Journal article
Putting the organization back into computational organization theory: a complex Perrowian model of organizational action
Computational and mathematical organization theory, Vol.14(2), pp.84-119
06/2008
Handle:
https://hdl.handle.net/2376/106925
Abstract
At best, computational models that study organizations incorporate only one perspective of how organizations are known to act within their environments. Such single-perspective models are limited in their generalizability and applicability to the real world and allow for researcher bias. This work develops a multi-agent simulation using eight different well-known organizational perspectives: Strategic choice, contingency theory, behavioral decision theory, enactment, resource dependence, institutional theory, population ecology, and transaction cost economics. A literature review of each field is applied to the construction of algorithms which, when combined with techniques derived from a literature review of computational modeling of organizations, was applied to the construction of a series of algorithms describing a multi-perspective computational model. Computer code was written based on the algorithms and run across different types of environments. Results were statistically analyzed to both validate the model and to generate contingency-oriented hypotheses. Conclusions were made with regard to the expected behavior of organizations and the model’s applicability toward further research.
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Details
- Title
- Putting the organization back into computational organization theory: a complex Perrowian model of organizational action
- Creators
- Brian Kulik - Department of Management, College of Business Central Washington University 400 E. University Way Ellensburg WA 98926 USATimothy Baker - Department of Management and Operations Washington State University 2710 University Drive, CIC 125N Richland WA 99352-1671 USA
- Publication Details
- Computational and mathematical organization theory, Vol.14(2), pp.84-119
- Academic Unit
- Finance and Management Science, Department of
- Publisher
- Springer US; Boston
- Identifiers
- 99900546777401842
- Language
- English
- Resource Type
- Journal article