How does privacy protection affect the innovation performance of artificial intelligence corporations: empirical evidence from the personal information protection law

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Authors: Yanling Wang, Yingying Jiang, Kaili Li, Xiangjian Zhang
Cited by: 1
References: 48

Abstract

As global data privacy protection regulations become increasingly stringent, privacy protection has emerged as a significant challenge for businesses. This study, based on AI companies listed on the Shanghai and Shenzhen A-share markets in China, empirically examines the impact of privacy protection on key technological innovation in AI firms and explores the underlying mechanisms through which this effect operates. The empirical results demonstrate that privacy protection significantly promotes innovation in key technological areas, especially in non-state-owned enterprises, non-loss-making firms, and firms with non-financial backgrounds, where the effect is particularly pronounced. Moreover, privacy protection indirectly drives core technological innovation by enhancing R&D investment, improving labor investment efficiency, and fostering a culture of collaboration. These findings underscore the importance of privacy protection not just as a compliance cost but as a strategic investment that can enhance long-term firm value. And it has important implications for investors, suggesting that privacy protection should be incorporated into investment evaluations and risk assessments, and can be a valuable signal of long-term sustainable growth.

Fields of Study & Subjects

Privacy Security and Data Protection Cyberloafing and Workplace Behavior Ethics and Social Impacts of AI

Publication details

Journal / source
International Review of Economics & Finance
Publisher
Elsevier BV
Volume
107
Pages
104991–104991
Publication date
6 February 2026
Language
EN