Thesis-1976-McCaffer.pdf (32.37 MB)
Contractors' bidding behaviour and tender price prediction
thesis
posted on 2011-02-10, 10:52 authored by Ronald McCafferData relating to the bids for 384 roads contracts and 190
buildings contracts and a library of individual unit prices were
obtained. The normality or near normality of the distribution of bids
for buildings and roads contracts is established. This allows the
relationship between mean and lowest bids to be defined using normal
order statistics. It also permits the application of outlier tests
to be used in identifying unrealistically low bids.
The average mean standardised bids of contractors have a strong
negative correlation with the contractor's success ratio. This allows
contractors to predict success ratios of others using their mean-standardised bids. The data required for this is not limited to the
competitions in which the contractor himself enters. Contractors have different behaviour patterns, some with disproportionate
numbers of high or low bids and others behave randomly.
These behaviour features correlate well with the average mean-standardised bids. Graphs of the cumulative sum of (bid-mean bid)/mean bid are
useful in identifying contractors who are seeking work and those who
are not. These can be used to identify serious rivals for particular
contracts.
Contractors have different sensitivity of success ratio to changes
in bid value thus indicating different market judgements.
Contractors also have different trends within their standardised
bids to contract value. This only affects success ratios in extreme
cases.
Designers have accuracies of standard deviations of 16.63% and
20.14% for predicting the lowest bid of buildings and roads contracts
respectively. Price models based on multiple regression analysis produce
similar accuracies for comparable construction works. The tender price prediction system developed, based on a library
of, untt prices and inflation indices achieved a standard deviation of
8,30% in predicting the mean bid and 11.08% in predicting the lowest
bid for roads contracts. This could be improved with more data in
the price library but nevertheless is a substantial improvement on the
results achieved by designer's estimating.
History
School
- Architecture, Building and Civil Engineering
Publisher
© Ronald McCafferPublication date
1976Notes
A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.EThOS Persistent ID
uk.bl.ethos.482228Language
- en