How controls influence organizational information processing: insights from a computational modeling investigation

Chris P. Long (), Sim B. Sitkin (), Laura B. Cardinal () and Richard M. Burton ()
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Chris P. Long: Georgetown University
Sim B. Sitkin: Duke University
Laura B. Cardinal: University of Houston
Richard M. Burton: Duke University

Computational and Mathematical Organization Theory, 2015, vol. 21, issue 4, No 4, 406-436

Abstract: Abstract In this study, we use a series of computational models to investigate an information processing perspective on organizational control use. We evaluate and compare the information processing capabilities of various formal and informal control configurations under different information uncertainty conditions. We find that a wide range of formal controls can be used to direct subordinates performing interdependent tasks while a more narrow range of informal controls are most effective for directing subordinates who perform complex tasks. Results of this study provide a basis for formalizing an information processing perspective on organizational control implementation that differs but is complementary to the current emphasis on agency in organizational control research.

Keywords: Organizational control; Information processing; Computational modeling (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s10588-015-9191-z

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