Big data analytics and management forecasting behavior

• Main Authors: GOH, Beng Wee, LI, Na, RANASINGHE, Tharindra
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Big data; data analytics; management forecasts; voluntary disclosure; Accounting; Corporate Finance
• Online Access: https://ink.library.smu.edu.sg/soa_research/2016; https://ink.library.smu.edu.sg/context/soa_research/article/3043/viewcontent/horizons_2020_145_pv.pdf
• Institution: Singapore Management University

This paper investigates whether the use of Big Data analytics by firms has a spillover effect on management forecasting behavior. Insights provided by Big Data could potentially improve firms’ ability to forecast earnings (supply channel) and investor demand for earnings information is likely higher for firms engaging in data analytics (demand channel). Using a text-based measure of firms’ commitments to and usage of Big Data analytics, we find that Big Data analytics usage is positively associated with the propensity to issue management earnings forecasts. Consistent with the “supply channel” explanation, we find that Big Data analytics usage is positively associated with management forecast accuracy as well. Also, supporting the “demand channel” explanation, we find that Big Data analytics usage is associated with greater analyst following. Our findings of improved disclosure following commitments to Big Data analytics highlight a potentially unintended benefit of the Big Data revolution.