Contingency Estimation Research Articles

Analyzing Contingency Estimation for Residential Turnkey Projects in Saudi Arabia: A Neural Network Approach

Utilizing a turnkey approach to deliver a construction project entails significant risks from the contractor’s perspective. Essentially, the owner awaits project completion without commitments regarding additional expenditures incurred by the contractor during the project’s duration. This paper specifically focuses on estimating and analyzing the contingency value for residential turnkey projects in Saudi Arabia. The contingency value across the project’s life cycle is estimated using six Artificial Neural Network (ANN) models, which are compared to identify the best-trained network according to project complexity, contingency factor, and contingency impact during the project phases. The output layer provides the contingency factor percentages for each project phase. A 13-story reinforced concrete (RC) residential building established in one of Saudi Arabia’s cities was selected to implement the developed methodology. The contingency estimation, performed using @Risk 7.5 and NeuralTools 7.5, was determined to be 11.34% and was distributed across the five phases of the project’s life cycle: 0.30% for predesign, 0.99% for design, 2.61% for preconstruction, 6.33% for construction, and 1.12% for postconstruction. Furthermore, it was found that the estimated contingency varies based on project complexity, which is 7.20% for low complexity, 8.16% for medium complexity, 9.41% for complicated, and 11.34% for very complicated projects. Historical data and peer review approaches are employed to validate the results, both of which are endorsed by professionals in this field. This paper highlights two main contributions: Firstly, it significantly enhances risk management by facilitating a comprehensive understanding and systematic analysis of risks, thus improving the contractors’ ability to mitigate potential negative impacts on projects. Secondly, it supports more informed decision-making through the use of advanced techniques to estimate and analyze contingency values. These contributions are critical for contractors engaged in Saudi construction projects, particularly those involving residential buildings.

Smart heuristics for decision-making in the ‘wild’: Navigating cost uncertainty in the construction of large-scale transport projects

Statistical approaches such as Reference Class Forecasting and Monte Carlo Simulation are widely used to estimate the cost contingency of large-scale transport projects (>$500 million) to mitigate cost overruns during construction. Such approaches may accommodate exposure to risk, but they will fall short in the face of the irreducible uncertainty that confronts project delivery. An underused alternative for formulating a cost contingency is smart heuristics (i.e. simple task-specific decision strategies), which are superior to statistical reasoning under Knightian uncertainty. We set forth an agenda for research on building and using an ‘adaptive toolbox’ of ecologically rational heuristics that decision-makers can apply to produce more accurate contingency estimates for large-scale transport projects. We identify several methodological considerations to support the adaptation and discovery of new heuristics for decision-makers to navigate judgments under uncertainty during the contingency estimation process. The implications for research, policy, and practice are also identified. The contributions of our paper are twofold as we: (1) provide a platform for challenging the effectiveness of the prevailing convention of using statistical reasoning to estimate a project’s cost uncertainty; and (2) identify an avenue for testing existing and discovering new heuristics that can assist decision-making in projects.

Project Phase–Based Contingency Adjustment Framework for Infrastructure Renewal Projects

Given the importance of accurate contingency estimation to properly absorb cost fluctuations, there have been enormous efforts to identify risk factors and measure contingency in roadway projects. However, no study has proposed a contingency framework that reflects the linkage effects of factors through the project phases. To this end, this research develops a project phase-based contingency adjustment framework using a path analysis drawing on a dataset of 1,053 rehabilitation, reconstruction, and resurfacing (3R) roadway projects in Florida. In particular, our framework incorporates the sequential effects of factors through the lenses of project phases from planning and bidding and contract to construction and completion. The developed path model shows that individual factors may have direct and/or indirect impacts on project costs. The results of this study can be applied to better contingency and cost estimation and proper risk management in the preconstruction phases of roadway renewal projects.

Reliable Time Contingency Estimation Based on Adaptive Neuro-Fuzzy Inference System in Construction Projects

Reliable Time Contingency Estimation Based on Adaptive Neuro-Fuzzy Inference System in Construction Projects

Estimating Project Cost under Uncertainty Using Universal Generating Function Method

AbstractOne of the important issues in project management is cost contingency estimation. Although this has been investigated in previous studies, the underlying assumptions on presuming specific p...

Cost Contingency Estimation in Public Projects in the Construction Digitalisation Era: A Case of Vietnam

Construction projects, in nature, are complex and dynamic, therefore, when estimating the project budget, there should be a budget set aside, called “contingency” for dealing with changes in the project internally and externally. This paper, used a case study of a public hospital in Vietnam, discussed the estimation of cost contingencies in the preliminary feasibility study and feasibility study stages. Cost contingencies estimation using the construction investment rates have low accuracy, therefore, have been adjusted and re-allocated through out the stages. Additional data is needed for improving the accuracy of the contingency estimation. This approach is facilitated in the construction digitalisation era, especially with the issuance of Circular 12/2019/TT-BXD guiding the development and management of the systems of databases on cost norms, prices and price indexes. Historical data can increase the accuracy of the estimation of costs for construction consultancy services, including BIM services, which are currently estimated by predefined rates based on construction and equipment costs.

Risk quantification using fuzzy-based Monte Carlo simulation

Estimating cost contingency of construction projects depends largely on data captured from previous projects and/or experience and judgment of members of project team. Mote Carlo simulation is commonly used in estimating contingency, where its accuracy was reported to depend on number of iterations used in the simulation process, probability density functions associated with each project cost item being considered and the correlation among these cost items. The literature reveals that the latter is the most important issue for accurate estimate of contingency. It, however, requires the calculation of coefficients of correlation among cost items based on captured historical records of cost data. Subjective correlation was introduced to alleviate the difficulties associated with the calculation of these coefficients. This paper presents a newly developed method for cost contingency estimation that considers subjective correlations and allows for contingency estimation with and without computer simulation. Unlike the methods reported in the literature, the present method considers uncertainty associated with the coefficients of correlation and utilizes earlier work of the first author in calculating the variance of total project cost. It also allows for assessing the impact of variable covariance matrix on the estimated project cost using a simple and user-friendly computational platform. The application of the developed method on cost data captured from two databases demonstrates its use and accuracy in estimating cost contingency. The results are compared to those produced by others using Monte Carlo Simulation with and without correlation using an actual project data.

Appraisal of risk contingency planning for construction projects

Risk contingency plan in a construction project allows for flexibility and effective responses to change orders and unforeseen risks arising at the construction phase of projects. A poor risk contingency allowance can result in cost overrun on a project as well as time overrun. However, a good risk contingency plan can be tailored based on the previous similar projects while taking into consideration the individuality of that particular project. The aim of the study is to review risk contingency planning for construction projects. Secondary data was used in carrying out this research study. Extant literatures were reviewed carefully for proper understanding of the methods used in carrying out risk contingency estimation, the importance of risk contingency to construction projects, the categories of risk contingency plans and the factors affecting the accuracy of risk contingency for construction projects. The study revealed and concluded that risk contingency serves as the extra budget that caters for uncertainties which can lead to cost overrun on construction projects thereby affecting the accuracy of the preliminary estimate. It was recommended that risk evaluation must be done appropriately at the planning phase of the construction project, so that the estimator can have more information necessary to factor into the estimation process thereby increasing the accuracy of the estimate prepared.

Dams, dam costs and damnable cost overruns

Major restructuring including commercialisation of the water authorities in Australia during the past several decades has resulted in the loss of much valuable information on dam infrastructure costs. This paper sets out to provide an Australian perspective on dam costs and dam cost overruns, examine patterns of dam costs and cost overruns, and develop a good predictor of costs and cost overruns for the Australian situation.Several cost metrics, dam costs and related data, were collated for 98 dams constructed across Australia since 1888. Dam costs, operation and maintenance (O&M) costs, and construction overrun costs were related to independent variables including dam site terrain characteristics and catchment and climate attributes. Each metric was related through multiple regression to mainly physical and climate attributes associated with the dam. Multiple correlation coefficients account for between 50% and 80% of the variance in the dependent variable. The exceedance range (defined as 75% exceedance to 25% exceedance) of final dam costs (2016 AUD) (98 dams) is from $393 per ML of reservoir storage to $2040 per ML. Annual O&M costs (33 dams), expressed as a % of final dam cost, varies from 0.14% to 0.35%, though these O&M costs do not include major upgrades. The results of this study of Australian dams are in keeping with international studies that have found the estimated costs of large infrastructure projects are systematically biased downwards. In this study the median and mean cost overruns (40 dams), expressed as a percentage of the dam cost estimated immediately prior to construction, are 49% and 120% respectively with the smallest and largest cost overrun values being −48% and 825% respectively. Based on the available data dam cost overruns appear to be more prevalent in sedimentary rock than hard rock (e.g. igneous and metamorphic rocks) settings. The strong likelihood of dam cost overruns occurring has implications to forecasted benefit-cost ratios, and supports assertions that large dam cost and contingency estimates should be checked at pre-feasibility and feasibility stages by an independent organisation and by persons highly experienced in dam design, construction and costing.

Predicting Cost Escalation Pathways and Deviation Severities of Infrastructure Projects Using Risk‐Based Econometric Models and Monte Carlo Simulation

AbstractIn the past decade, infrastructure‐related legislation in the United States has consistently emphasized the need to measure the variation associated with infrastructure project cost estimates. Such cost variability is best viewed from the perspective of the project development phases and how the project cost estimate changes as it evolves across these phases. The article first identifies a few gaps in the cost overrun literature. Then it introduces a methodology that uses risk‐based multinomial models and Monte Carlo simulation involving random draws to predict the probability that a project will follow a particular cost escalation pathway across its development phases and that it will incur a given level of cost deviation severity. The article then uses historical data to demonstrate how infrastructure agencies could apply the proposed methodology. Statistical models are developed to estimate the probability that a highway project will follow any specific cost escalation pathway and ultimately, a given direction and severity of cost deviation. The case study results provided some interesting insights. For a given highway functional class, larger project sizes are associated with lower probability of underestimating the final cost; however, such a trend is not exhibited by very large projects (total cost exceeding $30M). For a given project size, higher class roads were generally observed to have a lower probability of underestimating the final cost, compared to lower class roads and this gap in probability narrows as the project size increases. It was determined that a project's most likely pathway of cost escalation is not a guarantee that it will yield any particular direction of cost deviation. The case study results also confirmed the findings of a few past studies that the probabilities of cost escalation pathways and the cost overruns differ significantly across highway districts, and attributed this to differences in administrative culture and work practices across the districts. Infrastructure managers can use the developed methodology to identify which projects are likely to experience a particular pathway of cost escalation, the direction and severity of cost deviation, and to develop more realistic project contingency estimates.

CHOOSING AN APPROPRIATE CONTINGENCY SUM ESTIMATING METHODS FOR HIGHWAY CONSTRUCTION PROJECTS IN NIGERIA: A LITERATURE REVIEW

In order to establish a gap to be filled in a particular field, there is a need to gather information that allows the researcher to identify and analyse the current state of researches on the topic. Contingency sum estimation for projects plays an important role for inclusion for risk taken by the contractor on the bid amount. This is good in order to meet project objectives (cost, time, quality, health and safety, and environment). The main function of contingency sum is to cater forvariations that arise during the construction phase of projects. The aim of the study is to identifying and examine the various methods for estimating contingency sum for projects with a view to propose an appropriate method which will be suitable for a specific project in order to increase accuracy and reduce cost overrun. A literature review of selected papers (journals, conference proceedings and theses) on contingency estimation was carried out. The major findings from this study is that most studies were carried out on building projects while few were carried out on highway projects. From the analysis carried out, no single method of estimating has been effective for all types of projects. These methods of estimating contingency sums have developed over the years as a result of shortcomings of one method after the other. It is therefore recommended that peculiarity of each project, ease of using each of the methods and accuracy of the estimates needed should be the basis of choosing method of estimating contingency sum.

CHOOSING AN APPROPRIATE CONTINGENCY SUM ESTIMATING METHODS FOR HIGHWAY CONSTRUCTION PROJECTS IN NIGERIA: A LITERATURE REVIEW

In order to establish a gap to be filled in a particular field, there is a need to gather information that allows the researcher to identify and analyse the current state of researches on the topic. Contingency sum estimation for projects plays an important role for inclusion for risk taken by the contractor on the bid amount. This is good in order to meet project objectives (cost, time, quality, health and safety, and environment). The main function of contingency sum is to cater forvariations that arise during the construction phase of projects. The aim of the study is to identifying and examine the various methods for estimating contingency sum for projects with a view to propose an appropriate method which will be suitable for a specific project in order to increase accuracy and reduce cost overrun. A literature review of selected papers (journals, conference proceedings and theses) on contingency estimation was carried out. The major findings from this study is that most studies were carried out on building projects while few were carried out on highway projects. From the analysis carried out, no single method of estimating has been effective for all types of projects. These methods of estimating contingency sums have developed over the years as a result of shortcomings of one method after the other. It is therefore recommended that peculiarity of each project, ease of using each of the methods and accuracy of the estimates needed should be the basis of choosing method of estimating contingency sum.

Statistical numeracy as a moderator of (pseudo)contingency effects on decision behavior

Pseudocontingencies denote contingency estimates inferred from base rates rather than from cell frequencies. We examined the role of statistical numeracy for effects of such fallible but adaptive inferences on choice behavior. In Experiment 1, we provided information on single observations as well as on base rates and tracked participants' eye movements. In Experiment 2, we manipulated the availability of information on cell frequencies and base rates between conditions. Our results demonstrate that a focus on base rates rather than cell frequencies benefits pseudocontingency effects. Learners who are more proficient in (conditional) probability calculation prefer to rely on cell frequencies in order to judge contingencies, though, as was evident from their gaze behavior. If cell frequencies are available in summarized format, they may infer the true contingency between options and outcomes. Otherwise, however, even highly numerate learners are susceptible to pseudocontingency effects.

An N-k Analytic Method of Composite Generation and Transmission with Interval Load

N-k contingency estimation plays a very important role in the operation and expansion planning of power systems, the method of which is traditionally based on heuristic screening. This paper stringently analyzes the best and worst states of power systems given the uncertainties of N-k contingency and interval load. For the sake of simplification and tractable computation, an approximate direct current (DC) power flow model was used. Rigorous optimization models were established for identifying the worst and best scenarios considering the contingencies of generators and transmission lines together with their uncertain loads. It is very useful to identify the worst N-k contingencies with interval loads. If the worst existing scenario meets security standards, all scenarios must satisfy it. The mathematical model established for finding the worst N-k contingency with interval load is a bi-level optimization model. In this paper, strong duality theory and mathematical linearization were applied to the solution of bi-level optimization. The computational results of standard cases validate the effectiveness of the proposed method and illustrate that generator contingency has more impact on minimum load shedding than transmission line contingency.

A systems view of mother-infant face-to-face communication.

Principles of a dynamic, dyadic systems view of mother-infant face-to-face communication, which considers self- and interactive processes in relation to one another, were tested. The process of interaction across time in a large low-risk community sample at infant age 4 months was examined. Split-screen videotape was coded on a 1-s time base for communication modalities of attention, affect, orientation, touch, and composite facial-visual engagement. Time-series approaches generated self- and interactive contingency estimates in each modality. Evidence supporting the following principles was obtained: (a) Significant moment-to-moment predictability within each partner (self-contingency) and between the partners (interactive contingency) characterizes mother-infant communication. (b) Interactive contingency is organized by a bidirectional, but asymmetrical, process: Maternal contingent coordination with infant is higher than infant contingent coordination with mother. (c) Self-contingency organizes communication to a far greater extent than interactive contingency. (d) Self- and interactive contingency processes are not separate; each affects the other in communication modalities of facial affect, facial-visual engagement, and orientation. Each person's self-organization exists in a dynamic, homoeostatic (negative feedback) balance with the degree to which the person coordinates with the partner. For example, those individuals who are less facially stable are likely to coordinate more strongly with the partner's facial affect and vice versa. Our findings support the concept that the dyad is a fundamental unit of analysis in the investigation of early interaction. Moreover, an individual's self-contingency is influenced by the way the individual coordinates with the partner. Our results imply that it is not appropriate to conceptualize interactive processes without simultaneously accounting for dynamically interrelated self-organizing processes.

Hedgehogs vs. Foxes: Improving the Accuracy of Predictions

From the PFC Technical Director, a discussion of oil forcasting by use of aggregative contingent estimation.

The relative accuracy and interpretability of five sequential analysis methods: A simulation study.

A variety of sequential analysis methods exist to quantify close temporal associations between events from direct observation data. In the present study, we compared the relative accuracy and interpretability of five sequential-analysis methods using simulated data. The methods included three existing approaches (event lag, concurrent interval, and time window) and two proposed modifications of the event lag approach (event lag with contiguous pauses and event lag with noncontiguous pauses) designed to address limitations of the existing approaches. We evaluated accuracy on the basis of the extent to which the mean contingency estimates produced by each method approximated a known mean (i.e., zero). We evaluated interpretability on the basis of the extent to which the contingency estimates produced by each method were independent from chance estimates of the two-event sequence. The results indicated that the event lag with contiguous pauses method produced the most accurate and interpretable estimates of contingency. This modified method prevents the total number of event types from influencing contingency estimates, thus solving a problem associated with the traditional event lag method.

The computer-based contingency estimation through analysis cost overrun risk of public construction project

The causes of contract change at the construction phase can become the main risk factor which was not accurately understood or was unexpected leading to the increase in the direct and/or indirect costs. Therefore the contingency is necessary to swiftly handle and respond to such occasion However, when it comes to estimating contingency, it is difficult to respond to risks arising variously depending on the nature of the project. This is because the assessment method is based on lump-sum ratio application. To address such problems, the final contingency estimation system has been established using contingency estimation modeling based on the analysis on the current contract change status and on the results of identification and analysis of cost overrun risk. To verify the usability of the constructed system, case study has been performed targeting risk management experts. As a result of case application, it was possible to provide the information on the relevant project in advance, to derive the cost overrun factors, to identify the risk factors in detail, and thus to understand the nature of project by analyzing the contract change status in public construction projects. Furthermore, this method is differentiated from the traditional lump-sum ratio application because the accuracy of risk analysis improved by using 3 input variables instead of single variable and by putting risk analysis methods together (importance analysis+ fuzzy theory).

DEVELOPING A TOOL FOR PROJECT CONTINGENCY ESTIMATION IN A LARGE PORTFOLIO OF CONSTRUCTION PROJECTS

To enable the management of project-related risk on a portfolio level in an owner organisation, project contingency estimation should be performed consistently and objectively. This article discusses the development of a contingency estimation tool for a large portfolio that contains similar construction projects. The purpose of developing this tool is to decrease the influence of subjectivity on contingency estimation methods throughout the project life cycle, thereby enabling consistent reflection on project risk at the portfolio level. Our research contribution is the delivery of a hybrid tool that incorporates both neural network modelling of systemic risks and expected value analysis of project-specific risks. The neural network is trained using historical project data, supported by data obtained from interviews with project managers. Expected value analysis is achieved in a risk register format employing a binomial distribution to estimate the number of risks expected. By following this approach, the contingency estimation tool can be used without expert knowledge of project risk management. In addition, this approach can provide contingency cost and duration output on a project level, and it contains both systemic and project-specific risks in a single tool.

A comparison of fuzzy logic and multiple regression analysis models in determining contingency in international construction projects

Purpose – The main objective of this paper is to show how fuzzy logic and multiple regression analysis (MRA) techniques can be used by construction companies for determining the size of contingency that will be included in bid prices for international construction projects in a more systematic way and to compare their modelling performances. Design/methodology/approach – The steps followed in the execution of this study mainly consists of: conducting a literature review on international construction in order to identify the factors that may affect contingency amounts that will be included in bid prices for international construction projects; developing the general framework of the proposed contingency estimation model; designing a questionnaire based on the information gathered from the literature review, delivering these questionnaires to construction experts, and obtaining the actual data of 36 international construction projects; developing a fuzzy logic model based on expert judgments and three multi...