Key BIM Adoption Drivers to Improve Performance of Infrastructure Projects in the Ethiopian Construction Sector: A Structural Equation Modeling Approach

Solomon Belay, James Goedert, Asregedew Woldesenbet, Saeed Rokooei, José Matos, Hélder Sousa

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The aim of this paper is to explore the critical BIM adoption drivers across the Ethiopian public infrastructure construction sector. In this regard, a comprehensive systematic literature review was employed to identify potential BIM implementation attributes in developing countries and validated through a pilot test. Then, quantitative data was collected from experts working in various organizations using a structured questionnaire survey. A structural equation model was then developed based on five key BIM adoption constructs and 14 adoption drivers. Based on the path analysis, Application, Environment, and Project related factors positively affect BIM adoption in infrastructure projects, whereas Organization and Information Management are insignificant and negatively affect BIM adoption in the Ethiopian construction industry. The study highlighted key BIM adoption attributes that are helpful to enhance the overall project management performance in infrastructure projects. The proposed action plan is beneficial to various professionals, government, and stakeholders in an effort to improve the current level of BIM uptake in the horn of Africa. More so, the findings of this paper can be used to facilitate and promote BIM adoption in public infrastructure construction projects across the Ethiopian construction market.

Original languageEnglish (US)
Article number7473176
JournalAdvances in Civil Engineering
Volume2021
DOIs
StatePublished - 2021

ASJC Scopus subject areas

  • Civil and Structural Engineering

Fingerprint

Dive into the research topics of 'Key BIM Adoption Drivers to Improve Performance of Infrastructure Projects in the Ethiopian Construction Sector: A Structural Equation Modeling Approach'. Together they form a unique fingerprint.

Cite this