感知品牌开源文化对用户态度的影响

——人工智能产品信任与品牌的国家科技资产的链式中介效应

何佳讯¹　胡静怡¹　章子欣²

（1.华东师范大学；2.东华大学）

摘要：生成式人工智能（Generative AI）技术的快速发展在全球范围内掀起一场深刻的科技变革，在推动技术创新突破的同时深刻影响了国家间的科技竞争与战略博弈。人工智能研发领域的开源与闭源技术路径，催生出生成式人工智能产品差异化的发展战略。本文选取中美两国共计八个生成式人工智能品牌作为研究样本开展实证分析。基于734份有效调研数据的研究结果显示，感知品牌开源文化对用户长期使用意愿与信息自主披露意愿均存在正向影响；感知智能能够促进用户长期使用意愿，但其对信息自主披露意愿的影响兼具正向与负向双重效应；品牌国家科技资产与AI产品信任在上述关系中起中介作用。温暖型国家品牌印象与能力型国家品牌印象，分别对感知品牌开源文化、感知智能作用于品牌的国家科技资产的正向路径起调节作用。本文的研究从文化-技术双元视角，为阐释AI产品用户信任与态度形成机制补充了理论依据，也为国家层面AI品牌战略布局提供实践参考，尤其对生成式人工智能品牌借助技术与文化双重战略提升品牌竞争力、强化用户信任及使用意愿，具备重要的理论与现实意义。

关键词：生成式人工智能；感知品牌开源文化；感知智能；AI产品信任；品牌的国家科技资产

作者简介：何佳讯，华东师范大学亚欧商学院/上海国际首席技术官学院教授、博士生导师，通信作者，上海，200062；胡静怡，华东师范大学经济与管理学院博士；章子欣，东华大学机械工程学院助教，上海，200051。

基金项目：国家自然科学基金面上项目“人工智能对齐计算：品牌价值观的‘新基建’、智能产品开发与智能生态品牌战略研究”（72472052）

引用格式：何佳讯，胡静怡，章子欣. 感知品牌开源文化对用户态度的影响：人工智能产品信任与品牌的国家科技资产的链式中介效应［J］. 经济与管理研究，2026，47（9）：112-128.

Impact of Perceived Brand Open-Source Culture on User Attitudes

—The Chain Mediating Effect of AI Product Trust and Customer-Based National Technological Equity

HE Jiaxun¹, HU Jingyi¹, ZHANG Zixin²

(1. East China Normal University, Shanghai 200062；

2. Donghua University, Shanghai 200051）

Abstract: 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.

Keywords: generative AI; perceived brand open-source culture; perceived intelligence; AI product trust; customer-based national technological equity

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