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Al-Sinan, M A (2004) TQM and the construction industry: Saudi Arabia: a case study, Unpublished PhD Thesis, School of Mathematics, Computer Science & Engineering, City, University of London.

Apostolopoulos, C (2015) Risk assessment for change management within project management: a hierarchical model process approach, Unpublished PhD Thesis, , City, University of London.

Arvanitis, D (2017) Collaboration and contract management in the context of offshore oil and gas contracts: an English law analysis, Unpublished PhD Thesis, The City Law School, City, University of London.

Eaglestone, F N (1993) An improved method of requesting insurance under UK construction contracts, Unpublished PhD Thesis, , City, University of London.

Kamanda-Kabague, B M (1981) Application of mathematical model techniques to the planning and control of overhead costs in the construction industry, Unpublished PhD Thesis, School of Mathematics, Computer Science & Engineering, City, University of London.

Meaker, T A (1994) The role of intervention in strategic change, Unpublished PhD Thesis, Department of Systems Science, City, University of London.

Sweis, R K (1988) Construction insurance in the Arab Gulf area: an analysis of cover and contracts, Unpublished PhD Thesis, Business School, City, University of London.

Whittaker, J D (1970) A study of competitive bidding with particular reference to the construction industry, Unpublished PhD Thesis, Business School, City, University of London.

  • Type: Thesis
  • Keywords: bidding; competition; construction companies; decision theory; estimating; feasibility study; operational research; training; uncertainty
  • ISBN/ISSN:
  • URL: https://openaccess.city.ac.uk/id/eprint/7539/
  • Abstract:
    This thesis describes an operational research study applying decision theory and quantitative methods to the problems of competitive bidding. The study was provided with data and information by four English building construction companies. First a preliminary feasibility study was conducted which indicated that the potential for substantial benefits exists. Then the decision problem was formulated in a quantitative manner, which allows treatment of the variation due to estimating uncertainty, and of the constraining effect of resources. The Friedman model and some of the published variants were presented and discussed. This led to the development of i General Distribution decision model which incorporates managerial assessment of the competition into a probabilistic framework. This Model, four Friedman variants, and a feedback model were tested with data supplied by the participating companies. The sample was too small for the results to be conclusive but they did indicate that the basic Friedman Model and the General Distribution Model can equal or outperform actual company behaviour. Partial implementation of the General Distribution Model indicated that it may be practicable.