Artificial Intelligence and Firm Resilience: Empirical Evidence from Natural Disaster Shocks

弹性(材料科学) 自然灾害 经验证据 计算机科学 业务 数据科学 地理 哲学 物理 认识论 气象学 热力学
作者
Miaozhe Han,Hongchuan Shen,Jing Wu,Xiaoquan Zhang
出处
期刊:Information Systems Research [Institute for Operations Research and the Management Sciences]
卷期号:36 (4): 2116-2133 被引量:23
标识
DOI:10.1287/isre.2022.0440
摘要

Artificial intelligence (AI) has been increasingly deployed in business operations over the past decade, whereas direct evidence of its effectiveness in uncertain contexts is limited. Our work examines the contribution of AI to corporate resilience under natural disaster shocks, particularly concentrating on AI-using and goods-producing firms. We measure firm AI investment by the cumulative AI-relevant skills extracted from a comprehensive job posting database and firm resilience by the changes in corporate valuation in response to operational shocks. Evidence suggests that AI generates resilience: An average firm that equips 2.4% of total jobs to be AI-related could approximately recover the full damage of disasters reflected in corporate valuation over a short event window. From the product function test, we find that resilience is attributable to the moderating effect of AI on the damaged input responsiveness under the volatile production environment. Our analyses further reveal a pressing phenomenon: Although underperforming firms could benefit more from an additional unit of AI investment, the realized productivity is notably restrained due to a lack of complementary organizational designs. Our findings provide managerial implications regarding the interplay between environmental conditions and firm investments in both AI technology and complementary infrastructures.
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