An adaptive simulation based decision support approach to respond risk propagation in new product development projects

Abstract

Developing new products by multiple stakeholders is inclined to project delays and even failures due to complex risk propagation, calling for accurate predictions of varying risk states and stakeholders' potential response actions. This study proposes an adaptive simulation-based decision support approach, starting with an adaptive simulation model capable of generating future intervention actions on risk propagation by mimicking stakeholders' risk response decisions. Accordingly, the approach tailors a genetic algorithm to solve the proposed simulation optimization problem and produce a combination of response actions that optimally block risk propagation at the current stage. To control dynamic propagations timely, this approach allows managers to adjust risk control resources in line with the latest risk states, and become accessible to managers by developing a graphical user interface. The application to a real project enables the validation of the usefulness and practicality of the approach.