Assessing blockchain technology adoption in the Norwegian oil and gas industry using Bayesian Best Worst Method
Date of Original Version
Despite the promising features of blockchain, such as enhancing efficiency, transparency, immutability, cost savings, and traceability, the technology is still not widely adopted across industries. The oil and gas industry uses state-of-the-art engineering solutions for oil and gas exploration but substantially lags behind in using innovative digital technologies that can improve operational excellence. This study proposes a multi-criteria decision-making (MCDM) framework for assessing blockchain adoption strategies. The framework builds on critical factors for blockchain adoption and four adoption strategies — single use, localization, substitution, and transformation. Data were collected from ten experts in the Norwegian oil and gas industry using a structured web survey. The Bayesian Best Worst Method (BWM), a probabilistic MCDM method, was used for analysis. The results suggest that three sub-criteria, which are lack of expertise about technology, lack of supply chain partner collaboration, and reducing operation cost, have the most impact on the adoption process. As for blockchain adoption alternatives, the fourth phase, that is, transformation, is the most preferred in the context of the Norwegian oil and gas industry. The proposed framework lays the foundation for companies to understand the critical elements that need improvement to accelerate the blockchain technology adoption process.
Journal of Industrial Information Integration
Munim, Ziaul Haque, Srinivasan Balasubramaniyan, Mahtab Kouhizadeh, and Niamat Ullah Ibne Hossain. "Assessing blockchain technology adoption in the Norwegian oil and gas industry using Bayesian Best Worst Method." Journal of Industrial Information Integration 28, (2022). doi:10.1016/j.jii.2022.100346.