The effects of Artificial intelligence orientation on inefficient investment: Firm-level evidence from China's energy enterprises

Minhan Zhai, Wenqing Wu and Sang-Bing Tsai

Energy Economics, 2025, vol. 141, issue C

Abstract: The development of Artificial Intelligence (AI) has brought both opportunities and challenges for energy enterprises to make investment decisions. This paper considers an Artificial intelligence orientation (AIO) indicator that reflects AI introduction and deployment to analyze whether and how AIO affects inefficient investment in energy enterprises. By using machine learning methods to construct AIO indicators, this paper finds that AIO can effectively alleviate ineffective investments in energy enterprises. Furthermore, this paper explores the moderating effects of the absorbed slack resources and conducts heterogeneity analysis based on enterprises ownership and lifecycle. The research results indicate that absorbed slack resources can weaken the alleviating effect of AIO on investment inefficiency. Besides, heterogeneity analysis also reveals that AIO can significantly alleviate investment inefficiency in the non-state-owned energy enterprises and those in the growth stage. These findings are important for energy enterprises to adopt and deploy AI technologies.

Keywords: Ineffective investment; Artificial intelligence orientation; Absorbed slack resources; Enterprises ownership; Enterprise lifecycle; Machine learning (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:141:y:2025:i:c:s0140988324007576

DOI: 10.1016/j.eneco.2024.108048

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