• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.79-90
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• 2024

This study focused on user trust in ChatGPT, a generative AI technology, and explored the factors that affect usage status and intention to continue using, and whether the influence of trust varies depending on the purpose. For this purpose, the survey was conducted targeting people in their 20s and 30s who use ChatGPT the most. The statistical analysis deploying IBM SPSS 27 and SmartPLS 4.0. A structural equation model was formulated on the foundation of Bhattacherjee's Expectation-Confirmation Model (ECM), employing path analysis and Multi-Group Analysis (MGA) for hypothesis validation. The main findings are as follows: Firstly, ChatGPT is mainly used for specific needs or objectives rather than as a daily tool. The majority of users are cognizant of its hallucination effects; however, this did not hinder its use. Secondly, the hypothesis testing indicated that independent variables such as expectation- confirmation, perceived usefulness, and user satisfaction all exert a positive influence on the dependent variable, the intention for continuance intention. Thirdly, the influence of trust varied depending on the user's purpose in utilizing ChatGPT. trust was significant when ChatGPT is used for information retrieval but not for creative purposes. This study will be used to solve reliability problems in the process of introducing generative AI in society and companies in the future and to establish policies and derive improvement measures for successful employment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.591-597
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• 2022

As social anxiety is increasing due to the spread of the COVID-19 epidemic, the responses at the level of local governments are also changing depending on the characteristics. We analyzed the factors influencing perceptions of social safety as they relate to the trustworthiness of local governments. Based on a 2020 social survey of 16 cities, counties, and districts in Busan Metropolitan City, the effects of householder characteristics, economic characteristics, local attachment characteristics, and social safety perception characteristics on the reliability of the local government were analyzed through an ordinal logistic regression analysis. It was found that the more vulnerable the class was and the safer the region was, the higher the trust was in the basic local government. In order to respond and preemptively recover damage in natural and social disaster situations, continuous efforts are needed to strengthen the capabilities of basic local governments.

• Management & Information Systems Review
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• v.35 no.4
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• pp.185-211
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• 2016

This study examined the impact of learning organization activities on burnout and the moderating effect of supervisor trust in a learning organization. The results of the study shows that among the activities of a learning organization, independent variables in this study, promoting inquiry and dialogue as well as encouraging collaboration and team learning affect burnout. In other words, the dedication of an organization to creating a culture in which various learning approaches are experimented through questioning and giving feedback as well as collaborative learning that can reinforce the effective use of team resources have an impact on reducing emotional exhaustion, which is considered to be at the core of burnout. Plus, these factors reduce impersonalization, which is activated to prevent further emotional exhaustion by dealing with customers, colleagues and jobs in a cold, negative and perfunctory way. In this study, the dimensions of promoting inquiry and dialogue as well as encouraging collaboration and team learning were found to reduce the decline in personal sense of achievement of an employee with a negative assessment of himself or herself derived from a lack of achievement in his or her job. Supervisor trust (integrity, benevolence and ability) had a moderating effect on the relationship between strategic learning leadership and impersonalization/emotional exhaustion. This suggests that the trust of supervisor helps mediate and moderate the emotional exhaustion and impersonalization of organizational members by encouraging leaders to drive change and take the organization to a new direction. The study has provided implications that communication plays an important role in reducing burnout in the learning context such as positive, appreciative inquiry and feedback analysis to identify strength, and that supervisor trust is critical in order to ensure strategic learning leadership exerts greater influence on the organization.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.755-765
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• 2019

Purpose: Chatbots are widely diffusing across various industries to substitute human manpower in the industry. However as researchers only develop technology that is applied to chatbot, the diffusion is slow in progress. The purpose of this study is to propose useful implications to accelerate diffusion of chatbots across industries by analyzing the perception of customers. To achieve the research purpose this study analyzes causal effect relationship between characteristics of chatbot character, service quality, individual difference, and intention to use chatbot. Methods: This study developed a survey that contains various questionnaires for each construct based on literature review. Data collected through survey was tested for convergent validity and discriminant validity and further analyzed the relationship using PLS-SEM method to verify hypotheses. Results: Trustworthiness of the chatbot character, ease of use, application design, responsiveness, customization, assurance, inertia, and previous experience have significant influence on forming user satisfaction, consumer trust, and intention to use. The others, likability, appropriateness, technology anxiety, and need for interaction were not significant in this research. Conclusion: Although the constructs of the research model was significant in previous literatures, some do not have significant effect on intention to use chatbots. Based on the results, chatbot managers will be able to develop chatbot systems which are more appealing to users and more academic researchers will focus on analyzing user perception and intention.

• Journal of the Korean Dietetic Association
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• v.11 no.4
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• pp.440-448
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• 2005

This study explores some basic issues behind adults' seeking and using patterns of alternative medicine as well as health food (health food/medicine). In order to do this, 791 adult participants in Seoul and Busan were interviewed face-to-face. The results of the survey showed that 1) interpersonal influence was the most influential factor in relation to the adoption of health food/medicine(46.9% of the participants reported on the influences), 2) keeping healthy was the main motivation for the usage of health food/medicine(34.5% of the participants), 3) mass media was the important information source for health food/medicine, 4) with regard to trustworthiness of information sources, experts were believed to be the most trustworthy while information from acquaintances were thought less, and finally, 5) pharmacies and health food stores were main suppliers of health food/medicine. This study suggests some marketing strategies for health food/medicine. For example, it can be suggested that interpersonal communication among other information channels should be focused and might be increased trust by using professionals.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.183-187
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• 2019

The paper aims to provide some recommendations to improve the operational capacity of the Tra Vinh Provincial Center of Public Administrative Services and to improve the effectiveness and efficiency of management in the State administrative agencies. The study on people's satisfaction towards public services of Tra Vinh Provincial Center of Public Administrative Services was conducted by collecting primary data of 300 people who used public services provided by this Center from September 2018 to November 2018. By using the multivariate regression method, the author found that there were a number of factors affecting people's satisfaction towards public services at the Center, including procedures, service fee, and attitudes of the staff, empathy, staff capacity, and trust. These factors had an impact on people's satisfaction towards public administrative services performed by staff officers from Tra Vinh Provincial Center of Public Administrative Services. Since then, the study has proposed policy implications to improve people's satisfaction on service quality at the Center such as: Develop a flexible charge mechanism of public services; Enhance the sense of responsibility of staff officers; Pay attention to improving administrative procedures; Establish trustworthiness to people; Pay attention to professional improvement; and Build up a friendly and respectful team of staff.

• 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.

• The Journal of Information Systems
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• v.33 no.2
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• pp.105-124
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• 2024

Purpose This study aims to propose a blockchain-based platform that can guarantee enhanced trustworthiness in corporate ESG efforts, demanded by global ESG initiatives such as GRI and TCFD. Blockchain technology, recognized for its transparency and data immutability, can contribute to building trust in ESG disclosures, meeting the data transparency verification needs required by these initiatives. This research also explores the use of NFTs representing unique ESG efforts by companies, helping them in organizing and sharing ESG information with investors and consumers. Design/methodology/approach This study utilizes Hyperledger Fabric, a permissioned blockchain known for its enhanced transparency, scalability, and suitability for business transactions, to develop a blockchain platform for managing and disclosing ESG information assets in a trustworthy manner. Furthermore, it introduces the concept of ESG NFTs as a more reliable method for conveying ESG information to stakeholders, where ESG NFTs undergo verification process by third-party authenticators and evaluation by independent evaluators for credibility of ESG disclosure. Findings The use of NFTs, which has been predominantly intended for market trading in public blockchain, offers a credible means of disseminating corporate ESG status and evaluations in a permissioned blockchain, better fit for business transactions. By representing information assets as NFTs, which are tamper-proof and establish clear ownership, the proposed platform enables effective management of ESG-related information assets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1186-1207
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• 2024

Bearings are one of the main components of mechanical equipment and one of the primary components prone to faults. Therefore, conducting fault diagnosis on bearings is a key issue in mechanical equipment research. Belief rule base (BRB) is essentially an expert system that effectively integrates qualitative and quantitative information, demonstrating excellent performance in fault diagnosis. However, class imbalance often occurs in the diagnosis task, which poses challenges to the diagnosis. Models with interpretability can enhance decision-makers' trust in the output results. However, the randomness in the optimization process can undermine interpretability, thereby reducing the level of trustworthiness in the results. Therefore, a hierarchical BRB model based on extreme gradient boosting (XGBoost) feature selection with interpretability (HFS-IBRB) is proposed in this paper. Utilizing a main BRB alongside multiple sub-BRBs allows for the conversion of a multi-classification challenge into several distinct binary classification tasks, thereby leading to enhanced accuracy. By incorporating interpretability constraints into the model, interpretability is effectively ensured. Finally, the case study of the actual dataset of bearing fault diagnosis demonstrates the ability of the HFS-IBRB model to perform accurate and interpretable diagnosis.

• Journal of Information Processing Systems
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• v.20 no.4
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• pp.558-573
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• 2024

Considering factors such as illumination, camera quality variations, and background-specific variations, identifying a face using a smartphone-based facial image capture application is challenging. Face Image Quality Assessment refers to the process of taking a face image as input and producing some form of "quality" estimate as an output. Typically, quality assessment techniques use deep learning methods to categorize images. The models used in deep learning are shown as black boxes. This raises the question of the trustworthiness of the models. Several explainability techniques have gained importance in building this trust. Explainability techniques provide visual evidence of the active regions within an image on which the deep learning model makes a prediction. Here, we developed a technique for reliable prediction of facial images before medical analysis and security operations. A combination of gradient-weighted class activation mapping and local interpretable model-agnostic explanations were used to explain the model. This approach has been implemented in the preselection of facial images for skin feature extraction, which is important in critical medical science applications. We demonstrate that the use of combined explanations provides better visual explanations for the model, where both the saliency map and perturbation-based explainability techniques verify predictions.