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Contract awarding is the pivotal stage of the project life
cycle either for contractors or for owners. In the past three
decades, the academic community has developed several
competitive bidding models to which statistical techniques were
applied. Nowadays thanks to the development of the Artificial
Intelligence(AI) theories, the Fuzzy Sets and Neural Network
are also applied in the regard.
It is widely acknowledged that the construction industry
market in Taiwan is not of perfect competition. Unquantified
variables which powerfully influence the price decision of
contractors are usually involved. However, they were just
roughly quantified or ignored by the concerning academic
community in the past.
Based on the Game Theory, this study proposed three
appropriate game forms to construction competitive bidding with
three decision models, statistics , neural network, and fuzzy
sets, and it respectively verified the above-mentioned models
with empirical bidding data to find out the most suitable one.
To achieve the goal, this study conducted literature review at
first, and then interviewed people relating to bidding decision.
After that, it analyzed structures and types of information of
competitive bidding. Then it applied statistics, neural
networks, and fuzzy sets theory to develop the competitive
bidding models and finally came to the conclusion.
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