World energy needs are predicted to be 50% higher in 2030 than in 2007. As a result, an increasing number of energy megaprojects are being considered by governments and enterprises. Megaprojects are defined by their size, complexity, long duration and high demands on resources and technology. The practice and outcomes of megaprojects have shown an alarming rate of failure, with complexity aspects having been recognised as one of the main causes of these failures. Existing research scarcely exhibits robust methods for complexity evaluation which can be used effectively in practice. This research aims to tackle this problem by developing a Project Complexity Assessment (PCA) tool robustly built using a mathematical Group Decision Making (GDM) method integrating consistency-checking and consensus-building processes. Firstly a taxonomy of Project Complexity Indicators (PCIs) is introduced to establish the underpinning structure of the method. Then, an approach integrating the Delphi and Analytic Hierarchy Process (AHP) was opted for to elicit the consolidated weights of the PCIs. In the process of GDM, it is required that experts reach a high level of consensus between them. Also in any decision making method, only consistent and rational information which does not entail any type of contradiction should be applied in the process. Therefore a method is proposed to integrate a new automatic consistency checking process with a consensus building system. This advises experts how to change their judgements towards an aggregated consensus. Finally, robust numerical rating criteria were developed for all PCIs, critically enabling the use of the produced PCA tool in practice. Such an application is demonstrated in an energy megaproject case study, highlighting the potential benefits of the produced PCA tool in practice.
|Publication status||Published - 2015|
|Event||29th IPMA World Congress - Panama, Panama|
Duration: 28 Sep 2015 → 30 Sep 2015
|Conference||29th IPMA World Congress|
|Period||28/09/15 → 30/09/15|