Open Access

ARTICLE

Investigation of the Severity of Modular Construction Adoption Barriers with Large-Scale Group Decision Making in an Organization from Internal and External Stakeholder Perspectives

Muzi Li^*

Department of Civil Engineering, University of Southern California, Los Angeles, 90007, USA

* Corresponding Author: Muzi Li. Email:

(This article belongs to this Special Issue: AI and Machine Learning Modeling in Civil and Building Engineering)

Computer Modeling in Engineering & Sciences 2023, 137(3), 2465-2493. https://doi.org/10.32604/cmes.2023.026827

Received 27 September 2022; Accepted 07 March 2023; Issue published 03 August 2023

Abstract

Modular construction as an innovative method aids the construction industry in transforming to off-site construction production with high efficiency and environmental friendliness. Despite the obvious advantages, the uptake of modular construction is not booming as expected. However, previous studies have investigated and summarized the barriers to the adoption of modular construction. In this research, a Large-Scale Group Decision Making (LSGDM)- based analysis is first made of the severity of barriers to modular construction adoption from the perspective of construction stakeholders. In addition, the Technology-Organization-Environment (TOE) framework is utilized to identify the barriers based on three contexts (technology, organization, and environment). The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and LSGDM models are both implemented for the first time to analyze the severity of the barriers to modular adoption based on questionnaire results from internal and external stakeholders in an organization. Finally, in this research, in-depth insights into the severity of barriers are gained, providing a reference for construction organizations to manage modular adoption.

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Keywords

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