Decision Modelling

: Study of Interactions in the Risk Assessment of Complex Engineering Systems: An Application to Space PSA
Subject Areas: Mathematics, Decision Making
Year of Publication: 2011
Journal:Operations Research
Authors: Borgonovo E, Smith C.L.
Abstract: Risk managers are often confronted with the evaluation of operational policies in which two or more system components are simultaneously affected by a change. In these instances, the decision-making process should be informed by the relevance of interactions. In light of the central role played by the multilinearity of the decision support models, the study investigates the presence of interactions in multi-linear function and support managers in taking decisions.


Decision modelling tools are powerful business tools for making predictions and  for  comparing  those predictions with reality. By making the business logic explicit and by using the validation options that a decision modeling technique offers, the quality of the decision making process can be greatly improved.


We are skilled in a wide range of decision modelling methods and techniques including: Simulation modelling - agent based, discrete event, system dynamics. Optimization - linear and non-linear, genetic and meta-heuristics programming
Decision tree analysis
Statistical analysis - predictive data analysis, statistical modelling, machine learning.
Financial modelling - real options.
Executive dashboards
Data analysis is supported by our decision science lab and our learning lab

Biography of Claudio Dematté >


SDA Bocconi School of Management
Research Unit of Claudio Dematté Corporate and Financial Institutions Division
Via Bocconi, 8
20136 Milano

Action Research

Annarita Di Bitonto
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Jelena Urosevic
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Erica Cottarelli
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Roberta Aresu
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