In an era dominated by artificial intelligence (AI), establishing customer confidence is crucial for the integration and acceptance of AI technologies. This interdisciplinary study examines factors influencing custome...In an era dominated by artificial intelligence (AI), establishing customer confidence is crucial for the integration and acceptance of AI technologies. This interdisciplinary study examines factors influencing customer trust in AI systems through a mixed-methods approach, blending quantitative analysis with qualitative insights to create a comprehensive conceptual framework. Quantitatively, the study analyzes responses from 1248 participants using structural equation modeling (SEM), exploring interactions between technological factors like perceived usefulness and transparency, psychological factors including perceived risk and domain expertise, and organizational factors such as leadership support and ethical accountability. The results confirm the model, showing significant impacts of these factors on consumer trust and AI adoption attitudes. Qualitatively, the study includes 35 semi-structured interviews and five case studies, providing deeper insight into the dynamics shaping trust. Key themes identified include the necessity of explainability, domain competence, corporate culture, and stakeholder engagement in fostering trust. The qualitative findings complement the quantitative data, highlighting the complex interplay between technology capabilities, human perceptions, and organizational practices in establishing trust in AI. By integrating these findings, the study proposes a novel conceptual model that elucidates how various elements collectively influence consumer trust in AI. This model not only advances theoretical understanding but also offers practical implications for businesses and policymakers. The research contributes to the discourse on trust creation and decision-making in technology, emphasizing the need for interdisciplinary efforts to address societal challenges associated with technological advancements. It lays the groundwork for future research, including longitudinal, cross-cultural, and industry-specific studies, to further explore consumer trust in AI.展开更多
In recent years,with the rapid development of the automobile industry in China and even in the world,the demand for professional talents in automobile related enterprises is extremely urgent,and the requirements are a...In recent years,with the rapid development of the automobile industry in China and even in the world,the demand for professional talents in automobile related enterprises is extremely urgent,and the requirements are also increasing,so the teaching reform highlights its importance at present."The car"teaching quality,directly affects the new vehicle engineering applied talents under the background of engineering training,this article analysis the automobile theory teaching present situation,according to arcane knowledge,practice limited conditions and the evaluation method is proposed combining theory with practice,the practice of the project to drive the teaching plan,at the same time,put forward to reduce examination of course evaluation.The aim is to stimulate students'subjective initiative in learning,cultivate students'hands-on and brain-using ability,and let students devote themselves to the class,so as to make the boring derivation of theoretical formulas vivid and improve the efficiency of teaching.展开更多
文摘In an era dominated by artificial intelligence (AI), establishing customer confidence is crucial for the integration and acceptance of AI technologies. This interdisciplinary study examines factors influencing customer trust in AI systems through a mixed-methods approach, blending quantitative analysis with qualitative insights to create a comprehensive conceptual framework. Quantitatively, the study analyzes responses from 1248 participants using structural equation modeling (SEM), exploring interactions between technological factors like perceived usefulness and transparency, psychological factors including perceived risk and domain expertise, and organizational factors such as leadership support and ethical accountability. The results confirm the model, showing significant impacts of these factors on consumer trust and AI adoption attitudes. Qualitatively, the study includes 35 semi-structured interviews and five case studies, providing deeper insight into the dynamics shaping trust. Key themes identified include the necessity of explainability, domain competence, corporate culture, and stakeholder engagement in fostering trust. The qualitative findings complement the quantitative data, highlighting the complex interplay between technology capabilities, human perceptions, and organizational practices in establishing trust in AI. By integrating these findings, the study proposes a novel conceptual model that elucidates how various elements collectively influence consumer trust in AI. This model not only advances theoretical understanding but also offers practical implications for businesses and policymakers. The research contributes to the discourse on trust creation and decision-making in technology, emphasizing the need for interdisciplinary efforts to address societal challenges associated with technological advancements. It lays the groundwork for future research, including longitudinal, cross-cultural, and industry-specific studies, to further explore consumer trust in AI.
文摘In recent years,with the rapid development of the automobile industry in China and even in the world,the demand for professional talents in automobile related enterprises is extremely urgent,and the requirements are also increasing,so the teaching reform highlights its importance at present."The car"teaching quality,directly affects the new vehicle engineering applied talents under the background of engineering training,this article analysis the automobile theory teaching present situation,according to arcane knowledge,practice limited conditions and the evaluation method is proposed combining theory with practice,the practice of the project to drive the teaching plan,at the same time,put forward to reduce examination of course evaluation.The aim is to stimulate students'subjective initiative in learning,cultivate students'hands-on and brain-using ability,and let students devote themselves to the class,so as to make the boring derivation of theoretical formulas vivid and improve the efficiency of teaching.
