Fuzzy Approach to Prequalifying Construction Contractors

Construction contractor prequalification (CCPQ) is a crucial decision making process to select capable potential bidders and ensure the success of construction projects. The purpose of CCPQ is to guarantee a contractor’s characteristic to meet the construction project’s requirements, which has been established worldwide as a standard practice. However, existing methods, i.e., marking method, subjective judgment method, etc., for contractor prequalification have been inadequate because it is difficult for decision makers to investigate contractor’s capabilities against inexact, vagueness, and qualitative criteria. The objective of this paper is to propose a fuzzy framework-based fuzzy number theory to solve construction contractor prequalification issues, which include decision criteria analysis, weights assessment, and decision model development. Finally, a case study for a tunnel construction project was used to demonstrate the feasibility of fuzzy approaches.     

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.     

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.     

Efficacy of Using Support Vector Machine in a Contractor Prequalification Decision Model

Contractor prequalification is basically a nonlinear two-group classification problem. A robust contractor prequalification decision model should include the ability of handling both quantitative and qualitative data. Support vector machine (SVM) is a set of related supervised learning methods which can handle data in a high dimensional feature space for nonlinear separable problems. A new contractor prequalification decision model using SVM is proposed to assist clients to identify qualified contractors for tendering in this study. A case study was used to validate the proposed decision model and the classification ability was compared with neural networks (NNs) and principal component analysis (PCA). The results show that the proposed SVM model outperforms NN and PCA and the merits of using SVM to mitigate the limitations of using NN are elaborated. The proposed decision model is an ideal alternative for supporting clients to perform contractor prequalification decision making.     

Fuzzy Preference Relations Consensus Approach to Reduce Conflicts on Shared Responsibilities in the Owner Managing Contractor Delivery System

This paper proposes a fuzzy preference relations consensus (FPRC) approach that helps owners and contractors reach consensus on their responsibilities and reduce conflicts in shared tasks. A fuzzy similarity consensus (FSC) model was developed to aggregate experts’ opinions on roles and responsibilities in the owner managing contractor (OMC) project delivery system. The FSC model categorized 324 generic OMC tasks into three responsibility task lists: owner, contractor, and shared. In a consensus-reaching process, the FPRC approach is applied to shared tasks, where expert opinions on responsibility conflict are expressed, to achieve an aggregated responsibility decision for each task. Experts compare the three responsibility alternatives in pairs by using linguistic preferences, defined on a fuzzy preference scale, to select a preferred responsibility alternative for each of the conflicting tasks. A computed linguistic consensus degree guides the experts on their level of consensus in every round of the process. The quality of experts is defined with a fuzzy expert system–determined importance weight factor for each expert. The FPRC approach is relevant to the construction industry, as it incorporates consistency in decision making by allowing experts to measure and reach an adequate level of consensus linguistically when deciding on responsibilities. The proposed approach provides a method of reducing conflicts in the assignment of task responsibility between the owner and its contractors as early as the project initiation phase; thus, the project teams can concentrate on the work to be done rather than deal with responsibility conflicts during project execution.     

Evolutionary Fuzzy Neural Inference System for Decision Making in Geotechnical Engineering

Problems in geotechnical engineering are full of uncertain, vague, and incomplete information. In most instances, successfully solving such problems depends on experts’ knowledge and experience. The primary object of this research was to develop an evolutionary fuzzy neural inference system (EFNIS) to imitate the decision-making processes in the human brain in order to facilitate geotechnical expert decision making. First, an evolutionary fuzzy neural inference model (EFNIM) was constructed by combining the genetic algorithm (GA), fuzzy logic (FL), and neural network (NN). In the proposed model, GA is primarily concerned with optimizing parameters required in the fuzzy neural network; FL with imprecision and approximate reasoning; and NN with learning and curve fitting. This research then integrates the EFNIM with an object-oriented computer technique to develop an EFNIS. Finally, the potential to apply the proposed system to practical geotechnical decision making is validated using two real problems, namely estimating slurry wall duration and selecting retaining wall construction methods.     

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.     

Contractor’s Risk Attitudes in the Selection of International Construction Projects

International construction involves all of the uncertainties common to domestic construction projects as well as risks specific to international transactions. Consequently, despite the worldwide trend toward globalization, a very small portion of contractors actively seek international contracts due to concerns of probable failures. This paper describes findings from experiments done to investigate the risk attitude and bid decision behavior in the selection of international projects. The participants demonstrated either weak risk seeking in profit situations or strong risk seeking toward loss situations when choosing between conflicting options of risky opportunities and sure payoffs. On the other hand, another experimental test attempting to investigate bid behavior when making a realistic bid or no-bid decision in a complicated international construction project reveals the prevailing risk aversion. Further, this paper finds the experimental supports for some of the errors and biases due to risk attitude that commonly exist in bid decisions in this area. Finally, we present lessons learned and guidelines to make a qualified bid decision through feedback with the participants.     

Owner–Contractor Work Structures: Process Approach

This paper describes a process to assist project managers, within owner companies, define work relationships between owners and their contractors for capital project development, and execution. The owner–contractor work structure process was developed by the Construction Industry Institute as a step-by-step process for making rational decisions about the most appropriate owner–contractor work structure for capital projects. A work structure is described by a set of project competencies and the extent of involvement of the owner and contractor in performing, leading, and/or providing input with respect to those project competencies. The process is described using a formal process modeling technique. Three case studies, conducted to validate the owner–contractor work structure process, are discussed. The results from these case studies suggested some basic changes to the process that would enhance its use in practice. A modified owner–contractor work structure process is then presented.     

Impact of Shift Work on Labor Productivity for Labor Intensive Contractor

Generally, a contractor has three options in accelerating a construction schedule: working longer hours, increasing the number of workers, or creating an additional shift of workers. There has been a significant amount of research conducted on scheduled overtime on construction labor productivity. However, little information has been found in the literature addressing the labor inefficiency associated with working a second shift. This paper has qualitative and quantitative components. The qualitative part details why and how shift work affects labor productivity, and then addresses the appropriate use of shift work. The quantitative component determines the relationship between the length of shift work and labor efficiency. The results of the research show that shift work has the potential to be both beneficial and detrimental to the productivity of construction labor. Small amounts of well-organized shift work can serve as a very effective response to schedule compression. The productivity loss, obtained from the quantification model developed through this study, ranges from ?11 to 17% depending on the amount of shift work used.     

Web-Based Client Advisory Decision Support System for Design–Builder Prequalification

The design–build procurement route is gaining popularity and being extensively used by many clients. Scrutinizing the capabilities of design–build “candidate” organizations (who submit proposals for prequalification/short listing), is a complex task that demands the evaluation of several quantitative and qualitative attributes. The crucial task of design–builder prequalification needs multidisciplinary expertise that often poses tough challenges to many construction clients. A Hong Kong based cross-sectional research study of various international clients’ design–builder selection approaches unveiled several selection strategies and criteria used; and benchmarked some best practices. Based on such consolidated knowledge, a structured design–builder selection model was developed. The conceptualized frameworks for design–builder prequalification are described in this paper. An overview of the development and preliminary validation of a prototype web-based decision support system for design–builder prequalification is also presented in this paper.     

Quality-Based Contractor Rating Model for Qualification and Bidding Purposes

A quality contractor on every construction project would make project management simpler for Department of Transportation (DOT) project engineers and strategic planning more accurate for DOT executives. A qualification model that includes the quality of a contractor’s past work would be invaluable in assuring that each project had a quality contractor. Including the quality of past work in the bidding process would further help in this goal. Implementation of such a model for both its potential uses would require business process reengineering for the DOT in two important areas: qualification of contractors and contract award procedures. The research team has produced an innovative model, called the Quality-Based Performance Rating (QBPR) system. This model receives inputs from traditional subjective sources and integrates them with totally objective data input from the results of tests of the project’s materials and workmanship, then uses these inputs to produce a score for each project that is further used by the system to generate an index for each contractor reflecting that contractor’s quality of work over a specified time frame.     

Fuzzy Decision-Making Tool for Environmental Sustainable Buildings

Several alternatives are being attempted to obtain the sustainable residential building, based on the acceptable level of environmental impact and socio-economic characteristics of residential building. These criteria are in conflict each other, thus it is very difficult to assess or find the sustainable residential building. This paper presents a methodology of the assessment for residential building that is intended to assist the decision making for the building planners or practitioners. The results show that this approach can effectively work for the quantitative evaluation and selection of the best alternative of the residential buildings considered, especially when conflict relation exists. This approach allows the planner or construction companies to test design strategies against different sets of criteria.     

Guarantees for Contractor’s Performance and Owner’s Payment in China

This paper first analyzes the problem of default risk that contractors and owners often face in China, then stresses that establishing a construction contract guarantee system is a necessary and effective measure for solving this problem. Policy choice for establishing a construction contract guarantee system in China is presented in this paper by using the experience of developed countries for reference and taking Chinese domestic circumstances into account. Further discussion is included about how to protect contractors from default of payment of owners by exercising the right of legal mortgage in accordance with Chinese contract law.     

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.     

Exploring Factors for Ethical Decision Making: Views from Construction Professionals

The construction industry has experienced malpractice, which is a significant cause for concern. Does the nature of the industry provide some hint for tracing the underlying reasons of the relatively severe ethical problems in construction? Can one of the most influential stakeholders in the industry, the professionals, improve the situation? This study was conducted in Hong Kong to investigate what kinds of ethical problems are faced by construction professionals, and to explore the factors influencing their ethical decision making. Statistical factor analyses identified six intuitive underlying factors that affect ethical decision making when construction professionals are facing ethical dilemmas in the industry. Four of them influencing decision making are “deontological factor,” “consequential factor—egoism,” “consequential factor—utilitarianism,” and “legal requirement.” Two other factors are “oneself/family” and “stakeholders.” Results show that construction professionals’ ethical behavior is guided by legal requirements. When making ethical decisions, they adopt an egoism approach that prioritizes their self-interest and their families’ interests higher than the public’s interest; they would consciously evaluate the consequences of any unethical behavior.     

Managing Owner’s Risk of Contractor Default

The objective of the study presented in this paper is to provide owners with a decision-making mechanism that will free them from automatically taking the typical “transfer the risk to a surety” option and will allow them to make intelligent and economical decisions that include retaining or avoiding the risk of contractor default. The methodology involves using artificial neural network (ANN) and a genetic algorithm (GA) training strategies to predict the risk of contractor default. Prediction rates of 75 and 88% were obtained with the ANN and GA training strategies, respectively. The model is of relevance to owners because once the likelihood of contractor default is predicted and the owner’s risk behavior is established, the owner can make a decision to retain, transfer, or avoid the risk of contractor default. It is of relevance to surety companies too as it may speed up the process of bonding and of reaching more reliable and objective bond/not bond decisions. The comparative use of the ANN and GA training strategies is of particular relevance to researchers.     

Decisions in Construction Operations

A method for selecting the most desirable construction strategy is proposed in this paper. A decision analysis framework is developed considering the information on relative risk, along with the information on cost, benefit, and consequences of each construction strategy. Many factors affect the safety of construction operations. Labor skill, supervisors' experience and attendance, condition of falsework, weather conditions, type of equipment, level of operator's experience, etc., may be considered as the main factors that affect the safety of construction operations. From an engineering point of view, these factors are always desirable to be in their best states. However, it may not be practical in many cases due to time and money constraints. Consequently, the risk of failure and cost of construction operations, and the consequences of failure need to be estimated in order to decide about the optimum construction strategy. The decision problem is complicated since the state of the factors are generally expressed in linguistic terms. The theory of fuzzy sets is used to translate these terms into mathematical measures and to estimate the risk of failure. The proposed method is illustrated with the help of an example.     

Site Layout Planning using Nonstructural Fuzzy Decision Support System

Site layout planning can affect productivity and is crucial to project success. However, as construction is heterogeneous in the nature of its organizations, project designs, time constraints, environmental effects, etc., site layout planning for each project becomes unique. Affected by many uncertainties (variables) and variations, site layout planning is a typical multiobjective problem. To facilitate the decision-making process for these problems, a nonstructural fuzzy decision support system (NSFDSS) is proposed. NSFDSS integrates both experts’ judgment and computer decision modeling, making it suitable for the appraisal of complicated construction problems. The system allows assessments based on pairwise comparisons of alternatives using semantic operators that can provide a reliable assessment result even under the condition of insufficient precise information.     

Web-based Centralized Multiclient Cooperative Contractor Registration System

Despite perceived industry needs for developing a centralized contractor registration (CCR) system, such a system is still to be developed for a multiclient environment such as Hong Kong. A major barrier is that such a CCR system must be relatively easy to access to ensure that (i) contractors’ information is constantly updated (by contractors), (ii) contractors’ performance is reported promptly (by project teams and occupiers), and (iii) the latest analyzed information is available to any authorized clients anytime anywhere. A centralized multiclient cooperative contractor registration (CMCCR) system is proposed using web-based technology, which provides a powerful communication medium with a high potential for satisfying the above requirements. The conceptual framework of the proposed CMCCR system is presented, and the concept is illustrated through a prototype based on information collected in Hong Kong. The initial observations indicate that web-based technology is suitable for the proposed CMCCR system, and that the development of a fully functional web-based CMCCR is both feasible and useful.