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Brandao, L E T and Saraiva, E (2008) The option value of government guarantees in infrastructure projects. Construction Management and Economics, 26(11), 80.

Ding, Z and Ng, F (2008) A new way of developing semantic differential scales with personal construct theory. Construction Management and Economics, 26(11), 26.

Doloi, H (2008) Analysing the novated design and construct contract from the client's, design team's and contractor's perspectives. Construction Management and Economics, 26(11), 96.

Forbes, D, Smith, S and Horner, M (2008) Tools for selecting appropriate risk management techniques in the built environment. Construction Management and Economics, 26(11), 50.

Kheni, N A, Dainty, A R J and Gibb, A (2008) Health and safety management in developing countries: a study of construction SMEs in Ghana. Construction Management and Economics, 26(11), 69.

Kofoworola, O F and Gheewala, S (2008) An input-output analysis of Thailand's construction sector. Construction Management and Economics, 26(11), 40.

Nasirzadeh, F, Afshar, A, Khanzadi, M and Howick, S (2008) Integrating system dynamics and fuzzy logic modelling for construction risk management. Construction Management and Economics, 26(11), 212.

  • Type: Journal Article
  • Keywords: fuzzy logic; risk management; system dynamics
  • ISBN/ISSN: 0144-6193
  • URL: https://doi.org/10.1080/01446190802459924
  • Abstract:
    The complex structure of construction project risks arises from their internal and external interactions with their dynamic nature throughout the life cycle of the project. A system dynamics (SD) approach to construction project risk management is presented, including risk analysis and response process. Owing to the imprecise and uncertain nature of risks, fuzzy logic is integrated into system dynamics modelling structure. Risk magnitudes are defined by a fuzzy logic based risk magnitude prediction system. Zadeh's extension principle and interval arithmetic is employed in the SD simulation model to present the system outcomes considering uncertainties in the magnitude of risks resulting from the risk magnitude prediction system. The performance of the proposed method is assessed by employing the method in the risk management plan of a sample project. The impact of a sample risk is quantified and efficiency of different alternative response scenarios is assessed. The proposed approach supports different stages of the risk management process considering both the systemic and uncertain nature of risks.

Raiden, A B, Dainty, A R J and Neale, R H (2008) Understanding employee resourcing in construction organizations. Construction Management and Economics, 26(11), 43.

Raisbeck, P (2008) Perceptions of architectural design and project risk: understanding the architects' role in a PPP project. Construction Management and Economics, 26(11), 57.