A Study of the Cash Flow Forecasting Impact on the Owners Financial Management of Construction Projects in the State of Kuwait

Kotb, Moustafa; Ibrahim, M; Al-Olayan, Yousef Saleh

doi:10.20849/abr.v3i1.351

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…The primary reason for construction company failures is often the absence of sufficient funds to support daily operations [21,22]. Therefore, having a solid understanding of the actual cash flow requirements throughout the construction phases is essential [23]. Similarly, Duran (2006) noted that numerous projects are not completed on time, giving the construction sector a bad image for completing projects on time, and project managers are often held accountable for this [24].…”

Section: Literature Reviewmentioning

confidence: 99%

Building a Genetic Algorithm-Based and BIM-Based 5D Time and Cost Optimization Model

Alzara,

Attia,

Mahfouz

et al. 2023

IEEE Access

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The digitalization of data has recently had an impact on the building industry. Building information modeling (BIM) is a highly developed technology that is used to predict the cost, lifespan, energy use, and efficiency of buildings. To enhance the BIM accuracy of cost and time estimation currently, it's easier than before by Using evolutionary algorithms (EA), which include contemporary algorithms like evolutionary strategies (ES), evolutionary programming (EP), particle swarm optimization (PSO), differential evolution (DE), and genetic algorithms (GA), the integration of artificial intelligence (AI). This study uses a code (plugin) created by GA and integrated into the BIM-5D model via Navisworks as a plugin to reduce the overall time and cost of construction projects. The plugin code, developed with Microsoft Visual Studio and the C# programming language, is an interface that enhances the accuracy of time and cost during construction stages with various five project time scenarios. The study's findings indicate that the suggested plugin reduces project time by roughly 20% while also saving various amounts of money. INDEX TERMSArtificial Intelligence (AI), Building Information Modeling (BIM), Cash flow, Critical Path Method (CPM), Time and Cost optimization

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Section: Literature Reviewmentioning

confidence: 99%

Building a Genetic Algorithm-Based and BIM-Based 5D Time and Cost Optimization Model

Alzara,

Attia,

Mahfouz

et al. 2023

IEEE Access

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A data-driven approach for predicting cash flow performance of public owners in building projects: insights from Turkish cases

Kazar

2024

ECAM

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PurposeThe cash flow from government agencies to contractors, called progress payment, is a critical step in public projects. The delays in progress payments significantly affect the project performance of contractors and lead to conflicts between two parties in the Turkish construction industry. Although some previous studies focused on the issues in internal cash flows (e.g. inflows and outflows) of construction companies, the context of cash flows from public agencies to contractors in public projects is still unclear. Therefore, the primary objective of this study is to develop and test diverse machine learning-based predictive models on the progress payment performance of Turkish public agencies and improve the predictive performance of these models with two different optimization algorithms (e.g. first-order and second-order). In addition, this study explored the attributes that make the most significant contribution to predicting the payment performance of Turkish public agencies.Design/methodology/approachIn total, project information of 2,319 building projects tendered by the Turkish public agencies was collected. Six different machine learning algorithms were developed and two different optimization methods were applied to achieve the best machine learning (ML) model for Turkish public agencies' cash flow performance in this study. The current research tested the effectiveness of each optimization algorithm for each ML model developed. In addition, the effect size achieved in the ML models was evaluated and ranked for each attribute, so that it is possible to observe which attributes make significant contributions to predicting the cash flow performance of Turkish public agencies.FindingsThe results show that the attributes “inflation rate” (F5; 11.2%), “consumer price index” (F6; 10.55%) and “total project duration” (T1; 10.9%) are the most significant factors affecting the progress payment performance of government agencies. While decision tree (DT) shows the best performance among ML models before optimization process, the prediction performance of models support vector machine (SVM) and genetic algorithm (GA) has been significantly improved by Broyden–Fletcher–Goldfarb–Shanno (BFGS)-based Quasi-Newton optimization algorithm by 14.3% and 18.65%, respectively, based on accuracy, AUROC (Area Under the Receiver Operating Characteristics) and F1 values.Practical implicationsThe most effective ML model can be used and integrated into proactive systems in real Turkish public construction projects, which provides management of cash flow issues from public agencies to contractors and reduces conflicts between two parties.Originality/valueThe development and comparison of various predictive ML models on the progress payment performance of Turkish public owners in construction projects will be the first empirical attempt in the body of knowledge. This study has been carried out by using a high number of project information with diverse 27 attributes, which distinguishes this study in the body of knowledge. For the optimization process, a new hyper parameter tuning strategy, the Bayesian technique, was adopted for two different optimization methods. Thus, it is available to find the best predictive model to be integrated into real proactive systems in forecasting the cash flow performance of Turkish public agencies in public works projects. This study will also make novel contributions to the body of knowledge in understanding the key parameters that have a negative impact on the payment progress of public agencies.

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A Study of the Cash Flow Forecasting Impact on the Owners Financial Management of Construction Projects in the State of Kuwait

Cited by 2 publications

References 3 publications

Building a Genetic Algorithm-Based and BIM-Based 5D Time and Cost Optimization Model

Building a Genetic Algorithm-Based and BIM-Based 5D Time and Cost Optimization Model

A data-driven approach for predicting cash flow performance of public owners in building projects: insights from Turkish cases

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