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The aim of this research is to find and prioritize a multicriteria performance measurement based on the balanced scorecard (BSC) for oil and gas (O & G) companies in an uncertain environment using the hesitant fuzzy best-worst method (HFBWM). The O & G industry has a key role in the economies of many countries. Hence, the evaluation of the performance of the O & G industry plays an important role. We utilize BSC for this purpose, which usually considers the financial, customer-oriented, internal, learning-oriented, and growth perspectives. In our research, the social responsibility perspective will be added. After finding multiple performance measurements, many companies cannot implement all of them because of limited resources. Therefore, multicriteria decision-making (MCDM) methods can be applied for prioritizing and selecting the most important measurement criteria. One of the MCDM methods is the best-worst method (BWM). This approach has several advantages compared to other MCDM methods. Due to uncertainties in decision-making, a suitable method for decision-making in an uncertain environment is necessary. Hesitant fuzzy approaches are applied as one such uncertainty-based method in this research. Our results indicate that among the five perspectives of BSC that we considered, the customer and internal process perspectives are the most important ones, and the cost of the R & D indicator is the most important subcriterion among these. [ABSTRACT FROM AUTHOR]

Oil and gas (O&G) projects have a high social and economic impact in many countries. This study aims to identify the success factors in the O&G industry and to present a framework for evaluating the projects in an uncertain environment. In this study, 197 indicators are identified from a literature review and summarized to 34 indicators. Exploratory factor analysis (EFA) was performed, and seven main factors have been identified as success factors of O&G projects. Confirmatory factor analysis (CFA) confirmed the validity of the measurement model. A two-step fuzzy inference system is proposed to present an evaluation framework for assessing the performance of O&G projects. The hybrid framework was applied for the assessment of five Iranian O&G projects. [ABSTRACT FROM AUTHOR]