Success of Complex Megaprojects in Construction Industry Considering Formal I Semi-Formal/ Informal Framework

Abstract

Megaprojects are labeled as "hard to tame wild beasts'', with usually a negative hypothesis assigned, considering their complexity level and ratio of success. Though little empirical evidence supports this contention, yet practitioners do recognize this as an accepted fact. The tenn complexity, being fundamental characteristics of megaprojects, is still vague, and it is also hard to quantify in a precise manner. Therefore, this study aims at analyzing megaproject success based on their complexity, in tenns of management of megaprojects, rather than based on conventional fundamental characteristics of project performance. The relationship between various types of project complexity factors has already been studied. However, not all of the factors leading to overall complexity, affect project success significantly or equally. Therefore, there is a need to recognize which components, amongst these types have a substantial impact on performance during megaproject management, and predominantly contribute to its overall success in a significant manner. An in-depth analysis is however lacking on the extent of va1iations required in the standard project management processes and techniques about megaprojects, resulting in usually compromised execution. Based on the literature review, an endeavor has been made to analyze megaproject complexity and its management, in the context of the Pakistan construction industry. Subsequently, relevant data has been collected from the construction industry all across Pakistan. Factor analyses and correlation, along with the technique of Structural Equation Modelling (SEM), have been applied for testing of the proposed hypothesis. This has enabled to explore the effects of various factors of project complexities on its success, within the boundaries of 'FSI Framework' for project management processes. The study specifically aims to improve the existing hypothesized relationship between the success and complexity of construction megaprojects based on the selected variables.