Contractor financial prequalification using simulation method based on cash flow model

Although construction contractor prequalification highly prioritizes the financial capacity of the construction contractors, a special assessment of contractors' financial capacities has seldom been performed in the construction industry. Cash flows largely reflect a contractor's capacity to meet its financial obligations, this study assesses the credit qualities of construction contractors by using a cash flow based credit model (CFB credit model). The model uses historical continuously free cash flow to firm of construction contractors to simulate possible future cash flow paths. The credit quality scores of construction contractors are then assessed using the CFB credit model. The results demonstrate the effectiveness of assessment of the credit quality of construction contractors, and recommend the clients to adopt it in prequalification of the contractors' financial abilities.     

Systems analysis of project cash flow management strategies

Cash flow management is one of the most important determinants of the success of construction project management. Overdraft, retainage, financing, payment and billing policies constitute the most significant financial issues that contractors must plan, control and manage for the successful completion of construction jobs. Particularly, in an attempt to reduce project costs, contractors must balance cost savings of material discounts due to early payments and extra interest expenses because of additional overdraft. Through identifying feedback loops in project cash flows, a system dynamics model is developed for project cash flow management. The model is flexible to incorporate typical front‐end and back‐end loading cash flow management strategies and provides an interactive predication of project cash flows. A warehouse project is discussed to demonstrate how various cash flow strategies improve overdraft financing requirements and profitability. Especially, the analysis shows an 11% reduction on overdraft requirements while using an overbilling strategy, and 30% reduction if the trade credit strategy is implemented.     

Development of linear programming for capital budgeting of construction projects

The UK construction industry suffers the largest number of bankruptcies of any sector of the economy, with many companies failing because of poor financial management, especially inadequate attention to poor cash flow forecasting. The financial model outlined in this paper demonstrates the potential application of simulation methods in assessing financial alternatives.     

A Decision Support Model for Construction Cash Flow Management

Abstract: The excessive level of construction business failures and their association with financial difficulties has placed financial management in the forefront of many business imperatives. This has highlighted the importance of cash flow forecasting and management that has given rise to the development of several forecasting models. The traditional approach to the use of project financial models has been largely a project‐oriented perspective. However, the dominating role of “project economics” in shaping “corporate economics” tends to place the corporate strategy at the mercy of the projects. This article approaches the concept of cash flow forecasting and management from a fresh perspective. Here, the use of forecasting models is extended beyond their traditional role as a guideline for monitoring and control of progress. They are regarded as tools for driving the project in the direction of corporate goals. The work is based on the premise that the main parties could negotiate the terms and attempt to complement their priorities. As part of this approach, a model is proposed for forecasting and management of project cash flow. The mathematical component of the model integrates three modules: an exponential and two fourth‐degree polynomials. The model generates a forecast by potentially combining the outcome of data analysis with the experience and knowledge of the forecaster/organization. In light of corporate objectives, the generated forecast is then manipulated and replaced by a range of favorable but realistic cash flow profiles. Finally, through a negotiation with other parties, a compromised favorable cash flow is achieved. This article will describe the novel way the model is used as a decision support tool. Although the structure of the model and its mathematical components are described in detail, the data processing and analysis parts are briefly described and referenced accordingly. The viability of the model and the approach are demonstrated by means of a scenario.     

An empirical examination of project contractors' supply-chain cash flow performance and owners' payment patterns

Supply-chain (SC) cash flow performance is an essential component of SC performance management. Despite the panoply of approaches to SC cash flow modeling, relatively few published studies assess the effect of SC cash flow performance on a project contractor's financial performance. Little research thus explores the behavioral patterns in the project owner-contractor dyad in the context of payment-term negotiation for improving the SC cash flow performance of a project contractor. Using data from 42 Taiwanese construction project contracting corporations, this paper systematically quantifies the effects of SC cash flow performance on the financial performance of construction project contractors. Further analysis using data from 118 returned, usable surveys reveals important behavioral patterns of project owners regarding payment terms with project contractors during the contracting phase of construction projects. These behavioral patterns provide project contractors with a base for supporting implementation efforts for improving SC cash flow performance.     

Modelling financial decisions in construction firms

Some contractors predict their corporate cash flow on the basis of individual contracts without considering the relationships between the overall before-tax profit, risks, other crucial qualitative factors, or the allocation of resources within the company. Moreover, some contractors, in predicting their cash flow, focus only on the early-start progress in the project and their predictions of progress are too pessimistic, or result in the overuse of resource in order to make up for delays. In the present research a decision model is established for a contracting firm. It provides a methodical system for construction financial decision-making, and a way of solving a financial decision problem under qualitative and fuzzy circumstances. The model can be applied to the management of corporate cash flow, thereby facilitating the minimal use of resources. The information provided by the model allows the planner to eliminate excess use or idleness of resources during the scheduling of a project. Financial forecasting may also suggest the best time to invest in a new project. Four projects for a medium size construction firm in Hong Kong were employed as case studies in order to evaluate the mathematical model. The cases involve two objectives: maximize profit margin and minimize construction risk (consider in a qualitative factor). The model leads to a compromise optimal schedule that provides the contracting firm with the optimal schedule for achieving optimal profit and construction risk by making optimal use of the contractor's resources.     

改进GM(1,1)模型在建筑工程现金流预测中的应用

准确的建筑工程现金流预测是提高建筑行业投资和融资决策效果、获得稳定收益的前提,合理的现金流预测方法是确保预测结果准确的关键。引入灰色预测和"1/4:1/3"现金流预测理论,提出基于权重因子的背景值构造,并以实地收集的10余个建筑工程项目为样本,采用黄金分割法和对半分割法对GM(1,1)模型进行改进,以提高GM(1,1)模型在建筑工程现金流预测实践中的适用性和适应性。实证结果表明,改进后的灰色预测模型能够以较高精度预测建筑工程现金流,从而为公司投资、融资决策以及资金管理提供可靠依据。     

Cash farming in building and construction: a stochastic analysis

Cash flow management is a significant issue in the management of a building or construction firm. This paper steps back from the well researched area of poor cash management and its relationship with failure, to focus on the funds which are generated through operations, and the positive benefits which can follow in a well managed organization. A stochastic model is developed which illustrates how an average of 16% of turnover can be available for reinvestment. This is sufficient to allow investment in non-liquid assets, provided that this is managed carefully and precautions are taken against a severe reduction in turnover. This level of funds is sufficient to encourage firms to enter the industry with the motivation of generating funds, rather than a desire to build. This has implications for large clients and for government when dealing with the industry.     

Supporting financial decision-making based on time value of money with singularity functions in cash flow models

Existing budgeting approaches differ in whether or not they consider the time value of money. A novel use of singularity functions in construction management has the potential to enhance cash flow models in order to maximize their net present value. This type of function can model a complete schedule, which serves as the underlying timeline for all financial transactions. Their variable amounts and constraints are expressed by singularity functions, converted from costs via bills into payments, and compounded towards the overall net present value for financial decision-making. Contributions to the body of knowledge include deriving exact amounts of interest on variable balances for any duration, creating a valuation algorithm, and exploring how the uneven solution space that cash flow profiles create can be searched successfully with a genetic algorithm.     

基于现金流视角的PPP项目财务预警指标体系构建研究

PPP项目具有建设周期较长、投资巨大、融资结构复杂、参与方众多等特点,因此存在着很大的财务风险,现金流能实时反映PPP项目资金流动情况,而对项目资金的预测又是PPP项目资金风险管理的关键。本文将结合企业财务预警与项目的评价方法,从现金流的视角构建PPP项目财务预警指标体系,以期提高PPP项目资金管理效率,确保PPP项目顺利实施及运营。     

An integration of the fuzzy reasoning technique and the fuzzy optimization method in construction project management decision-making

Most real world decision-making combines quantitative and qualitative (linguistic) variables. Conventional mathematics that combines qualitative and quantitative concepts exhibits difficulty in modelling actual problems. The research presented in this paper illustrates a mathematical approach to the solution of decision-making problems that combine qualitative and quantitative objectives. A methodical system for construction project management decision-making was developed using a combination of fuzzy multiple-objective decision-making theory and the fuzzy reasoning technique. The mathematical model can be applied to construction project management problems by suggesting an optimal path of corporate cash flow that results in the minimum use of resources. The information provided by the mathematical model allows the planner to eliminate excess use, or idleness, of resources during the construction of a project. Such information is indispensable for decision-makers in analysing the best time to invest in a new project. A case study is demonstrated to illustrate the application to a management decision problem.     

Finance‐based CPM/LOB scheduling of projects with repetitive non‐serial activities

Projects of repetitive non‐serial activities constitute a major category of construction projects which can be scheduled more conveniently using the line of balance (LOB) technique. Generally, scheduling activities such that the expenditures are always in balance with the available cash is a must to devise financially feasible schedules. The objective is to integrate a CPM/LOB model for a project of repetitive non‐serial activities with a cash flow model and utilize the integrated model to devise financially feasible schedules. The genetic algorithms (GAs) technique is employed to maximize the profit at the end of the project under the constraints of available cash. The optimization of the integrated models was demonstrated using an example project of 15 activities carried out at five units. The CPM/LOB model was validated against the results of a dynamic programming model in the literature and further by conducting a sensitivity analysis of the results of the integrated model. Finally, the model offers an effective financial planning tool for projects of repetitive non‐serial activities.     

Artificial intelligence approaches to achieve strategic control over project cash flows

The ability over the course of a construction project to make reliable predictions regarding cash flows enhances project cost management. This paper uses artificial intelligence (AI) approaches to predict cash flow trends for such projects in order to develop appropriate strategies that apply factors such as float, process execution time, construction rate and resource demand to project cash flow control. AI approaches involved in this paper include K-means clustering, genetic algorithm (GA), fuzzy logic (FL), and neural network (NN). K-means clustering is employed to categorize similar projects, while the other approaches are used to develop the Evolutionary Fuzzy Neural Inference Model (EFNIM), a knowledge learning model. FL and NN are employed in the EFNIM to develop a neural-fuzzy model that can deal with uncertainties and knowledge mapping. GA is used to optimize the membership functions of FL and NN parameters globally. The major target of this AI learning is to address sequential cash flow trends. This trained result is furthermore applied to a strategic project cash flow control. This cash flow control affects project performance within the banana envelope of the S-curve for project management.     

Evolutionary fuzzy decision model for cash flow prediction using time-dependent support vector machines

The ability of project managers to make reliable cash flow predictions enhances project cost flow control and management. Reliable cash flow prediction over the course of a construction project puts the project manager in a better position to identify potential problems and develop appropriate strategies to mitigate the negative effects of such on overall project success. Therefore, managers should monitor project progress using cash flow data, which has unique characteristics, as time series data. However, the complex, mutable nature of construction projects currently requires significant reliance on experience and expert opinions to predict cash flow on an ongoing basis. Recent studies have indicated good potential for using artificial intelligence to reduce reliance on human input in cash flow prediction processes. The Evolutionary Fuzzy Support Vector Machine Inference Model for Time Series Data (EFSIM_T), an artificial intelligence hybrid system focusing on the management of time series data characteristics which fuses fuzzy logic (FL), weighted support vector machines (weighted SVMs) and a fast messy genetic algorithm (fmGA), represents a promising alternative approach to predicting cash flow. Simulations performed on historical cash flow data demonstrate the EFSIM_T is an effective tool for predicting cash flow.     

Efficiency measurement of the construction industry in Taiwan: a stochastic frontier cost function approach

Construction firms require a large cash flow, thereby creating a significant financial leverage. Therefore, identifying a highly effective cost efficiency model is essential for construction firms, especially under the pressure of competition in today’s global market. This research used stochastic frontier analysis (SFA) to model and measure the cost efficiency of construction firms in Taiwan, and to investigate the relationships between input resources and cost efficiency. The main findings include: (1) subcontracting reduces labour capacity; (2) larger firms can be more cost efficient; (3) appropriate financial leverage increases cost efficiency and capital; and (4) reducing equipment costs increases cost efficiency. These findings can help construction firms to strategically adjust the management of their firm and improve cost efficiency.     

合同付款条件对国际工程项目承包商财务状况的影响

合同付款条件对国际工程项目承包商财务具有重要影响。尽管承包商能够定性识别合同付款条件是否对本方有利,但并不能仅凭定性判断而获知其对资金压力和盈利水平的具体影响。为帮助承包商在合同谈判中能正确决策合同付款条件,在分析国际工程项目合同付款条件内容与性质的基础上,提出了定量分析合同付款条件对承包商现金流和财务影响的模型。以非洲某EPC 道路工程为案例,假设了不同进度付款方式和预付款比例所构成的6 种合同付款条件组合,分析了合同付款条件对现金流入、现金支出、垫资成本和盈利水平的影响,识别了不可接受的合同付款条件,为承包商正确决策提供了支持。     

基于 SEM 的建设项目造价控制影响因素研究

在城市化推进过程中,我国建筑产业逐渐形成以建设项目工程造价为主的市场竞争点。但在工程项目建设活动中,就造价成本而言,容易出现预算与决算相差过大、成本控制难、投资失控等问题。基于文献研究,构建了建设过程、材机选取、造价依据、项目管理、组织管理及财务管理对建设项目造价控制构成影响的假设模型,将问卷调研数据代入结构方程模型实证分析建设项目造价控制的关键影响因素。研究发现,建设项目造价控制受建设过程的直接影响,以及材机选取、造价依据、项目管理、组织管理及财务管理的直接和间接影响,影响程度由大到小依次为建设过程、项目管理、材机选取、组织管理、造价依据、财务管理。该研究结果对建设项目成本造价的控制和管理具有一定的应用价值。     

Total project cost: a simplified model for decision makers

A simplified model for total project cost is developed in this paper to meet the numerous requests from decision makers for a model that can be used to estimate the total project cost from the estimated cash flows and, more importantly, to check the accuracy of the project cost estimates in feasibility studies that require prudent decisions. It begins with a base cost estimate in constant dollars and discrete cash flows with discrete inflation rates as practised by the construction industry. The discrete inflation rates are used to estimate the current dollar costs of the project. The effects of inflation are estimated as escalation during construction. Using the future value concept, interest during construction is estimated, in a simplified approach, to estimate the total project cost. Data from an actual feasibility study is used to highlight the strengths and weaknesses of the simplified model. The model is extended to treat discrete cash flows with continuous inflation rates.     

Artificial neural network cost flow risk assessment model

Previous attempts have been made to model cash flow forecast at the tender stage using net cash flow, value flow and cost flow approaches. Despite these efforts, significant variations between the actual and modelled forecasts were still observable. The main cause identified is the issue of risk inherent in construction. Using the cost flow approach, a model is developed to assess the impacts of risk occurring during the construction stage on the initial forecast cost flow. A questionnaire survey and case study approach were employed. As a first step, a questionnaire survey was administered to UK construction contractors to determine the significant risk factors impacting on their cost flow forecast. Using mean ranking analysis, the survey yielded 11 significant risk factors. The second stage of data collection involves the collection of forecast and actual cost flow data from case study projects to establish their variations at predetermined time periods. Using the significant risk factors identified in the first phase, relevant construction professionals who worked on the case study projects were requested to score the extent of risk occurrence that resulted in the observed variations. A combination of these two sets of data was used to model the impact of risk on cost flow forecast using an artificial neural network back propagation algorithm. The model enables a contractor to predict the likely changes to a cost flow profile due to risks occurring in the construction stage.     

Payment for offsite goods and materials: the Scottish perspective*

Materials are a critical element within the construction industry yet- the conditions and legality surrounding their ownership remains an area of uncertainty. The difficulty in ascertaining ownership is often found in the instances of payment, delivery and complex contractual relationships. Additionally, the nature of the construction industry whereby raw materials are purchased within a supply chain and are incorporated into the fabric of buildings or goods often creates further confusion. The importance of ownership is most apparent in the instance of disputes or insolvencies, both of which are regular occurrences within the construction industry and in the management of a project regarding cash flow and programme. To inform the position and stance of Scots Law in relation to ownership of materials it is necessary to evaluate current law regarding ownership of materials in Scotland through the undertaking of a literature review which establishes the prevailing legal structure. Conclusions and recommendations propose that parties of a construction contract, for which Scots Law is applicable, are aware of current law surrounding the intricate matter regarding ownership of materials in Scots Law