A review of analytical models, approaches and decision support tools in project monitoring and control

This paper reviews the problems, approaches and analytical models on project control systems and discusses the possible research extensions. We focused on literature in Earned Value Analysis (EVA), optimization tools, and the design of decision support systems (DSS) that will contribute to helping p...

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Bibliographic Details
Published in:International journal of project management Vol. 33; no. 4; pp. 808 - 815
Main Author: Hazır, Öncü
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01.05.2015
Elsevier Science Ltd
Subjects:
Control systems
Decision support systems
Design optimization
Earned Value Analysis
Project management
Project management software
Project monitoring and control
Studies
Systems design
Decision support systems
Project monitoring and control
Project management software
Earned Value Analysis
Project management
ISSN:0263-7863, 1873-4634
Online Access:Get full text
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Summary:This paper reviews the problems, approaches and analytical models on project control systems and discusses the possible research extensions. We focused on literature in Earned Value Analysis (EVA), optimization tools, and the design of decision support systems (DSS) that will contribute to helping project managers in planning and controlling under uncertain project environments. The review reveals that further research is essential to develop analytical models using EVA metrics to forecast project performance. It also suggests that DSS should be model driven, function as early warning systems and should be integrated to commercial project management software. •We explore problems, analytical models, and algorithms on project monitoring and control.•We summarize DSS tools and emphasize integration to project management.•This review differs from the previous ones on project management; the scope is narrower.•We discuss the possible research extensions.•Our conclusion serves as a basis to develop efficient decision support systems.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0263-7863
1873-4634
DOI:10.1016/j.ijproman.2014.09.005