Framework for Evaluating the Performance of Engineering Consultants

The evaluation of consultant’s performance is crucial to the success of a consulting assignment especially when today’s construction projects are becoming more sophisticated, large-scale, and risky. However, since individual clients have developed their own consultant’s performance evaluation (CPE) procedures, the sharing of performance information, though desirable, may not be too meaningful as the results of evaluation could be inconsistent. There is a need to examine whether a unified framework can be derived for CPE. The aim of this paper is to improve the transparency and rigorousness of CPE through the establishment of an evaluating framework for gauging the performance of engineering consultants. In this paper, a comprehensive set of evaluation criteria is identified, and the significance of these criteria is discussed through an empirical survey. Then, a multicriteria model for evaluating the performance of engineering consultants is presented. The results indicate that once an acceptable CPE framework is devised, the performance scores can be utilized for various purposes, including monitor and control, incentive and sanction, preselection, technical assessment, and bid evaluation.     

Performance Modeling for Contractor Selection

This paper proposes a contractor selection system that incorporates the contractor’s performance prediction as one of the criteria for selection. This research was developed working with an owner organization that was interested in developing a framework for evaluating contractors for future work. A modeling framework, developed in previous research, was used to develop a conceptual model of a project that depicts a causal structure of the variables, risks, and interactions that affect a contractor’s performance for a specific project from the owner’s point of view. The conceptual model helps to identify information needed for a comprehensive evaluation; some information can be readily available from historical records, while other can be unavailable and can be replaced by estimates based on experience. Ideally, over time, the owner should collect most of the information required for future evaluations. A mathematical component of the model can generate predictions of multiple project performance outcomes for each contractor under evaluation; these predictions and a contractors’ bid prices are then used for contractor evaluation purposes.     

A Fuzzy Decision Framework for Contractor Selection

Contractor selection is the process of selecting the most appropriate contractor to deliver the project as specified so that the achievement of the best value for money is ensured. Construction clients are becoming more aware of the fact that selection of a contractor based on tender price alone is quite risky and may lead to the failure of the project in terms of time delay and poor quality standards. Evaluation of contractors based on multiple criteria is, therefore, becoming more popular. Contractor selection in a multicriteria environment is, in essence, largely dependent on the uncertainty inherent in the nature of construction projects and subjective judgment of decision makers (DMs). This paper presents a systematic procedure based on fuzzy set theory to evaluate the capability of a contractor to deliver the project as per the owner’s requirements. The notion of Shapley value is used to determine the global value or relative importance of each criterion in accomplishing the overall objective of the decision-making process. The research reported upon forms part of a larger study that aims to develop a fuzzy decision model for construction contractor selection involving investigating multiple criteria selection tendencies of construction clients, relationship among decision criteria, and construction clients’ preferences of criteria in the contractor selection process. An illustration with a bid evaluation exercise is presented to demonstrate the data requirements and the application of the method in selecting the most appropriate contractor for the project under uncertainty. The proposed model is not intended to supplant the work of decision-making teams in the contractor selection process, but rather to help them make quality evaluations of the available candidate contractors. One major advantage of the proposed method is that it makes the selection process more systematic and realistic as the use of fuzzy set theory allows the DMs to express their assessment of contractors’ performance on decision criteria in linguistic terms rather than as crisp values.     

An Ontology for Relating Features with Activities to Calculate Costs

It is the cost estimator’s task to determine how the building design influences construction costs. Estimators must recognize the design conditions that effect construction costs and adjust the project’s activities, resources, and resource productivity rates accordingly to create a cost estimate for a particular design. Current tools and methodologies help estimators to establish relationships between product and cost information to calculate quantities automatically. However, they do not provide a common vocabulary to represent estimators’ rationale for relating product and cost information. This paper presents the ontology we formalized to represent estimators’ rationale for relating features of building product models to construction activities and associated construction resources to calculate construction costs. A software prototype that implements the ontology enables estimators to generate activities that know what feature requires their execution, what resources are being used and why, and how much the activities’ execution costs. Validation studies of use of the prototype system provide evidence that the ontology enabled estimators to generate and maintain construction cost estimates more completely, consistently, and expeditiously than traditional tools.     

Tender Evaluation by Fuzzy Sets

The process of evaluating tenders is considered to be largely dependent on subjective judgment when cost is not the only criterion used. A systematic procedure based on fuzzy set theory and multicriteria modeling is proposed for the selection of bid contracts. The proposed procedure is suitable for a general tender evaluation process that may involve many decision‐making parties and noninteractive multiple criteria. Illustrative examples are given for cases involving three major criteria: cost, present bid information, and past experience of tenderers.     

The System of Objectified Judgement Analysis (SOJA). A tool in rational drug selection for formulary inclusion

Rational drug selection for formulary purposes is important. Besides rational selection criteria, other factors play a role in drug decision making, such as emotional, personal financial and even unconscious criteria. It is agreed that these factors should be excluded as much as possible in the decision making process. A model for drug decision making for formulary purposes is described, the System of Objectified Judgement Analysis (SOJA). In the SOJA method, selection criteria for a given group of drugs are prospectively defined and the extent to which each drug fulfils the requirements for each criterion is determined. Each criterion is given a relative weight, i.e. the more important a given selection criterion is considered, the higher the relative weight. Both the relative scores for each drug per selection criterion and the relative weight of each criterion are determined by a panel of experts in this field. The following selection criteria are applied in all SOJA scores: clinical efficacy, incidence and severity of adverse effects, dosage frequency, drug interactions, acquisition cost, documentation, pharmacokinetics and pharmaceutical aspects. Besides these criteria, group specific criteria are also used, such as development of resistance when a SOJA score was made for antimicrobial agents. The relative weight that is assigned to each criterion will always be a subject of discussion. Therefore, interactive software programs for use on a personal computer have been developed, in which the user of the system may enter their own personal relative weight to each selection criterion and make their own personal SOJA score. The main advantage of the SOJA method is that all nonrational selection criteria are excluded and that drug decision making is based solely on rational criteria. The use of the interactive SOJA discs makes the decision process fully transparent as it becomes clear on which criteria and weighting decisions are based. We have seen that the use of this method for drug decision making greatly aids the discussion in the formulary committee, as discussion becomes much more concrete. The SOJA method is time dependent. Documentation on most products is still increasing and the score for this criterion will therefore change continuously. New products are introduced and prices are also subject to change. To overcome the time-dependence of the SOJA method, regular updates of interactive software programs are being made, in which changes in acquisition cost, documentation or a different weighting of criteria are included, as well as newly introduced products. The possibility of changing the official acquisition cost into the actual purchasing costs for the hospital in question provides a tailor-made interactive program.     

Relative Importance of Subcontractor Selection Criteria: Evidence from Singapore

Subcontractors carry out a large portion of the work done in construction projects. Thus, selecting the right subcontractor essentially contributes to the project’s success. We designed a choice-based conjoint experiment to examine the relative importance of four criteria in the subcontractor selection process of main contractors from Singapore: price, technical know-how, quality, and cooperation. Although main contractors adopt a multicriteria selection process and perceive all four criteria to be important for their choice decision, the actual choice situation reveals that price is still by far the most important selection criterion, followed by quality, cooperation, and technical know-how. Main contractors are not willing to compromise on price but accept a lower performance of a known subcontractor on the remaining criteria.     

Discussion of Criteria for Prioritization of Predictive Maintenance of Building Fa?ades: Survey of 30 Experts

The practice of predictive maintenance depends significantly on the diagnosis of in-service performance and on the decision criteria for the selection of maintenance tasks. The definition of these criteria is limited because several actors are involved, each with their own perspectives of performance and maintenance needs. This paper discusses a set of 17 criteria to help the maintenance choice for building fa?ades, from three viewpoints: physical performance, risk, and costs. A group of experts was surveyed and 30 answers were received. Therefore, each criterion will be discussed according to the answers collected. The relative importance (using quantitative weights) and subclasses for each criterion are proposed.     

Predicting and Evaluating Construction Trades Foremen Performance: Fuzzy Logic Approach

This paper illustrates a fuzzy logic model for use in predicting and evaluating the performance of construction trades foremen. The model assists in measuring the effectiveness of a foreman, monitoring improvements in effectiveness over time, and identifying areas where a foreman requires training or mentoring to improve his/her performance. This paper also discusses the factors that affect the performance of a foreman in each area of responsibility. The structure of the model and the use of fuzzy logic are described. The model is validated using data collected from an actual construction company, illustrating its high level of linguistic accuracy. This model is relevant to researchers and makes a contribution to performance evaluation by developing a methodology for evaluating and predicting the performance of construction trades foremen. The model provides a complete approach for handling uncertainty inherent in performance evaluation by using fuzzy logic. The use of fuzzy logic in the model allows users to express themselves linguistically and to make assessments that are subjective in nature. It is relevant to construction industry practitioners since it provides them with a useful technique for evaluating the performance of foremen and identifying the factors that affect their performance on a daily basis. Last, the model offers the advantage of benchmarking foreman performance, allowing organizations to develop plans to improve the performance of their foremen over time.     

Contractor Selection Criteria: Investigation of Opinions of Singapore Construction Practitioners

The construction industry has witnessed the failure of many contractors due to varying reasons such as financial problems, poor performance, or accidents arising from the lack of adequate safety consideration at worksites. All these incidents have led to the impression that the current system of awarding the contracts is inefficient in selecting the contractor capable of meeting the demands and challenges of present times and hence needs to be reviewed accordingly. Therefore, in an attempt to investigate the current situation of the Singapore construction industry a questionnaire survey was conducted for accruing the data required to identify the important contractor selection criteria (CSC) and to draw upon construction practitioners’ opinions regarding the importance of those CSC in assessing the capabilities of the candidate contractors during the selection process. The research reported upon forms part of a larger study that aims to develop a computer-interactive multicriteria decision system for contractor selection involving identification of CSC for inclusion in the system, investigation of CSC preferences of construction practitioners, and establishment of weights for those CSC from their perceived importance determined through the questionnaire survey of Singapore construction practitioners. The study highlights that there are statistically significant differences in opinions regarding the degree of importance assigned to some CSC among public clients, private clients, and contractors. Findings from the study may act as an aid in improving the Singapore construction industry by helping construction clients identify multiple CSC apart from cost which should always be considered when assessing the capability of candidate contractors during the selection process, by assisting contractors in improving their attributes in line with clients’ preferences and by facilitating Singapore construction clients and researchers to develop a contractor selection system capable of assessing multiple attributes of the candidate contractors so that the risk of the project failure due to the selection of an inappropriate contractor is minimized.     

Software for Planning and Cost Control in Directional Drilling Projects

As the complexity and size of the projects undertaken by horizontal directional drilling (HDD) contractors rapidly increase, there is a growing need for the development of dedicated software designed to meet the industry’s special needs and requirements. This paper presents the results of a survey of the HDD industry’s software needs as well as a summary of commercially available software specifically designed for this industry. In addition, the development of two computerized applications tailored for the HDD industry are described. The first of these applications is an integrated data management system that combines asset management, cost control, estimating, and project tracking capabilities, enabling decision makers to closely monitor field performance in terms of expenditure and productivity. The second application is a simulation model developed for optimizing the utilization of drilling rigs and hydro-vacuum trucks on large-scale urban projects. Both applications are designed to improve the planning, estimating, and productivity of directional drilling projects, ultimately reducing the cost of expanding underground infrastructure networks.     

Life-Cycle Costs of Commercial Roof Systems

The roofing industry in the United States generates annual revenues in excess of $23 billion. This represents a significant annual investment in infrastructure maintenance cost and the opportunity cost of these resources can significantly detract from an owner’s ability to invest in other areas. In addition, a failed or failing roof system represents a heightened opportunity for failure in the building envelope and inherently increases the risk of additional costs. Present roof asset management practice typically bases replacement decisions on fixed intervals, inspection results, maintenance issues, and, occasionally, failure risk. This paper develops a model for evaluating occupant costs and considering their impact in the roof management decision process through a total life-cycle cost (LCC) model that includes user/occupant cost model and correlates minimum total cost with improved intervention points in the asset deterioration cycle. The model is estimated from and applied to the extensive roof systems at Carnegie Mellon University in Pittsburgh, Pa. For these roofs, we find that the least cost roof service lives are roughly 30 years, but there can be considerable variation around this average for individual roofs.     

Performance Evaluating Model for Construction Companies: Egyptian Case Study

The dynamic nature of today’s construction industry compels construction partners to seek strategies in order to improve performance. Current research introduces a performance evaluation model for construction companies in order to provide a proper tool for a company’s managers, owners, shareholders, and funding agencies to evaluate the performance of construction companies. The model developed helps a company’s management to make the right decisions. Financial, economical, and industrial data are collected from Egyptian construction companies for nine consecutive years (1992–2000). Five indices (models) are developed: company performance score, economy performance score, industry performance score, performance index, and performance grade. The models developed consider companies in four construction sectors: general building, heavy, special trade, and real estate. These models accommodate the effect of macroeconomic and industry related factors and company size on the performance evaluation. The final outcome of current research is a performance grade, which provides the performance of a construction company. The developed model is validated, which shows robust results.     

Essential carbamoyl-amino acids formed in vivo in patients with end-stage renal disease managed by continuous ambulatory peritoneal dialysis: isolation, identification, and quantitation

Drugs of various classes are prescribed for intermittent claudication. However, there is some discrepancy between medical practice and the scientific basis for drug selection. We have developed a quantitative criteria-based decision analysis to evaluate all implications of drug treatment choices for intermittent claudication. Pentoxifylline, buflomedil, naftidrofuryl and ticlopidine were the drugs selected for analysis. The evaluation criteria were 1) therapeutic efficacy, 2) safety, 3) patient acceptance and 4) cost. A review panel of experts determined the relative importance of each criterion by assigning points (or utility values) to each one. The points were 48, 20, 14 and 18, respectively, for criteria 1, 2, 3 and 4. A probability value, or numerical estimate of how well a drug meets a criterion, was assigned to each drug for each of the 4 criteria. The probability value was multiplied by the utility value to determine the score for each drug and criterion. The criteria points for each drug were added for a total score for the drug. The drug with the highest overall score was pentoxifylline, with 69 points out of an ideal score of 100. The rank order for the other drugs was buflomedil, ticlopidine and naftidrofuryl. A sensitive analysis showed that the relative ranking of the drugs remained unchanged over a series of data modifications.     

Decision Support System for Monthly Operation of Hydropower Reservoirs: A Case Study

This paper presents a decision support system for multipurpose reservoir operation. The mathematical models in the system are formulated for monthly operation of hydropower reservoirs. The key components of the system are four main modules: database management, inflow modeling and forecasting, operation management, and real-time operation. Flexibility is the key feature of the system, providing the users with different decision tools and different indices for measuring the performance of each tool. A cost function is developed based on the present value of the total capital cost and the cost of operation and maintenance of the system. This cost function, which is developed based on “reasonable” estimates of water and energy prices, is used to measure the performance of reservoir operation policies. A utility function based on multicriterion decision making (MCDM) that uses an analytical hierarchy process is also developed. The MCDM utility function enables decision makers to incorporate the priority of different objectives in developing optimal operating policies and can be effectively used when the priority of objectives is not clear and the decision-making process relies mainly on the decision maker’s preferences. Both economic and MCDM utility functions are implemented and coupled with deterministic and stochastic optimization models. The decision support system (DSS) is applied to the largest surface water resources system in Iran, namely, the Dez and Karoon river-reservoir system. The results of the case study have shown that the DSS has been able to significantly increase the long-term power generation of the system while satisfying water demands for different purposes.     

Discriminant Analysis for Predicting Ranges of Cost Variance in International Construction Projects

Unanticipated market conditions as well as project-related risks can easily lead to cost overruns in international construction projects. For a contractor to be financially successful in international projects, a careful examination of the project is a prerequisite to understanding the cost variance characteristics. Based on the reasonably accurate characterization of the cost performance, the markup or contingency amount is determined to ensure both a decent level of profit and a good chance of winning the contract. This paper presents a classification model to categorize international construction projects, particularly faced by Korean contractors, into five cost-variation classes: extreme cost overrun, moderate cost overrun, neutral, moderate cost saving, and extreme cost saving. The model is able to characterize an international project for its cost performance prediction in comparison to the contractor’s initial cost estimate. A linear discriminant analysis is utilized to develop the predictive classification model with the support of the bootstrap method. Tests show that the proposed model is able to help cost estimators determine a proper level of cost contingency before bidding on an international project.     

Contextual Information Requirements of Cost Estimators from Past Construction Projects

Past project data sources provide key information for construction cost estimators. Previous research studies show that relying only on one’s own experience during estimation results in estimators’ bias. Having and referring to historical databases, containing objective information on what happened in past projects, are essential for reducing estimators’ biases. The first step toward development of useful project history databases is to understand what information estimators require from past projects. The research described in this paper targets estimators’ information needs identified through interviews, brainstorming sessions, task analyses, and card games conducted with estimators with different experience levels and specialized in heavy/civil and commercial construction projects, and exploration of historical and standard databases available in companies to determine what is being currently represented. Findings show that estimators need contextual information, depicting the conditions under which specific production rates were achieved, so that they can identify which production rate would be more realistic to use during the production rate estimation of an activity in a new bid. Comparison of the contextual information needs identified in this research with information items available in historical data sources (such as company cost reports, RSMeans, previous studies) highlighted some gaps and important opportunities for improvements in those sources. The identified contextual information items are significant for practitioners in developing ways to augment their existing project history databases to make them more beneficial for estimators.     

Hybrid Models of Neural Networks and Genetic Algorithms for Predicting Preliminary Cost Estimates

This technical note applies hybrid models of neural networks (NN) and genetic algorithms (GA) to cost estimation of residential buildings to predict preliminary cost estimates. Data used in the study are for residential buildings constructed from 1997 to 2000 in Seoul, Korea. These are used in training each model and evaluating its performance. The models applied were Model I, which determines each parameter of a back-propagation network by a trial-and-error process; Model II, which determines each parameter of a back-propagation network by GAs; and Model III, which trains weights of NNs using genetic algorithms. The research revealed that optimizing each parameter of back-propagation networks using GAs is most effective in estimating the preliminary costs of residential buildings. Therefore, GAs may help estimators overcome the problem of the lack of adequate rules for determining the parameters of NNs.     

Contractor Performance Prediction Model for the United Kingdom Construction Contractor: Study of Logistic Regression Approach

An accurate prediction of contractor potential is of vital importance during contractor selection and evaluation process. Such prediction enables identification and classification of contractor performance to ease the selection process. This paper outlines the use of clients' tender evaluation preferences for predicting a contractor performance via a logistic regression (LR) approach. A total of 31 clients’ tender evaluation criteria were selected to develop a LR model for predicting contractor performance. The proposed model was developed based on 48 of United Kingdom public and private construction projects and validated in 20 independent cases. It was found that 75% of the cases correctly and the model statistically accurate for contractor performance prediction, where the input variables consist of nominal and interval data. The paper summarized techniques and advantages of LR analysis and discussed literature findings of contractor selection and evaluation methodologies undertaken by construction researchers and commentators from the United Kingdom and Northern America.