A better project performance prediction model using fuzzy time series and data envelopment analysis

Mostafa Salari () and Homayoun Khamooshi
Additional contact information
Mostafa Salari: University of Calgary
Homayoun Khamooshi: George Washington University

Journal of the Operational Research Society, 2016, vol. 67, issue 10, 1274-1287

Abstract: Abstract Earned value management (EVM) is a critical project management methodology that evaluates and predicts project performance from cost and schedule perspectives. The novel theoretical framework presented in this paper estimates future performance of a project based on the past performance data. The model benefits from a fuzzy time series forecasting model in the estimation process. Furthermore, fuzzy-based estimation is developed using linguistic terms to interpret different possible conditions of projects. Eventually, data envelopment analysis is applied to determine the superior model for forecasting of project performance. Multiple illustrative cases and simulated data have been used for comparative analysis and to illustrate the applicability of theoretical model to real situations. Contrary to EVM-based approach, which assumes the future performance is the same as the past, the proposed model can greatly assist project managers in more realistically assessing prospective performance of projects and thereby taking necessary and on-time appropriate actions.

Keywords: earned value management; cost and schedule performance index; fuzzy time series; forecasting; performance management; data envelopment analysis (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1057/jors.2016.20 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:jorsoc:v:67:y:2016:i:10:d:10.1057_jors.2016.20

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/41274

DOI: 10.1057/jors.2016.20

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald and Jonathan Crook

More articles in Journal of the Operational Research Society from Palgrave Macmillan, The OR Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().