Does Artificial Intelligence Promote Firms’ Innovation Efficiency: Evidence from the Robot Application

Shuai Wang (), Xin Huang (), Mengyue Xia () and Xing Shi ()
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Shuai Wang: Hefei University of Technology
Xin Huang: Hefei University of Technology
Mengyue Xia: Hefei University of Technology
Xing Shi: Hefei University of Technology

Journal of the Knowledge Economy, 2024, vol. 15, issue 4, No 35, 16373-16394

Abstract: Abstract While artificial intelligence (AI) is widely acknowledged as a transformative technology with the potential to boost productivity, there is limited understanding of its specific impact on firm innovation efficiency. This study leverages robot data from the International Federation of Robotics (IFR) and detailed data on Chinese manufacturing firms spanning 2015 to 2019. The analysis utilizes the Data Envelopment Analysis (DEA) method to evaluate firms’ innovation efficiency and employs the Tobit model to examine the influence of AI on innovation efficiency. Furthermore, the study delves into the heterogeneity of this impact by considering variations in firm ownership, industries, and regions and explores the mechanisms through which AI affects innovation efficiency. The findings demonstrate that AI application significantly enhances firms’ innovation efficiency, a result that holds robustly even after employing alternative AI proxies and instrumental variable regression. Moreover, the positive effects of AI adoption are primarily observed in state-owned enterprises, traditional manufacturing industries, and developed cities. Further analyses indicate that AI adoption modifies human capital, innovation patterns, and the market environment, thereby influencing innovation efficiency. This research provides valuable insights into unleashing the innovation potential of AI technology.

Keywords: Artificial intelligence; Innovation efficiency; Manufacturing firms; Robot application (search for similar items in EconPapers)
JEL-codes: L25 O32 Q55 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13132-023-01707-w

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