Date of Award

Summer 1996

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Engineering Management & Systems Engineering

Committee Director

Laurence Richards

Committee Member

Barry Clemson

Committee Member

Derya Jacobs

Committee Member

Irwin Levinstein

Abstract

The research objective is, using engineer turnover, to develop an Artificial Life (A-Life) model and simulation methodology useful for studying behavioral variables of individuals in an organization.

One consequence of work stress is burnout, and its extreme expression is quitting or turnover. Various models have been used to explain and predict this behavior. Behavior models are useful tools to explore the ability of organizational policies to reduce stress levels and turnover. Advancing the usefulness of models is a goal which assists all research on human behavior. A-Life offers a new and different methodology for this purpose. It provides an ability to model large numbers of individuals where the individuals are modeled truly as individuals rather than as statistical condensations. A-Life models also allow modeling large numbers of individuals simulating an organization. This modeling, in preserving the individual, allows the observation of holistic dynamics of the system. It also provides an ability to model multi-generational effects so that extremely long-term simulations can be performed.

Modeling human behavior represents a challenge to the degree of adaptation that can be made in A-Life models. This study uses engineer turnover and thinking of quitting as a test case for developing, exploring, and expanding A-Life techniques. Data appropriate for A-Life models was collected to use for the simulation.

The utility of this research is twofold: first, it can produce a standard methodology and off-the-shelf tools to model and simulate individuals' behavior in an organizational setting and second, it offers the prospect of a tool by which future policy decisions can be formulated and simulated before implementation to lower turnover and consequently its cost.

DOI

10.25777/z33x-v862

ISBN

9780591048629

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