Developing a Parametric Cash Flow Forecasting Model for Complex Infrastructure Projects: A Comparative Study

Mahir Msawil , Faris Elghaish, Krisanthi Seneviratne , Stephen McIlwaine

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
179 Downloads (Pure)


Forecasting the cash flow for infrastructure projects has not received much attention in the existing models. Moreover, disregarding the cost flow behaviour and proposing models that entail a relatively high dimensionality of inputs have been the main drawbacks of the existing models. This study proposes a heuristic cash flow forecasting (CFF) model for infrastructure projects, and it explores the underlying behaviour of the cost flow. The proposed model was validated by adopting a case study approach,the actual cost flow datasets were mined from a verified data system. The results invalidated the employment of a dominant heuristic rule with regard to a cost-flow-time relationship in infrastructure projects. On the other hand, a mathematical parameter-based comparison between the trends analysed from previous studies revealed that the cost flows of infrastructure projects procured through a design-bid-build (D-B-B) route behaved in a similar manner to building projects procured through a construction management route. This research contributes to the body of knowledge providing a method to enable infrastructure contractors to accurately forecast the required working capital through adding a new dimension for project classification by coining the term “the quaternary flow percentage”. In addition, this study indicates the importance of identifying the impact of root risks on the individual cost flow components rather than on the aggregated cost flow, which is a recommendation for future research.
Original languageEnglish
Article number11305
Issue number20
Publication statusPublished - 13 Oct 2021


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