Analyzing Models of Project Cash Flow in Construction Projects in Australia

Running head: LITERATURE REVIEW
Literature Review
by Student Name
Course & Course Code
Professor
University
City & State
Date

LITERATURE REVIEW 2
Topic: Analysing models of project cash flow in the context of construction projects in
Australia
Introduction
Construction projects are associated with high uncertainty and risks. During the cost
estimation phase, before the execution of a project, contractors are faced with limited
information to rely on for reliable financial planning. Likewise, initial budget estimation
tends varying because of micro and macroeconomic forces. Without effective cash flow
management, constructing companies cannot survive in the industry. Construction projects
are executed within a specific period. Therefore, cash flow refers to the balance between cash
received and cash spent on construction during a project period (Zayed & Liu, 2012, pp. 170-
73).
Lack of financial liquidity has been cited as the main reason why construction companies fail.
A census report conducted in the United States associated construction companies with a
higher failure rate at 14% compared to other companies. Another study by BizMiner industry
reports realised in 2005 showed that 28.5% of the 853,372 construction companies that had
been established in 2002 had failed two years later. 26.71% of the failures were caused by
poor financial management and lack of liquidity (Park, et al., 2005, p. 165).
Cash flow forecasting and control is important for the survival of construction companies.
Today, financial management has become part and parcel of organisational management.
Using financial tools and models, contractors can easily forecast the construction budget.
Moreover, contractors use cash flow diagrams to determine if the budget estimation is below
or over budget (Kenley & Wilson, 1986, p. 214).
Contractors use both mathematical and nonmathematical approaches to forecast project cash
flow. Nonmathematical models use traditional estimation methods; they are expensive, time-

LITERATURE REVIEW 3
consuming and complicated. On the other hand, mathematical models use deterministic
approaches hence cheaper and more straightforward (Ock & Park, 2016, p. 2170).
This paper is a review of the previous studies that have analysed models of project cash flow
in the context of construction projects in Australia. Specific focus has been paid on the
factors that cause discrepancies in the actual and projected cash flows as well as financial
models used to control such forecast in the construction industry.
Reviewed literature
Zayed & Liu (2012, pp. 170-3), examined both micro- and macroeconomic factors that
impact cash flow forecasting and how these factors can be used to develop a new cash flow
modelling. Zayed & Liu identified 43 factors which were grouped into seven categories
namely financial management, communication skills, subcontractors, and suppliers among
others. The categorisation of the factors is based on their influence on the Cash inflows and
outflows. This study established cash flow factors that should be considered as cash retention
which influences cash inflow and is a loss to a contractor if a project is not completed;
fluctuation of material cost which impacts cash outflow; change in project duration also
affect both cash inflows and outflows.
Other factors that have been identified in this study are the change of contract order which
affect the Internal Rate of Return (IRR) of a contract; Rework also hurts the cash flow of a
project. Lastly, contract terms also make it difficult to manage liquidity and cash flow.
Clauses like "pay if paid" or "pay when paid" make it difficult for contractors to manage
project liquidity and cash flow. Zayed & Liu uses the identified factors to; first, establish the
advantages and disadvantages of the previous cash flow forecasting models. Second,
categorise the factors into three parameters of cash inflow, cash outflow, and overdraft which
are important in developing new cash flow forecasting model (Zayed & Liu, 2012, p. 175).