The Effect of Big Data and Analytics on Firm Performance: An Econometric Analysis Considering Industry Characteristics

• 成果类型: Article
• 署名作者: Mueller, Oliver; Fay, Maria; vom Brocke, Jan
• 署名单位: IT University Copenhagen; University of Liechtenstein; University of Liechtenstein; University of Liechtenstein; University of Liechtenstein; University of Liechtenstein
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222
• DOI: 10.1080/07421222.2018.1451955
• 发表日期: 2018
• 页码: 488-509
• 关键词: information-technology value; business analytics; x-efficiency; PRODUCTIVITY; IMPACT; INVESTMENT; INNOVATION; systems; ORGANIZATION; COMPETITION

摘要

The emergence of big data has stimulated enormous investments into business analytics solutions, but large-scale and reliable empirical evidence about the business value of big data and analytics (BDA) remains scarce. This article presents the results of an econometric study that analyzes the direction, sign, and magnitude of the relationship between BDA and firm performance based on objective measurements of BDA assets. Using a unique panel data set that contains detailed information about BDA solutions owned by 814 companies during the time frame from 2008 to 2014, on the one hand, and their financial performance, on the other hand, we estimate the relationship between BDA assets and firm productivity and find that live BDA assets are associated with an average of 3-7 percent improvement in firm productivity. Yet we also find substantial differences in returns from BDA when we consider the industry in which a firm operates. While firms in information technology-intensive or highly competitive industries are clearly able to extract value from BDA assets, we did not detect measurable productivity improvement for firms outside these industry groups. Taken together, our findings provide robust empirical evidence for the business value of BDA, but also highlight important boundary conditions.