Publication:
Unleashing Computational Organization Theory with Quantum Probability Theory

Loading...
Thumbnail Image
Authors
Mortimore, David
Canan, Mustafa
Subjects
Computational organization theory
Probability theory
Quantum theory
Decision-making
Advisors
Date of Issue
2022
Date
2022
Publisher
Springer International Publishing
Language
Abstract
Since its nascence, computational organization theory has predominantly relied on classical probability theory to model and simulate organizational properties. However, key assumptions of classical probability theory conflict with empirical studies of organizational behaviors and processes, thereby raising the question if an alternate theoretical basis for probabilistic modeling of organizations might improve the relevancy of computational organization research. In the context of the garbage can model of organizational decision-making, this paper provides two examples—path dependency and system measurement—to illustrate the inadequacy of classical probability theory and to stimulate discussion on the merits of incorporating quantum probability theory in computational models. This paper recommends that future work explore the sensitivity of computational models to probability theories, the impacts theoretical assumptions might have on modeling and simulating dynamic organizational interdependencies, and the implications to methods.
Type
Article
Description
The article of record as published may be found at http://dx.doi.org/10.1007/978-3-031-17114-7_19
Author David Mortimer is an NPS student author.
Series/Report No
Department
Other Units
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
America’s Sea Land Air Military Research Initiative (SLAMR) at the Naval Postgraduate School
Naval Undersea Warfare Center Division, Keyport
Funder
Format
10 p.
Citation
Mortimore, David, and Mustafa Canan. "Unleashing computational organization theory with quantum probability theory." International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation. Cham: Springer International Publishing, 2022.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
Collections