TY - JOUR
T1 - Project complexity and risk management (ProCRiM)
T2 - towards modelling project complexity driven risk paths in construction projects
AU - Qazi, Abroon
AU - Quigley, John
AU - Dickson, Alex
AU - Kirytopoulos, Konstantinos
PY - 2016/7/2
Y1 - 2016/7/2
N2 - Project complexity has been extensively explored in the literature because of its contribution towards the failure of major projects in terms of cost and time overruns. Focusing on the interface of Project Complexity and Interdependency Model ling of Project Risks, we propose a new process that aids capturing interdependency between project complexity, complexity induced risks and project objectives. The proposed modelling approach is grounded in the theoretical framework of Expected Utility Theory and Bayesian Belief Networks. We consider the decision problem of identifying critical risks and selecting optimal risk mitigation strategies at the commencement stage of a project, taking into account the utility function of the decision maker with regard to the importance of project objectives and holistic interaction between project complexity and risk. The proposed process is supported by empirical research that was conducted in the construction industry in order to explore the current practices of managing project compl exity and the associated risks. The experts interviewed acknowledged the contribution of the proposed process to the understanding of complex dynamics between project complexity attributes and risks. Application of the proposed process is illustrated through a simulation study.
AB - Project complexity has been extensively explored in the literature because of its contribution towards the failure of major projects in terms of cost and time overruns. Focusing on the interface of Project Complexity and Interdependency Model ling of Project Risks, we propose a new process that aids capturing interdependency between project complexity, complexity induced risks and project objectives. The proposed modelling approach is grounded in the theoretical framework of Expected Utility Theory and Bayesian Belief Networks. We consider the decision problem of identifying critical risks and selecting optimal risk mitigation strategies at the commencement stage of a project, taking into account the utility function of the decision maker with regard to the importance of project objectives and holistic interaction between project complexity and risk. The proposed process is supported by empirical research that was conducted in the construction industry in order to explore the current practices of managing project compl exity and the associated risks. The experts interviewed acknowledged the contribution of the proposed process to the understanding of complex dynamics between project complexity attributes and risks. Application of the proposed process is illustrated through a simulation study.
KW - project complexity
KW - project risks
KW - project objectives
KW - expected utility theory
KW - Bayesian belief networks
KW - empirical research
UR - http://www.sciencedirect.com/science/journal/02637863
U2 - 10.1016/j.ijproman.2016.05.008
DO - 10.1016/j.ijproman.2016.05.008
M3 - Article
SN - 0263-7863
VL - 34
SP - 1183
EP - 1198
JO - International Journal of Project Management
JF - International Journal of Project Management
IS - 7
ER -