Research on the Green and Low-Carbon Development Path of Digital Intelligence Empowering Enterprises in Manufacturing Industry

Xiaofei Wang, Shaowen Zhan (), Longlong Liu and Peng Zhang
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Xiaofei Wang: School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China
Shaowen Zhan: School of Public Administration, Xi’an University of Architecture and Technology, Xi’an 710055, China
Longlong Liu: School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China
Peng Zhang: School of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China

Sustainability, 2025, vol. 17, issue 6, 1-23

Abstract: The Fourth Industrial Revolution, driven by advancements in information technology, has ushered humanity into the age of intelligence. As digital technologies like artificial intelligence and large-scale models continue to evolve and gain traction, the convergence of digital innovation and green development within manufacturing enterprises has emerged as a pivotal trend. This integration not only fosters high-quality, sustainable growth, but also increasingly validates the impact of digital intelligence on advancing low-carbon performance. This study delves into how manufacturing enterprises can attain sustainable and low-carbon growth via digital transformation, employing the entropy TOPSIS evaluation model to assess the effectiveness of various empowerment strategies. Based on the findings, the paper offers actionable recommendations for enhancing sustainable practices in manufacturing during this digital shift. Beyond enriching the theoretical framework on the synergy between digital intelligence and sustainability in manufacturing, this research provides practical insights and guidance for enterprises leveraging next-generation digital technologies to drive their green and low-carbon initiatives more effectively.

Keywords: manufacturing enterprises; intellectualization of numbers; green and low-carbon development; efficiency measurement; lifting path (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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