Dynamic bipolar fuzzy aggregation operators: A novel approach for emerging technology selection in enterprise integration

Dilshad Alghazzawi; Sajida Abbas; Hanan Alolaiyan; Hamiden Abd El-Wahed Khalifa; Alhanouf Alburaikan; Qin Xin; Abdul Razaq; Dilshad Alghazzawi; Sajida Abbas; Hanan Alolaiyan; Hamiden Abd El-Wahed Khalifa; Alhanouf Alburaikan; Qin Xin; Abdul Razaq

doi:10.3934/math.2024261

AIMS Mathematics

2024, Volume 9, Issue 3: 5407-5430. doi: 10.3934/math.2024261

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Research article

Dynamic bipolar fuzzy aggregation operators: A novel approach for emerging technology selection in enterprise integration

1.
Department of Mathematics, College of Science & Arts, King Abdul Aziz University, Rabigh, Saudi Arabia
2.
Department of Mathematics, Division of Science and Technology, University of Education, Lahore 54770, Pakistan
3.
Department of Mathematics, King Saud University, Riyadh, Saudi Arabia
4.
Department of Mathematics, College of Science and Arts, Qassim University, Al-Badaya 51951, Saudi Arabia
5.
Department of Operations and Management Research, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, Egypt
6.
Faculty of Science and Technology, University of the Faroe Islands, Vestara Bryggja 15, FO 100 Torshavn, Faroe Islands, Denmark

Received: 01 December 2023 Revised: 13 January 2024 Accepted: 22 January 2024 Published: 29 January 2024
MSC : 90B50, 94D05

Emerging technology selection is crucial for enterprise integration, driving innovation, competitiveness, and streamlining operations across diverse sectors like finance and healthcare. However, the decision-making process for technology adoption is often complex and fraught with uncertainties. Bipolar fuzzy sets offer a nuanced representation of uncertainty, allowing for simultaneous positive and negative membership degrees, making them valuable in decision-making and expert systems. In this paper, we introduce dynamic averaging and dynamic geometric operators under bipolar fuzzy environment. We also establish some of the fundamental crucial features of these operators. Moreover, we present a step by step mechanism to solve MADM problem under bipolar fuzzy dynamic aggregation operators. In addition, these new techniques are successfully applied for the selection of the most promising emerging technology for enterprise integration. Finally, a comparative study is conducted to show the validity and practicability of the proposed techniques in comparison to existing methods.
Citation: Dilshad Alghazzawi, Sajida Abbas, Hanan Alolaiyan, Hamiden Abd El-Wahed Khalifa, Alhanouf Alburaikan, Qin Xin, Abdul Razaq. Dynamic bipolar fuzzy aggregation operators: A novel approach for emerging technology selection in enterprise integration[J]. AIMS Mathematics, 2024, 9(3): 5407-5430. doi: 10.3934/math.2024261

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Abstract

Emerging technology selection is crucial for enterprise integration, driving innovation, competitiveness, and streamlining operations across diverse sectors like finance and healthcare. However, the decision-making process for technology adoption is often complex and fraught with uncertainties. Bipolar fuzzy sets offer a nuanced representation of uncertainty, allowing for simultaneous positive and negative membership degrees, making them valuable in decision-making and expert systems. In this paper, we introduce dynamic averaging and dynamic geometric operators under bipolar fuzzy environment. We also establish some of the fundamental crucial features of these operators. Moreover, we present a step by step mechanism to solve MADM problem under bipolar fuzzy dynamic aggregation operators. In addition, these new techniques are successfully applied for the selection of the most promising emerging technology for enterprise integration. Finally, a comparative study is conducted to show the validity and practicability of the proposed techniques in comparison to existing methods.

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