A Performance-Based Integrated System for the Assessment of Project Procurement Departments of Construction Companies

Abstract

Numerous hypotheses in the literature claim that there must be some correlations among the attributes of different types of entities such as project, organization, decision makers, etc., and performance of other entities such as sectors, companies, projects, operations, individuals etc. Project procurement departments of construction companies seem to be one of the most important entities to be investigated for this matter since their performance is vital for the companies’ survival. This study is currently being conducted as one of the sub-projects of the master project entitled “SIMURG: A performance-based and Sustainability-oriented Integration Model Using Relational database architecture to increase Global competitiveness of Turkish construction industry in industry 4.0 era. The master project was designed to include research and development of related models at all hierarchical levels of performance-based design and construction of built environment approach with open-ended approach in various sub-projects in two complementary areas, i.e., product and process dimensions. The hierarchical levels of these dimensions are a. building components, b. building elements, c. building premises, d. buildings, e. projects, f. lands, g. quarters, h. settlements, i. counties and j. cities levels on product side and a. operations, b. projects, c. departments, d. firms, e. groups of firms, f. sectors, g. national economies, and h. global economy levels on process side. Each levels need their own level-specific Key Performance Indicators (KPIs) and associated weights to be determined in addition to organisational, computational and computer models to be designed. In this study the conceptual and practical models of performance-based evaluation system at departments level have been developed to solve above stated problem in “project procurement” context. SIMURG_PERISCOPE, the relational database model developed in this PhD thesis for performance-based evaluation of the related department is enriched by additional functions and reports to be able to investigate these relationships among these entities and risk factors.