contributor author | Ehsan Kian Manesh Rad | |
contributor author | Ming Sun | |
contributor author | Frédéric Bosché | |
date accessioned | 2017-12-16T09:05:02Z | |
date available | 2017-12-16T09:05:02Z | |
date issued | 2017 | |
identifier other | %28ASCE%29ME.1943-5479.0000517.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4238253 | |
description abstract | Megaprojects are characterized by their large-scale capital costs, long duration, and extraordinary levels of technical and process complexity. Empirical data demonstrate that these projects experience alarming rates of failure. One of the main causes of such project failure is the high level of complexity and the absence of effective tools for assessing and managing it. This study developed a new project complexity assessment method that is specifically aimed at megaprojects in the energy sector. The assessment method contains a taxonomy of 51 complexity indicators and their consolidated weights, which are established through a novel Delphi and analytic hierarchy process (AHP) group decision-making method. Numerical scoring criteria for all indicators were defined on the basis of a synthesis of existing knowledge of megaprojects to facilitate the application of the new method. The method was reviewed and evaluated by experts and tested through a case study of an energy megaproject. | |
publisher | American Society of Civil Engineers | |
title | Complexity for Megaprojects in the Energy Sector | |
type | Journal Paper | |
journal volume | 33 | |
journal issue | 4 | |
journal title | Journal of Management in Engineering | |
identifier doi | 10.1061/(ASCE)ME.1943-5479.0000517 | |
tree | Journal of Management in Engineering:;2017:;Volume ( 033 ):;issue: 004 | |
contenttype | Fulltext | |