A NEW MODEL PROPOSAL FOR BID FORECASTING IN CONSTRUCTION TENDERING
Abstract 
This doctoral thesis is divided into two main parts:
The focus of first chapters are to provide a brief description of the casuistry of tendering in construction from Spain, and, after, link with the still nascent science of Tender Price Forecasting.
The aim is to explain and show some mathematical and statistical tools for improving the confidence in making the right choices in order to submit bid prices with greater chance of success, starting from previous experience gathered in previous bidding processes.
It will be shown Tender Price Forecast in tendering and auctions as a science, relatively underdeveloped in some countries in which it has evolved (Australia and United States), almost totally unknown in ours (so skeptical even considered by many people yet), but that is increasing for the great value that it brings for guiding a tender price decision in its bidding phase.
Showed the relationship with tendering and starting from a previous account of the utility of certain tools that reflect the experience and the facts occurred in bidding processes, it will be make an historic journey of the main models for Tendering Price Forecast until current times.
Based on an analysis of Pim’s Equal Probability Model will be presented a series of more modern models that have been improving gradually the forecast quality in the last 50 years. The aim of this review of the state of the art, not delving into the purely mathematical basis of these models, but rather to collect their basic design to display his philosophy in the handling of data and variables by which it is feasible to anticipate, with a margin of inaccuracy, consistent outputs with the reality of a forthcoming tender.
The first part of the thesis ends with a summary of the emerging trends in the prediction models for Tender Price Forecasting and with a brief of weaknesses and gaps that still exhibits those models.
Last chapters of the doctoral thesis show the contributions of the author. They generate, justify, test and validate a new model for any kind of Tender and Auction Price Forecasting.