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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.

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.

  • Type: Journal Article
  • Keywords: contingency; engineering construction; insurance; risk management; target cost
  • ISBN/ISSN: 0144-6193
  • URL: https://doi.org/10.1080/014461998372565
  • Abstract:

    A probabilistic framework is developed to analyse a risk management approach adopted by an insurance firm. The analysis shows that when the insurance firm classifies a client as ’superior’ and ’most acceptable’, the probability of the insurer having to pay out on those claims is negligible. Even for a policy that is classified as ’acceptable’, the highest probability of a claim is only 12%. When the probability of a claim is over50%, the client is considered to be ’unacceptable’ for an insurance policy. Based on that analysis, the insights that the engineering construction industry can gain from risk management in the insurance firm with respect to project duration and cost are highlighted. It is shownthat, in responding to risks and uncertainty, the engineering construction industry should not allocate contingency at a predetermined probability of success for global variables such as project cost or duration as suggested in the literature, but at the input level. It is suggested that the predetermined probability of success value to allocate contingency at the input level should be at least 70%. Then, the contingency available for project cost and duration can ensure a high probability of success in the completion of the project.

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.