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Alani, A M, Petersen, A K, Chapman, K G and Khosrowshahi, F (2004) A proposed quantitative model for building repair and maintenance -theory, model development and application. Journal of Construction Research, 5(02), 193–210.

Blyth, K, Lewis, J and Kaka, A (2004) Predicting project and activity duration for buildings in the UK. Journal of Construction Research, 5(02), 329–47.

Collins, A and Baccarini, D (2004) Project success -a survey. Journal of Construction Research, 5(02), 211–31.

Han, S H and Diekmann, J (2004) Judgment-based cross-impact method for predicting cost variance for highly uncertain projects. Journal of Construction Research, 5(02), 171–92.

Haupt, T C and Smallwood, J (2004) HIV and AIDS in SA construction: attitudes and perceptions of workers. Journal of Construction Research, 5(02), 311–27.

Moore, J E, Kuprenas, J, Lee, J-J, Gordon, P, Richardson, H and Pan, Q (2004) Cost analysis methodology for advanced treatment of stormwater: the Los Angeles case. Journal of Construction Research, 5(02), 149–70.

Ofori, G, Dulaimi, M F and Ling, F Y Y (2004) Improving performance of construction industry in Singapore: motivators, enablers and lessons for developing countries. Journal of Construction Research, 5(02), 267–89.

Sebastian, R (2004) Critical appraisal of design management in architecture. Journal of Construction Research, 5(02), 255–66.

Soetanto, R and Proverbs, D G (2004) Intelligent models for predicting levels of client satisfaction. Journal of Construction Research, 5(02), 233–53.

  • Type: Journal Article
  • Keywords: artificial neural network; client satisfaction; contractor performance; performance assessment; project coalition
  • ISBN/ISSN: 1609 9451
  • URL: http://www.worldscinet.com/jcr/05/0502/S1609945104000164.html
  • Abstract:
    This paper presents the development of artificial neural network models for predicting client satisfaction levels arising from the performance of contractors, based on data from a UK-wide questionnaire survey of clients. Important independent variables identified by the models indicate that long-term relationships may encourage higher satisfaction levels. Moreover, the performance of contractors was found to only partly contribute to determining levels of client satisfaction. Attributes of the assessor (i.e. client) were also found to be of importance, confirming that subjectivity is to some extent prevalent in performance assessment. The models demonstrate accurate and consistent predictive performance for "unseen" independent data. It is recommended that the models be used as a platform to develop an expert system aimed at advising project coalition (PC) participants on how to improve performance and enhance satisfaction levels. The use of this tool will ultimately help to create a performance-enhancing environment, leading to harmonious working relationships between PC participants.

Wood, B and Kenley, R (2004) The effectiveness of the bills of quantities in Australia. Journal of Construction Research, 5(02), 291–309.