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Purpose

This paper aims to enhance procurement strategies within the construction industry by examining real-world contexts. It seeks to demonstrate the relationships among environmental, social and economic performance to thoroughly assess procurement alternatives and promote informed decision-making.

Design/methodology/approach

A cohesive framework is established by integrating two dual approaches: theoretical implications and practical applications, specifically using F-ANP and Benefits, Opportunities, Costs and Risk (BOCR) analysis. This method uses key performance indicators (KPIs) in conjunction with the F-ANP to align construction procurement strategies with sustainable practices. It facilitates a comprehensive evaluation of procurement alternatives through the BOCR framework.

Findings

This study ensures that informed decisions reflect economic viability as well as environmental and social responsibility. The findings reveal considerable cost savings of up to 7.35%, alongside a decrease in environmental impact ranging from 15.5% to 17.25%, which can be attributed to the adoption of sustainable practices.

Research limitations/implications

The limited sample size can impact the generalization of the findings, indicating that a larger sample may be necessary to enhance the reliability of the results.

Practical implications

The study’s Findings strengthen the theoretical model and offer insights into the practical application of the findings, influencing the selection of procurement strategies. By analyzing procurement strategies in construction using the BOCR framework, theoretical insights are derived, which include the integration of sustainability and innovation theories.

Social implications

Resistance to change among stakeholders is accustomed to traditional construction practices. Also, there is a lack of awareness about the benefits of sustainable construction methods.

Originality/value

This study highlights the trend toward making informed decisions that prioritize sustainability in construction procurement. By using machine learning tools, the study aims to expand the conceptualization of sustainability beyond the traditional practices, thereby balancing economic, social and environmental considerations. This approach provides significant insights into assessing the long-term effects of procurement strategies on construction projects.

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