Generative AI and Sustainable Performance in Manufacturing Firms: Roles of Innovations and AI Regulation
Tengfei Shen () and
Alina Badulescu
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Tengfei Shen: International College, Shinhan University, Seoul 11644, Republic of Korea
Alina Badulescu: Department of Economics and Business, University of Oradea, 410087 Oradea, Romania
Sustainability, 2025, vol. 17, issue 19, 1-23
Abstract:
This study scrutinizes the effects of generative artificial intelligence (GenAI) on sustainable performance (SP) in Chinese manufacturing firms through the mediating role of novelty-centered and efficiency-centered business model innovations (BMIs). It also explores the moderating effect of AI regulation on the GenAI–BMIs and GenAI–SP relationships. Data were collected from 1192 middle-level managers across 500 Chinese manufacturing firms using a two-wave survey design. Partial least squares structural equation modeling (PLS-SEM) was employed to test direct, mediating, and moderating relationships. The findings show that GenAI adoption has a significant positive effect on novelty-centered BMI, efficiency-centered BMI and sustainability performance. The GenAI–SP relationship is mediated by both BMIs, indicating that GenAI contributes to sustainability both directly and through innovative business practices. Moreover, AI regulation significantly strengthens the effects of GenAI on both BMI and SP, emphasizing the importance of regulatory alignment in maximizing technological benefits. This research shows that firms should emphasis AI tools and strategies to innovate their business model for better sustainable outcomes. Firms need to follow regulations and rules embedded into digitalization to ensure a sustainable competitive position in the market.
Keywords: GenAI; business model innovations; sustainable performance; AI regulation; manufacturing firms; China (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:19:p:8661-:d:1758835
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