A Hybrid Group Decision Approach Based on MARCOS and Regret Theory for Pharmaceutical Enterprises Assessment under a Single-Valued Neutrosophic Scenario

Abstract

Evaluating pharmaceutical enterprises with sustainable and high-quality development ability (SHQDA) can not only provide strategies for the pharmaceutical management department in formulating enterprise development plans, but also provide suggestions and guidance for enterprises to enhance their core competitiveness. Nevertheless, the prior research possesses several deficiencies in coping with the assessment of enterprises with SHQDA under uncertain environments to predict the psychological behavior of the evaluator and the correlation among the evaluation criteria. To conquer the aforementioned defects, we propose an integrated framework for rating pharmaceutical enterprises that incorporates regret theory, measurement alternatives and ranking based on the compromise solution (MARCOS) and Heronian mean operating within a single-value neutrosophic set (SVNS) environment. First, the single-valued neutrosophic number (SVNN) is employed to portray the assessment information of experts. Then, a novel single-valued neutrosophic score function is presented to enhance the rationality of the SVNN comparison. Next, a combined criteria weight model is constructed by synthesizing the best and worst method (BWM) and criteria importance through intercriteria correlation (CRITIC) approach to attain more reasonable and credible weight information. Furthermore, the integrated assessment framework combining regret theory-MARCOS method and Heronian mean operator is put forward to assess and select the enterprises with SHQDA under a single-valued neutrosophic setting. Ultimately, an empirical concerning the pharmaceutical enterprises assessment is presented within SVNS to illustrate the usefulness and effectiveness of the presented SVNS regret theory-MARCOS method. Thereafter, the sensitivity analysis and comparison analysis are implemented to provide evidence for the rationality and superiority of the proposed method.