Cryptocurrency mining in developing economies operates under intertwined economic, institutional, energy, and technological uncertainties, making strategic planning difficult for both policymakers and industry participants. This study investigates and prioritizes the factors shaping the sustainability of cryptocurrency mining in developing Middle Eastern economies. A structured decision framework combining the Delphi method with fuzzy pivot pairwise relative criteria importance assessment (PIPRECIA) was applied. Nineteen factors grouped into economic, governance, and information technology dimensions were identified from the literature and evaluated by 11 experts with experience in cryptocurrency-related projects. The Delphi process was used to validate the selected factors, while fuzzy PIPRECIA was employed to determine their relative importance under uncertain expert judgments. The results showed that unclear laws and regulations ranked first, with a final weight of 0.1335, followed by cryptocurrency market volatility at 0.1074 and energy costs at 0.0994. Monetary instability, inflation, cybersecurity threats, banking constraints, and international sanctions also received substantial weights. Economic factors were ranked above governance and information technology factors, indicating that access to technical infrastructure alone did not ensure sustainable mining operations. The findings demonstrate that the viability of cryptocurrency mining in developing Middle Eastern economies depends primarily on regulatory predictability, macroeconomic stability, energy-pricing conditions, and access to secure financial channels. The proposed framework provides a structured basis for strategic policy formulation, investment assessment, and resource allocation in cryptocurrency mining environments characterized by institutional and market uncertainty.
Efficient logistics processes are essential to the operational performance of process-industry companies, where material receipt, warehousing, and internal distribution are closely connected with production continuity. However, evaluating these processes remains difficult because logistics performance depends on multiple criteria with different levels of importance, while conventional assessments often provide limited information about the relative efficiency of individual logistics units. This study investigates the efficiency of logistics activities through an integrated decision-analytics framework combining the Full Consistency Method (FUCOM) and Data Envelopment Analysis (DEA). FUCOM was used to determine the relative importance of the evaluation criteria, and DEA was applied to measure the technical efficiency of the logistics units. The framework was examined through a case study of the Modriča Oil Refinery, covering material receipt, warehousing, and the internal distribution of products to production facilities. The results showed clear differences in efficiency among the analyzed logistics segments and identified the processes that represented critical points within the logistics system. The sensitivity analysis further confirmed the stability of the evaluation results under changes in the criteria weights. These findings indicate that combining criterion weighting with efficiency measurement provides a structured basis for identifying operational weaknesses and setting improvement priorities. The proposed framework supports data-informed logistics decisions in the process industry and can be adapted to comparable industrial settings involving interconnected logistics activities.
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