Evaluating the Performance of Oil and Gas Companies by an Extended Balanced Scorecard and the Hesitant Fuzzy Best-Worst Method

Abstract

The aim of this research is finding and prioritizing performance indicators based on Balanced Scorecard (BSC) for oil and gas (O&G) companies in an uncertain environment using the Hesitant Fuzzy Best-Worst Method (HFBWM). As the O&G industry has a key role in many countries, its evaluation of performance is crucial. We utilize BSC for this purpose considering the traditional financial, customer-oriented, internal, and learning-oriented and growth perspectives and adding the social responsibility perspective. As it is usually not possible to implement all found performance indicators, we use Multi-Criteria Decision Making (MCDM) methods for prioritizing them. We employ the Best-Worst Method (BWM) which has several advantages compared to other MCDM methods. Due to uncertainties in the considered decision-making environment, we use hesitant fuzzy sets as a suitable method. Our results indicate that among the considered five perspectives of BSC, the customer and internal process perspectives are the most important ones, and the cost of R&D indicator is the most important sub-criterion.