Reconfiguring IVHF-TOPSIS decision making method with parameterized reference solutions and a novel distance for corporate carbon performance evaluation

Abstract

The hesitant and imprecise uncertainties widely exist in real decision-making problems. For solving the class of problems, this work is aimed at reconfiguring a novel method under the TOPSIS framework to solve the general uncertain decision problem that with both the ratings of alternatives and weights of criteria represented by interval-valued hesitant fuzzy (IVHF) information. Three novelties are proposed to support the reconfigured method. First, a parameterized approach for generating apt positive and negative IVHF reference solutions is proposed, which permits decision makers (DMs) to express their different aspiration strengths for fitting complex and uncertain decision scenarios and situations. Second, a novel distance for IVHF elements is constructed based on the modification of Wave-Hedges measurement to address the defects of the previous hesitant distances and to measure the separations of alternatives in TOPSIS. Third, a nine-step solution procedure of IVHF-TOSPSIS method is reconfigured to solve effectively the general problem that the ratings and weights are expressed with IVHF information. Finally, the reconfigured method is exploited to settle the carbon performance evaluation of industrial firms and some sensitivity and comparison analyses are conducted to validate the proposed method.