Early Prediction of Project Duration: A Longitudinal Study. Issue 3 (3rd July 2018)

• Record Type: Journal Article
• Authors: Chen, Hong Long
• Is Part Of: Engineering management journal. Volume 30:Issue 3(2018)
• Page Start: 191
• Page End: 202
• Publication Date: 2018-07-03
• Subjects: Project Management -- Project Duration Prediction -- Project Time Performance -- Schedule -- Performance Measurement; Program and Project Management; Engineering -- Management -- Periodicals; Engineering -- Management; Periodicals; 620.0068
• DOI: 10.1080/10429247.2018.1483169
• Languages: English
• ISSNs: 1042-9247

Abstract

Abstract: Using earned value management (EVM) protocols, numerous innovative models for the critical task of predicting project duration have been proposed in recent years. Due to the nature of EVM, these models, however, appear to be useful only after the project's construction phase begins. The objective of this study is to examine the longitudinal relationships between completed project time and project variables' performance prior to the construction phase and to model those useful relationships to predict completed project duration. The research results confirm the significance of scope, team, communication, risk, and innovation performance prior to the construction phase and reveal reasonable estimation accuracy and a relatively small difference in prediction rates between in-sample (88.13%) and out-of-sample (85.49%) data.