Data Analytics and Operational Efficiency
研究了2004至2018年美国上市公司采用数据分析对一年后运营效率的影响，发现能显著提升效率且持续至少两年，对复杂或信息不确定环境中的企业效果更明显。
SYNOPSIS In a hand-collected sample of U.S. public firms from 2004 to 2018, we investigate the impact of data analytics (DA) adoption on future operational efficiency. Utilizing a propensity score matching difference-in-differences methodology, we find that DA adoption leads to significantly higher one-year ahead operational efficiency, as measured by data envelopment analysis. This positive effect persists for at least two years, and both basic and advanced analytics adoption contribute to this improvement. Furthermore, we find that one-year ahead return on assets and asset turnover are improved for DA-adopting firms, without increasing capital expenditure or cost of goods sold, and potentially even reducing employee salaries or marketing-related expenses. Cross-sectional analyses reveal that the benefits of DA adoption are particularly pronounced for firms operating in more complex or informationally uncertain environments. Our findings provide valuable insights for managers seeking to leverage DA to enhance operational efficiency and achieve sustainable long-term performance gains. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: L20; M10; M15.