Sustainability assessment in construction projects: a sustainable earned value management model under uncertain and unreliable conditions

Environ Syst Decis. 2023 Apr 30:1-24. doi: 10.1007/s10669-023-09913-2. Online ahead of print.

Abstract

All three pillars of sustainability must be met for a construction project to be considered sustainable. Although several studies have been carried out on sustainability in the construction industry under uncertain conditions, there has been a lack of a comprehensive model to assess all three pillars of sustainability during the execution of a construction project with consideration of the uncertain and unreliable nature of the gathered data. In this article, a fuzzy inference system model was developed to fill this research gap. The Cost Performance Index from earned value management, an effective tool for cost control of projects, is used to assess the economic sustainability status during the project execution. Besides, from the expert opinions and literature review, sustainability-related attributes are gathered to identify the dimensions and enablers of a construction project. This research aimed not only to improve the previous social sustainability Indexes for construction projects by using Z-numbers but also to develop and introduce a comprehensive Z Construction Environmental Sustainability Index alongside the other two pillars. The previous hierarchal method to calculate the Fuzzy indexes is also improved to overcome possible complexity problems. Calculating the three pillars of sustainability and using them as inputs into the Mamdani FIS model to obtain the overall sustainability status, the proposed model, which is calculated with the Z-numbers, is compared with the results of conventional Fuzzy numbers and deterministic approach. The results of the comparison show that the proposed model is more rigorous and effective than the previous methods in the numerical case.

Keywords: Earned value management; Fuzzy inference system; Linguistic variables; Sustainability; Sustainability performance assessment; Z-numbers.