scholarly journals CASH FLOW FORECASTING WITH RISK CONSIDERATION USING BAYESIAN BELIEF NETWORKS (BBNS)

2017 ◽  
Vol 23 (8) ◽  
pp. 1045-1059 ◽  
Author(s):  
Mostafa KHANZADI ◽  
Ehsan ESHTEHARDIAN ◽  
Mahdiyar MOKHLESPOUR ESFAHANI
Keyword(s):  
Risk Factors ◽  
Cash Flow ◽  
Construction Projects ◽  
Bayesian Belief Networks ◽  
Influence Diagrams ◽  
Belief Networks ◽  
Cash Flow Management ◽  
Construction Companies ◽  
Cash Flow Forecasting

Cash-flow management is very important for contractors given that inadequate cash resources typically are the main causes for bankruptcy of construction companies. In comparison to most other industries, the construction industry is severely plagued by risk, and the success of construction projects usually depends on valuating all risks. However, conventional methods suggested by extant research on cash flow forecasting do not consider comprehensive identifica­tion of risk factors, interactions between the factors, and simultaneous occurrences of the factors. This study introduced a simple and appropriate probabilistic cash flow forecasting model using Bayesian Belief Networks (BBNs) to avoid bankruptcy of contractors by considering influence diagrams and risk factors that affect a project. Workability and reli­ability of the proposed approach was tested on an important building construction project in Iran as a real case study, and the results indicated that the model performed well.

Cash Flow Management of Construction Projects in Saudi Arabia

2018 ◽  
Vol 49 (5) ◽  
pp. 48-63 ◽  
Author(s):  
Ali A. Shash ◽  
Abdulaziz Al Qarra
Keyword(s):  
Saudi Arabia ◽  
Cash Flow ◽  
Construction Projects ◽  
Flow Management ◽  
Cash Flow Management ◽  
Construction Companies ◽  
Cash Flow Forecasting ◽  
Credit Financing ◽  
Cash Inflow ◽  
Project Level

Cash flow management entails forecasting, monitoring, and controlling practices of the cash inflow and outflow and arrangement of deficits over a project’s duration. This article reveals, through a questionnaire survey, the techniques and practices that construction companies in the Eastern Province of Saudi Arabia follow to forecast and manage cash flow at the project level. The majority of the contractors perform cash flow forecasting for setting a cash flow baseline and determining the proper financing method. They use credit financing for materials, subcontract a good portion of projects, and use company assets and credit financing to pay for equipment and labor.

Cash flow modeling for construction projects

2014 ◽  
Vol 21 (2) ◽  
pp. 170-189 ◽  
Author(s):  
Tarek Zayed ◽  
Yaqiong Liu
Keyword(s):  
Cash Flow ◽  
Financial Management ◽  
Construction Projects ◽  
Mean Value ◽  
Major Step ◽  
Flow Management ◽  
Content Type ◽  
Cash Flow Management ◽  
Cash Flow Forecasting ◽  
The Impact

Purpose – Construction projects are well known for their complexity and ambiguity. These projects carry out higher risk than traditional ones because they entail high capital outlays and intricate site conditions. Poor financial management of these projects may lead to bankruptcy; therefore, effective cash flow management is essential. Although the peculiar characteristics of construction projects, the accuracy of cash flow forecasting has been a long lasting problem. The paper aims to discuss these issues. Design/methodology/approach – Many unforeseen factors affect the cash flow forecasting of construction projects. Therefore, the objective of the presented research in this paper is to examine the impact of these factors on contractor's cash flow. A model has been established by integrating analytic hierarchy process and simulation to examine the impact of various factors on cash flow. Data on the selected factors have been collected through questionnaires from various agencies in North America and China. Findings – Results show that the most significant factors are: change of progress payment, payment duration, financial position of the contractor, project delays, and poor planning. It also shows that the effect of cash inflow factors varied approximately from 9.7 to 16.3 percent with a mean value of 12.4 percent. Research limitations/implications – The implementation of the developed models are limited to few case study projects in testing the models. However, the developed models and framework are sound for future improvement. They are considered as a major step toward a broader cash flow planning. Practical implications – The developed methodology and models play essential roles in decision-making process. Originality/value – The developed model is expected to help contractors realistically forecast project cash flow under uncertainty. This may lead to more dependable and professional cash flow management, which might substantially reduce failures in construction business.

scholarly journals AN INVESTIGATION ON THE IMPROVEMENT OF CONSTRUCTION EXPENDITURE FORECASTING

2013 ◽  
Vol 19 (5) ◽  
pp. 759-711 ◽  
Author(s):  
Andrew Ross ◽  
Katie Dalton ◽  
Begum Sertyesilisik
Keyword(s):  
Cash Flow ◽  
Construction Projects ◽  
Case Study Research ◽  
Research Strategy ◽  
Flow Models ◽  
Improved Model ◽  
Work Affect ◽  
Cash Flow Forecast ◽  
Parameter Values

This study aims to determine the accuracy of the cash flow models and to investigate if these models could be more accurate if they accounted for the potentially influential variables specific to individual construction projects. An analytical case study research strategy has been implemented in collecting data for the construction projects. The data collected has been tested against recognised models. Statistical analyses have been carried out on the data for the specified variables, culminating in the potential proposal of an improved model with respect to these identified variables. The results revealed that the independent variables (type of construction, procurement route and type of work) affect the cash flow forecast. The findings suggested that a model could be more accurate with the input of more job-specific variables and that Hudson's DHSS model is best suited to a construction project procured traditionally. Adopting the ‘trial and error’ approach, Hudson's DHSS model has been recognised as an accurate model that could be adapted slightly, through changing the parameter values. The clients and the contractors are the main beneficiaries approached for this study.

scholarly journals Application of BIM and 3D Laser Scanning for Quantity Management in Construction Projects

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Thu Anh Nguyen ◽  
Phong Thanh Nguyen ◽  
Sy Tien Do
Keyword(s):  
Construction Industry ◽  
Construction Projects ◽  
Laser Scanning ◽  
Essential Role ◽  
Industrial Revolution ◽  
Management Process ◽  
3D Laser Scanning ◽  
Economic Sectors ◽  
Construction Companies

The construction industry has played an essential role in the process of modernization and industrialization and it has also been a major factor in determining the development of the infrastructure for other economic sectors. Construction companies consider the measurement of work progress, which often wastes time and has a low resolution, to be one of the most challenging problems faced by project management. Therefore, this research aimed to propose practical solutions by applying recent technological achievements of the 4.0 industrial revolution to improve the efficiency of the quantity management process. By utilizing the advantages and features of a BIM model and 3D laser scanning, this paper proposes that adopting a BIM model and 3D laser scanning has the potential to improve the accuracy and efficiency of the quantity management process. The case study demonstrated some typical tasks to evaluate accuracy and efficiency as well as to showcase the research proposal.

Bayesian Belief Networks in IT Investment Decision Making

2017 ◽  
pp. 75-107 ◽  
Keyword(s):  
Decision Making ◽  
Investment Decision ◽  
Bayesian Belief Networks ◽  
Influence Diagrams ◽  
Belief Networks ◽  
It Investment ◽  
Investment Decision Making ◽  
Availability Modeling

This section aims at describing the concept of Bayesian Belief Networks (BBN), building principles and application of BBN and influence diagrams, as well as the reasons why BBN are considered an adequate tool for IS availability modeling.

Exploring ecosystem service issues across diverse knowledge domains using Bayesian Belief Networks

2011 ◽  
Vol 35 (5) ◽  
pp. 681-699 ◽  
Author(s):  
Roy Haines-Young
Keyword(s):  
Ecosystem Services ◽  
Social Values ◽  
Early Stage ◽  
Bayesian Belief Networks ◽  
Decision Makers ◽  
Belief Networks ◽  
Knowledge Domains ◽  
Study Materials ◽  
Shared Social Values

The analysis of the relationships between people and nature is complex, because it involves bringing together insights from a range of disciplines, and, when stakeholders are involved, the perspectives and values of different interest groups. Although it has been suggested that analytical-deliberate approaches may be useful in dealing with some of this complexity, the development of methods is still at an early stage. This is particularly so in relation to debates around the concept of ecosystem services where biophysical, social and economic insights need to be integrated in ways that can be accessed by decision-makers. The paper draws on case studies to examine the use of Bayesian Belief Networks (BBNs) as a means of implementing analytical-deliberative approaches in relation to mapping ecosystem services and modelling scenario outcomes. It also explores their use as a tool for representing individual and group values. It is argued that when linked with GIS techniques BBNs allow mapping and modelling approaches rapidly to be developed and tested in an efficient and transparent way, and that they are a valuable scenario-building tool. The case-study materials also show that BBNs can support multicriteria forms of deliberative analysis that can be used to capture stakeholder opinions so that different perspectives can be compared and shared social values identified.

scholarly journals Impact of Risk Factors on Construction Projects’ Completion Cost in Nigeria

2021 ◽  
Vol 6 (2) ◽  
Author(s):  
Z. H Ishaq
Keyword(s):  
Risk Factors ◽  
Construction Projects ◽  
Sampling Technique ◽  
Related Factors ◽  
Cash Flow Management ◽  
Project Completion ◽  
Contract Administration ◽  
Potential Risks ◽  
The Impact ◽  
Cost Of Construction

Construction projects are prone to a number of risks due to their complexity, dynamic nature, capital intensive nature and involvement of many stakeholders. These risks if left unmanaged will negatively influence the completion cost and other primary objectives of construction projects. Numerous studies have been conducted globally to determine the potential risks that negatively impacts construction projects; however, the risks aren’t alike across all the regions and the potential degree of impact may changes with time. This study assessed the impact of risk factors on completion cost of construction projects in Nigeria. Data was collected using structured questionnaires administered to 192 construction practitioners using convenience sampling technique. Descriptive statistics (mean and standard deviation) were used to analyse the data. The study found ‘inadequate cost estimate’ (MS = 4.39), ‘risk incurred due to bribery and corruption’ (4.30), ‘increase in prices of materials’ (4.25), ‘increase in cost of labour’’ (4.11), ‘poor cash flow management’ (4.04) ‘mistakes/errors in design’ (4.04) and ‘mistakes during construction’ to be the topmost risk factors that impact on project completion cost. The study concludes that ‘economic’, ‘financial’ and ‘contract administration and project management’ related factors group are those with high impact on project completion cost.

scholarly journals THE EFFECT OF FAIR VALUE IMPLEMENTATION ON CASH FLOW FORECASTING (CASE STUDY: BANKING COMPANY LISTED IN INDONESIAN STOCK EXCHANGE YEAR 2014-2015)

AKUNTABILITAS ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 59-70
Author(s):  
Riesa Morita Yuliasari ◽  
Mukhtaruddin Mukhtaruddin ◽  
Tertiarto Wahyudi
Keyword(s):  
Cash Flow ◽  
Quantitative Research ◽  
Stock Exchange ◽  
Secondary Data ◽  
Sampling Technique ◽  
Fair Value ◽  
Financial Statement ◽  
Historical Cost ◽  
Cash Flow Forecasting

This study has one main objectives; to investigate about the significant effect of fair value implementation in forecasting cash flow on Banking Company in Indonesia. The methodology used in this research is quantitative research, so the data are collected from secondary data by using purposive sampling technique of Banking Company’s Financial Statement uploaded in Indonesian Stock Exchange which related to this research. The number of sample in this research are 36 financial statement of Banking Company in Indonesia for year 2014 and 2015 consist of 18 financial statement that implement fair value and 18 financial statement that still implement historical cost. The results of this study show that the implementation of fair value does significantly influence cash flow forecasting of Banking Company in Indonesia.

scholarly journals Productivity Metrics and Its Implementations in Construction Projects: A Case Study of Singapore

2021 ◽  
Vol 13 (21) ◽  
pp. 12132
Author(s):  
Ming Shan ◽  
Yu-Shan Li ◽  
Bon-Gang Hwang ◽  
Jia-En Chua
Keyword(s):  
Construction Projects ◽  
Statistical Tests ◽  
Construction Productivity ◽  
Construction Companies ◽  
Four Levels ◽  
Project Company ◽  
Different Levels ◽  
Design Score ◽  
Assessment Results

Although some studies have used or developed different types of metrics to assess construction productivity in the existing literature, few of them investigated those metrics systematically and the differences between assessment results. This study examined the various types of metrics used in the assessment of the productivity of construction projects. First, a literature review was conducted first to identify prevailing productivity metrics at four levels, namely trade, project, company, and industry. Then, the questionnaire was developed and disseminated to 53 Singapore-based construction companies for data collection. Subsequently, non-parametric statistical tests were conducted to analyze the data collected by the questionnaire. Results showed that the top five metrics in terms of usage frequency and relative importance were “constructability score”, “buildable design score”, “square meter of built-up floor area per man-day”, “square meter per dollar”, and “output per worker.” In addition, results showed that differences existed in the assessment results when productivity metrics at different levels were used to conduct the same measurement. This is the first study to explore the most widely used metrics in productivity assessments of construction projects and investigate possible differences in assessment results. This study could help the authorities to review, evaluate, and modify the productivity metrics used in practice. Thus, this study is beneficial to the practice as well.

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