Some strategic business problems cannot be expressed in analytical forms and, in most cases, are difficult to define in a deterministic manner. This chapter explores the use of probabilistic modelling using Monte Carlo methods in modelling of decision problems. The focus is on using the Monte Carlo simulation to provide a quantitative assessment of uncertainties and key risk drivers in business decisions. Using an example based on hypothetical data, we illustrate decision problems where uncertainties make simulation modelling useful to obtain decision insights and explore alternative choices. We will explore how to propagate uncertainty in the input decision variables to get a probability distribution of the output(s) of interest..
|Title of host publication||Decision Science-Recent Advances and Applications|
|Editors||Tien M. Nguyen|
|Publication status||Accepted/In press - 30 Jun 2022|
- Monte Carlo methods
- probability distribution
- decision variables
- stochastic models