Improving Risk Assessment for Transporting Dangerous Goods through European Road Tunnels: A Delphi Study

Kalogeraki, Marianna; Antoniou, Fani

doi:10.3390/systems9040080

Cited by 8 publications

(3 citation statements)

References 28 publications

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“…In addition to Delphi's characteristics of cyclic feedback, anonymity, ability to maximize the variety of expert opinions, and collegiate analysis of expert input, Delphi framework was adopted due to its efficacy as a consensus-making approach widely used in risk factor identification within different fields such as transportation, healthcare, energy, construction, supply chain, and product development [65][66][67].…”

Section: Delphi Methods For Risk Identification By Expertsmentioning

confidence: 99%

Investigating Risks to the Implementation of the Great Equatorial Landbridge (GELB) Highway Project across Africa

Kazungu,

Sharifi

2023

Sustainability

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Transboundary Trade Corridors (TTC) are becoming increasingly important for achieving national, regional, and global development objectives. However, the cross-boundary nature of these projects involves dealing with diverse contexts that span across different countries and involve multiple stakeholders with varying interests. These circumstances exacerbate the risks and uncertainties that arise during their implementation, intensifying the challenges involved in making decisions about how to proceed with their execution. Insufficient evaluations of development projects have been identified as a contributing factor to unforeseen risks, which in turn can result in the underperformance and failure of transportation infrastructure projects. This ultimately acts as an impediment to achieving sustainable development goals. Further, rapid deployment of post risk-event corrective measures can exacerbate, for instance, macro-economic crisis and civil unrest. The Great Equatorial Land Bridge is a TTC planned to traverse five countries: Cameroon, Central African Republic, South-Sudan, Ethiopia, and Kenya. Despite the anticipated advantages for globalization, political cooperation, and regional integration, the risks that must be addressed to successfully implement this project are still uncertain. We, therefore, use a Multicriteria Decision-Making (MCDM) framework to investigate risks to its successful implementation. The analysis results highlight that effectively managing economic, political, and geographic risks is crucial for the successful implementation of the project. Policy-makers, contractors and multiple stakeholders will benefit from this study’s depiction of the risks and their relative importance. Results can also inform actions toward sustainable development of the project.

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Section: Delphi Methods For Risk Identification By Expertsmentioning

confidence: 99%

Investigating Risks to the Implementation of the Great Equatorial Landbridge (GELB) Highway Project across Africa

Kazungu,

Sharifi

2023

Sustainability

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“…The studies investigated construction site accidents in the USA, Australia, In the national universities' postgraduate research repositories, at least 262 Greek research efforts were found that identified factors contributing to accidents in construction during the past 20 years [50]. The aim of most of these studies was to evaluate the importance of the identified factors contributing to accidents based on collected data from questionnaire surveys or actual accident statistics [6,19,26] or to develop risk analysis models for specific case studies [51,52]. As numerous studies exist providing lists of factors leading to accidents in the Greek construction industry and their rankings, the issue is regarded to have attained sufficient readiness to undergo rigorous meta-analysis to highlight their common results.…”

Section: Introductionmentioning

confidence: 99%

Should We Depend on Expert Opinion or Statistics? A Meta-Analysis of Accident-Contributing Factors in Construction

Antoniou,

Agrafioti,

Aretoulis

2024

Buildings

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International research overflows with studies looking into the causes of construction accidents. Hundreds of studies by postgraduate students in the past 20 years focus on identifying and assessing risks contributing to accidents on Greek construction workplace sites. Many base their work on results from questionnaire surveys that collect the opinions of construction site professionals or on the analysis of data from actual accident records or statistics. Consequently, this study seeks to determine if the data source leads to differing conclusions by using two techniques to synthesize individual results and rank the accident-contributing factors investigated in the original studies. The first utilizes their relative importance index (RII) values, and the second uses their overall ranking index (ORI) to execute meta-analyses. The professional opinion concludes that factors related to operative behavior are the most significant accident-contributing factors. At the same time, actual accident statistics point to site risk factors of the construction process itself as the most important, indicating that expert opinion of Greek professionals should be considered in conjunction with data from actual accident records to provide the focus points for mitigation and assurance of safe construction sites in Greece.

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“…Construction projects always differ from manufacturing initiatives. Consequently, there are always risks and unknowns when estimating building costs [1][2][3]. Cost projection is additionally made difficult by the absence of a trustworthy database of building costs, as well as the contractors' reluctance to supply accurate cost information.…”

Section: Introductionmentioning

confidence: 99%

A Final Cost Estimating Model for Building Renovation Projects

Papadimitriou,

Aretoulis

2024

Buildings

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The construction sector in Greece has been developing radically in the field of building renovations. The foremost problem for projects in the building construction industry is producing an accurate and reliable cost estimate at the onset of construction. The artificial neural network (AΝΝ) approach, using data available at the early stages of the project, can help resolve or prevent any kind of difficulty that could make the successful completion of a building less likely. ANNs have been highly efficient in gaining results which could prevent the failure of building constructions projects. The ultimate goal is to highlight the usefulness of the adoption of ANNs models to predict the final cost of a building renovation project. Thus, construction companies could avoid financial failure, provided that the gap between cost prediction and final cost for renovation projects is minimized. This paper presents an artificial neural network (ANN) approach for predicting renovation costs in Greek construction projects. The study, based on a comprehensive literature review and real renovation data from construction companies, employs IBM SPSS Statistics software to build, train, and test the ANN model. The model, which uses initial cost, estimated time, and initial demolition cost as inputs, is based on the radial basis function procedure. The model presents high performance with up to 2% sum of squares error and near zero relative error, demonstrating the ANN’s effectiveness in estimating total renovation costs.

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Improving Risk Assessment for Transporting Dangerous Goods through European Road Tunnels: A Delphi Study

Cited by 8 publications

References 28 publications

Investigating Risks to the Implementation of the Great Equatorial Landbridge (GELB) Highway Project across Africa

Investigating Risks to the Implementation of the Great Equatorial Landbridge (GELB) Highway Project across Africa

Should We Depend on Expert Opinion or Statistics? A Meta-Analysis of Accident-Contributing Factors in Construction

A Final Cost Estimating Model for Building Renovation Projects

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