Abstract

The Best Paper Award recognizes BULING XIA for outstanding academic contributions through the research titled “Sustainable Use Intention of Text-to-Image Generative AI in Higher Education: An S–O–R Model with Parallel Trust and Risk Pathways.The study investigates factors influencing the sustainable adoption of text-to-image generative artificial intelligence in higher education. By applying the Stimulus–Organism–Response framework, the research examines the influence of trust and perceived risk on users’ intentions toward AI technologies. The findings provide valuable theoretical and practical insights for responsible AI integration, digital transformation, and interdisciplinary research within Arts and Humanities.

Keywords

Arts and Humanities; Generative Artificial Intelligence; Text-to-Image AI; Higher Education; Sustainable Use Intention; S–O–R Model; Trust; Perceived Risk; Educational Technology; Artificial Intelligence Adoption.

Introduction

Artificial intelligence technologies are transforming educational environments by introducing innovative approaches to teaching, learning, and knowledge creation. Understanding user acceptance and sustainable usage of AI tools has become increasingly important. BULING XIA’s research contributes to this field by examining how trust and perceived risks influence the adoption of text-to-image generative AI in higher education.

Research Profile

BULING XIA is affiliated with Hanyang University, China. The researcher focuses on emerging areas including generative artificial intelligence, educational technology, technology acceptance, and digital innovation. With published research contributions and citation impact, the work demonstrates growing influence in interdisciplinary studies connecting technology, education, and Arts and Humanities perspectives.

Scientific Background

The rapid development of generative artificial intelligence has created new opportunities and challenges in higher education. Research on AI adoption requires understanding technological benefits, psychological factors, trust mechanisms, and potential risks. BULING XIA’s research provides a scientific foundation for exploring sustainable interaction between users and AI-powered educational technologies.

Methodology

The research applies the Stimulus–Organism–Response (S–O–R) model to analyze sustainable use intentions toward text-to-image generative AI. The study examines parallel pathways involving trust and perceived risk, providing a structured framework for understanding behavioral responses and decision-making processes related to AI adoption in higher education.

Key Findings

The study demonstrates that trust and perceived risk play important roles in shaping users’ intentions to adopt text-to-image generative AI technologies. The findings highlight the importance of developing reliable, transparent, and user-centered AI systems that encourage sustainable technology utilization within educational environments.

Scientific Contributions

BULING XIA’s research contributes to artificial intelligence and educational technology studies by integrating behavioral theory with practical technology adoption challenges. The work strengthens understanding of sustainable AI implementation through interdisciplinary approaches combining information technology, education research, and human behavioral perspectives.

Conclusion

The Best Paper Award celebrates BULING XIA’s contribution to advancing research on sustainable text-to-image generative AI adoption in higher education. The study demonstrates academic excellence, innovative methodology, and interdisciplinary significance by addressing important factors that influence responsible artificial intelligence usage and future educational technology development.

External Links

• ORCID Profile

• Best Paper Awards Website

• Hanyang University
  

References

1. ORCID Profile.
   https://orcid.org/0009-0001-3018-0837
2. Best Paper Awards.
   https://bestpaperawards.com/
3. Hanyang University.
   https://www.hanyang.ac.kr/