Determinants and performance outcomes of artificial intelligence adoption: Evidence from U.S. Hospitals

Phuoc Pham, Huilan Zhang, Wenlian Gao and Xiaowei Zhu

Journal of Business Research, 2024, vol. 172, issue C

Abstract: Integrating Artificial Intelligence (AI) technology in hospitals offers a unique opportunity to improve hospitals’ operating and financial performance. This study is among the first to investigate the determinants and subsequent performance outcomes associated with AI adoption. Using an extensive dataset encompassing 941 AI hospital-year observations and 941 non-AI hospital-year observations, we find that hospitals with a larger market share are great candidates to adopt AI. Furthermore, these hospitals can leverage AI technology to enhance various aspects of performance, including total outpatient revenue, total inpatient revenue, productivity, and occupancy. Importantly, we demonstrate that controlling for endogeneity is essential in assessing the performance outcomes of AI adoption. Our findings shed light on the determinants of AI adoption decisions in healthcare and underscore the manifold benefits AI technology brings to hospital operations and financial outcomes.

Keywords: Artificial Intelligence; AI Adoption; Hospital Performance; Healthcare (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:172:y:2024:i:c:s0148296323007610

DOI: 10.1016/j.jbusres.2023.114402

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