Adopting Artificial Intelligence Technology for Network Operations in Digital Transformation

Min, Seoungkwon; Kim, Boyoung

doi:10.3390/admsci14040070

Cited by 3 publications

(1 citation statement)

References 59 publications

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“…In the field of decision sciences, MAGDM holds significant importance as it provides a fascinating framework for analyzing and resolving complex problems. In the modern era, decision-making is used in digital transformation for a more informed and effective approach (Haudi, 2024 ; Jones, 2024 ; Min and Kim, 2024 ). It examines how to encourage a panel of DMs in differing preferences and viewpoints to reach a consensus on a complex problem involving multiple criteria and options.…”

Section: Introductionmentioning

confidence: 99%

Enhancing breast cancer treatment selection through 2TLIVq-ROFS-based multi-attribute group decision making

Rasheed,

Mahboob,

Mustafa

et al. 2024

Front. Artif. Intell.

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IntroductionBreast cancer is an extremely common and potentially fatal illness that impacts millions of women worldwide. Multiple criteria and inclinations must be taken into account when selecting the optimal treatment option for each patient.MethodsThe selection of breast cancer treatments can be modeled as a multi-attribute group decision-making (MAGDM) problem, in which a group of experts evaluate and rank alternative treatments based on multiple attributes. MAGDM methods can aid in enhancing the quality and efficacy of breast cancer treatment selection decisions. For this purpose, we introduce the concept of a 2-tuple linguistic interval-valued q-rung orthopair fuzzy set (2TLIVq-ROFS), a new development in fuzzy set theory that incorporates the characteristics of interval-valued q-rung orthopair fuzzy set (IVq-ROFS) and 2-tuple linguistic terms. It can express the quantitative and qualitative aspects of uncertain information, as well as the decision-makers' level of satisfaction and dissatisfaction.ResultsThen, the 2TLIVq-ROF weighted average (2TLIVq-ROFWA) operator and the 2TLIVq-ROF weighted geometric (2TLIVq-ROFWJ) operator are introduced as two new aggregation operators. In addition, the multi-attribute border approximation area comparison (MABAC) method is extended to solve the MAGDM problem with 2TLIVq-ROF information.DiscussionTo demonstrate the efficacy and applicability of the suggested model, a case study of selecting the optimal breast cancer treatment is presented. The results of the computations show that the suggested MAGDM model is able to handle imprecision and subjectivity in complicated decision-making scenarios and opens new research scenarios for scholars.

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Section: Introductionmentioning

confidence: 99%

Enhancing breast cancer treatment selection through 2TLIVq-ROFS-based multi-attribute group decision making

Rasheed,

Mahboob,

Mustafa

et al. 2024

Front. Artif. Intell.

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Understanding School Readiness Factors in relation to the Incorporation of Artificial Intelligence using TOE Framework: An Empirical Evidence from India

Karan,

Angadi

2024

TechTrends

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Adoption of artificial intelligence for manufacturing SMEs’ growth and survival in South Africa

Akoh

2024

IJRBS

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This study advances research and practice related to adopting artificial intelligence (AI) in the context of South Africa (SA). The study evaluated AI adoption by South African manufacturing Small and Medium Enterprises (SMEs); established the challenges faced by manufacturing SMEs in adopting AI; and developed a framework for adopting AI for manufacturing SMEs’ growth and survival. The study adopted a systematic literature review approach. Articles from Scopus and Google scholar databases, ranging from the years 2018 to 2024, were used. Of the 206 articles found, 54 were shortlisted. The systematic review analysis was performed using the PRISMA framework. The results identified AI adoption by South African manufacturing SMEs is low, limiting their innovation and productivity. The results also show, despite the numerous benefits AI adoption can offer manufacturing SMEs in the country, a major constraint is the lack of a framework to enhance adoption and implementation. Hence, this study was conducted to develop a framework to improve AI adoption by South African manufacturing SMEs. The findings contribute to the body of knowledge and provide new insights to manufacturing SME owners/managers, policymakers and practitioners into AI adoption to enhance manufacturing SMEs’ ability to compete on the global stage.

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Adopting Artificial Intelligence Technology for Network Operations in Digital Transformation

Cited by 3 publications

References 59 publications

Enhancing breast cancer treatment selection through 2TLIVq-ROFS-based multi-attribute group decision making

Enhancing breast cancer treatment selection through 2TLIVq-ROFS-based multi-attribute group decision making

Understanding School Readiness Factors in relation to the Incorporation of Artificial Intelligence using TOE Framework: An Empirical Evidence from India

Adoption of artificial intelligence for manufacturing SMEs’ growth and survival in South Africa

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