Investigating the effect of risk reduction strategies on the construction of mega infrastructure project (MIP) success: a SEM-ANN approach
Engineering, Construction and Architectural Management
ISSN: 0969-9988
Article publication date: 4 August 2023
Issue publication date: 10 September 2024
Abstract
Purpose
Managing mega infrastructure projects (MIPs) is more complex because of time, size, social, environmental and financial implications. This study aims to address the management approaches, complexity and risk factors involved in MIPs. The study focuses on project success criteria and their individual effects on the success of MIPs.
Design/methodology/approach
To address the challenges and identify the most influencing factor for the success of MIPs, the study deployed a cross-sectional survey approach. Six hundred eighty-two usable samples were collected from the respondents to understand the impact of predetermined factors on the success of MIPs. The structural equation model and artificial neural network approach were used to derive the importance of factors affecting the success of MIPs.
Findings
The study's outcome confirms that all three influencing factors: feasibility studies, community engagements and contract selection, have a significant positive impact on the success of MIPs. Community engagement amongst all three has the most influential predictor for the success of MIPs.
Originality/value
The developed model will enable practitioners and policymakers from Indian construction companies and other emerging nations to concentrate on recognized risk reduction variables to enhance project success criteria and project management success, especially for MIPs.
Keywords
Citation
Malek, M.S. and Bhatt, V. (2024), "Investigating the effect of risk reduction strategies on the construction of mega infrastructure project (MIP) success: a SEM-ANN approach", Engineering, Construction and Architectural Management, Vol. 31 No. 9, pp. 3575-3598. https://doi.org/10.1108/ECAM-12-2022-1166
Publisher
:Emerald Publishing Limited
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