Conceptual design evaluation considering the ambiguity semantic variables fusion with conflict beliefs: An integrated Dempster-Shafer evidence theory and intuitionistic fuzzy -VIKOR

Evaluation of Student-Perceived Service Quality in Higher Education for Sustainable Development: A Fuzzy TODIM-ERA Method

“…However, fuzzy set can only describe the preference of "either one or the other" [56]. Intuitionistic fuzzy sets (IFSs) are characterized by membership and non-membership functions [57], can provide more auxiliary decision information, and are useful when representing uncertainty [38,39,52,58]. In terms of evaluating information aggregation, evidence theory is one of the best solutions to fuse uncertain information and is well-known for making the maximum use of all available information [38,39,52].…”

“…In contrast, the intuitionistic fuzzy set characterized by three states of support, opposition, and neutrality can better describe uncertain information. This study lists the relations between IFS and the seven-level linguistic preference scale, as shown in Table 2 [39]. The concept of IFS was initially promulgated by Atanassov [57].…”

“…As a generalization of Bayes probability theory, it is an efficient tool for uncertainty reasoning. Then, Yang and Xu extended the D-S evidence theory to advocate an evidential reasoning algorithm (ERA) for MCDM [65] and has been applied widely in various fields, such as performance evaluation [38] and design decisions [39]. The related concepts are described as follows.…”

“…First, the frame of discernment (FOD) can be constructed based on a seven-level linguistic preference scale [39], Θ = H = {VL, LR, L, M, H, HR, V H}. Then, the linguistic preference in the evaluation matrix can be considered to be the body of evidence (BOE) on the FOD Θ.…”

“…Additionally, subjective evaluation behavior is more akin to bounded rationality [22,36,37]. According to the literature [34][35][36][37][38][39], fuzzy set theory can reasonably describe the subjective uncertainty related to educational quality evaluation [34]; ERA (evidential reasoning algorithm) can minimize the loss of uncertainty in the fusion process of evaluation information [38,39]; and TODIM (an acronym in Portuguese for interactive and multicriteria decision-making) can express the psychological behavior of decision makers in MCDM problems [36,37]. Therefore, this study develops the MCDM method based on fuzzy set theory, TODIM, and ERA for student-perceived service quality evaluation with uncertain information and bounded rationality of decision makers.…”