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Probability of Winning the Tender When Proposing Using BIM Strategy: A Case Study in Saudi Arabia

Author(s):
ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 7, v. 11
Page(s): 306
DOI: 10.3390/buildings11070306
Abstract:

The procurement process is one of the most important phases in any project life cycle, particularly when it comes to selecting the right contractor for the job. Awarding the contract to the best bid proposal is a critical step to ensure the greatest value. BIM has been recognized as not only a geometric modelling of buildings, but also, it facilitates the different stages in management of construction projects. The purpose of this paper is to study the impact of using Building Information Modeling (BIM) in the tendering process from the contractor’s perspective, based on a probability model able to predict winning probability, regardless of relative weight. The main objective of this research is to measure the likelihood of winning a tender in the case of implementing BIM strategy, compared with contractors who do not use BIM. The research uses a literature review, surveys, and interviews with experts to develop a model that predicts the probability of winning a contract; this is determined by measuring the BIM impact on each selection criterion in a multicriteria selection process using the Analytical Hierarchy Process (AHP) to develop a probability-based model. The results of the survey and the interview show that BIM strategy has a variant influence on the score the contractor could have on each of them raising the probability of winning the tender. The main result of this paper is the property-based model, which is able to predict BIM winning probability regardless of relative weight, which can be applied in any country. Nonetheless, the Saudi case study shows that utilizing BIM when proposing could increase the winning probability by up to 9.42% in the case of Quality-Based Selection (QBS), and to 5.5% in the case of Cost-Based Selection (CBS).

Copyright: © 2021 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10625774
  • Published on:
    26/08/2021
  • Last updated on:
    14/09/2021
 
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