Earticle

초록

영어

Firms increasingly reference artificial intelligence in annual reports to signal technological sophistication, yet whether such disclosures represent genuine innovation commitment or symbolic posturing remains unclear. This distinction carries significant theoretical and practical stakes: the proliferation of AI-related corporate communication introduces information asymmetry into capital markets, complicates the design of disclosure standards, and distorts the allocation of innovation subsidies toward firms engaging in rhetorical rather than substantive technological commitment. This study examines how AI-related corporate disclosures translate into innovation outcomes and financial performance, addressing gaps in understanding performative versus symbolic dimensions of technology communication. Drawing on signaling theory, the resource-based view, and institutional perspectives, we theorize AI disclosure operates through dual pathways: externally, by inviting stakeholder monitoring and attracting complementary resources; internally, by creating accountability mechanisms coordinating organizational attention and stimulating innovation momentum. We test this framework using comprehensive panel data from 36,200 firm-year observations of Chinese listed firms spanning 2007-2023, employing firm- and year-fixed effects regressions, propensity score matching, and mediation analyses with bootstrapped standard errors. Results demonstrate AI disclosure intensity strongly predicts subsequent invention patent output, with 10% increase in disclosure associating with approximately 2.8% increase in patent applications. Innovation partially mediates the disclosure-performance relationship, with significant positive indirect effects confirmed through bootstrapped estimates, though direct effects are negative, reflecting short-term costs before innovation benefits materialize. Critically, the disclosure-innovation effect diminishes among R&D-intensive firms, suggesting signaling substitution wherein communicative emphasis provides limited incremental value when firms already demonstrate technological commitment through observable R&D spending. Conversely, the effect strengthens by 34% in market-oriented institutional contexts—specifically among non-financially distressed firms operating under fewer regulatory constraints—indicating external accountability structures amplify conversion of symbolic communication into substantive innovation. Theoretically, we reconceptualize disclosure as performative communication catalyzing capability development when embedded in accountability structures, extending signaling theory by demonstrating communicative acts mobilize resources beyond passive information revelation. We identify absorptive capacity and institutional accountability as critical boundary conditions for symbolic-substantive conversion, specifying micro-mechanisms through which external signals become internal capabilities.

목차

Abstract
1. Introduction
2. Theoretical Framework and Hypotheses
2.1. From Signaling to Substance: AI Disclosure as Performative Communication
2.2. Innovation as Mediating Pathway to Financial Performance
2.3. Absorptive Capacity as Conversion Mechanism
2.4. Institutional Context: Ownership and Market Discipline
2.5. Integrative Framework
3. Research Methodology
3.1. Data and Sample
3.2. Variable Measurement
3.3. Empirical Strategy
3.4. Addressing Endogeneity
4. Results
4.1. Descriptive Statistics
4.2. Main Effects: AI Disclosure and Innovation
4.3. Mediation Analysis
4.4. Endogeneity Checks
4.5. Institutional Heterogeneity
4.6. Summary of Findings
5. Discussion and Conclusion
5.1. Theoretical Contributions
5.2. The Chinese Institutional Context: Why It Matters for AI Disclosure
5.3. Practical Implications
5.4. Limitations and Future Research
5.5. Conclusion
References

키워드

저자

• Han, Byoung-Sop [ College of Business Administration, Chonnam National University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  Journal of China Studies

• 간기

  계간

• pISSN

  1975-5902

• eISSN

  3022-5590

• 수록기간

  2006~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 912 DDC 951