ORIGINAL RESEARCH article
Front. Sustain. Food Syst.
Sec. Agricultural and Food Economics
Volume 9 - 2025 | doi: 10.3389/fsufs.2025.1618551
This article is part of the Research TopicEnvironmental Resilience and Sustainable Agri-food System ManagementView all 23 articles
The Impact of Environmental Tax Policies on Artificial Intelligence Investment: Evidence from Agri-Food, Food Processing, and Other Industries
Provisionally accepted
- Hunan University, Changsha, China
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As China's environmental governance policies become increasingly stringent, the Environmental Protection Tax, as a key market-based regulatory instrument, has begun to exert a profound influence on corporate technological behaviour. Taking the 2018 implementation of the Environmental Protection Tax Law as a quasi-natural experiment, this study uses a difference-in-differences model to systematically evaluate the impact of the tax on artificial intelligence investment by Chinese A-share listed companies from 2010 to 2022. Using the agri-food and food processing industries as representative cases, this study explores their pathways toward digital and green transformation. The findings indicate that enterprises are adopting AI technologies in management, investment, operations, and labour to respond to environmental pressures, making AI investment a key driver of industrial intelligent transformation. In regions with stricter environmental regulations, particularly the eastern coastal areas, the adoption rate of AI in the food industry is the highest, with the most evident policy effect in dairy and beverage manufacturing enterprises. Further analysis reveals that the Environmental Protection Tax significantly promotes AI investment, with more pronounced effects among state-owned enterprises, manufacturing firms, and companies in resource-based cities. Mechanism tests suggest that the tax indirectly facilitates the application of AI technologies by alleviating financing constraints and boosting R&D input. This study enriches the theoretical foundation at the intersection of environmental regulation and digital transformation. The findings provide empirical evidence and practical insights for policy-making and corporate strategy in the context of green and low-carbon development.
Keywords: Food Industry Systems Intelligence, Food Industry Supply Chain Management, DID method, Food Industry Sustainable Development, Environmental protection tax, Artificial Intelligence Investment
Received: 26 Apr 2025; Accepted: 12 Jun 2025.
Copyright: © 2025 Hu, Li and Lai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Bin Li, Hunan University, Changsha, China
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