Reducing Capital Market Anomaly: The Role of Information Technology Using an Information Uncertainty Lens

• 成果类型: Article
• 署名作者: Jia, Ning; Rai, Arun; Xu, Sean Xin
• 署名单位: Tsinghua University; University System of Georgia; Georgia State University; University System of Georgia; Georgia State University; Tsinghua University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2018.3235
• 发表日期: 2020
• 页码: 979-1001
• 关键词: capital market; Anomaly; market efficiency; INFORMATION UNCERTAINTY; enterprise systems; IT business value

摘要

We investigate how firms use information technology (IT) implementation to mitigate an anomaly in capital markets: investors underreacting to new public information. The theory of information uncertainty (IU) suggests that the anomaly is amplified with IU; that is, with ambiguity in information about firm value. We theorize that a firm's IT in general- and enterprise systems (ES) in particular-can mitigate IU, thus reducing the NJ-induced underreaction anomaly. Based on a difference-in-differences analysis of a sample of 572 ES implementations, our main finding is that ES implementation does reduce NJ-induced underreaction anomaly. This is achieved through a reduction in the firm's fundamentals volatility and an improvement in information quality. We also find that firms with greater capability are better positioned to realize the anomaly-reducing benefits of ES implementation and that ES's anomaly-reducing effect is most pronounced when high levels of both functional and operational ES modules are implemented. We obtain remarkably consistent results when using alternate empirical design, samples, and measures of news. Such IT impacts are economically highly consequential because they improve capital market efficiency.