TY - JOUR
T1 - Engineering economics for MBA students
AU - Wilck, Joseph
AU - Lynch, Paul C.
N1 - Funding Information:
Dr. Joe Wilck is a Faculty Director of Business Analytics and Clinical Associate Professor of Business Analytics at the College of William & Mary. He is a registered Professional Engineer. He is a volunteer leader with the Institute of Industrial and Systems Engineers (IISE) and the American Society for Engineering Education (ASEE). He is also an active member of INFORMS, MORS, INCOSE, ASEM, and TRB. His research is in the areas of applied optimization and STEM education, and he has been funded by the National Science Foundation, the Department of Energy, DARPA, and the North Carolina Department of Transportation; among others. He primarily teaches courses in analytics, operations research, supply chain, operations management, and logistics.
Publisher Copyright:
© American Society for Engineering Education, 2019
PY - 2019/6/15
Y1 - 2019/6/15
N2 - The purpose of this paper is to provide details on an Engineering Economy course offered to a part-time (evening) MBA program at William & Mary. The students included engineers and non-engineers. All students had taken multiple courses in accounting and finance prior to taking Engineering Economy. Thus, the focus of the course was on relevant applications of engineering economy through journal paper reviews, public media, traditional homework assignments, and the creation of a Social Security tool. The course was not focused primarily on typical time value of money concepts, since those concepts were well known from the finance courses. The course included a project, which was completed in pieces. The project was to build an individual Social Security tool in Microsoft Excel. The tool incorporated the various breakpoints for when to claim and the risk of claiming early versus late, etc. The first stage of the tool was to complete the Microsoft Excel tool for just the basic breakpoints (i.e., earliest claiming age, full retirement age, and age 70) where month-by-month was the time frame; calculating the Net Present Value (NPV) for a given time value of money rate (8%) and age of death (85th birthday). The second stage of the tool was to determine the optimal claiming age given different ages of death. The third stage was to do a sensitivity analysis on the age of death, the time value of money rate, and whether or not Social Security “runs out of money” (i.e., drops benefits to 75%). This stage used a mortality calculator to assign a probability of death in any given month, and to calculate the NPV and the standard deviation of the various claiming scenarios (i.e., to measure risk). The readers of this paper will benefit from learning about this course since it is an applied course with professional students. The students were fairly aware of the time value of money concepts, but were lacking in applications outside of their industry domain and the usage of Microsoft Excel to calculate these problems. Furthermore, using a project that impacts all (Social Security) sparked interest in the course and its material.
AB - The purpose of this paper is to provide details on an Engineering Economy course offered to a part-time (evening) MBA program at William & Mary. The students included engineers and non-engineers. All students had taken multiple courses in accounting and finance prior to taking Engineering Economy. Thus, the focus of the course was on relevant applications of engineering economy through journal paper reviews, public media, traditional homework assignments, and the creation of a Social Security tool. The course was not focused primarily on typical time value of money concepts, since those concepts were well known from the finance courses. The course included a project, which was completed in pieces. The project was to build an individual Social Security tool in Microsoft Excel. The tool incorporated the various breakpoints for when to claim and the risk of claiming early versus late, etc. The first stage of the tool was to complete the Microsoft Excel tool for just the basic breakpoints (i.e., earliest claiming age, full retirement age, and age 70) where month-by-month was the time frame; calculating the Net Present Value (NPV) for a given time value of money rate (8%) and age of death (85th birthday). The second stage of the tool was to determine the optimal claiming age given different ages of death. The third stage was to do a sensitivity analysis on the age of death, the time value of money rate, and whether or not Social Security “runs out of money” (i.e., drops benefits to 75%). This stage used a mortality calculator to assign a probability of death in any given month, and to calculate the NPV and the standard deviation of the various claiming scenarios (i.e., to measure risk). The readers of this paper will benefit from learning about this course since it is an applied course with professional students. The students were fairly aware of the time value of money concepts, but were lacking in applications outside of their industry domain and the usage of Microsoft Excel to calculate these problems. Furthermore, using a project that impacts all (Social Security) sparked interest in the course and its material.
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M3 - Conference article
AN - SCOPUS:85078716313
SN - 2153-5965
JO - ASEE Annual Conference and Exposition, Conference Proceedings
JF - ASEE Annual Conference and Exposition, Conference Proceedings
T2 - 126th ASEE Annual Conference and Exposition: Charged Up for the Next 125 Years, ASEE 2019
Y2 - 15 June 2019 through 19 June 2019
ER -