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Fuzzy Agent–Based Modeling of Competency and Performance Measures in Construction.

Authors :
Gebretekle, Yisshak Tadesse
Fayek, Aminah Robinson
Source :
Journal of Construction Engineering & Management. Dec2023, Vol. 149 Issue 12, p1-12. 12p.
Publication Year :
2023

Abstract

Construction organizations are project-based organizations in which both competencies and performance develop through project execution. A competency measure is a combination of knowledge, skill, processes, practices, and/or technology possessed by a construction organization. Performance measures are used to assess an organization's competitiveness within its industry. An organization can analyze competencies to predict and improve performance. Previous studies investigated project- and organization-level competencies with respect to performance measures. However, multilevel assessment is needed, although it is challenging because the nature of construction competency and performance measures is complex, dynamic, and subjectively uncertain. To address these challenges, this paper presents a methodology for developing a fuzzy agent–based model (FABM) of competency and performance that models a set of organizational- and project-level competency measures as decision-making entities (i.e., agents) and predicts multiple performance measures as their emergent behavior. A case study was implemented to demonstrate, verify, and validate the proposed FABM model, with encouraging results in performance prediction. The academic contribution of this paper is providing a novel systematic, bottom-up modeling approach for measuring and assessing competencies at the project and organization levels and mapping these multilevel competencies to construction performance measures. Furthermore, the outcomes of this study are expected to support construction practitioners by providing a set of comprehensive hierarchical competency and performance metrics at the project and organization levels for managerial actions taken to identify, construct, and develop competency models to assess performance at both levels. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
*FUZZY logic

Details

Language :
English
ISSN :
07339364
Volume :
149
Issue :
12
Database :
Academic Search Index
Journal :
Journal of Construction Engineering & Management
Publication Type :
Academic Journal
Accession number :
173009094
Full Text :
https://doi.org/10.1061/JCEMD4.COENG-13672