Estimating project and activity duration: a risk management approach using network analysis

Hdl Handle:
http://hdl.handle.net/10149/98189
Title:
Estimating project and activity duration: a risk management approach using network analysis
Authors:
Dawood, N. N. (Nashwan)
Affiliation:
The University of Teesside. School of Science and Technology. Division of Civil Engineering and Building.
Citation:
Dawood, N. N. (1998) 'Estimating project and activity duration: a risk management approach using network analysis', Construction Management & Economics, 16 (1), pp.41-48.
Publisher:
Taylor & Francis
Journal:
Construction Management & Economics
Issue Date:
Jan-1998
URI:
http://hdl.handle.net/10149/98189
DOI:
10.1080/014461998372574
Abstract:
Variations in the durations of activities are commonplace in the construction industry. This is due to the fact that the construction industry is influenced greatly by variations in weather, productivity of labour and plant, and quality of materials. Stochastic network analysis has been used by previous researchers to model variations in activities and produce more effective and reliable project duration estimates. A number of techniques have been developed in previous literature to solve the uncertain nature of networks, these are: PERT (program evaluation and review techniques), PNET (probabilistic network evaluation technique), NRB, (narrow reliability bounds methods) and MCS (Monte Carlo simulation). Although these techniques have proved to be useful in modelling variations in activities, dependence of activity duration is not considered. This can have a severe impact on realistically modelling projects. In this context, the objective of the present research is to develop a methodology that can accurately model activity dependence and realistically predict project duration using a risk management approach. A simulation model has been developed to encapsulate the methodology and run experimental work. In order to achieve this, the following tasks are tackled: identify risk factors that cause activity variations using literature reviews and conducting interviews with contractors; model risk factors and their influence on activity variations through conducting case studies and identifying any dependence between them; develop a computer based simulation model that uses a modified Monte Carlo technique to model activity duration and dependence of risk factors; and run experimental work to validate and verify the model.
Type:
Article
Language:
en
Keywords:
network analysis; Monte Carlo simulation; pert; stochastic analysis
ISSN:
0144-6193; 1466-433X
Rights:
Subject to restrictions, author can archive post-print (ie final draft post-refereeing). For full details see http://www.sherpa.ac.uk/romeo/ [Accessed 07/05/2010]
Citation Count:
11 [Scopus, 07/05/2010]

Full metadata record

DC FieldValue Language
dc.contributor.authorDawood, N. N. (Nashwan)en
dc.date.accessioned2010-05-07T13:36:15Z-
dc.date.available2010-05-07T13:36:15Z-
dc.date.issued1998-01-
dc.identifier.citationConstruction Management & Economics; 16(1):41-48en
dc.identifier.issn0144-6193-
dc.identifier.issn1466-433X-
dc.identifier.doi10.1080/014461998372574-
dc.identifier.urihttp://hdl.handle.net/10149/98189-
dc.description.abstractVariations in the durations of activities are commonplace in the construction industry. This is due to the fact that the construction industry is influenced greatly by variations in weather, productivity of labour and plant, and quality of materials. Stochastic network analysis has been used by previous researchers to model variations in activities and produce more effective and reliable project duration estimates. A number of techniques have been developed in previous literature to solve the uncertain nature of networks, these are: PERT (program evaluation and review techniques), PNET (probabilistic network evaluation technique), NRB, (narrow reliability bounds methods) and MCS (Monte Carlo simulation). Although these techniques have proved to be useful in modelling variations in activities, dependence of activity duration is not considered. This can have a severe impact on realistically modelling projects. In this context, the objective of the present research is to develop a methodology that can accurately model activity dependence and realistically predict project duration using a risk management approach. A simulation model has been developed to encapsulate the methodology and run experimental work. In order to achieve this, the following tasks are tackled: identify risk factors that cause activity variations using literature reviews and conducting interviews with contractors; model risk factors and their influence on activity variations through conducting case studies and identifying any dependence between them; develop a computer based simulation model that uses a modified Monte Carlo technique to model activity duration and dependence of risk factors; and run experimental work to validate and verify the model.en
dc.language.isoenen
dc.publisherTaylor & Francisen
dc.rightsSubject to restrictions, author can archive post-print (ie final draft post-refereeing). For full details see http://www.sherpa.ac.uk/romeo/ [Accessed 07/05/2010]en
dc.subjectnetwork analysisen
dc.subjectMonte Carlo simulationen
dc.subjectperten
dc.subjectstochastic analysisen
dc.titleEstimating project and activity duration: a risk management approach using network analysisen
dc.typeArticleen
dc.contributor.departmentThe University of Teesside. School of Science and Technology. Division of Civil Engineering and Building.en
dc.identifier.journalConstruction Management & Economicsen
ref.citationcount11 [Scopus, 07/05/2010]en
or.citation.harvardDawood, N. N. (1998) 'Estimating project and activity duration: a risk management approach using network analysis', Construction Management & Economics, 16 (1), pp.41-48.-
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