Strategic orchestration of intellectual capital and human resources for AI-driven business model innovation

Purpose The emergence of generative artificial intelligence (AI) has significantly transformed business model innovation (BMI), yet the extent to which intellectual capital (IC) can mitigate the capability gap in orchestrating ambidextrous human resources for AI-driven BMI remains underexplored. This study investigates how an IC-enhancing human resource management (HRM) system facilitates AI-based BMI through capability reconfiguration. Design/methodology/approach A questionnaire survey was administered using a combination of online and offline methods, yielding a dataset of 472 respondents from Chinese firms. Stratified regression analysis was conducted to examine the relationships among IC-enhancing HRM configurations, capability reconfiguration and BMI. Findings The results indicate that three IC-enhancing HRM configurations – human capital, social capital and organizational capital reconfigurations, positively influence BMI. Furthermore, capability reconfiguration mediates these relationships, while environmental dynamism moderates their effects, reinforcing the critical role of IC in AI-driven business transformation. Research limitations/implications This study is based on a general sample of firms in China; future research could extend the analysis to specific industries or different regional contexts. Additionally, while this research adopts a unidirectional approach to IC-enhancing HRM systems, future studies could explore their interactive effects on innovation. Practical implications The findings underscore the strategic importance of IC-driven HRM systems in fostering AI-based BMI. Organizations can leverage IC as a key knowledge resource to bridge capability gaps, integrate ambidextrous human resources and enhance adaptability in AI-driven business environments. Originality/value This study advances BMI and HRM research by elucidating the role of capability reconfiguration in AI-based BMI. By integrating resource orchestration theory and dynamic capability theory, it provides a comprehensive framework for understanding how IC-enhancing HR systems act as catalysts for innovation in the era of AI.

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Publication Details

Journal
Journal of Intellectual Capital
Published
2025-08-11
DOI
https://doi.org/10.1108/jic-03-2025-0097
Citations
3
Primary Topic
Intellectual Capital and Performance Analysis
Type
article
Field-Weighted Citation Impact
6.68
Controls
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article

Strategic orchestration of intellectual capital and human resources for AI-driven business model innovation

Francesco Caputo, Tachia Chin, Xia Li, Teresa Marrone
3 citations
Journal of Intellectual Capital
Intellectual Capital and Performance Analysis
6.68
article

Strategic orchestration of intellectual capital and human resources for AI-driven business model innovation

Francesco Caputo, Tachia Chin, Xia Li, Teresa Marrone
article en
3 citations

Abstract

Purpose The emergence of generative artificial intelligence (AI) has significantly transformed business model innovation (BMI), yet the extent to which intellectual capital (IC) can mitigate the capability gap in orchestrating ambidextrous human resources for AI-driven BMI remains underexplored. This study investigates how an IC-enhancing human resource management (HRM) system facilitates AI-based BMI through capability reconfiguration. Design/methodology/approach A questionnaire survey was administered using a combination of online and offline methods, yielding a dataset of 472 respondents from Chinese firms. Stratified regression analysis was conducted to examine the relationships among IC-enhancing HRM configurations, capability reconfiguration and BMI. Findings The results indicate that three IC-enhancing HRM configurations – human capital, social capital and organizational capital reconfigurations, positively influence BMI. Furthermore, capability reconfiguration mediates these relationships, while environmental dynamism moderates their effects, reinforcing the critical role of IC in AI-driven business transformation. Research limitations/implications This study is based on a general sample of firms in China; future research could extend the analysis to specific industries or different regional contexts. Additionally, while this research adopts a unidirectional approach to IC-enhancing HRM systems, future studies could explore their interactive effects on innovation. Practical implications The findings underscore the strategic importance of IC-driven HRM systems in fostering AI-based BMI. Organizations can leverage IC as a key knowledge resource to bridge capability gaps, integrate ambidextrous human resources and enhance adaptability in AI-driven business environments. Originality/value This study advances BMI and HRM research by elucidating the role of capability reconfiguration in AI-based BMI. By integrating resource orchestration theory and dynamic capability theory, it provides a comprehensive framework for understanding how IC-enhancing HR systems act as catalysts for innovation in the era of AI.

Journal of Intellectual CapitalVol. 26(6)
Zhejiang University of Science and Technology (CN), Federico II University Hospital (IT), Zhejiang University of Technology (CN), University of Naples Federico II (IT)
Openalex Percentile: Top 4%
Intellectual Capital and Performance Analysis
6.68
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