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Corporate Sustainability

Jun Luo & Xin Zhang

International Journal of Enterprise Information Systems2025https://doi.org/10.4018/ijeis.387397article
AJG 1ABDC C
Weight
0.50

What the paper says

This study utilizes panel data of worldwide listed companies from 2013 to 2022 and employs a fixed-effects model to empirically examine the impact of artificial intelligence (AI) on corporate sustainable development and its underlying mechanisms. The results indicate that AI significantly enhances corporate sustainable development capabilities. Heterogeneity analysis reveals that the effect of AI on sustainable development varies across firm characteristics such as firm size, market competition intensity, and firm age. Specifically, AI has a more pronounced impact on firms with larger asset scales compared to those with smaller scales, firms with fewer employees compared to those with more employees, firms in highly competitive markets compared to those in less competitive markets, and mature firms compared to younger firms. Mechanism analysis shows that AI facilitates corporate sustainable development by reducing information asymmetry, enhancing internal financial efficiency through real-time cash flow monitoring and predictive analytics, and alleviating financing constraints by improving access to diversified financial services. Furthermore, AI supports sustainability by optimizing environmental and social performance, thereby enhancing ESG ratings and advancing sustainable development goals. This study establishes a theoretical framework linking artificial intelligence and corporate sustainability based on the Resource-Based View (RBV). By further integrating perspectives on financing, collaboration, and ESG performance, the research offers valuable insights for firms and policymakers aiming to enhance sustainable competitiveness.

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https://doi.org/https://doi.org/10.4018/ijeis.387397

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@article{jun2025,
  title        = {{Corporate Sustainability}},
  author       = {Jun Luo & Xin Zhang},
  journal      = {International Journal of Enterprise Information Systems},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.4018/ijeis.387397},
}

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Corporate Sustainability

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.