Shinetsetseg Jargalsaikhan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Shinetsetseg Jargalsaikhan has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- I-Tung Shih
Department of Business Administration, College of Management, Chaoyang University of Technology, Taichung 411310, Taiwan
5 shared publications - Andri Dayarana K. Silalahi
Chaoyang University of Technology
4 shared publications - Chung-Jen Fu
Department of Business Administration, Chaoyang University of Technology, Taichung 411310, Taiwan
2 shared publications - Do Thi Thanh Phuong
Department of Marketing and Logistics Management, Chaoyang University of Technology, Taichung 411310, Taiwan
2 shared publications - Ixora Javanisa Eunike
Master of Management Program, Graduate School, University of Technology, Medan 20235, Indonesia
2 shared publications Chung Jen Fu
1 shared publication
Latest Publications
- Open Access
- 13 January 2026
- Published by Elsevier in Journal of Open Innovation: Technology, Market, and Complexity
- Vol. 12 (1)
Linking personal cultural values to consumer value perception through perceived sustainability
- 13 January 2026
- Published by Elsevier in Journal of Open Innovation: Technology, Market, and Complexity
- Vol. 12 (1)
Open AccessLinking personal cultural values to consumer value perception through perceived sustainability
- Open Access
- 26 November 2024
- Published by Taylor & Francis in Cogent Business & Management
- Vol. 11 (1)
Exploring the impact of perceived sustainability on customer satisfaction and the mediating role of perceived value
- 26 November 2024
- Published by Taylor & Francis in Cogent Business & Management
- Vol. 11 (1)
Open AccessExploring the impact of perceived sustainability on customer satisfaction and the mediating role of perceived value
- Open Access
- 3 September 2024
- Published by MDPI AG in Engineering Proceedings
- Vol. 74 (1) , 45
Digital Diplomacy: A Case Study of Foreign Relations of Mongolian and India in Social Media by Big Data Analysis and Computation
We explored digital diplomacy, an evolving field, focusing on the digital engagement strategies of India and Mongolia from 2012 to 2022 through a quantitative analysis of secondary data sourced from social media platforms. We investigated how these countries utilized digital tools to shape their international relations, highlighting the impact of digital diplomacy on traditional diplomatic practices and the potential for enhancing public diplomacy. By examining parameters such as post frequency and engagement rates, significant differences were determined to suggest strategic improvements for Mongolia. The findings offer the basis for the adoption of digital diplomacy, emphasizing its role in reshaping global interactions in the digital era.
- 3 September 2024
- Published by MDPI AG in Engineering Proceedings
- Vol. 74 (1) , 45
Open AccessDigital Diplomacy: A Case Study of Foreign Relations of Mongolian and India in Social Media by Big Data Analysis and Computation
We explored digital diplomacy, an evolving field, focusing on the digital engagement strategies of India and Mongolia from 2012 to 2022 through a quantitative analysis of secondary data sourced from social media platforms. We investigated how these countries utilized digital tools to shape their international relations, highlighting the impact of digital diplomacy on traditional diplomatic practices and the potential for enhancing public diplomacy. By examining parameters such as post frequency and engagement rates, significant differences were determined to suggest strategic improvements for Mongolia. The findings offer the basis for the adoption of digital diplomacy, emphasizing its role in reshaping global interactions in the digital era.
- Open Access
- 26 August 2024
- Published by MDPI AG in Engineering Proceedings
- Vol. 74 (1) , 3
To Satisfy or Clarify: Enhancing User Information Satisfaction with AI-Powered ChatGPT
The effective use of AI-powered ChatGPT in higher education highlights its potential as a knowledge acquisition tool, yet it brings to the fore the less-explored area of user information satisfaction (UIS), a gap addressing the development of the UIS model tailored to ChatGPT. In this foundational research grounded in UIS theory, a model was proposed based on critical factors to guide educational stakeholders in investigating issues such as plagiarism and ethical use. By analyzing responses from a diverse group of Indonesian users employed in higher education and using Structural Equation Modeling with Smart-PLS 4.0, we identified five key determinants: completeness, precision, timeliness, convenience, and format. The determinants affect user satisfaction, while traditionally emphasized factors such as accuracy and reliability do not significantly impact the academic utilization of ChatGPT. The results advocate for reliance on ChatGPT with limitations in regard to accuracy and suggest a change in the academic use of technology. The results also offer a perspective that blends theoretical innovation with practical application in educational settings.
- 26 August 2024
- Published by MDPI AG in Engineering Proceedings
- Vol. 74 (1) , 3
Open AccessTo Satisfy or Clarify: Enhancing User Information Satisfaction with AI-Powered ChatGPT
The effective use of AI-powered ChatGPT in higher education highlights its potential as a knowledge acquisition tool, yet it brings to the fore the less-explored area of user information satisfaction (UIS), a gap addressing the development of the UIS model tailored to ChatGPT. In this foundational research grounded in UIS theory, a model was proposed based on critical factors to guide educational stakeholders in investigating issues such as plagiarism and ethical use. By analyzing responses from a diverse group of Indonesian users employed in higher education and using Structural Equation Modeling with Smart-PLS 4.0, we identified five key determinants: completeness, precision, timeliness, convenience, and format. The determinants affect user satisfaction, while traditionally emphasized factors such as accuracy and reliability do not significantly impact the academic utilization of ChatGPT. The results advocate for reliance on ChatGPT with limitations in regard to accuracy and suggest a change in the academic use of technology. The results also offer a perspective that blends theoretical innovation with practical application in educational settings.
- Open Access
- 1 February 2024
- Published by MDPI AG in Preprints.org
Balancing Satisfaction and Clarity: Enhancing User Information Satisfaction with AI-Powered ChatGPT in Higher Education
Incorporating AI tools like ChatGPT into higher educational settings has been beneficial for education, yet the extent of user satisfaction with the information provided by these tools, known as user information satisfaction (UIS), remains underexplored. Our study introduces a UIS model specifically designed for ChatGPT's application in the educational sector. Drawing from established UIS theory, we crafted a model centered around seven essential factors that influence the effective use of ChatGPT, aiming to guide both educators and learners in overcoming common challenges such as plagiarism and ensuring the ethical use of AI. We gathered data from Indonesian university participants and applied Structural Equation Modeling using Smart-PLS 4.0 for our data analysis. The results reveal that completeness, precision, timeliness, convenience, and the format of information as the most influential factors driving user satisfaction with ChatGPT. Interestingly, our research indicated that the accuracy and reliability of the information, typically deemed paramount, were not the primary concerns in the academic use of ChatGPT. Our findings lead to a recommendation for a cautious approach to the integration of ChatGPT in higher education. We advocate for a strategic use that recognizes its innovative potential while also acknowledging its limitations, thus ensuring a responsible and effective application in educational contexts. This balanced perspective is crucial for integrating AI tools into the academic fabric without compromising educational integrity or quality.
- 1 February 2024
- Published by MDPI AG in Preprints.org
Open AccessBalancing Satisfaction and Clarity: Enhancing User Information Satisfaction with AI-Powered ChatGPT in Higher Education
Incorporating AI tools like ChatGPT into higher educational settings has been beneficial for education, yet the extent of user satisfaction with the information provided by these tools, known as user information satisfaction (UIS), remains underexplored. Our study introduces a UIS model specifically designed for ChatGPT's application in the educational sector. Drawing from established UIS theory, we crafted a model centered around seven essential factors that influence the effective use of ChatGPT, aiming to guide both educators and learners in overcoming common challenges such as plagiarism and ensuring the ethical use of AI. We gathered data from Indonesian university participants and applied Structural Equation Modeling using Smart-PLS 4.0 for our data analysis. The results reveal that completeness, precision, timeliness, convenience, and the format of information as the most influential factors driving user satisfaction with ChatGPT. Interestingly, our research indicated that the accuracy and reliability of the information, typically deemed paramount, were not the primary concerns in the academic use of ChatGPT. Our findings lead to a recommendation for a cautious approach to the integration of ChatGPT in higher education. We advocate for a strategic use that recognizes its innovative potential while also acknowledging its limitations, thus ensuring a responsible and effective application in educational contexts. This balanced perspective is crucial for integrating AI tools into the academic fabric without compromising educational integrity or quality.
- Top Cited PapersOpen Access
- 1 January 2024
- Published by Wiley in Human Behavior and Emerging Technologies
- Vol. 2024 (1)
Assessing ChatGPT’s Information Quality Through the Lens of User Information Satisfaction and Information Quality Theory in Higher Education: A Theoretical Framework
Incorporating AI tools like ChatGPT into higher education has been beneficial, yet the extent of user satisfaction with the quality of information provided by these tools, known as user information satisfaction (UIS) and information quality (IQ) theory, remains underexplored. This study introduces a UIS model specifically designed for ChatGPT’s application in the educational sector based on multidimensions of IQ theory. Drawing from established UIS and IQ theory, we crafted a model centered around seven essential factors that influence the effective use of ChatGPT, aiming to guide educators and learners in overcoming common challenges such as plagiarism and ensuring the ethical use of AI. Data was collected from Indonesian university participants (N = 508) and analyzed using structural equation modeling with Smart‐PLS 4.0. The results reveal that completeness, precision, timeliness, convenience, and information format are the most influential factors driving user satisfaction with ChatGPT. Interestingly, our research indicated that the accuracy and reliability of the information, typically deemed paramount, were not the primary concerns in the academic use of ChatGPT. Our findings recommend a cautious approach to integrating ChatGPT in higher education. We advocate for strategic use that recognizes its innovative potential while acknowledging its limitations, ensuring responsible and effective application in educational contexts. This balanced perspective is crucial for integrating AI tools into the academic fabric without compromising educational integrity or quality.
- 1 January 2024
- Published by Wiley in Human Behavior and Emerging Technologies
- Vol. 2024 (1)
Top Cited PapersOpen AccessAssessing ChatGPT’s Information Quality Through the Lens of User Information Satisfaction and Information Quality Theory in Higher Education: A Theoretical Framework
Incorporating AI tools like ChatGPT into higher education has been beneficial, yet the extent of user satisfaction with the quality of information provided by these tools, known as user information satisfaction (UIS) and information quality (IQ) theory, remains underexplored. This study introduces a UIS model specifically designed for ChatGPT’s application in the educational sector based on multidimensions of IQ theory. Drawing from established UIS and IQ theory, we crafted a model centered around seven essential factors that influence the effective use of ChatGPT, aiming to guide educators and learners in overcoming common challenges such as plagiarism and ensuring the ethical use of AI. Data was collected from Indonesian university participants (N = 508) and analyzed using structural equation modeling with Smart‐PLS 4.0. The results reveal that completeness, precision, timeliness, convenience, and information format are the most influential factors driving user satisfaction with ChatGPT. Interestingly, our research indicated that the accuracy and reliability of the information, typically deemed paramount, were not the primary concerns in the academic use of ChatGPT. Our findings recommend a cautious approach to integrating ChatGPT in higher education. We advocate for strategic use that recognizes its innovative potential while acknowledging its limitations, ensuring responsible and effective application in educational contexts. This balanced perspective is crucial for integrating AI tools into the academic fabric without compromising educational integrity or quality.