Modeling and Agent-Based Simulation of Organization in a Stochastic Environment
Abstract
This paper describes a generic model and agent-based simulation to facilitate the analysis of interplay of information collection (task identification) and decision making (task execution) processes, as well as the information flow behaviors in organizations in the face of stochastic mission environments. In these mission environments, task arrivals are stochastic, the characteristics of tasks are not known a priori, but maybe inferred to a certain degree by undertaking the information collection or task identification processes. Through the information collection processes the organization collects the relevant attributes of tasks to estimate the resources necessary for their execution. This information is then used to allocate resources effectively for the execution of tasks. Our model, following structural contingency theory, depicts an organization as consisting of an information-processing, communication and coordination structure that is designed to achieve a specific set of goals, and is comprised of individuals with different information collecting and task execution capabilities. We develop a simulation toolkit based on a discrete event simulator, specifically the ANY LOGIC R simulation package, to quantify the performance of an organization based on this model. We illustrate our approach using a number of coordinating organizational structures operating in a stochastic mission environment.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2007
- Accession Number
- ADA481443
Entities
People
- David Lee Kleinman
- Krishna R. Pattipati
- Sui Ruan
- Swapna S. Gokhale
- Woosun An
Organizations
- University of Connecticut