权力下放
任务(项目管理)
工作(物理)
知识管理
计算机科学
新兴技术
业务
集合(抽象数据类型)
信息技术
营销
考试(生物学)
工作设计
早期采用者
大数据
外包
工作强度
技术管理
工程管理
数据科学
控制(管理)
自动化
绩效管理
并列争球
自举(财务)
过程管理
高级管理人员
作者
Piyush Gulati,Arianna Marchetti,Phanish Puranam
出处
期刊:Management Science
[Institute for Operations Research and the Management Sciences]
日期:2026-03-20
卷期号:72 (11): 9584-9608
被引量:5
标识
DOI:10.1287/mnsc.2023.04127
摘要
Do digital technologies reinforce managerial hierarchies or, instead, make them less relevant? We propose that the answer to this question depends on the nature of the technology: specifically, its relative impact on managers’ capacity to supervise and on subordinates’ need for supervision. Applying this framework to collaborative work management (CWM) technologies that facilitate real-time collaboration, communication, and task coordination, we predict that the adoption of such technologies should reduce managerial intensity and increase decentralization in organizations. To test this prediction, we use a difference-in-differences design on a novel data set built from over 26 million job listings (Lightcast) and over 20 million social profiles (Revelio) matched to 3,017 U.S. public firms in Compustat, which we track over the period from 2010 to 2019. We find that over the observation window, CWM technology adopters show a 3% reduction in managerial intensity and a 5%–7% increase in nonmanagerial skills linked to decentralization in their job postings in the years following adoption. The pattern of results is robust to a battery of validations, alternative measures, and specifications, and it strongly supports the idea that these technologies enable collaboration and make organizations less hierarchical along the dimensions that we studied. This paper was accepted by Sameer Srivastava, organizations. Funding: P. Gulati acknowledges financial support from the UCL School of Management, the Ian Potter ‘93 PhD Award at INSEAD, and the Will Mitchell Dissertation Research Grant. P. Puranam acknowledges financial support from the Desmarais Fund at INSEAD for the Organizations & Algorithms Project. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.04127 .
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