Data envelopment analysis for performance measurement in the construction field: a systematic review

Purpose-This paper systematically presents a critical review of data envelopment analysis (DEA) for performance measurement in the construction field. Design/methodology/approach-The review approach consists of a systematic literature search, validation analysis and content analysis. The paper systematically reviews previous papers according to the year of publication, journal, authors, region, research keywords, performance measurement indicators and methodology framework. Findings-A total of 192 journal papers from the first year of publication to 2022 are identified. DEA applications have increased over the years, particularly after 2020. All of the top five journals which published the most identified papers are Q1 journals. Around 74 primary indicators of performance measurement are recognised for the construction industry, company and project levels. A total of 21 top keywords are identified and then divided into five clusters using VOSviewer. DEA has been widely utilised to measure construction performance and benchmark technologies, particularly where sustainable development performance has become a popular topic recently. Practical implications-How to effectively distinguish performance indicators, collect research data, build DEA models and deeply analyse DEA results are illustrated for future practitioners. The performance measurement and improvement cycle based on DEA is provided. Research directions and method recommendations are developed for future scholars using DEA. Originality/value-This is the first comprehensive review that has initially presented various performance indicators and a methodology framework for developing DEA models to investigate performance measurement in the construction field. The methodology framework of DEA is developed, including data collection, model construction and further analysis of DEA results.