Knowledge-based DSS for construction contractor prescreening

Taha, Mahmoud A.; Park, Sang C.; Russell, Jeffrey S.

doi:10.1016/0377-2217(94)00316-5

Cited by 8 publications

(4 citation statements)

References 15 publications

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“…Different knowledge-based systems were developed for multifarious applied functions such as construction planning (Shaked and Warszawski 1995), construction-site organization (Sauce and Mommessin 1995), contractor pre-screening (Taha et al 1995), contractor proposal evaluation (Kuprenas and Madjidi 1996), and decision-making support (Shalomygin et al 1999). Expert knowledge base and information technology supported these systems.…”

Section: Major Topicsmentioning

confidence: 99%

Knowledge Management Research in the Construction Industry: a Review

Yang

2016

J Knowl Econ

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Knowledge management (KM) is important to the knowledge-intensive construction industry. The diversified and changing nature of works in this field warrants us to stocktake, identify changes, and map out KM research framework for future exploration. The study involves three aspects. First, three stages of KM research in construction were distinguished in terms of the time distribution of 217 target publications. Major topics in the stages were extracted for understanding the changes of research emphasis from evolutionary perspective. Second, the past works were summed up in a three-dimensional research framework in terms of management organization, managerial methodology and approach, and managerial objective. Finally, potential research orientations in the future were predicted to expand the existing research framework. It was found that (1) KM research has significantly blossomed in the last two decades with a great potential; (2) major topics of KM were changing in terms of technology, technique, organization, attribute of knowledge, and research objectives; (3) past KM studies centred around management organization, managerial methodology and approach, and managerial objective, thus a threedimensional research framework was proposed; (4) within the research framework, team-level, project-level, and firm-level KM were studied to achieve project, organizational, and competitive objectives by integrated methodologies of information technology, social technique, and KM process tool; and (5) nine potential research orientations were predicted corresponding to the three dimensions. Finally, an expanded J Knowl Econ research framework was proposed to encourage and guide future research works in this field. The paper only focused on the construction industry. The findings need further exploration in order to discover any possible missing important research works which were not published in English or not included in the time period. The paper formed a systematic framework of KM research in construction and predicted the potential research orientations. It provides much value for the researchers who want to understand the past and the future of global KM research in the construction industry.

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Section: Major Topicsmentioning

confidence: 99%

Knowledge Management Research in the Construction Industry: a Review

Yang

2016

J Knowl Econ

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“…(1990) developed a rule‐based ES called ‘QUALIFIER‐2’ for contractor pre‐qualification. Ng (1993) developed an integrated object oriented ES for contractor pre‐qualification, whilst Taha et al . (1995) proposed a knowledge‐based DSS for predicting construction contract bond claims using contractor financial data.…”

Section: Knowledge Acquisitionmentioning

confidence: 99%

Addressing the contractor selection problem using an evidential reasoning approach

Sönmez¹,

Yang²,

Holt³

2001

Eng Const Arch Manage

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Selecting the ‘best’ main contractor is a complex decision process for construction clients. It requires a large number of criteria to be simultaneously measured and evaluated. Many of these criteria are related to one another in a complex way and therefore, they very often conflict insofar as improvement in one often results in decline of another(s). Furthermore, as contractors’ attributes are expressed in both quantitative and qualitative terms, decision‐makers have to base their judgements on both quantitative data and experiential subjective assessments. In this paper, the evidential reasoning (ER) approach (which is capable of processing both quantitative and qualitative measures) is applied as a means of solving the contractor selection problem (CSP). The process of building a multiple criteria decision model of a hierarchical structure is presented, in which both quantitative and qualitative information is represented in a unified manner. The CSP is then fully investigated using the ER approach. Both the advantages of applying this model in practice and the analysis process itself are discussed.

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“…Russell et al (1990) developed a rule-based ES called 'QUALIFIER-2' for contractor pre-qualification. Ng (1993) developed an integrated object oriented ES for contractor pre-qualification, whilst Taha et al (1995) proposed a knowledge-based DSS for predicting construction contract bond claims using contractor financial data. This DSS employed inductive learning and neural networks to extract the problem solving knowledge.…”

Section: Literature Review On Contractor Selectionmentioning

confidence: 99%

Addressing the contractor selection problem using an evidential reasoning approach

Sönmez

Yang

Holt

2001

Engineering, Construction and Architectural Management

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Selecting the ‘best’ main contractor is a complex decision process for construction clients. It requires a large number of criteria to be simultaneously measured and evaluated. Many of these criteria are related to one another in a complex way and therefore, they very often conflict insofar as improvement in one often results in decline of another(s). Furthermore, as contractors' attributes are expressed in both quantitative and qualitative terms, decision‐makers have to base their judgements on both quantitative data and experiential subjective assessments. In this paper, the evidential reasoning (ER) approach (which is capable of processing both quantitative and qualitative measures) is applied as a means of solving the contractor selection problem (CSP). The process of building a multiple criteria decision model of a hierarchical structure is presented, in which both quantitative and qualitative information is represented in a unified manner. The CSP is then fully investigated using the ER approach. Both the advantages of applying this model in practice and the analysis process itself are discussed.

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Knowledge-based DSS for construction contractor prescreening

Cited by 8 publications

References 15 publications

Knowledge Management Research in the Construction Industry: a Review

Knowledge Management Research in the Construction Industry: a Review

Addressing the contractor selection problem using an evidential reasoning approach

Addressing the contractor selection problem using an evidential reasoning approach

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