Date of Award

2014

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Industrial and Systems Engineering and Engineering Management

Committee Chair

Dawn Utley

Committee Member

Phillip A. Farrington

Committee Member

Sampson Gholston

Committee Member

Gillian M. Nicholls

Committee Member

Eric Sholes

Subject(s)

Systems engineering, Ambiguity, Logic--Systems engineering, Decision making

Abstract

Systems engineers routinely engage in exercises, such as a trade studies or Multiple Criteria Decision Analysis processes, to select the best among multiple options. Managers ideally assume that these processes are conducted in a manner that is strictly rational and repeatable. A cognitive bias leading to selection of a sub-optimal choice could then have significant consequences. Research has demonstrated a number of biases in the general population, but these have not been specifically studied in systems engineers. Two such biases are ambiguity aversion and status quo bias. A survey instrument was developed to test for ambiguity aversion and status quo bias, incorporating questions from prior research on these topics. The survey was administered to a large federal aerospace and defense agency, as well as to certain private employers in a variety of engineering fields. A total of 250 survey responses were analyzed, including 126 engineers and 124 non-engineers. A number of common statistical techniques were used to analyze the data gathered, including χ2 tests for independence, two-proportion tests, MANOVA and discriminant analysis. Analysis of the survey results revealed that engineers exhibit a very strong ambiguity aversion, and that this aversion is significantly stronger than it is in the general population. Analysis further demonstrated that some status quo bias exists in engineers, but that this bias is weaker than it is in the general population. Additionally, the weak status quo bias in engineers did still overcome the ambiguity aversion in engineers when the two were tested against each other. Secondary findings indicated that engineering managers may exhibit slightly less status quo bias than working-level engineers, and that status quo bias may decrease slightly with increased age and experience. Engineering managers must be aware that engineers do exhibit some cognitive biases, but that they may do so to a greater or lesser degree than what is seen in the general population. Results of trade studies or other selection exercises must be viewed with this reality in mind.

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