How artificial intelligence promotes new quality productive forces of firms: A dynamic capability view

IF 12.9 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change Pub Date : 2025-04-13 DOI:10.1016/j.techfore.2025.124128

Tachia Chin , Zhisheng Li , Leping Huang , Xinyu Li

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引用次数: 0

Abstract

Global economic growth has entered into the recovery phase of the economic cycle that is resilient yet slow, while the main culprit lies in the lower growth of green total factor productivity (TFP) caused by climate change intensification. It is imperative to formulate unconventional productivity models that can simultaneously solve ecological concerns and the crucial challenges posed by low innovation-driven productivity. This research aims to explore how and whether artificial intelligence (AI) as a critical dynamic capability to strengthen the development of firms' new quality productive forces (NQPFs). Based on the sample of Chinese manufacturing listed companies from 2011 to 2022, our findings show that AI promotes the development of firms' NQPFs; green innovation mediates the AI–NQPFs relationship, while economic policy uncertainty (EPU) moderates the above-mentioned mediating mechanism. Theoretically, our research extends Marx's view of productive forces to create a new construct of advanced productivity in China. Considering AI as a critical dynamic capability, we also provide insights into how productive forces are formed by human intelligence and AI. Practically, our findings help policymakers and practitioners reduce the impact of EPU caused partly by climate changes through AI usage and thereby predict the next trend of sustainable development.

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人工智能如何促进企业新的优质生产力：动态能力视角

全球经济增长已进入有韧性但缓慢的经济周期恢复期，其主因在于气候变化加剧导致绿色全要素生产率增长放缓。制定非常规的生产率模型是当务之急，它可以同时解决生态问题和低创新驱动生产率带来的关键挑战。本研究旨在探讨人工智能（AI）作为一种关键的动态能力如何以及是否能够加强企业新质量生产力（NQPFs）的发展。基于2011 - 2022年中国制造业上市公司样本，我们的研究结果表明：人工智能促进了企业NQPFs的发展；绿色创新在AI-NQPFs关系中起中介作用，而经济政策不确定性（EPU）在上述中介机制中起调节作用。从理论上讲，我们的研究延伸了马克思的生产力观，以创造中国先进生产力的新建构。考虑到人工智能是一种关键的动态能力，我们还提供了人类智能和人工智能如何形成生产力的见解。实际上，我们的研究结果有助于政策制定者和从业者通过人工智能的使用减少部分由气候变化引起的EPU的影响，从而预测可持续发展的下一个趋势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Technological Forecasting and Social Change Multiple-

CiteScore

21.30

自引率

10.80%

发文量

813

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