Production Chain Organization in the Digital Age: Information Technology Use and Vertical Integration in U.S. Manufacturing

生产(经济) 纵向一体化 产业组织 业务 链条(单位) 信息技术 运营管理 制造工程 过程管理 营销 计算机科学 经济 工程类 微观经济学 物理 操作系统 天文
作者
Chris Forman,Kristina McElheran
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
卷期号:71 (2): 1027-1049 被引量:15
标识
DOI:10.1287/mnsc.2019.01586
摘要

Advances in information technology (IT) may affect the organizational design of production. Exploiting the rapid diffusion of the internet in the United States, we assess the sensitivity of production chain organization to this innovation in IT access and use. Extending theories of the firm that recognize the importance of downstream transfers (selling as opposed to sourcing) and plural governance in organizational design, we predict IT-driven shifts in downstream vertical integration. In a detailed panel of Census Bureau data for over 5,600 manufacturing plants, we observe the extent of a production unit’s downstream transactions within the firm alongside concurrent sales to external customers—a mix we refer to as plural selling. Our main finding is that the use of the internet for external coordination precipitated a significant decline in downstream vertical integration across the manufacturing sector. Instrumental variables estimation points to a causal relationship but also heterogeneous treatment effects. Key drivers of plural organization, such as complementarities and constraints across differently governed transactions, help explain such heterogeneity, as does concurrent use of internal production management IT. Our study is the first study to leverage a plural governance framework and large-scale microdata to understand how U.S. production chain organization shifted in response to this rapid and far-reaching technological change. This paper was accepted by David Simchi-Levi, information systems. Funding: This research was performed at the Atlanta, Boston, and Cornell (supported by the Cornell Center for the Social Sciences) Federal Statistical Research Data Centers [Project 1069 (CBDRB-FY22-279)]. Support for the Research Data Centers network from the National Science Foundation [Grant ITR-0427889] is gratefully acknowledged, as is support from the Social Sciences and Humanities Research Council of Canada. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2019.01586 .
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