• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.113-128
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• 2022

The objective of this study is to pay attention to the personal media environment that is in the center of rapid changes in the media industry, to especially explore the activity area of one-person or minority media creators who lead the mobile media environment that could be connected, watched, and produced anywhere, and to closely examine the mutual ecosystem between creators and viewers. Especially, paying attention to the recommendation service YouTube provides, for example, based on the big data algorithm related to users' habitual use, when users' data used are provided more, the users face the advanced service, this study aimed to examine the effects of recommendation service on the formation of trust between user and producer, user flow, and subscription intention, and also to demonstrate the process of forming this mutual relation through concrete data. In the conclusion, implications that can be inferred based on the research results and suggestions for further research in the future were presented.

• Quality Improvement in Health Care
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• v.28 no.1
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• pp.34-44
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• 2022

Purpose:We investigated physicians' responses to a series of clinical vignettes consisting of patient safety incidents, with and without disclosure of patient safety incidents (DPSI). Methods: An anonymous survey was conducted to investigate physicians' responses to the DPSI via online communities of physicians, and additional participants were recruited using a snowballing sampling method. We evaluated physicians' responses to the DPSI using eight hypothetical scenarios (HS) from the following perspectives: thoughts regarding medical errors, revisiting the physician, recommendation, lawsuit, criminal prosecution, trust score, and compensation amounts. We used the chi-square test to evaluate the overall differences in response rates among the scenarios. Statistical analyses were performed using the Student's t-test to compare the trust scores and compensation amounts. Results: A total of 910 physicians participated in this survey. An overall comparison of trust scores among HS showed that HS 1 (unclear medical errors, minor harm, and DPSI) had the highest trust score. In contrast, in the opposite scenario, HS 8 (clear medical errors, major harm, and DPSI not conducted) received the lowest scores. Cases with minor harm to patients (HS 1, 2, 5, and 6) showed lower compensation amounts than the others (HS 3, 4, 7, and 8). Physicians were more likely to think of situations with DPSI as not having medical errors (53.1% vs. 55.2%). In addition, the scenarios with DPSI were evaluated favorably in terms of intention to revisit, recommend, suit, and engage in criminal proceedings. Physicians showed higher trust scores (6.2 vs 5.4) and gave lower compensation amounts ($27.7 million vs $28.1 million), although there was no significant difference in terms of compensation amounts to the physician conducting DPSI. Conclusion: Our study showed overall positive perceptions regarding DPSI among Korean physicians.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.82-104
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• 2023

This study analyzes the effect of users' experiences using AI chatbot services on relationship quality and behavioral intention. For the study, a survey was conducted on users who experienced AI chatbot services, and the research hypothesis was verified by analyzing the final 299 copies of valid data. As a result of the analysis, it was confirmed that satisfaction and trust, which are the relationship quality dimensions of AI chatbot service, were formed in users through the cognitive experience, emotional experience, and relational experience. In addition, it was confirmed that satisfaction and trust have a positive effect on the intention to continue using and recommending AI chatbot services, which correspond to the level of consumers' behavioral intentions, respectively. In addition, in terms of relationship quality, it was significant in all paths of the road of behavior, but in satisfaction, the path coefficient of the road of continuous use of AI chatbot and recommended road was significantly higher than the path coefficient in trust. This study provided a theoretical foundation that the relationship with relationship quality that affects behavioral intention also affects AI chatbot services in the online environment, and it is significant in that it suggests that relationship quality is an important mediating factor in establishing long-term relationships with consumers.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.203-214
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• 2020

Nowadays, smart speakers are increasingly personalized and serve as recommendation agents for user. The aim of this study is find out effects of 'Explanation facilities' on transparency, perceived trust, user satisfaction, behavioral intentions of users to reuse, privacy risk, and quality of recommendation in the context of an interact with smart speaker's conversational agents. And we also use measurement for level of privacy concerns to see individuals's level of privacy concerns affected the assessment. The result of this study as follow; First, all measurement variable are significantly related to 'Explanation facilities' Second, perceived trust, privacy risk are significantly related to individual's level of privacy concern. This study found that 'Explanation facilities' could be applied in context of smart speaker and possibility of cognitive dissonance according to the level of privacy concerns.

• Knowledge Management Research
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• v.21 no.4
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• pp.175-193
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• 2020

With the proliferation of information technology communication and smart device, the environment where contents are produced and distributed is changing. People can use the contents quickly and easily, and the content industry is attracting attention and creating newly added value by converging with other industries. Accordingly, there is a need for content-related companies to understand the quality of content perceived by users in order to succeed in content, and to use it strategically. Therefore, this study aims to examine the relationship between content quality factors, user satisfaction, and recommendation intention through empirical analysis based on an IS success model. The analysis was conducted using smartPLS3.0 based on a total of 301 survey responses. As a result of the study, it was found that content usefulness, accessible system quality, convenient system quality, service provider trust, and interaction had a significant effect on user's satisfaction. Perceived privacy protection had a significant effect on user satisfaction and recommendation intention. Lastly, it was found that user satisfaction had a significant effect on recommendation intention. The results of this study are expected to provide useful information and therefore content companies can understand about the quality perceived by users.

• Journal of Distribution Science
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• v.15 no.12
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• pp.73-84
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• 2017

Purpose - Over recent years, O2O and shared economy have been an eye-catching topic. Many researches on O2O and shared economy have been published gradually. The emerging enterprise of chauffeured car services developed rapidly in the past two years. Therefore, it is necessary to explore the influencing factors of use intention of the chauffeured car services users. Through active use of O2O and shared economy, put up with operation strategy in line with their use intention. Research design, data, and methodology - After collecting 324 respondents in China with questionnaires, this study begin the empirical research with users of Chauffeured Car Services, and analyzes data with IBM SPSS 24.0 and IBM AMOS 24.0. Results - Personal Propensity to Trust significantly affects the Initial Trust of chauffeured car services users. Firm Reputation significantly affects the Initial Trust and use intention of chauffeured car services users. Initial Trust significantly affects the use intention of chauffeured car services users. Performance Expectancy and Effort Expectancy significantly affect chauffeured car services users' use intention. Social Influence also significantly affects the use intention of chauffeured car services users. Conclusions - First, Initial Trust significantly affects the use intention of chauffeured car services users. Thus, the enterprise should make efforts to improve users' initial trust in order to attract their attention. For this reason, chauffeured car services enterprises should conduct questionnaires to deeply explore what needs can improve users' initial trust. Second, performance expectancy and effort expectancy significantly affect chauffeured car services users' use intention. When users enjoy chauffeured car services, they attach great importance to the convenience, simplicity and efficiency, which reflects that chauffeured car services' desire for greater development in the O2O and shared economy market. Therefore, they need to grasp users' needs (convenience, simplicity and efficiency) and carefully improve the quality of chauffeured car services. Finally, social influence also significantly affects the use intention of chauffeured car services users. It means friend recommendation or mass media influences users' intention. So, it is more important to increase differentiated benefits, advertising and publicity of chauffeured car services.

• Journal of Information Technology Applications and Management
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• v.31 no.3
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• pp.1-18
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• 2024

This study analyzed the impact of YouTube creator characteristics and channel access factors on the intention to continue watching content, noting that the development of the digital media environment has diversified media audiences' content preferences and access routes. Specifically, we analyzed the effects of YouTube creator trustworthiness, attractiveness, familiarity, and social influence, as well as the effects of recommendation services on perceived usefulness, perceived ease, and perceived enjoyment. The study found that creator credibility and recommendation service had a positive impact on the perceived usefulness of content, while intimacy and charm were important factors in increasing the easy of use and playfulness of content. These perceived usefulness, ease, and playfulness also had a strong positive impact on users' intention to continue watching the channel. This suggests that trust and intimate relationships with creators and appropriate content recommendations play an important role in increasing user satisfaction and channel persistence. The significance of this study's analysis of creator and channel access factors based on the extended technology acceptance model is that it shows the potential for extending and applying the existing technology acceptance model to the digital content environment.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.1-10
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• 2013

Personalization aims to provide customized contents to each user by using the user's personal preferences. In this sense, the core parts of personalization are regarded as recommendation technologies, which can recommend the proper contents or products to each user according to his/her preference. Prior studies have proposed novel recommendation technologies because they recognized the importance of recommender systems. Among several recommendation technologies, collaborative filtering (CF) has been actively studied and applied in real-world applications. The CF, however, often suffers sparsity or scalability problems. Prior research also recognized the importance of these two problems and therefore proposed many solutions. Many prior studies, however, suffered from problems, such as requiring additional time and cost for solving the limitations by utilizing additional information from other sources besides the existing user-item matrix. This study proposes a novel implicit rating approach for collaborative filtering in order to mitigate the sparsity problem as well as to enhance the performance of recommender systems. In this study, we propose the methods of reducing the sparsity problem through supplementing the user-item matrix based on the implicit rating approach, which measures the trust level among users via the existing user-item matrix. This study provides the preliminary experimental results for testing the usefulness of the proposed model.

• Journal of Distribution Science
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• v.18 no.5
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• pp.25-33
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• 2020

Purpose: The use of e-Samsat services in East Java has not been significant in the amount of use of its services for tax payments as a whole. The purpose of this study is to analyze what factors East Java e-Samsat services practice and the existence of recommendations as a basis for government decisions to improve the quality of East Java e-Samsat services. Research design, data and methodology: Our model hypothesizes that three key factors determine the intention to use e-samsat platform such as: trust, awareness, ease to use. Data collection methods by distributing questionnaires and interviews. Results: The results of the study provide two findings, firstly, Trust, Ease of Use, Awareness directly or indirectly affects the Intention to Use the East Java e-Samsat service for motor vehicle taxpayers. Thus it is essential to pay attention to these three variables in terms of clarity, reliability, and timeliness as a recommendation to improve the quality of East Java e-Samsat services.. Conclusions: The results of this study can be applied and developed in other countries besides Indonesia with the same cultural patterns. Several variables have been measured in previous studies in several Asian continent countries.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.119-140
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• 2007

Recommender systems enable a user to decide which information is interesting and valuable in our world of information overload. As the recent studies of distributed computing environment have been progressing actively, recommender systems, most of which were centralized, have changed toward a peer-to-peer approach. Collaborative Filtering (CF), one of the most successful technologies in recommender systems, presents several limitations, namely sparsity, scalability, cold start, and the shilling problem, in spite of its popularity. The move from centralized systems to distributed approaches can partially improve the issues; distrust of recommendation and abuses of personal information. However, distributed systems can be vulnerable to attackers, who may inject biased profiles to force systems to adapt their objectives. In this paper, we consider both effective CF in P2P environment in order to improve overall performance of system and efficient solution of the problems related to abuses of personal data and attacks of malicious users. To deal with these issues, we propose a multi-agent framework for a distributed CF focusing on the trust relationships between individuals, i.e. web of trust. We employ an agent-based approach to improve the efficiency of distributed computing and propagate trust information among users with effect. The experimental evaluation shows that the proposed method brings significant improvement in terms of the distributed computing of similarity model building and the robustness of system against malicious attacks. Finally, we are planning to study trust propagation mechanisms by taking trust decay problem into consideration.