Locatelli, G orcid.org/0000-0001-9986-2249, Mikic, M, Kovacevic, M et al. (2 more authors) (2017) The successful delivery of megaprojects: a novel research method. Project Management Journal, 48 (5). pp. 78-94. ISSN 8756-9728
Abstract
Megaprojects are often associated with poor delivery performance and poor benefits realization. This article provides a method of identifying, in a quantitative and rigorous manner, the characteristics related to project management success in megaprojects. It provides an investigation of how stakeholders can use this knowledge to ensure more effective design and delivery for megaprojects. The research is grounded in 44 megaprojects and a systematic, empirically based methodology that employs the Fisher's exact test and machine learning techniques to identify the correlation between megaprojects’ characteristics and performance, paving the way to an understanding of their causation.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2017 by the Project Management Institute. This is an author produced version of a paper published in Project Management Journal. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | megaprojects; case studies; statistical analysis; budget; schedule |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > EPS Faculty Services (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) |
Funding Information: | Funder Grant number EU - European Union CGA-TU1003-2 EU - European Union CGA-TU1003-4 |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Jun 2017 09:53 |
Last Modified: | 30 Jun 2020 14:55 |
Published Version: | https://www.pmi.org/learning/library/successful-me... |
Status: | Published |
Publisher: | Sage / Project Management Institute |
Identification Number: | 10.1177/875697281704800506 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:117838 |