Predictive analytics and centralization of authority

• 成果类型: Article
• 署名作者: Labro, Eva; Lang, Mark; Omartian, James D.
• 署名单位: University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of Michigan System; University of Michigan
• 刊物名称: JOURNAL OF ACCOUNTING & ECONOMICS
• ISSN/ISSBN: 0165-4101
• DOI: 10.1016/j.jacceco.2022.101526
• 发表日期: 2023
• 关键词: performance; ORGANIZATION; INFORMATION; TECHNOLOGY; DESIGN

摘要

We examine the relation between plant-level predictive analytics use and centralization of authority for more than 25,000 manufacturing plants using proprietary US Census data. We focus on headquarters' authority over plants through delegation of decision-making and design of performance-based incentives. We find that increased predictive analytics use is associated with reduced delegation of decision-rights to local managers, increased centralization of control over data gathering and reduced plant managerial payrolls. In terms of incentives, predictive analytics use is associated with more accurate targets and tighter linkages between rewards to workers (performance-based bonuses, promotions and firings) and measured performance. Overall, our findings suggest that predictive analytics use is associated with increased centralization of authority in headquarters. (c) 2022 Elsevier B.V. All rights reserved.