Exploring Cost Variability and Risk Management Optimization in Natural Disaster Prevention Projects

Jin Ho Cho, Young Su Shin, Jae June Kim, Byung Soo Kim

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The purpose of this study is to analyze the causes of cost variation in natural disaster prevention projects (NDPPs) in Gyeongsangbuk-do, South Korea, and develop tailored cost and risk management strategies. Utilizing a binary logistic regression model, this research uniquely focuses on the Gyeongsangbuk-do region, gathering data from 244 stakeholders through an online survey. The study identifies critical variables influencing cost deviation, including project management risk (PMR), project costing and execution risk (PCER), project execution strategy risk (PESR), construction project risk (CPR), project cost and schedule risk (PCSR), project management challenges (PMCs), and construction project subcontractor and safety management (CPSSM). Significant findings revealed PMR (OR = 3.744, 95% C.I. [1.657, 8.457]), PCER (OR = 5.068, 95% C.I. [2.236, 11.484]), and PESR (OR = 3.447, 95% C.I. [1.853, 6.413]) as the primary causes of cost deviation, alongside the notable impacts of other factors such as CPSSM. The developed predictive model is instrumental for NDPP stakeholders in Gyeongsangbuk-do, providing advanced risk management capabilities and aiding in effective preventive measures. This study not only corroborates theoretical hypotheses from previous research but also offers new insights into cost deviation causes in NDPPs, thereby enhancing strategic decision-making and advancing risk management perspectives.

Original languageEnglish
Article number391
JournalBuildings
Volume14
Issue number2
DOIs
StatePublished - Feb 2024

Keywords

  • binary logistic regression
  • cost deviation
  • natural disaster prevention projects
  • project management optimization
  • risk management strategy

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