Spherical Fuzzy Decision-Making Approach Integrating Delphi and TOPSIS for Package Tour Provider Selection

Abstract

The spherical fuzzy sets were recently developed among various fuzzy sets to handle the hesitancy representation issue in multiple criteria decision-making (MCDM) problems, where experts provide information about attributes in the form of spherical fuzzy numbers using linguistic variables. The main purpose of this study is to develop a novel approach integrating Delphi Technique for Order of Preference by Similarity to Ideal Solution based on spherical fuzzy sets (SF-Delphi and SF-TOPSIS). First, the SF-Delphi technique is suggested to derive a valid set of critical criteria based on qualitative information and linguistic preferences. Second, the SF-TOPSIS approach is utilized to rank alternatives based on different spherical fuzzy aggregating operators. Hence, to validate the effectiveness of the proposed methodology, an empirical case study of package tour provider selection is given. Seventeen critical criteria related to four main dimensions (price, service quality, information and technology, and location) were shortlisted and validated from literature and expert opinions. Ten potential package tour providers from Vietnam were ranked in this study. A comparative analysis was conducted to check the proposed methodology’s robustness and validity. The results indicated that the novel SF-Delphi technique may become very helpful for dealing with critical factors, and SF-TOPSIS could be applied to decision problems in uncertain data environments. Furthermore, this research’s findings imply that tour operators should emphasize the most critical attributes to increase the appeal and competitiveness of their package tour products.

A Data-Driven MCDM Approach-Based Spherical Fuzzy Sets for Evaluating Global Augmented Reality Providers in Education

“…Phase I: The SF-Delphi approach is employed to filter the factors. The newly modified SF-Delphi method proposed by Nguyen [60] is represented as follows:…”

“…Phase II: Evaluating the alternatives' rankings using the SF-TOPSIS method [60]. Step 1: Let DMs fill in the decision matrices using the linguistic terms in Table 3.…”

“…Intuitionistic fuzzy sets (IFS) and Pythagorean fuzzy sets (PFS) have limitations that render them inadequate for handling uncertainty in data and capturing all data. Specifically, there is no function to represent the hesitancy level of decision-makers [60]. Recently, SFSs have provided an effective method for determining ambiguity in information and better represent the opinion of decision-makers than existing fuzzy sets.…”

A Grey Simulation-Based Fuzzy Hierarchical Approach for Diagnosing Healthcare Service Quality

“…Tseng [13] described service quality standards as service forecasts, an optimal level, an attribute of value, and customer appraisal of service quality. There have been numerous researchers studying this topic in various fields: manufacturing [14]; banking and finance [15]; healthcare service [16]; airline [17]; tourism and hospitality [18]; supply chain management [19]. Because of the intangibility, heterogeneity, and simultaneity of healthcare, determining the quality of service can be challenging.…”

GA-GDEMATEL: A Novel Approach to Optimize Recruitment and Personnel Selection Problems

“…MCDM approaches can outrank alternatives or decide the final decision, depending on the purpose [9][10][11][12][13]. MCDM methods have been applied for solving many problems in various industries, such as hotel and hospitality [14,15], import-exporting activities [16,17], supply chain management [18,19], and finance and banking [20,21], as well as being suitable approaches for dealing with recruitment and personnel selection [22]. Due to the ambiguity and complexity of decision problems, the difficulties of MCDM are constantly paired with uncertain and fuzzy topics.…”