An integrated SWOT based fuzzy AHP and fuzzy MARCOS methodology for digital transformation strategy analysis in airline industry

Büyüközkan, Gülçin; Havle, Celal Alpay; Feyzıog̃lu, Orhan

doi:10.1016/j.jairtraman.2021.102142

Cited by 58 publications

(21 citation statements)

References 41 publications

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“…Linear Discriminant Analysis (LDA) [123] Quadratic Discriminant Analysis (QDA) [123] Gaussian Mixture Model (GMM) [153,190-195] [196-198] Autoencoder [199] Fuzzy Logic [200] [117,201,202] [ [203][204][205][206][207] Logistic Regression [131,150] [126,208] Bayesian Network [30,[209][210][211] Multi-Layer Perceptron (MLP) [125,163,251] Graph-Theoretic Clustering [253] Hidden Markov Model (HMM) [254] Markov Decision Process (MDP) [78,235,240,255] Not referenced [256,257] [258]…”

Section: Categorisation Insightsmentioning

confidence: 99%

A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory

et al. 2022

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Air Traffic Management (ATM) will be more complex in the coming decades due to the growth and increased complexity of aviation and has to be improved in order to maintain aviation safety. It is agreed that without significant improvement in this domain, the safety objectives defined by international organisations cannot be achieved and a risk of more incidents/accidents is envisaged. Nowadays, computer science plays a major role in data management and decisions made in ATM. Nonetheless, despite this, Artificial Intelligence (AI), which is one of the most researched topics in computer science, has not quite reached end users in ATM domain. In this paper, we analyse the state of the art with regards to usefulness of AI within aviation/ATM domain. It includes research work of the last decade of AI in ATM, the extraction of relevant trends and features, and the extraction of representative dimensions. We analysed how the general and ATM eXplainable Artificial Intelligence (XAI) works, analysing where and why XAI is needed, how it is currently provided, and the limitations, then synthesise the findings into a conceptual framework, named the DPP (Descriptive, Predictive, Prescriptive) model, and provide an example of its application in a scenario in 2030. It concludes that AI systems within ATM need further research for their acceptance by end-users. The development of appropriate XAI methods including the validation by appropriate authorities and end-users are key issues that needs to be addressed.

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Section: Categorisation Insightsmentioning

confidence: 99%

A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory

et al. 2022

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“…Over the last few decades, several MCDM methods have been proposed, each with its advantages and limitations [56]. Among them, the Analytic Hierarchy Process (AHP) has the advantages of simplicity of application, repeatability, and consistency of results [57], and for that reason, it gained recognition, and currently is one of the most employed MCDM techniques by academics, and by industry in general [58][59][60]. The AHP method was developed by Saaty [61] and its approach is based on the fragmentation of the decision process into smaller parts, constituting a hierarchical system of objectives, metrics, and scenarios [62][63][64].…”

Section: Literature Reviewmentioning

confidence: 99%

“…If CR < 0.10, the degree of consistency is considered satisfactory. Otherwise, evaluations are inconsistent, and the rating a ij in the pairwise comparison matrix must be revised to remove inconsistency [57,59,63,66,85,86].…”

Section: Fuzzy Analytic Hierarchy Process (Fahp) Multicriteria Analys...mentioning

confidence: 99%

Sustainability Assessment of a Low-Income Building: A BIM-LCSA-FAHP-Based Analysis

et al. 2022

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The construction industry is one of the most significant consumers of environmental resources worldwide. Faced with the need to produce new buildings, but without further burdening the environment, attempts to improve social, economic, and environmental indicators have turned attention to building construction in recent decades. The objective of this research is to develop a novel framework to assess the most sustainable choice of materials applied to the construction of low-income buildings, according to the three pillars of the Triple Bottom Line (TBL). A BIM-LCSA-FAHP-based model was proposed with the creation of nine different scenarios, where the materials of the structure (precast concrete, cast-in-place concrete, and structural masonry), painting (PVA water-based and acrylic), and roofing (ceramic and fiber cement tiles) varied. The proposed procedure consists of the elaboration of a 3D Building Information Modeling (BIM) model, for which the parameters described above were evaluated according to the Life Cycle Sustainability Assessment (LCSA)-TBL-based criteria, divided into ten sub-criteria, that includes: (1) environmental (acidification, eutrophication, global warming, ozone depletion, smog formation, primary energy, non-renewable energy, and mass total), (2) economic (construction cost) and (3) socio-political issues (community impact). Finally, the Fuzzy Analytical Hierarchy Process (AHP) was used as a multi-criteria decision-making technique that helps in aggregating and classifying the impacts of each scenario in a sustainability index (SI). Regarding the best option for low-income construction, the results indicated that precast concrete when combined with acrylic paint and fiber cement tiles (scenario 3) proved to be the most advantageous and achieved first place in the sustainability index (SI) developed in this work. This methodology is replicable for different construction typologies and several categories of materials, making it a robust decision-aiding tool for engineers, architects, and decision makers.

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“…There are many different fuzzy MCDM methods, but it is difficult to determine the best or most suitable one for a practical issue [55]. The proposed hybrid fuzzy MCDM method for the comprehensive performance evaluation of pumped storage power stations in this paper is compared with the recently proposed MCDM method, namely fuzzy Measurement of Alternatives and Ranking according to the Compromise Solution (MARCOS).…”

Section: Comparative Analysismentioning

confidence: 99%

A Hybrid Novel Fuzzy MCDM Method for Comprehensive Performance Evaluation of Pumped Storage Power Station in China

2021

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Considering the goals of carbon peaking and carbon neutrality, along with their related policies, pumped storage power stations are set to develop quickly in China. The comprehensive performance of pumped storage power stations must urgently be evaluated, which can help investors in decision making and provide a reference for policymakers. In this paper, a hybrid novel fuzzy multicriteria decision-making (MCDM) method combining the fuzzy best worst method (BWM) and fuzzy TOPSIS was proposed for the comprehensive performance evaluation of pumped storage power stations in China. The fuzzy BWM was utilized to determine the criteria weights describing the comprehensive performance of pumped storage power stations, while the fuzzy TOPSIS was used to rank the comprehensive performance of pumped storage power stations. The index system for the comprehensive performance evaluation of pumped storage power stations in China incorporated economic, social, and environmental aspects. The comprehensive performance of four pumped storage power stations in China was empirically evaluated using the proposed hybrid novel fuzzy MCDM method, and the results indicate that pumped storage power station PSPS2 exhibited the best comprehensive performance, followed by pumped storage power stations PSPS1 and PSPS4, whereas pumped storage power station PSPS3 had the worst comprehensive performance. A sensitivity analysis and comparative analysis were also conducted. The results indicate that the proposed hybrid novel fuzzy MCDM method, combining the fuzzy BWM and fuzzy TOPSIS for comprehensive performance evaluation of pumped storage power stations, is robust and effective.

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An integrated SWOT based fuzzy AHP and fuzzy MARCOS methodology for digital transformation strategy analysis in airline industry

Cited by 58 publications

References 41 publications

A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory

A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory

Sustainability Assessment of a Low-Income Building: A BIM-LCSA-FAHP-Based Analysis

A Hybrid Novel Fuzzy MCDM Method for Comprehensive Performance Evaluation of Pumped Storage Power Station in China

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