Balanced scorecard-based cost analysis of service industry using a novel hybrid decision making approach based on golden cut-oriented bipolar and q-ROF sets

This study aims to create a strategy for reducing energy costs in hospitals to ensure the sustainability of health services. In this framework, a novel hybrid decision making approach is generated based on golden cut-oriented bipolar and q-rung orthopair fuzzy sets (q-ROFs). Firstly, balanced scorecard (BSC)-based criteria are evaluated by using multi stepwise weight assessment ratio analysis (M-SWARA) approach. Secondly, alternatives are examined with the help of technique for order preference by similarity to ideal solution (TOPSIS) technique. The novelty of this study is to find critical factors that affect the energy costs of health institutions with an original fuzzy decision-making model. This proposed model has also some superiorities by comparing with previous models in the literature. First, SWARAmethod is improved, and this technique is generated with the name of M-SWARA. Hence, the relationship between the criteria can be examined owing to this issue. Additionally, golden cut is taken into consideration to compute the degrees in bipolar q-ROFSs to achieve more accurate results. These two issues have an important impact on the originality of the proposed model. The findings demonstrate that consciousness level of employees has the highest weight with respect to the energy costs in hospitals. Additionally, the type of energy used also plays a significant role for this issue. Thus, renewable energy sources should be considered in meeting the energy needs of hospitals. Although the installation costs of these energy types are higher, it will be possible to significantly reduce energy costs in the long run.