Abstract

In bidding process, the important decissions are to bid or not to bid for a project and to determine how much bid price to allocate, if then decide to bid. There decisions influenced by many factors, but the decision also based on the contractor’s instinct. Bid price becomes very important because company’s profit come from here. Wrong bid price will make a a right decission to bid became useless. Then its value must be low enough to ensure a good chance of winning the tender and high enough to gain profit from it. The purpose of the study is to identify the factors that infuence bid/no bid and bid price decision among general contractors bidding on construction project and to get the optimum bid price that can be proposed in bidding. Identification of these factors will be done by distributing questionnaires to contractors who participate in the government construction project tenders. Furthermore, the data will be analyzed using relative importance index to get the rank of the factors. Then the top five of the factors will be the input in the estimated model for contractor using neurofuzzy. Neuro-fuzzy is a combination of neural network and fuzzy logic, which aims to benefit from both methods by covering each other’s deficiencies. This study has found that the most important factors on bid/no bid decisions are expected profits, project size, contractor financial ability, historical data of profit/loss on similar projects, and experience on similar projects. While the most important factors on the decision to determine the bid price are expected profits, project size, project cost, project location, and historical data of profit/loss on similar projects. The model decide to bid/no bid in tender as well as determining how much the bid price can be submitted. Model achieves 100% accuracy for bid/no bid decission and 94,48% accuracy for bid price decission. Modeling has a 3.125 rules combination with a winning probability is 75%.

Original languageEnglish
Article numberIJCIET_09_07_102
Pages (from-to)976-984
Number of pages9
JournalInternational Journal of Civil Engineering and Technology
Volume9
Issue number7
Publication statusPublished - Jul 2018

Keywords

  • Bid price
  • Bid/no bid
  • Bidding factor
  • Neuro-fuzzy
  • Strategic decision

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