AI and ML patent intensity and firm performance: A machine learning-based lagged analysis

Küçük Resim Yok

Tarih

2025

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Elsevier Sci Ltd

Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

This study investigates the long-term impact of artificial intelligence (AI) and machine learning (ML) patent intensity on firms' performance, focusing on innovation-driven competitive advantage. Using a panel of 20 technology-intensive firms from 2013 to 2023, this study employs eXtreme gradient boosting (XGBoost) and random forest algorithms to capture nonlinear relationships between AI and ML patent intensity and key financial indicators, including return on assets (ROA), operating margin, and net profit margin. The results indicate that AI and ML patents significantly enhance ROA and operating margins, particularly with a five-year lag, highlighting the delayed but positive influence of such innovations. However, the effect on net profit margin remains limited. These findings underscore the strategic value of AI and ML innovation in driving sustainable firm performance while also emphasizing the importance of long-term planning and complementary investments for maximizing financial returns.

Açıklama

Anahtar Kelimeler

Artificial intelligence, Machine learning, Patent intensity, Firm performance

Kaynak

European Research on Management And Business Economics

WoS Q Değeri

Q1

Scopus Q Değeri

Q1

Cilt

31

Sayı

3

Künye