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This paper aims to propose a new blockchain system design to improve engineering, procurement and construction (EPC) companies’ supply chain for constructing oil and gas infrastructure, by mitigating cost and time inefficiencies.

A case study analyses the supply chain of a sample EPC company. First, a literature review is conducted to explore the subject in academic literature. Second, information flows are mapped using responsible, accountable, consulted and informed analysis and cross-functional process mapping. Third, inefficiencies are identified. Fourth, the root causes of the inefficiencies are pinpointed using fishbone and five-times-why analysis. Fifth, a comparison is made between the linear and the blockchain information system via force-field analysis. Sixth, a specific blockchain system design is identified based on three external expert interviews. Finally, the new system is designed and a cost-benefit analysis is conducted.

Major cost and time inefficiencies in oil and gas infrastructure developments are caused by a poor information flow in the supply chain. The new blockchain system design is a feasible solution, reducing cost inefficiencies by 12.4% and operation lead-times by 36.5%.

The confidentiality of the sample EPC company’s information represents a limitation.

The research introduces a new blockchain system design, reducing cost and time inefficiencies in the project-development supply chain, including implementation processes.

In the study, a five-dimensional-safety risk assessment model (5D-SRAM) is developed to improve the construction safety risk assessment approaches available in the literature. To that purpose, a hybrid multi-dimensional fuzzy-based model is proposed, which provides a comprehensive ranking system for the safety risks existing in a project by considering the contextualization of the construction-related activities resulting in an accident.

The developed 5D-SRAM is based on an amalgamation of different fuzzy-based techniques. Through the proposed fuzzy analytic hierarchy process (AHP) method, the importance weights of essential risk dimensions playing role in defining the magnitude of the construction-related risks are obtained, while a precise prioritized ranking system for the identified safety risks is acquired using the proposed fuzzy technique of order preference similarity to the ideal solution (FTOPSIS).

Through the application of the proposed 5D-SRAM to a real-life case study – which is the case of green building construction projects located in Hong Kong – contributions are realized as follows: (1) determination of a more complete range of risk dimensions, (2) calculation of importance weightings for each risk dimension and (3) obtainment of a precise and inclusive ranking system for safety risks. Additionally, the supremacy of the developed 5D-SRAM against the other safety assessment approaches that are commonly adopted in the construction industry is proved.

The developed 5D-SRAM provides the concerned safety decision-makers with not only all the crucial dimensions that play roles toward the magnitude of safety risks posing threats to the workers involved in construction activities, but also they are given hindsight regarding the importance weights of these dimensions. Additionally, the concerned parties are embellished with the final ranking of safety risks in a more comprehensive way than those of existing assessment methods, leading to sagacious adoption of future prudent strategies for dealing with such risks occurring on construction sites.

Numerous studies have documented the safety risks faced by construction workers including proposals for risk assessment models. However, the dimensions considered by such models are limited, generally constrained to risk event probability combined with risk impact severity. Overlooking other dimensions that are essential towards the calculation of safety risks' magnitude culminates in overshadowing the further adoption of fruitful mitigative actions. To overcome this shortcoming, this study proposes a novel 5D-SRAM.