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An estimation model of construction project segmentation for optimum project pricing

  • Fang Jye Shiue
  • , Hsin Yun Lee
  • , Meng Cong Zheng
  • , Akhmad F.K. Khitam
  • , Sintayehu Assefa

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Purpose: For large projects, project segmentation and planning the size of contract packages in construction bids is a complex and critical issue. Due to the nature of construction projects, which frequently have large budgets, long durations and many activities with complex procedures, project segmentation involves complicated decision-making. To fill this gap, this study aims to develop an integrated model for planning project segmentation. Design/methodology/approach: The proposed model integrates a simulation and multiple attribute decision-making method. The simulation is used to evaluate the bidding outcome of various project segmentations. The owner can then determine the bid-price behavior of contractors in response to varying work package sizes. The multiple attribute decision-making method is used to select the optimal segmentation solution from the simulated scenarios. Findings: The proposed model is applied to a large road preservation project in Indonesia and incorporates bid participants and market conditions. The model provides seven scenarios for segmentation. The range of scenarios captures increasing competitiveness in the construction with the average bid price becoming gradually more beneficial for the owner. The model also utilizes a multiple attribute decision-making method to select the optimum scenario for the owner. Originality/value: This study presents an applicable model for project segmentation that is useful for both project owners and contractors. By utilizing the proposed model, a project owner can segment a large project into smaller contract packages to create improved project pricing.

Original languageEnglish
Pages (from-to)2361-2380
Number of pages20
JournalEngineering, Construction and Architectural Management
Volume28
Issue number9
DOIs
StatePublished - 2 Nov 2021

Bibliographical note

Publisher Copyright:
© 2020, Emerald Publishing Limited.

Keywords

  • Multiple attribute decision-making
  • Project management
  • Simulation

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