Fuzzy Intellectual Capital Index for Construction Firms

Construction firms are now operating in a new era. Gaining and sustaining competitive advantage in this era primarily depends on effective and efficient management of knowledge assets. This paper proposes a performance evaluation model called fuzzy intellectual capital index (FICI) that can guide construction business executives to effectively and efficiently manage their knowledge assets. FICI incorporates an intellectual capital performance measurement model with fuzzy set theory to adequately handle imprecision, vagueness, and uncertainty that prevail in this process. FICI uses the fuzzy-weighted average algorithm to compute the intellectual capital performance of architectural/engineering/construction (A/E/C) firms. It is an internal reporting model that can guide executives of A/E/C firms to evaluate their firm’s ability to achieve their strategic objectives and to pinpoint their firm’s strengths and weaknesses in order to neutralize threats and to exploit opportunities presented by today’s construction business environment. A real-world case study is presented to illustrate the implementation and utility of the proposed model. Implications for practitioners and directions for future research are discussed.     

SuretyAssist: Fuzzy Expert System to Assist Surety Underwriters in Evaluating Construction Contractors for Bonding

In construction, many owners mitigate the risk of unforeseen contractor default by accepting only bonded contractors who must endure a rigorous evaluation process by surety brokers and surety underwriters. This evaluation process includes a financial analysis and a review of work on hand and past performance, all of which have reliable structured methods for their evaluation. Additionally, a number of subjective criteria are considered that are more difficult to capture and assess objectively but which can be modeled effectively using fuzzy logic. The purpose of this paper is to illustrate how fuzzy logic and expert systems can be combined to provide a structured approach to evaluating contractors for surety underwriting purposes. Fuzzy logic is used to model both the objective and subjective factors considered in contractor evaluation using linguistic terms, and expert rules are used to capture the surety experts’ reasoning process. A fuzzy expert system, SuretyAssist, is presented that can be used to provide an initial evaluation of general contractors as well as periodic reviews to determine whether or not to accept them as clients for bonding. SuretyAssist was validated using 31 actual cases of contractor evaluation and found to be accurate in 81% of the cases.     

Identification of Effective Management Practices and Technologies for Lessons Learned Programs in the Construction Industry

Organizations in the construction industry cannot afford to make repetitive mistakes on major projects. Conversely, there are great benefits to repeating positive experiences from past projects. This need for institutional memory is amplified by the reality that in the course of normal turnover and retirement, people with years of experience leave their organizations. An effective lessons learned program is a critical element in the management of institutional knowledge; it will facilitate the continuous improvement of processes and procedures and provide a direct advantage in an even more competitive industry. This paper describes a research study that aimed to identify effective management practices and technologies for lessons learned programs in the construction industry. Data from 70 organizations that participated in this study are presented. Research found that even though more lessons learned programs are being initiated, the potential for savings and improvement has not been fully met. The study has also identified seven crucial characteristics of a successful program and verified that most organizations are stronger in some categories and weaker in others. The key to an effective program is to address all seven areas and guidance is provided for those wishing to implement lessons learned programs.     

Capturing Knowledge in Construction Projects: Knowledge Platform for Contractors

Managing knowledge effectively is critical to the survival and advance of a company, especially in project-based industries such as construction. However, capturing knowledge in construction projects is a tedious task, as knowledge is usually experience based, tacit, and hard to pass on to others. In this study, a survey was carried out among eight leading Turkish construction contractors that are operating within the international construction market. The specific objectives of this survey are to find out how the tacit and explicit knowledge are captured, stored, shared, and used in forthcoming projects, as well as major drivers and barriers for knowledge management. Based on the survey, it was determined that most of these firms do not have a knowledge management strategy and a systematic way of capturing and storing tacit knowledge. A conceptual framework is proposed to formalize the knowledge-capturing process within construction companies. To demonstrate how the conceptual framework can be implemented in practice, a Web-based system, namely, Knowledge Platform for Contractors (KPfC) is presented. It is hypothesized that KPfC can be used to manage both tacit and explicit knowledge effectively in construction projects.     

Applying Concept Similarity to the Evaluation of Common Understanding in Multidisciplinary Learning

The success of an architecture, engineering, and construction (AEC) project largely depends on the effective collaboration of project participants. This characteristic of the industry requires that AEC education shall foster multidisciplinary collaboration skills of students. On the other hand, many AEC education programs have started using information and communication technologies (ICTs) to facilitate teaching and learning such as distance learning. One of the challenges in a computer-mediated learning environment arises from the need for computer systems to determine whether a common understanding regarding a certain subject is established among a group of students. To achieve this goal, ICT needs to be able to detect changes in the knowledge structure of students in order to provide better mediation. This paper presents a study on the development of a concept similarity measure that has less computational complexity than graph-based similarity analyses. The similarity measure is intended to determine the similarity of multiple knowledge structures [e.g., concept maps (CMAPs)] of students. The concept similarity measure is developed based on the feature-based method in which propositions associated with a concept are considered as features of the concept. Therefore, the similarity of concepts can be measured by comparing the propositions of the concepts. In addition, since concepts are the key component of a knowledge structure, the common understanding of students can be determined by measuring the similarity of concepts in the knowledge structure of the students. The proposed measure is evaluated by (1) comparing it with the Dice coefficient for analyzing two sets of concepts; (2) analyzing its performance in a generic case of four CMAPs; and (3) applying it to a case using “photovoltaic system” as an example. In this case, results are intuitively obvious so that calculation results can be corroborated by human judgment. Finally, the concept similarity measure is applied to derive the similarity of CMAPs in the case study. Based on the initial evaluations, this study shows that the proposed measure has demonstrated promising features for determining the similarity of multiple knowledge structures or the common understanding of students. However, when the number of knowledge structures increases, concept similarity analyses become more complicated because uncertain situations arise due to ambiguous human perception to propositions that are shared by multiple concepts. Future research is thus needed to understand and clearly define concept similarity in those situations. In addition, other studies are also identified for future research.     

Construction Engineering Process and Knowledge Requirements for Fostering Creative Design Solutions on Infrastructure Projects

Construction engineering for major infrastructure projects covers a wide range of activities to evaluate and select the techniques for assembling materials and components. Construction engineering inherently presents a very challenging opportunity for creative design, particularly on infrastructure projects. This construction engineering activity can be described as one of creating and developing workable, cost-effective, low-risk technical solutions for an array of infrastructure construction problems that must be solved from the plans and specifications stage through facility completion. The purpose of this paper is to illustrate a 10-step construction engineering process and define important knowledge requirements to foster creative design solutions using four case studies, including (1) positioning and holding a concrete bridge caisson in a 7-knot tidal current for a 4-month period; (2)?skidding a 55,000-t immersed tube tunnel element 200?m on dry land from casting site to launch site; (3)?building a major dam without the use of river diversion or on-site dewatering systems; and (4)?building underwater bridge piers without the use of conventional bottom-founded cofferdams. The creative design process was able to successfully devise a plan for solving highly technical construction challenges using a process-based approach. The key requirements of knowledge, skill, and experience necessary to perform these activities are presented to assist construction engineers in preparing for these creative opportunities.     

Exploring Problems and Undesired Effects in the Construction Development Process: The Case of a Small- to Medium-Sized Developer in Taiwan

This study explored the construction development process of an individual case to identify and summarize the problems small- to medium-sized developers could be having with such process in Taiwan. To identify the problems, the writers used a case-based approach and interviewed the chairman of one small- to medium-sized enterprise (SME). Findings derived from the interview were validated by further interviewing four members of the construction union in Taiwan, three government officials, and four managers of mortgage banks. The theory of constraints approach was used to examine the construction development process of the SME and indicate the undesirable effects that hindered it and needed immediate attention. The study results were systemized into a conceptual model for developers’ future reference to improve management of the development process and identify the root causes of problems.     

Domain Taxonomy for Construction Concepts: Toward a Formal Ontology for Construction Knowledge

With the advancement of the semantic web, the construction industry is at a stage where intelligent knowledge management systems can be used. Such systems support more effective collaboration, where virtual teams of skilled users, not software, exchange ideas, decisions, and best practice. To achieve that, there is a need to create consistent semantic representation of construction knowledge. Existing representations, in the form of classification systems and product data models, lack effective modeling of concept semantics—a fundamental requirement for human-based exchange of knowledge. Toward this objective, this paper presents a domain taxonomy that was developed as part of the e-COGNOS project. The taxonomy was developed as a first step in the establishment of domain ontology for construction. The taxonomy was developed to be process-centered and to allow for utilization of already existing classification systems (BS6100, Master Format, and UniClass, for example). The taxonomy uses seven major domains to classify construction concepts: Process, Product, Project, Actor, Resource, Technical Topics, and Systems. The taxonomy was developed and validated through extensive interaction with domain experts. The taxonomy was used to develop a prototype ontology for the construction domain including semantic relationships and axioms. The ontology was used to support several applications in semantic knowledge management as part of the e-COGNOS portal, including semantic indexing and retrieval of information and ontology-based collaborative project development.     

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.     

Development of a Methodology for Live Capture and Reuse of Project Knowledge in Construction

The efforts to share and reuse knowledge generated on construction projects are undermined mainly by the loss of important insights and knowledge due to the time lapse in capturing the knowledge, staff turnover, and people’s reluctance to share knowledge. To address this, it is crucial for knowledge to be captured “live” in a collaborative environment while the project is being executed and presented in a format that will facilitate its reuse during and after the project. This paper uses a case study approach to investigate the end-users’ requirements for a methodology for the live capture and reuse of knowledge, and the shortcomings of current practice in meeting these requirements. A methodology for the live capture and reuse of project knowledge is then presented and discussed. The methodology, which comprises a web-based knowledge base, an integrated work-flow system and a project knowledge manager as the administrator, allows project knowledge to be captured live from ongoing projects. This also incorporates mechanisms to hasten knowledge validation and the dissemination of the knowledge once it has been validated.     

Fuzzy Similarity Consensus Model for Early Alignment of Construction Project Teams on the Extent of Their Roles and Responsibilities

A fuzzy similarity consensus (FSC) model is presented for alignment of construction project owner and contractor project teams to their roles and responsibilities, identifying and reducing fundamental problems of conflicts, duplication, and gaps in roles and responsibilities as early as the project initiation stage. The model achieves its objective by incorporating consensus and quality of construction project teams in aggregating their opinions to decide on the party responsible for every standard task of a construction project. The roles and responsibilities of the owner and contractors are described to different extents using seven linguistic terms defined by triangular membership functions and constructed using a three-step Delphi approach, which allows experts to develop common understanding of the meaning of the terms by determining their overlap on a fuzzy linguistic scale. A modified similarity aggregation method (SAM) aggregates experts’ opinions in a linguistic framework using a consensus weight factor for each expert that is based on the similarity of his or her opinion relative to the other experts to ensure that the experts’ final decision is a result of common agreement. A fuzzy expert system (FES) determines an importance weight factor, representing expert quality for each expert; opinions are aggregated using this factor and the consensus weight factor. The FSC model contributes to the construction industry by solving a fundamental problem for project owners who want to identify and reduce potential conflicts between their project teams on the extent of their roles and responsibilities prior to the construction stage. Also, the FSC model provides an improvement over previous consensus-based approaches, which rely on a subjective assessment of experts’ important weights in aggregating their opinions, and it modifies the SAM to adapt it to a linguistic environment.     

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.     

Exploiting Knowledge Management: The Engineering and Construction Perspective

Construction companies have always relied on their knowledge assets to provide services to clients. In recent years the terminology “knowledge management” has been introduced. Knowledge management (KM) seeks to formalize the manner in which companies exploit their knowledge assets by harnessing organizational knowledge, promoting greater collaboration between groups with similar interests, capturing and using lessons learned on previous projects, etc. This paper investigates how major United States engineering design and construction firms are implementing knowledge management initiatives in order to identify best practice. It adopts a case study methodology to investigate companies’ strategy and implementation, people aspects, and metrics for performance. The study finds that there is a clear distinction between the knowledge management activities undertaken by large engineering design firms and those of construction firms. There is also a much greater emphasis on knowledge sharing, which is just one component of knowledge management. Moreover, some companies have specific KM initiatives while others have activities that are part of their normal business processes.     

Domain Ontology for Processes in Infrastructure and Construction

With the increasing demands for domain-wide integrated construction and infrastructure development, there is a need for developing a domain ontology to build a knowledge model that describes the multistakeholder project development process. This paper presents a domain ontology for supporting knowledge-enabled process management and coordination across various stakeholders, disciplines, and projects. The ontological model is composed of concepts, relations, and axioms. Concepts represent the “things” in the domain of interest; relations establish the interconcept links; and axioms specify the definitions of concepts and relations and constraints on their behavior and interpretation. The ontology models the most fundamental concepts in the domain in a structured, extendable, and flexible format to facilitate future evolution and extension of the ontology for representing application-specific and/or enterprise-specific knowledge. The ontology was evaluated through technical evaluation and user evaluation. User evaluation was conducted through one-to-one expert evaluation interviews.     

Organizational Culture and Knowledge Management Success at Project and Organizational Levels in Contracting Firms

This research focuses on contracting firms within the construction sector. It characterizes and evaluates the composition of organizational culture using four culture types (clan, adhocracy, market, and hierarchy), the strategic approach for knowledge flow, and the success of knowledge management (KM) systems at different hierarchical levels of contracting organizations (project and parent organization level). Responses from managers of local or overseas contracting firms operating in Hong Kong were collected using a carefully constructed questionnaire survey that was distributed through electronic mail. The organizational value is analyzed in terms of the four cultural models. Clan culture is found to be the most popular at both project and organization levels, which means that the culture of contracting firms very much depends on honest communication, respect for people, trust, and cohesive relationships. On the other hand, hierarchy culture, which focuses on stability and continuity, and analysis and control, seems to be the least favored at both levels. Another significant finding was that the two main KM strategies for knowledge flow, codification and personalization, were employed at both project and organization levels in equal proportion. This indicates that successful KM efforts at both enterprise levels utilize a hybrid and balanced approach for their knowledge flow, and that they complement each other. The findings also revealed that knowledge management system success factors emphasize the support of the management level. The results show that KM is critical and beneficial as indicated by 64% at the project and 74% at the organization level. The expectation is higher for organizations as they are the organizational memories in which experiences of past projects are archived and connected. Understanding these factors and the relationships among them has been demonstrated to be critical in order to increase the chances of success or to help with making decisions when applying KM.     

Fuzzy Reliability Analyzer: Quantitative Assessment of Risk Events in the Construction Industry Using Fuzzy Fault-Tree Analysis

Fault trees are deductive techniques constructed by taking a system failure event and deconstructing it into its root causes (basic events, gate events). Fault trees can be solved qualitatively, by determining minimal cut sets, and quantitatively, by calculating the probability of occurrence of the risk event. In conventional fault-tree analysis (FTA), the probability of occurrence for all basic events must be assessed in order to allow for quantitative fault-tree analysis. However, conducting quantitative fault-tree analysis, especially in construction projects, entails several difficulties owing to the lack of sufficient data, leading to an approximation of the probability of occurrence for some basic events. Assuming probabilities for any basic event will add further uncertainty to the analysis, resulting in a potentially questionable end result. To overcome the challenge of assessing probabilities, this paper presents a comprehensive framework in which experts can use linguistic terms rather than numerals to assess the probability of occurrence of basic events. Fuzzy arithmetic operations are used to perform quantitative fault-tree analysis. Fuzzy Reliability Analyzer (FRA) was developed to automate both qualitative and quantitative FTA. The method presented is demonstrated via a case study to quantify the probability of failure of horizontal directional drilling (HDD) in meeting project objectives. Fourteen minimal cut sets were identified and the fuzzy probability (FPro) of the top event (TE) was calculated. The proposed approach offers the advantage of allowing experts to express themselves linguistically to assess the probability of occurrence of basic events, which is more appropriate for the construction domain. In addition, the proposed method offers the risk analyst the advantage of ranking basic events according to their level of contribution to the probability of the risk event, which can help in establishing more effective risk response strategies.     

Overview of the Application of “Fuzzy Techniques” in Construction Management Research

During the last decade, “fuzzy techniques” have been increasingly applied to the research area of construction management discipline. To date, however, no paper has attempted to summarize and present a critique of the existing “fuzzy” literature. This paper, therefore, aims to comprehensively review the fuzzy literature that has been published in eight selected top quality journals from 1996 to 2005, these being Journal of Construction Engineering and Management, ASCE; Journal of Management in Engineering, ASCE; Construction Management and Economics; Engineering, Construction and Architectural Management; International Journal of Project Management; Building Research and Information; Building and Environment; and Benchmarking: An International Journal. It has been found that fuzzy research, as applied in construction management discipline in the past decade, can be divided into two broad fields, encompassing: (1) fuzzy set/fuzzy logic; and (2) hybrid fuzzy techniques, with the applications in four main categories, including: (1) decision making; (2) performance; (3) evaluation/assessment; and (4) modeling. The comprehensive review provided in this paper offers new directions for fuzzy research and its application in construction management. Based on a comprehensive literature review on the applications of fuzzy set/fuzzy logic, and hybrid fuzzy techniques in construction management research, an increasing trend of applying these techniques in construction management research is observed. Therefore, it is suggested that future research studies related to fuzzy techniques can be continuously applied to these four major categories. Fuzzy membership functions and linguistic variables in particular can be used to suit applications to solving problems encountered in the construction industry based on the nature of construction, which are widely regarded as complicated, full of uncertainties, and contingent on changing environments. Moreover, hybrid fuzzy techniques, such as neurofuzzy and fuzzy neural networks, can be more widely applied because they can better tackle some problems in construction that fuzzy set/fuzzy logic alone may not best suit. For example, neural networks are strong in pattern recognition and automatic learning while fuzzy set and fuzzy logic are strong in modeling certain uncertainties. Their combination can assist in developing models with uncertainty under some forms of pattern. Finally, an increasing trend of applying fuzzy techniques in the building science and environmental disciplines is also observed; it is believed that the application of fuzzy techniques will go beyond the construction management area into these disciplines as well.     

Case-Based Reasoning Approach to Construction Safety Hazard Identification: Adaptation and Utilization

Risk assessment, consisting of hazard identification and risk analysis, is an important process that can prevent costly incidents. However, due to operational pressures and lack of construction experience, risk assessments are frequently poorly conducted. In order to improve the quality of risk assessments in the construction industry, it is important to explore the use of artificial intelligence methods to ensure that the process is efficient and at the same time thorough. This paper describes the adaptation process of a case-based reasoning (CBR) approach for construction safety hazard identification. The CBR approach aims to utilize past knowledge in the form of past hazard identification and incident cases to improve the efficiency and quality of new hazard identification. The overall approach and retrieval mechanism are described in earlier papers. This paper is focused on the adaptation process for hazard identification. Using the proposed CBR approach, for a new work scenario (the input case), a most relevant hazard identification tree and a set of incident cases will be retrieved to facilitate hazard identification. However, not all information contained in these cases are relevant. Thus, less relevant information has to be pruned off and all the retrieved information has to be integrated into a hazard identification tree. The proposed adaptation is conducted in three steps: (1) pruning of the retrieved hazard identification tree; (2) pruning of the incident cases; and (3) insertion of incident cases into the hazard identification tree. The adaptation process is based on the calculation of similarity scores of indexes. A case study based on actual hazard identifications and incident cases is used to validate the feasibility of the proposed adaptation techniques.     

Risk Management in the Construction Industry Using Combined Fuzzy FMEA and Fuzzy AHP

Failure mode and effect analysis (FMEA) is recognized as one of the most beneficial techniques in reliability programs. FMEA is a structured technique that can help in identifying all failure modes within a system, assessing their impact, and planning for corrective actions. Although this technique has been widely used in many industries, it has some limitations. The purpose of this paper is to extend the application of FMEA to risk management in the construction industry. Fuzzy logic and fuzzy analytical hierarchy process (AHP) are used to address the limitations of traditional FMEA. In essence, this method explores the concept of fuzzy expert systems to map the relationship between impact (I), probability of occurrence (P), and detection/control (D) and the level of criticality of risk events. A case study is presented to validate the concept. The results obtained confirm the capability of fuzzy FMEA and fuzzy AHP to address several drawbacks of the traditional FMEA application. The use of this approach can support the project management team to establish corrective actions in a timely manner.