Supplier Performance Evaluation in Construction Projects: Challenges and Possible Solutions

Research output: Contribution to journalArticleScientificpeer-review

Details

Original languageEnglish
Article number04019007
Number of pages13
JournalJOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT: ASCE
Volume145
Issue number4
Publication statusPublished - 1 Apr 2019
MoE publication typeA1 Journal article-refereed

Researchers

Research units

  • University of Queensland

Abstract

Supplier performance analysis can enlighten a construction company about improvement possibilities for better project outcomes. However, for systematic evaluation of a supplier across projects, changing the operating environment between projects should be addressed. Therefore, we first elaborate how supplier evaluation is challenged due to differences between projects in three characteristic groups: project product and location characteristics, project organization characteristics, and buyer-supplier transaction characteristics. We next discuss the possibility of applying data envelopment analysis (DEA) for supplier evaluation in construction, and argue how changing the operating environment can lead to nonhomogenous decision-making units in DEA. Building on these, we propose the process for supplier evaluation in the presence of a changing operating environment and different input-output profiles. Characteristics of 12 projects and supplier evaluations in 44 projects are used to illustrate evaluation challenges. The research extends current knowledge on supplier evaluation in construction by underlining how changing the operating environment across projects challenges systematic performance evaluation and by suggesting the process which further research could develop toward practical applications. (C) 2019 American Society of Civil Engineers.

    Research areas

  • Supplier evaluation, Construction projects, Data envelopment analysis, Changing operating environment, Nonhomogenous decision-making units, DEA, INDUSTRY, BENCHMARKING, ENVIRONMENT, DATA ENVELOPMENT ANALYSIS, DECISION-MAKING UNITS, MODELS, PRODUCTIVITY, EFFICIENCY, DARK SIDE

ID: 31538670