感知品牌开源文化对用户态度的影响OACHSSCD

The rapid development of generative artificial intelligence(AI)has propelled technological innovation and reshaped the strategic landscape of global technological competition.Against this backdrop,open-source and closed-source technical routes in AI development embody distinct innovation logic and strategic orientations.Representative open-source models,such as DeepSeek's MoE-16B and Meta's LLaMA-2,advance transparent and controllable innovation through code auditability and developer ecosystem co-development.By contrast,closed-source models,such as OpenAI's GPT-4 and Google's Gemini,preserve advantages in technological leadership and patent development. From the perspective of open innovation theory,open-source and closed-source approaches are not merely alternative technical routes;they represent contrasting modes of knowledge governance and innovation paradigms.Open-source innovation emphasizes resource integration and sharing,whereas closed-source innovation prioritizes the control of intellectual property and value appropriation.Accordingly,both extend beyond firm-level technology strategy to broader questions of how AI brands balance user trust with national strategic imperatives through governance frameworks,thereby strengthening the institutional and cultural foundations for long-term competitiveness in the global AI landscape. This paper examines eight representative generative AI product brands from China and the United States to clarify how perceived brand open-source culture and perceived intelligence shape user attitudes.Based on a survey of 734 users across China,the results show that perceived brand open-source culture positively predicts both long-term usage intention and willingness to disclose information.Perceived intelligence strengthens long-term usage intention.Its direct effect on willingness to disclose information is significantly positive,but becomes negative after mediating variables are introduced.Customer-based national technological equity(NTE)and AI product trust mediate these effects.In addition,national brand warmth and national brand competence moderate the positive effects of perceived brand open-source culture and perceived intelligence on customer-based NTE,respectively. From a techno-cultural perspective,this paper extends open-source culture from a technical dichotomy of open versus closed to a branding-oriented cultural construct.By incorporating customer-based NTE into the analytical framework,it enriches the application of national brand equity theory in the AI domain.Further,from the standpoints of privacy and information management,it highlights privacy trade-offs in human-machine interaction and explicates the negative role of high perceived intelligence in willingness to disclose information.Overall,the findings offer practical insights into how generative AI firms can leverage perceived brand open-source culture and technological innovation to strengthen their competitive advantage.