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The construction industry is characterized by complex environments, adversity, fierce competition, and heavy tasks, and faces many challenges during project execution, including cost acceleration, delays, and quality issues. Tendering is a competitive procurement process used to select the main contractor or supplier. The process is often associated with high risk, and its success is strongly influenced by how it is managed. These factors make selecting a qualified and suitable contractor for a construction project a challenging and complex task. The results of a selection can have an impact on a project's performance and success; selecting unsuitable contractors can cause delays, cost overruns, low-quality work, disputes, and additional costs for the owner. Research shows that public agencies, in particular, face the challenge of selecting the most appropriate tender. Generally, public construction projects are awarded at the lowest price for financial accountability, but it is not the best option because it may damage the balance between time, cost, and quality. However, as contracting authorities recognize the benefits of evaluating tenders based on non-price criteria, they are increasingly using them instead of just price. Therefore, this study proposes an innovative formulaic scoring model by evaluating the price offer as well as eleven non-price factors that have been examined in previous studies to select the most suitable contractor for the project. This method uses partial value functions differently, and tenderers' past performance scores are modified using the time decay correction function. The most unique aspect of this study is the requirement for tenderers to determine their own suitability and risks. To validate the proposed model, a hypothetical scenario based on a real case has been used. It is evident from the results that the optimal choice depends on the weights of criteria, contractors' self-determined offers, and past performance. Tenderers, as well as contracting authorities, can benefit greatly from the application of the proposed model.
Burak Öz (Thu,) studied this question.