The weight fuzzy judgment method for benchmarking sustainability of oil companies

In today’s complicated world, decision-making has become significantly more difficult, especially as it relates to evaluating oil companies. Multi-criteria decision-making (MCDM) techniques have become more common in recent years because they offer a systematic approach to weighting criteria in the assessment process. However, classical MCDM techniques have problems related to inconsistency because of the subjective nature of pairwise comparison. The purpose of this study is to develop an MCDM model. The weight fuzzy judgment method (WFJM) can determine the weight coefficients of criteria with zero consistency. This new method combines both criteria values and expert judgment for decision-making; thus, it can be considered halfway between the mathematical approach and the human approach. The five phases of the WFJM method include an input unit containing exploration and definition, normalization technique determination, selecting experts and forms for evaluation, filling up data transformation, and applying a fuzzy membership function to compute the final weight. 9 main criteria and 11 alternative integrations with VIKOR and evaluation statistics have been presented in a case study to determine the effectiveness of the proposed approach WFJM. As the outcomes showed, WFJM had managed to cope with the problem related to inconsistency and provide stable weight values for each criterion while shortening the time spent on making decisions. In addition, the results of this study indicate that the proposed method is more effective and precise than the traditional MCDM approach. Moreover, results from the correlation analysis revealed that it was 72% in two scenarios only, and others were at a count of 98%. In summary, the WFJM technique is a unique approach to solving complicated decision-making problems, and its influence can be significant. Furthermore, this method can be applied in other sectors besides energy, including banking, medical services, and engineering, where decision-making is not straightforward and requires a systematic approach.

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