A Confidence-Interval Circular Intuitionistic Fuzzy Method for Optimal Master and Sub-Franchise Selection: A Case Study of Pizza Hut in Europe

Effective franchise selection is crucial for global brands like Pizza Hut to maintain consistent quality and operational excellence amidst a competitive landscape. This paper introduces a novel confidence-interval circular intuitionistic fuzzy set (CIC-IFS) framework, designed to address the intrica...

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Main Authors: Velichka Nikolova Traneva, Venelin Todorov, Stoyan Tranev Tranev, Ivan Dimov
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Axioms
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Online Access:https://www.mdpi.com/2075-1680/13/11/758
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author Velichka Nikolova Traneva
Venelin Todorov
Stoyan Tranev Tranev
Ivan Dimov
author_facet Velichka Nikolova Traneva
Venelin Todorov
Stoyan Tranev Tranev
Ivan Dimov
author_sort Velichka Nikolova Traneva
collection DOAJ
description Effective franchise selection is crucial for global brands like Pizza Hut to maintain consistent quality and operational excellence amidst a competitive landscape. This paper introduces a novel confidence-interval circular intuitionistic fuzzy set (CIC-IFS) framework, designed to address the intricate challenges of master and sub-franchise selection in the European market. By integrating competence coefficients of decision-makers into the final evaluations, the model allows for a more accurate representation of expert judgments. Decision-makers can choose from various scenarios, ranging from super pessimistic to super optimistic, using ten forms of aggregation operations over index matrices. The proposed approach leverages confidence intervals within the circular intuitionistic fuzzy set paradigm to capture the uncertainty, vagueness, and hesitancy inherent in the decision-making process. A case study involving Pizza Hut’s European operations demonstrates the model’s efficacy in differentiating potential franchisees and identifying those best aligned with the brand’s values. The results indicate a significant improvement in selection accuracy compared to traditional methods and other fuzzy approaches, thereby enabling Pizza Hut to make more informed decisions and solidify its market position.
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spelling doaj-art-7bbbe273097144aaa86c5593f0eae0f22024-11-26T17:50:49ZengMDPI AGAxioms2075-16802024-10-01131175810.3390/axioms13110758A Confidence-Interval Circular Intuitionistic Fuzzy Method for Optimal Master and Sub-Franchise Selection: A Case Study of Pizza Hut in EuropeVelichka Nikolova Traneva0Venelin Todorov1Stoyan Tranev Tranev2Ivan Dimov3Department of Natural Sciences, Prof. Assen Zlatarov University, Prof. Yakimov Blvd. 1, 8010 Bourgas, BulgariaInstitute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev Str. Bl. 25A, 1113 Sofia, BulgariaDepartment of Social Sciences, Prof. Assen Zlatarov University, Prof. Yakimov Blvd. 1, 8010 Bourgas, BulgariaInstitute of Information and Communication Technologies, Bulgarian Academy of Sciences, Acad. G. Bonchev Str. Bl. 25A, 1113 Sofia, BulgariaEffective franchise selection is crucial for global brands like Pizza Hut to maintain consistent quality and operational excellence amidst a competitive landscape. This paper introduces a novel confidence-interval circular intuitionistic fuzzy set (CIC-IFS) framework, designed to address the intricate challenges of master and sub-franchise selection in the European market. By integrating competence coefficients of decision-makers into the final evaluations, the model allows for a more accurate representation of expert judgments. Decision-makers can choose from various scenarios, ranging from super pessimistic to super optimistic, using ten forms of aggregation operations over index matrices. The proposed approach leverages confidence intervals within the circular intuitionistic fuzzy set paradigm to capture the uncertainty, vagueness, and hesitancy inherent in the decision-making process. A case study involving Pizza Hut’s European operations demonstrates the model’s efficacy in differentiating potential franchisees and identifying those best aligned with the brand’s values. The results indicate a significant improvement in selection accuracy compared to traditional methods and other fuzzy approaches, thereby enabling Pizza Hut to make more informed decisions and solidify its market position.https://www.mdpi.com/2075-1680/13/11/758aggregation operationsconfidence-interval circular intuitionistic fuzzy setsdecision-makingmaster franchisesub-franchise
spellingShingle Velichka Nikolova Traneva
Venelin Todorov
Stoyan Tranev Tranev
Ivan Dimov
A Confidence-Interval Circular Intuitionistic Fuzzy Method for Optimal Master and Sub-Franchise Selection: A Case Study of Pizza Hut in Europe
Axioms
aggregation operations
confidence-interval circular intuitionistic fuzzy sets
decision-making
master franchise
sub-franchise
title A Confidence-Interval Circular Intuitionistic Fuzzy Method for Optimal Master and Sub-Franchise Selection: A Case Study of Pizza Hut in Europe
title_full A Confidence-Interval Circular Intuitionistic Fuzzy Method for Optimal Master and Sub-Franchise Selection: A Case Study of Pizza Hut in Europe
title_fullStr A Confidence-Interval Circular Intuitionistic Fuzzy Method for Optimal Master and Sub-Franchise Selection: A Case Study of Pizza Hut in Europe
title_full_unstemmed A Confidence-Interval Circular Intuitionistic Fuzzy Method for Optimal Master and Sub-Franchise Selection: A Case Study of Pizza Hut in Europe
title_short A Confidence-Interval Circular Intuitionistic Fuzzy Method for Optimal Master and Sub-Franchise Selection: A Case Study of Pizza Hut in Europe
title_sort confidence interval circular intuitionistic fuzzy method for optimal master and sub franchise selection a case study of pizza hut in europe
topic aggregation operations
confidence-interval circular intuitionistic fuzzy sets
decision-making
master franchise
sub-franchise
url https://www.mdpi.com/2075-1680/13/11/758
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