Unpacking the Inverted U-shape between Regional AI and Business Performance

Abstract

This study examines how regional artificial intelligence (AI) influences firms’ business performance from the viewpoint of economic geography. We employ the instrumental variable method to analyze 3633 American listed companies. We find the “regional AI and business performance” relationship appears in an inverted U-shape. By applying the plausible instrumental variable method, our robustness check suggests that our findings are reliable. Theoretically, our paper enriches current regional AI studies with firm-level evidence; practically, our paper sheds light on how to make firm location decisions in the AI era.

Keywords:

• Artificial intelligence
• firm performance
• return on equity
• America

JEL CLASSIFICATION CODES:

• R11
• L10

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 According to preliminary math using the equation: y = β₀+β₁X + β₂X², when β₂ is significant, then the (inverted) U-shape exists. β₀ and β₁ can change the position of the (inverted) U-shape in the coordinate axis, but it is β₂ that determines the (inverted) U-shape. Therefore, “β₁ is insignificant but β₂ is significant” never means that the (inverted) U-shape does NOT exist or means that it is an increasing (or decreasing) return.

2 We would like to thank our two anonymous reviewers for bringing this to our attention.

Additional information

Funding

This paper is financed by the Humanity and Social Science Foundation (grant number: 22YJCZH117), the National Social Science Funds of China (grant number: 22CJL013) and the Innovative Team Project of Guangdong Universities (grant number: 2019WCXTD008).