TY - GEN
T1 - DECISION ENGINEERING
AU - Monroe, Thomas J.
AU - Beruvides, Mario G.
N1 - Publisher Copyright:
© American Society for Engineering Management, 2021
PY - 2021
Y1 - 2021
N2 - Time is an important parameter in decisions made under uncertainty but is often not modeled in risk analyses. This research considers time effects upon decisions in the past, present, and future by incorporating the effects of prior outcomes, decision pressure in the present, and hope that a chosen outcome will remain valid (future utility, endowment, or reliability). According to Jeremy Bentham, utility theory is made up of four factors: magnitude, proximity, certainty, and time. So far, the Entropy Decision Risk Model Utility (EDRM-U) has addressed the first three factors by deriving the relationship between objective probability (relative certainty) and subjective probability (proximity), and demonstrating the validity of expected utility as the measure of magnitude in decision-making under uncertainty (behavioral economics, positive decision theory). EDRM-U also identified the measure of risk perception in terms of risk aversion and sensitivity. This follow-on research will introduce time as a parameter to both risk aversion and risk sensitivity elements of EDRM-U and then consider methods to validate and apply the new model. The goal of this research is to further the field of decision engineering by properly modeling all four dimensions of utility to accurately predict risk choices, permitting better choice design or decision maker calibration to achieve desired outcomes. This research will ultimately impact engineering management by advancing understating of how people make decisions involving uncertainty to more closely align risk analysis and management tools with decision-maker expectations.
AB - Time is an important parameter in decisions made under uncertainty but is often not modeled in risk analyses. This research considers time effects upon decisions in the past, present, and future by incorporating the effects of prior outcomes, decision pressure in the present, and hope that a chosen outcome will remain valid (future utility, endowment, or reliability). According to Jeremy Bentham, utility theory is made up of four factors: magnitude, proximity, certainty, and time. So far, the Entropy Decision Risk Model Utility (EDRM-U) has addressed the first three factors by deriving the relationship between objective probability (relative certainty) and subjective probability (proximity), and demonstrating the validity of expected utility as the measure of magnitude in decision-making under uncertainty (behavioral economics, positive decision theory). EDRM-U also identified the measure of risk perception in terms of risk aversion and sensitivity. This follow-on research will introduce time as a parameter to both risk aversion and risk sensitivity elements of EDRM-U and then consider methods to validate and apply the new model. The goal of this research is to further the field of decision engineering by properly modeling all four dimensions of utility to accurately predict risk choices, permitting better choice design or decision maker calibration to achieve desired outcomes. This research will ultimately impact engineering management by advancing understating of how people make decisions involving uncertainty to more closely align risk analysis and management tools with decision-maker expectations.
KW - Decision engineering
KW - Endowment effect
KW - Gain affection
KW - Loss aversion
KW - Objective probability
KW - Risk aversion
KW - Risk perception
KW - Subjective probability
UR - http://www.scopus.com/inward/record.url?scp=85124401773&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85124401773
T3 - 2021 ASEM Virtual International Annual Conference "Engineering Management and The New Normal"
SP - 428
EP - 437
BT - 2021 ASEM Virtual International Annual Conference "Engineering Management and The New Normal"
PB - American Society for Engineering Management
Y2 - 27 October 2021 through 30 October 2021
ER -