Open Access

ARTICLE

Promoting Tailored Hotel Recommendations Based on Traveller Preferences: A Circular Intuitionistic Fuzzy Decision Support Model

Sana Shahab¹, Ibtehal Alazman², Ashit Kumar Dutta³, Mohd Anjum⁴, Vladimir Simic^5,6,7,*, Željko Stević⁸, Nouf Abdulrahman Alqahtani²

1 Department of Business Administration, College of Business Administration, Princess Nourah Bint Abdulrahman University, Riyadh, 11671, Saudi Arabia
2 Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11623, Saudi Arabia
3 Department of Computer Science and Information Systems, College of Applied Sciences, AlMaarefa University, Ad Diriyah, Riyadh, 13713, Saudi Arabia
4 Department of Computer Engineering, Aligarh Muslim University, Aligarh, 202002, India
5 Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade, 11010, Serbia
6 Department of Industrial Engineering and Management, College of Engineering, Yuan Ze University, Taoyuan City, 320315, Taiwan
7 Department of Computer Science and Engineering, College of Informatics, Korea University, Seongbuk-Gu, Seoul, 02841, Republic of Korea
8 Department of Railway Transport and Mobile Machinery, Faculty of Transport Engineering, Vilnius Gediminas Technical University, Vilnius, 10105, Lithuania

* Corresponding Author: Vladimir Simic. Email:

(This article belongs to the Special Issue: Algorithms, Models, and Applications of Fuzzy Optimization and Decision Making)

Computer Modeling in Engineering & Sciences 2025, 143(2), 2155-2183. https://doi.org/10.32604/cmes.2025.064553

Received 19 February 2025; Accepted 15 April 2025; Issue published 30 May 2025

Abstract

With the increasing complexity of hotel selection, traditional decision-making models often struggle to account for uncertainty and interrelated criteria. Multi-criteria decision-making (MCDM) techniques, particularly those based on fuzzy logic, provide a robust framework for handling such challenges. This paper presents a novel approach to MCDM within the framework of Circular Intuitionistic Fuzzy Sets (C-IFS) by combining three distinct methodologies: Weighted Aggregated Sum Product Assessment (WASPAS), an Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN), and the CRITIC method (Criteria Importance Through Intercriteria Correlation). To address the dynamic nature of traveler preferences in hotel selection, the study employs a comprehensive set of criteria encompassing aspects such as location proximity, amenities, pricing, customer reviews, environmental impact, safety, booking flexibility, and cultural experiences. The CRITIC method is used to determine the importance of each criterion by assessing intercriteria correlations. AROMAN is employed for the systematic evaluation of alternatives, considering their additive relationships and providing a weighted assessment. WASPAS further analyzes the results obtained from AROMAN, incorporating both positive and negative aspects for a comprehensive evaluation. The integration of C-IFS enhances the model’s ability to manage uncertainty and imprecision in the decision-making process. Through a case study, we demonstrate the effectiveness of this integrated approach, offering decision-makers valuable insights for selecting the most suitable hotel option in alignment with the diverse preferences of contemporary travelers. This research contributes to the evolving field of decision science by showcasing the practical applicability of these methodologies within a C-IFS framework for complex decision scenarios.

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