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Integrated construction supply chain: an optimal decision-making model with third-party logistics partnership

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  • Phuoc Luong Le
  • Imen Jarroudi
  • Thien-My Dao
  • Amin Chaabane

Abstract

Studies have confirmed the benefits of using Third-party logistics (TPL) for efficient construction management, especially in large projects. Nevertheless, there is a dearth of decision-making models evaluating the exact role of TPL providers as drivers for supply chain (SC) integration and optimisation. This study aims to develop a decision-making model for construction supply chain (CSC) optimisation, with possible TPL integration. The proposed model considers two types of purchased materials (type-1 and type-2) and assists the main contractor in determining construction supply chain management (CSCM) strategies, including supplier selection, order quantity determination, and TPL use evaluation. Using the model, the main contractor can take advantage of the TPL provider’s warehouse and order larger quantities, if necessary, to obtain lower prices offered by suppliers. Through case examples in Canada, we find that the proposed model performs better in optimising total SC cost, as compared to the model without TPL. Model validations also show that TPL can be conditionally used to improve construction logistics performance and to meet practical requirements targeting issues in the construction industry.

Suggested Citation

  • Phuoc Luong Le & Imen Jarroudi & Thien-My Dao & Amin Chaabane, 2021. "Integrated construction supply chain: an optimal decision-making model with third-party logistics partnership," Construction Management and Economics, Taylor & Francis Journals, vol. 39(2), pages 133-155, February.
  • Handle: RePEc:taf:conmgt:v:39:y:2021:i:2:p:133-155
    DOI: 10.1080/01446193.2020.1831037
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    Cited by:

    1. Victoria Muerza & Cindy Guerlain, 2021. "Sustainable Construction Logistics in Urban Areas: A Framework for Assessing the Suitability of the Implementation of Construction Consolidation Centres," Sustainability, MDPI, vol. 13(13), pages 1-19, June.

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