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.     

Integration of Simulation-Based Cost Model and Multi-Criteria Evaluation Model for Bid Price Decisions

Abstract:   Several criteria affect bidding decisions. Current bidding models determine a markup based on a fixed project construction cost. This work presents a novel bid price determination procedure that is built by integrating a simulation-based cost model and a multi-criteria evaluation model. The cost model is used to consider cost uncertainties and generate a bid price cumulative distribution, whereas the multi-criteria evaluation model applies pairwise comparisons and fuzzy integrals to reflect bidder preferences regarding decision criteria. The relationship between the two models is based on a practical phenomenon in that a bidder has a high probability of winning when criteria evaluations favor his bid, and, consequently, the bidder would bid a low price, and vice versa. The merits of the proposed procedure are demonstrated by its application to two construction projects in Taiwan .     

A method to determine minimum contract bids for incentive highway projects

An increasing number of state highway agencies (SHAs) are using Incentive/Disincentive (I/D) bidding for highway construction. The I/D bidding concept is designed to shorten the total contract time by allowing the contractor to obtain incentives for early completion and pay disincentives for late completion of a project. Contractors are then presented with the problem of determining a better strategy to develop their bid estimate, including construction cost, construction time, and I/D. This research offers a quantifying model to determine an optimum low bid to submit for both linear I/D and escalating I/D type projects. A functional relationship between the construction cost and time duration is developed from the Florida Department of Transportation (FDOT) projects. The equation is then combined with the I/D to determine the optimum low bid price and time. Finally, several projects completed by the FDOT will be utilized to illustrate the validity of this model.     

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。     

Predicting final cost for competitively bid construction projects using regression models

This paper studies the relationship between the low bid and completed cost for competitively bid highway projects. Data are analyzed from several agencies managing highway and dredging projects. A natural log transformation of the low bid and final cost was found to produce regression models for each agency that had high R and R² values. These models can predict completed project cost using only the project low bid as input. A separate regression model was determined for each agency. Based on the form of the calculated models it appears that highway agencies construct projects where the final cost increases as an increasing percentage of the low bid price as the project magnitude increases. The dredging projects appear to follow different mechanisms of cost increase than the highway projects and were not predicted as well by the regression models. The regression models can also be used for budgeting purposes by submitting the sum of the low bids for a group of projects as input. The regression models output a prediction of the cost of the group of projects that was found to be highly accurate.     

Risk‐minimizing approach to bid‐cutting limit determination

Intense price competition is quite common in the construction industry. In many markets, contractors have to cut their bids to compete, giving priority to winning enough contracts to sustain normal operation, and it is common to see a winning bid close to the expected project cost. While cutting bids not only gives up profits but also undoubtedly increases the risk of making a loss, the behaviour of contractors in intense competition is difficult to explain by existing academic bidding models. An approach to determining the lower limit of the bid for a project is proposed based on minimization of the overall loss risk defined by a probabilistic model. The approach can be used to prevent arbitrary over‐cuts in final bid decision where price competition is intense. Factors influencing the suggested bid‐cutting limit for a project are analysed. An illustrative example using real case data is provided.     

工程量清单投标报价中措施项目费竞争力分析研究

工程量清单报价中的措施项目费的确定，是建设工程项目投标报价的竞争内容。本文作者通过工程实例中措施项目费的报价，对不同投标人的投标报价做出分析研究，提出了掌握工程造价中各项费用组成的内在联系，熟悉建筑工程内容、施工技术措施和施工方法，建立施工企业定额，完善投标报价的方法与技巧，以确定合理的措施项目费用，提高投标人的竞争能力。     

基于现金流模型的地铁项目融资方案设计与评价

地铁项目融资问题是目前各地铁建设城市面临的实际问题.本文针对地铁项目财务融资的可操作问题进行了系统研究,提出了地铁项目现金流模型,并设计了地铁项目融资方案评价软件,为地铁项目融资问题的解决提供了通用性的工具.     

Determining bid markup and resources allocated to cost estimation in competitive bidding

To win a project contract through competitive bidding, contractors submit a bid price that is determined by putting a markup on the estimated project cost. The success of the bid is therefore heavily dependent on the accuracy of that estimate, meaning that sufficient resources should be allocated to the estimation process. This paper develops a novel optimization model for simultaneously determining the bid markup and the resources that should be allocated to cost estimation. We begin by deriving optimality conditions for this simultaneous optimization model and illustrating them with numerical examples, for which purpose only we assume a single competitor and uniformly distributed estimation errors. To analyze a more realistic situation, we then examine computational solutions to our model. Through these two approaches, we investigate the effects of the bid-markup decision and resource allocation on the contractor's expected profit, and we highlight the significance in competitive bidding of the markup and allocation.     

Detection and prevention of unbalanced bids

Unbalanced bidding is a serious problem for the construction owner because it may increase the cost of construction The most common way to mathematically unbalance a bid is frontloading where a bidder overstates the unit price of line items scheduled to be performed early in the project and understates the unit price of line items performed later. A bidder can also overstate the unit price of a line item whose quantity was somehow underrated by the engineer. If the owner proves that a mathematically unbalanced bid costs more to perform, the bid is said to be materially unbalanced, in which case the owner can reject the bid. A model is presented that formalizes and automates the process of detecting mathematically and materially unbalanced bids by comparing line item prices with the engineer’s estimates and the average prices offered by the bidders. This model allows owners to detect and reject unbalanced bids, and deters bidders from unbalancing their bid.     

机电设备招评标阶段的造价控制

针对现代工程中机电设备含量越来越高，设备购置费比例不断提高的趋势，结合工程量清单计价模式，介绍了机电安装工程的造价构成及编制，阐述了机电设备评标阶段的造价控制，以期建立统一开放，竞争有序的市场秩序，保证工程建设的顺利进行。     

基于灰色关联理论的建设工程评标方法研究

推行工程量清单计价模式是我国工程造价计价改革的重点,而工程量清单计价模式的核心是“合理低价中标”。论文针对目前我国在招投标中采用方法的不足,将层次分析法和灰色关联分析的方法有机地结合起来,即建立灰色多层次综合评判模型,为工程项目招标评标提供定量决策依据,对业主根据合理低价中标的规定确定合适的投标单位起到科学的参考作用。     

Time to build options in construction processes

Time to build is a very important factor in a real estate development venture. Delay in completion of a project not only affects the financing costs and the rental revenue but also it may, on a more strategic note, determine the success or failure of a project. A time to build option model consisting of a stochastic rate of completion and a stochastic net project payoff is applied to the sequential construction process of a large scale construction project. The results of the sensitivity analysis show that the optimal payoff value, that triggers the exercise of the option to invest at a maximum rate, increases positively with the increases in cash flow volatility, input cost uncertainty, excess asset return per unit risk and maximum rate of investment. However, it has a negative relationship with the rental yield. In a case study involving a commercial project, the premium for hedging the payoff risks by pre-leasing a project was estimated at 11.29%, whereas the additional cost incurred for shielding a project against input cost risks in a design and build contract was estimated at 7.80%, where each is given as a percentage of the total construction costs.     

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.     

工程量清单计价模式下的投标报价分析

本文通过对工程费计价和措施项目费计价原则、规费计价和税金计价原则、投标总价计价和其他项目费计价原则的研究,可以更好地掌握投标报价技巧,希望本文能为相关人员提供参考。     

浅谈工程施工招标工作中的策略和技巧

本文论述了业主在工程施工招标工作中,在发布招标公告(或发出投标邀请书)、编制招标文件、评标、与中标人签订施工承包合同等几个重要的阶段所应注意的问题及应该采取的策略和技巧。特别着重论述了在编制招标文件过程中应该着重解决好的几个问题,包括招标范围和标段划分、选择报价形式、评标的方法和标准、合同价格形式、材料设备的采购和供应、质量标准、工期要求和奖惩、保函或保证金的设置等。     

工程量清单计价模与式企业投标

工程量清单计价模式，是指建设工程招标投标中，招标人按照国家统一的工程量计算规则提供工程数量，由投标人依据工程量清单，结合自身的消耗水平、技术特点、材料采购渠道和组织管理自主报价，并按照经评审低价中标的工程造价的计价方式。在这一新的计价模式下，施工企业应如何采取积极的应对措施。文章就此问题作了简单的探析。     

国际总承包项目涨价预备费蒙特卡罗模拟分析方法

后金融危机下持续动荡的经济环境使得国际总承包项目涨价预备费的合理准确测算变得比较困难,传统的测算方法不能体现涨价风险的不确定性与影响因素的随机性特征,为此有必要构建基于蒙特卡罗模拟的国际总承包涨价预备费分析模型。在给出了涨价预备费的基本定义与传统测算方法的基础上,分析了影响涨价预备费的费用、进度、现金流与价格系数4 种参数的随机性特征,并提出了涨价预备费蒙特卡罗模拟分析流程。通过实际案例,阐述了影响因素概率分布的合理定义过程,分析了涨价预备费概率分布与敏感性分析结果,验证了此方法的实用性与有效性。     

现有工程招标评标的不规范现象及对策

工程项目评标是招标工作的主要环节,评标决策方法的科学、客观与否,直接关系到招标工作的成功,保证公开、公平、公正地选择中标人,是建筑市场环境的综合反映。现有工程招标评标的不规范现象,其根源就是标底的存在。随着市场经济的发展,采用“最低价中标”的方法是大势所趋。但“最低价中标”原则却遭到了许多人的反对。投标人为了不使总报价过高,对在施工过程中无望增加工程量或可能减少工程量的项目压低报价。同时,有些投标人不惜一切手段了解专家名单,长期拉拢某些专家,影响评标的科学性和公正性。规范招投标行为,提高招投标透明度,实质是通过公开、公平、公正的招投标活动,将建立高效、规范的管理体系的过程法律化。     

Impact of crude oil market behaviour on unit bid prices: the evidence from the highway construction sector

It is well known that the cost of highway construction is affected by the cost of crude oil. While this relationship is highly visible for construction items such as asphalt cement (a by‐product in the process of refining oil), the effects of the crude oil prices on the cost of other construction items, such as concrete cement or construction operations are less direct, but equally important. For unit‐based contracts without price adjustment clauses, this relationship is of a particular significance. In fact, an increase in price of fuel could result in substantial losses, as contractors are not protected. Hence, to hedge against this risk, contractors are likely to incorporate a premium in bid prices to manage project risks. The objective of this paper is to investigate the evidence of this behaviour. New evidence shows that the expected change in oil prices (the difference between future and spot price) and the implied volatility in the oil market affect the price of bid items for contracts without price adjustment clauses. Such results allow for more effective implementation of risk management on project‐ and programme‐level basis.