Artificial intelligence capability, CEO-TMT interface and corporate innovation failure
Bibliographic Data
| ID | 17832178 |
|---|---|
| Authors | Junru Shang (Shanghai University), Kun Zhang (0000-0003-1636-5373, corresponding author) |
| Year | 2026 |
| Volume | 13 |
| Issue | 1 |
| Publication date | 2026-03-07 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Humanities and Social Sciences Communications (JOURNAL) |
| Journal identifiers | ISSN: 2662-9992 • E-ISSN: 2662-9992 |
| Publisher | Palgrave Macmillan (PUBLISHER • GB) |
| DOI | 10.1057/s41599-026-06856-2 |
| OpenAlex | W7134211984 |
| Language | EN |
| References cited | 81 |
Artificial intelligence (AI) capability has demonstrated significant potential in driving knowledge recombination, fostering knowledge discovery and enhancing organisational innovation performance. However, the interplay between AI capability and corporate innovation failure remains underexplored. To address this research gap, this study investigated the impact of AI capability on corporate innovation failure while further examining the moderating role of top management team (TMT) digital knowledge and its variation under different levels of integrative leadership shown by chief executive officers (CEOs). Using panel data from 3,829 firm-year observations in China from 2017 to 2022, the empirical analysis reveals that AI capability significantly reduces the likelihood of corporate innovation failure. Moreover, TMT digital knowledge exerts a significant positive moderating effect on this relationship. Further analysis reveals that this positive moderating effect is more pronounced when the CEO exhibits a high level of integrative leadership
Empirical research · Innovation Management · Knowledge economy · Knowledge sharing · Panel data · Patent analysis · Technology Innovation · AI in Service Interactions · Digital Transformation in Industry · Ethics and Social Impacts of AI
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| Citation velocity | historical |
|---|---|
| Highly cited | No |