will allow for consumers to acquire a highly reliable service that meet their quality and functional requirements.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.779-789
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• 2010

Sport commentators play an increasingly influential role in commercial sports broadcasting. Public trust is regarded as one of the most significant qualifications for sport commentators and this study used a Fuzzy AHP method in deciding the relative importance of professionalism, reliability, dynamic, and narrative skill. Based on the results, we conducted an evaluation of the public trust for the four SBS sport commentators for the 2010 South-Africa World Cup. The conclusion showed that professionalism and narrative skill were regarded as the most important factors for sport commentators to gain public trust. Among the four commentators evaluated, commentator # 1 got highest score overall, the soccer expert group highly appreciated commentator # 2, and the non-expert group highly appreciated commentator # 3.