Опубликована: Ноя. 22, 2024
Язык: Английский
Behavioral Sciences, Год журнала: 2025, Номер 15(4), С. 491 - 491
Опубликована: Апрель 8, 2025
In the context of digital transformation era, extensive application artificial intelligence (AI) is profoundly altering workplace environment, thereby underscoring critical need to elucidate its impact on employee innovation behavior. Such insights are essential for optimizing human resource management and enhancing organizational competitiveness. Grounded in cognitive evaluation theory, this study explores underlying mechanisms through which AI usage influences behavior develops an integrated theoretical model that incorporates both personality traits job characteristics. A two-wave questionnaire survey was conducted, hierarchical regression analysis employed test hypotheses using a sample 339 employees from 13 manufacturing enterprises China. The findings reveal positively associated with behavior, self-efficacy serving as significant mediator. Furthermore, openness complexity moderate relationship between self-efficacy, facilitating innovative Additionally, moderated mediation mechanism identified. conclusions not only enrich understanding how impacts but also offer practical guidance organizations leveraging foster during transformation.
Язык: Английский
Процитировано
0
Journal of Engineering Design, Год журнала: 2024, Номер unknown, С. 1 - 20
Опубликована: Июль 24, 2024
Utilising the Theory of Inventive Problem Solving (TRIZ) and Artificial Intelligence Generated Content (AIGC) models, this paper explores AI-assisted creative design uses traffic cone as a case. The objective is to evaluate whether AIGC can assist or potentially replace TRIZ in field. Despite being an established methodology renowned for its effectiveness systematic problem solving, it faces challenges related implementation complexity adaptability across different cultures industries. In contrast, AIGC, through data-driven tools, offers automation enhanced innovation, showing promise overcome these limitations. Evidence from qualitative case studies quantitative indicate that while enhances efficiency stability limitations system analysis innovative thinking prevent independently solving complex issues, thereby not fully replacing TRIZ. However, effectively complement model by enhancing practicality solutions data processing capabilities, improving overall innovation. This synergy has potential accelerate development conceptual designs, indicating integrating with leverages strengths both methodologies produce more effective outcomes.
Язык: Английский
Процитировано
3
Learning and Individual Differences, Год журнала: 2024, Номер unknown, С. 102547 - 102547
Опубликована: Сен. 1, 2024
Язык: Английский
Процитировано
3
The Design Journal, Год журнала: 2024, Номер unknown, С. 1 - 21
Опубликована: Дек. 17, 2024
The advancement of Generative Artificial Intelligence (GenAI) has introduced diverse opportunities and challenges in product design, demanding a corresponding evolution design education. This study investigated GenAI's roles its implications for education through semi-structured interviews with 24 participants, comprising practitioners, educators, students, who had hands-on experience leveraging GenAI design. Through thematic analysis, we identified critical functions including generating inspiration, exploring potential solutions, conducting prototyping, performing evaluations, finalizing detailed outputs, serving as materials, presenting both challenges. Moreover, fully incorporating requires adaptation educational initiatives, capability development, curriculum content, assessment methods. provides insights from multi-stakeholder perspective, revealing the advancing curricula to prepare next-generation designers be proficient effectively innovation.
Язык: Английский
Процитировано
1
Frontiers in Computer Science, Год журнала: 2024, Номер 6
Опубликована: Сен. 9, 2024
Despite the widespread recognition of artificial intelligence’s advantages, it cannot replace human independent thinking and creativity, especially in fields such as artistic design that require creativity. Previous studies often examined its development trends from perspective technical advantages or application processes. This study explores attitudes acceptance creative industry practitioners towards Artificial Intelligence Generated Content (AIGC) user behavior modification. Utilizing Stimulus-Organism-Response Model (SOR) theoretical background, this research integrates Technology Acceptance Model, Theory Planned Behavior, Self-Efficacy to form framework. By employing a mixed-method approach combining quantitative qualitative analyses, data 226 designers were explored, structural equation modeling was used verify correlations between endogenous factors. The results indicate users’ facilitating conditions significantly influence self-efficacy, which turn determines their intention adopt AIGC. Additionally, semi-structured interviews revealed factors hindering AIGC mainly encompass legal security, ethical risks, fairness. extends scope (SOR), enriches provides new framework for industry, detailing responsibilities, processes, content Design (AIGD) process.
Язык: Английский
Процитировано
0
Journal of Educational Research and Policies, Год журнала: 2024, Номер 6(10), С. 40 - 44
Опубликована: Окт. 30, 2024
Curriculum construction is an important part of improving the quality higher education. With rapid development artificial intelligence technology, generative AI having a profound impact on first-class courses in art majors colleges and universities. This study aims to explore how can enable majors, analyze its specific application effect curriculum through practical cases.
Язык: Английский
Процитировано
0
Опубликована: Сен. 13, 2024
Язык: Английский
Процитировано
0
Опубликована: Ноя. 22, 2024
Язык: Английский
Процитировано
0