Fuzzy Uncertainty analysis of NIOC ComponentsUsing Rough Set Theory

There are various effective components in the NationalIranian Oil Company (NIOC) that encounter uncertainty indata collection, analysis, and output. The technology andinnovation levels of the company can be deemed crucial in itsfuture success based on these components. We employed therough set theory (RST) approach in this work to analyze theuncertainty in these parameters, as we had done in earlierstudies. Rough gives the ideal conditions for communicatingambiguity and making sound decisions. The rough set has beendeveloped into the six categories of infrastructure, technology,scientific research, management, legal, and human resources asa result of this research, and the priority of the categories fordecision making has been decided by identifying theapproximate number. According to the findings of this study,the scientific-research category has the highest degree ofuncertainty among the six categories considered in the effectivefactors, while the infrastructure and management classes havenearly the same conditions in the next rank, and the legal classhas the lowest degree of uncertainty. Furthermore, the RSTclusters reveal management's difficulty in exploiting thecompany's resources, as well as an imbalanced development oftechnology, infrastructure, and human resources. Changingresearch techniques, establishing appropriate researchorganizations, developing technical and inventive infrastructure,and changing management attitudes toward innovation andknowledge development are some of the most significantstrategies to explore .