Panel study reveals that digital technology enhances new quality productivity in carbon-intensive enterprises, highlighting knowledge integration mechanisms.
Purpose This study aims to explore how and whether digital technology (DT) is positively associated with the development of New Quality Productivity (NP) in carbon-intensive enterprises. Design/methodology/approach Grounded in the Knowledge-Based View (KBV), this paper uses panel data from China’s A-share-listed carbon-intensive enterprises from 2011to 2022 to empirically examine the impact of digital technology on NP. It further investigates the mediating role of knowledge integration (KI) and its two dimensions – knowledge integration creation (KIC) and knowledge integration reuse (KIR) – in this relationship. Findings The results reveal that digital technology significantly promotes the development of NP in carbon-intensive enterprises. Moreover, knowledge integration, through its creation and reuse processes, plays a significant mediating role between digital technology and new quality productivity, uncovering the internal mechanism by which digital technology enhances NP. Research limitations/implications Theoretically, this study expands the research boundary of Marxist productivity theory by constructing a conceptual framework of NP for carbon-intensive enterprises. Practical implications The findings provide practical insights for carbon-intensive enterprises seeking low-carbon and high-quality development. By leveraging digital technology to strengthen knowledge integration and innovation capabilities, enterprises can identify low-carbon development pathways aligned with their industrial characteristics, thereby promoting continuous improvement in NP and advancing sustainable development goals. Originality/value This study develops a knowledge-based framework explaining how digital technology restructures firms’ internal knowledge architecture to facilitate productivity upgrading. It further clarifies the mediating role of knowledge integration in this process.
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Yang et al. (2026) studied this question.
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