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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.14709 |
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| _version_ | 1866908671964872704 |
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| author | Aghaei, Raha Kiaei, Ali A. Boush, Mahnaz Rofoosheh, Mahan Zavvar, Mohammad |
| author_facet | Aghaei, Raha Kiaei, Ali A. Boush, Mahnaz Rofoosheh, Mahan Zavvar, Mohammad |
| contents | This study analyzes the multiple functions of Large Language Models (LLMs) in transforming research and development (R&D) processes. By automating knowledge discovery, boosting hypothesis creation, integrating transdisciplinary insights, and enabling cooperation within innovation ecosystems, LLMs dramatically improve the efficiency and effectiveness of research processes. Through extensive analysis of scientific literature, patent databases, and experimental data, these models enable more flexible and informed R&D workflows, ultimately accelerating innovation cycles and lowering time-to-market for breakthrough ideas. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_14709 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Strategic Innovation Management in the Age of Large Language Models Market Intelligence, Adaptive R&D, and Ethical Governance Aghaei, Raha Kiaei, Ali A. Boush, Mahnaz Rofoosheh, Mahan Zavvar, Mohammad Computation and Language This study analyzes the multiple functions of Large Language Models (LLMs) in transforming research and development (R&D) processes. By automating knowledge discovery, boosting hypothesis creation, integrating transdisciplinary insights, and enabling cooperation within innovation ecosystems, LLMs dramatically improve the efficiency and effectiveness of research processes. Through extensive analysis of scientific literature, patent databases, and experimental data, these models enable more flexible and informed R&D workflows, ultimately accelerating innovation cycles and lowering time-to-market for breakthrough ideas. |
| title | Strategic Innovation Management in the Age of Large Language Models Market Intelligence, Adaptive R&D, and Ethical Governance |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2511.14709 |