A hybrid approach based on the fuzzy AHP and HFACS framework for identifying and analyzing gross navigation errors during transatlantic flights

Havle, Celal Alpay; Kılıç, Bilal

doi:10.1016/j.jairtraman.2019.02.005

Cited by 39 publications

(13 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, we adopted Buckley's (1985) approach, which received the least criticism in the existing literature (Kahraman et al, 2018). The application steps can be summarized as follows (Havle & Kılıç, 2019;Singh & Prasher, 2019):…”

Section: The F-ahp Methodsmentioning

confidence: 99%

Application of Fuzzy AHP and Fuzzy MARCOS Approach for the Evaluation of E-Service Quality in the Airline Industry

Bakır

Atalık

2021

Decis. Mak. Appl. Manag. Eng.

119

View full text Add to dashboard Cite

Airlines today use e-services extensively for marketing activities and the distribution of services. Monitoring and evaluating e-service quality are essential for customers’ satisfaction and thus the success of airlines. This study aims to evaluate e-service quality in the airline industry from the point of view of the consumers. To achieve this, an integrated Fuzzy Analytical Hierarchy Process (F-AHP) and Fuzzy Measurement Alternatives and Ranking according to Compromise Solution (F-MARCOS) approach was proposed to handle the uncertain and imprecise nature of e-service evaluation. In the first stage, e-service quality criteria were prioritized using the F-AHP method. Then, a real-world case study was carried out on scheduled airlines to demonstrate the applicability of the proposed approach using the F-MARCOS method, utilizing a total sample of 395 airline passengers in Turkey. As a result, the top three e-service criteria were found as reliability, understandability and security. A three-stage sensitivity analysis was also conducted to examine the credibility and stability of the results. This study is the first study to integrate F-AHP and F-MARCOS methods for the first time in literature.

show abstract

Section: The F-ahp Methodsmentioning

confidence: 99%

Application of Fuzzy AHP and Fuzzy MARCOS Approach for the Evaluation of E-Service Quality in the Airline Industry

Bakır

Atalık

2021

Decis. Mak. Appl. Manag. Eng.

119

View full text Add to dashboard Cite

show abstract

“…In addition, Li et al [ 20 ] used HFACS combined with the Systems–Theoretical Accident Modelling and Processes and human information process to analyze the error factors in railway accidents. Havle and Kılıç [ 46 ] applied HFACS combined with fuzzy AHP to analyze gross navigation errors. The current study also combined HFACS with AHP and fuzzy TOPSIS to determine the improvement priority for error factors.…”

Section: Discussionmentioning

confidence: 99%

An Investigation of Human Errors in Medication Adverse Event Improvement Priority Using a Hybrid Approach

et al. 2021

View full text Add to dashboard Cite

The aim of this study was to analyze and provide an in-depth improvement priority for medication adverse events. Thus, the Human Factor Analysis and Classification System with subfactors was used in this study to analyze the adverse events. Subsequently, the improvement priority for the subfactors was determined using the hybrid approach in terms of the Analytical Hierarchy Process and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution. In Of the 157 medical adverse events selected from the Taiwan Patient-safety Reporting system, 25 cases were identified as medication adverse events. The Human Factor Analysis and Classification System and root cause analysis were used to analyze the error factors and subfactors that existed in the medication adverse events. Following the analysis, the Analytical Hierarchy Process and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution were used to determine the improvement priority for subfactors. The results showed that the decision errors, crew resource management, inadequate supervision, and organizational climate contained more types of subfactors than other error factors in each category. In the current study, 16 improvement priorities were identified. According to the results, the improvement priorities can assist medical staff, researchers, and decisionmakers in improving medication process deficiencies efficiently.

show abstract

“…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

View full text Add to dashboard Cite

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.

show abstract

A hybrid approach based on the fuzzy AHP and HFACS framework for identifying and analyzing gross navigation errors during transatlantic flights

Cited by 39 publications

References 26 publications

Application of Fuzzy AHP and Fuzzy MARCOS Approach for the Evaluation of E-Service Quality in the Airline Industry

Application of Fuzzy AHP and Fuzzy MARCOS Approach for the Evaluation of E-Service Quality in the Airline Industry

An Investigation of Human Errors in Medication Adverse Event Improvement Priority Using a Hybrid Approach

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

Contact Info

Product

Resources

About