Leveraging AI-driven knowledge networks for sustainable business model innovation: the mediating role of absorptive capacity and the moderating role of sustainable entrepreneurial orientation

Purpose This study examines how artificial intelligence (AI)-powered knowledge networks support sustainable business model innovation, focusing on the mediating role of knowledge absorptive capacity and the moderating role of sustainable entrepreneurial orientation. Design/methodology/approach Drawing on the knowledge-based view and dynamic capability theory, the study tests a moderated mediation model using a final dataset of 400 valid responses affiliated with business schools in China. Partial least squares structural equation modelling was used to examine direct, mediated, moderated and moderated mediation effects. Findings The findings show that AI integration capability, innovation network strength and knowledge-sharing culture influence sustainable business model innovation both directly and indirectly through knowledge absorptive capacity. Sustainable entrepreneurial orientation strengthens selected relationships, particularly those involving AI capability, knowledge-sharing culture and absorptive capacity. Research limitations/implications The study is based on cross-sectional, self-reported data from business-school-affiliated respondents in China. Future research should test the model using practitioner-based samples, longitudinal designs and different industrial and national contexts. Practical implications Managers should not only invest in AI tools and collaborative networks but also develop employees' ability to interpret AI-generated knowledge and translate external knowledge into sustainability-oriented innovation. Social implications The findings highlight how AI-enabled knowledge networks can support sustainability-oriented innovation, resource efficiency, circular economy practices and broader social innovation goals. Originality/value The study integrates technological, relational, cultural, absorptive and entrepreneurial dimensions into a single framework explaining sustainable business model innovation.

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Publication Details

Journal
Business Process Management Journal
Published
2026-06-29
DOI
https://doi.org/10.1108/bpmj-06-2025-0992
Primary Topic
Knowledge Management and Sharing
Type
article
Field-Weighted Citation Impact
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article

Leveraging AI-driven knowledge networks for sustainable business model innovation: the mediating role of absorptive capacity and the moderating role of sustainable entrepreneurial orientation

Georgia Sakka, Massoud Moslehpour, K T Chau, Muhammad Sadiq et al.
Business Process Management Journal
Knowledge Management and Sharing
article

Leveraging AI-driven knowledge networks for sustainable business model innovation: the mediating role of absorptive capacity and the moderating role of sustainable entrepreneurial orientation

Georgia Sakka, Massoud Moslehpour, K T Chau, Muhammad Sadiq, Aisha Khan
article en

Abstract

Purpose This study examines how artificial intelligence (AI)-powered knowledge networks support sustainable business model innovation, focusing on the mediating role of knowledge absorptive capacity and the moderating role of sustainable entrepreneurial orientation. Design/methodology/approach Drawing on the knowledge-based view and dynamic capability theory, the study tests a moderated mediation model using a final dataset of 400 valid responses affiliated with business schools in China. Partial least squares structural equation modelling was used to examine direct, mediated, moderated and moderated mediation effects. Findings The findings show that AI integration capability, innovation network strength and knowledge-sharing culture influence sustainable business model innovation both directly and indirectly through knowledge absorptive capacity. Sustainable entrepreneurial orientation strengthens selected relationships, particularly those involving AI capability, knowledge-sharing culture and absorptive capacity. Research limitations/implications The study is based on cross-sectional, self-reported data from business-school-affiliated respondents in China. Future research should test the model using practitioner-based samples, longitudinal designs and different industrial and national contexts. Practical implications Managers should not only invest in AI tools and collaborative networks but also develop employees' ability to interpret AI-generated knowledge and translate external knowledge into sustainability-oriented innovation. Social implications The findings highlight how AI-enabled knowledge networks can support sustainability-oriented innovation, resource efficiency, circular economy practices and broader social innovation goals. Originality/value The study integrates technological, relational, cultural, absorptive and entrepreneurial dimensions into a single framework explaining sustainable business model innovation.

Business Process Management Journal
Asia University (TW), Shenzhen Polytechnic University (CN), Limassol General Hospital (CY), Scottish School of Christian Mission (GB), Taylor's University (MY), Mediterranean Institute of Management (CY), California State University, San Bernardino (US), Hang Seng University of Hong Kong (HK), Fuzhou University (CN), Vikram University (IN), University of Hong Kong (HK)
Decent work and economic growth
Openalex Percentile: Top 4%
Knowledge Management and Sharing
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