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Brandon, P S and Ribeiro, F L (1998) A knowledge-based system for assessing applications for house renovation grants. Construction Management and Economics, 16(01), 57-69.
Chau, K W, Raftery, J and Walker, A (1998) Note - The baby and the bathwater: research methods in construction management. Construction Management and Economics, 16(01), 99-104.
Chinyio, E A, Olomolaiye, P O, Kometa, S T and Harris, F C (1998) A needs-based methodology for classifying construction clients and selecting contractors. Construction Management and Economics, 16(01), 91-8.
Dawood, N N (1998) Estimating project and activity duration: a risk management approach using network analysis. Construction Management and Economics, 16(01), 41-8.
- Type: Journal Article
- Keywords: Monte Carlo simulation; network analysis; stochastic analysis; PERT
- ISBN/ISSN: 0144-6193
- URL: https://doi.org/10.1080/014461998372574
- Abstract:
Variations in the duration 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 technique shave 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.
Edwards, P J and Bowen, P A (1998) Practices, barriers and benefits of risk management process in building services cost estimation: comment. Construction Management and Economics, 16(01), 105-8.
Harriss, C (1998) Why research without theory is not research: a reply to Seymour et al.. Construction Management and Economics, 16(01), 113-6.
Kumaraswamy, M M and Chan, D W M (1998) Contributors to construction delays. Construction Management and Economics, 16(01), 17-29.
McDonald, B and Smithers, M (1998) Implementing a waste management plan during the construction phase of a project: a case study. Construction Management and Economics, 16(01), 71-8.
Noyce, D A and Hanna, A S (1998) Planned and unplanned schedule compression: the impact on labour. Construction Management and Economics, 16(01), 79-90.
Ranasinghe, M (1998) Risk management in the insurance industry: insights for the engineering construction industry. Construction Management and Economics, 16(01), 31-9.
Seymour, D E, Rooke, J D and Crook, D (1998) The role of theory in construction management: reply to Runeson. Construction Management and Economics, 16(01), 109-12.
Tam, C M and Fung, I W H (1998) Effectiveness of safety management strategies on safety performance in Hong Kong. Construction Management and Economics, 16(01), 49-51.
Wang, C-H and Huang, Y-C (1998) Controlling activity interval times in LOB scheduling. Construction Management and Economics, 16(01), 5-16.