Authors: Rueben Laryea
Addresses: Department of Computer and Systems Sciences, Stockholm University, Forum 100, 16440, Kista, Stockholm, Sweden
Abstract: Project distress predictions are essential in project management. Developing appropriate methods to classify projects and building prediction models for multi-criteria decisions requires empirical methods to minimise misclassification errors. This paper carries out multi-criteria analysis to classify projects risks using a preference disaggregation method, utilités additives discriminantes - UTADIS. The UTADIS requires predefined classification which is implemented using critical path analysis. The methods are applied on three projects and result in no misclassification error and an effective prediction model.
Keywords: project risks; uncertainty; multicriteria decision making; MCDM; classifications; utilités additives discriminantes; UTADIS; critical path analysis; CPA; risk classification; project management; prediction models; modelling.
International Journal of Decision Sciences, Risk and Management, 2013 Vol.5 No.1, pp.55 - 79
Received: 05 Jul 2013
Accepted: 01 Aug 2013
Published online: 07 Nov 2013 *