Document Type
Article
Publication Date
2001
DOI
10.1023/A:1011342615178
Publication Title
Computational & Mathematical Organization Theory
Volume
7
Issue
1
Pages
5-44
Abstract
When an organization’s output declines due to either internal changes or changes in its external environment, it needs to adapt. In order to evaluate the effectiveness of different adaptation strategies on organizational per- formance, an organizational model composed of individual models of a five stage interacting decision maker was designed using an object oriented design approach and implemented as a Colored Petri net. The concept of entropy is used to calculate the total activity value, a surrogate for decision maker workload, based on the functional partition and the adaptation strategy being implemented. The individual decision maker’s total activity is monitored, as overloaded decision makers constrain organizational performance. A virtual experiment was conducted; organizations implementing local and global adaptation strategies were compared to a control organization with no adaptation. The level of tolerance of the organization, the workload limit based on the concept of the bounded rationality constraint, was used to determined when a decision maker was overloaded: the limiting effect of theworkload on performance. The timeliness of the organization’s responsewas used in order to evaluate organizational output as a function of adaptation strategy.
Original Publication Citation
Handley, H. A., & Levis, A. H. (2001). A model to evaluate the effect of organizational adaptation. Computational & Mathematical Organization Theory, 7(1), 5-44. doi: 10.1023/A:101134261517
Repository Citation
Handley, Holly A. H. and Levis, Alexander H., "A Model to Evaluate the Effect of Organizational Adaptation" (2001). Engineering Management & Systems Engineering Faculty Publications. 38.
https://digitalcommons.odu.edu/emse_fac_pubs/38
Included in
Management Sciences and Quantitative Methods Commons, Operational Research Commons, Systems Engineering Commons, Theory and Algorithms Commons