Journals / Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi / 2026 / Cilt: 32 Sayı: 5
Using the fuzzy VIKOR method to rank the mental workload weights of an airline company employees
- Pages
- 902–910
- Publication Date
- 2026-09-13
Abstract
In recent years, air transportation has become increasingly popular because it saves time and offers more comfortable travel opportunities. Considering the competitive conditions and the risks brought by the job, high performance is expected from employees. In particular, the expectation of quality and correct work from the flight crews who are on duty during the flight is increasing, and this situation causes an increase in the mental workload on the employees. In this study, during the flight; it was aimed to determine which of the stages of preparing the aircraft and welcoming the passengers, preparations for departure, catering, preparations for landing and farewelling the passengers was more mentally challenging for the flight crew. As evaluation criteria in determining perceived workloads, the six dimensions of the NASA-TLX method, the mental workload measurement methods applied in many studies in the aviation sector, were used. In the process of determining the mental workload, the fuzzy VIKOR method was used in order to minimize individual regret and maximize group benefit in these stages where there are many decision makers and evaluated with fuzzy thoughts. The study found that the catering phase of the flight was when participants experienced the highest mental workload. However, when participants were evaluated by gender and crew roles, it was observed that the tasks which increased mental workload -aircraft preparation, departure preparations, catering, and landing preparations - differed.
Özet
Son yıllarda hava yolu taşımacılığı, zaman tasarrufu sağlaması ve daha konforlu seyahat imkânı sunması nedeniyle çok fazla tercih edilir hale gelmiştir. Rekabet koşulları ve işin getirdiği riskler göz önüne alındığında çalışanlardan yüksek performans beklenmektedir. Özellikle uçuş esnasında görev başında olan uçuş ekiplerinden kaliteli ve doğru iş beklentisi artmakta ve bu durum çalışanlar üzerindeki zihinsel iş yükünün artmasına neden olmaktadır. Bu çalışmada uçuş esnasında; uçağın hazırlanması ve yolcuların karşılanması, kalkış hazırlığı, ikram, iniş hazırlığı ve yolcuların uğurlanması aşamalarından hangisinin uçuş ekibi için zihinsel olarak daha zorlayıcı olduğunun belirlenmesi amaçlanmıştır. Algılanan iş yüklerinin belirlenmesinde değerlendirme kriteri olarak havacılık sektöründe birçok çalışmada uygulanan zihinsel iş yükü ölçüm yöntemlerinden olan NASA-TLX yönteminin altı boyutu kullanılmıştır. Zihinsel iş yükünün belirlenmesi sürecinde çok sayıda karar vericinin bulunduğu ve bulanık düşüncelerle değerlendirilen bu aşamalarda bireysel pişmanlığın en aza indirilmesi ve grup faydasının en üst düzeye çıkarılması amacıyla bulanık VIKOR yöntemi kullanılmıştır. Çalışma sonucunda, katılımcıların uçuş esnasında en fazla zihinsel yük hissettikleri aşama ikram olarak bulunmuştur. Ancak katılımcılar cinsiyet ve ekip içerisindeki rollerine göre değerlendirildiğinde zihinsel iş yükü hissedilen görevlerin (uçak hazırlığı, kalkış hazırlıkları, ikram hizmetleri ve iniş hazırlıkları) farklılık gösterdiği görülmüştür.
Cite This Article
References (43)
- [1] Bolton ML, Biltekoff E, Humphrey L. “The mathematical meaninglessness of the nasa task load index: a level of measurement analysis”. IEEE Transactions On Human-Machine Systems, 53(3), 590-599, 2023.
- [2] Tosun S, Yılmaz İ. “Measuring the mental workload of specialists and practitioners with the carmen-Q method and evaluating the differences”. Ergonomics, 6(2), 132–144, 2023.
- [3] Boet S, Sharma B, Pigford AA, Hladkowicz E, Rittenhouse N, Grantcharov T. “Debriefing decreases mental workload in surgical crisis: a randomized controlled trial”. Surgery, 161(5), 1215-1220, 2017.
- [4] Yavuz M, Akca M, Tepe Küçükoğlu M. “Measurement of mental workload: Turkish adaptation of CarMen-Q questionnaire”. Journal of Yasar University, 15(60), 675-691, 2020.
- [5] Öztürk GD. A Qualitative Study on the Relationship Between Mental Workload and Organizational Health: Case Of Research. Phd. Thesis, Ondokuz Mayis University Institute of Social Science Department of Business Administration, Samsun, Türkiye, 2019.
- [6] Longo L. “Mental workload in medicine: foundations, applications, open problems, challenges and future perspectives”. IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS), Dublin, Ireland, 20-24 June 2016.
- [7] Nikulin C, Lopez G, Piñonez E, Gonzalez L, Zapata P. “NASA-TLX for predictability and measurability of instructional design models: case study in design methods”. Education Technology Research and Development, 67, 467–493, 2019.
- [8] Chatterjee P, Chakraborty S. “Material selection using preferential ranking methods”. Materials and Design, 35, 384-393, 2012.
- [9] Liao H, Yang S, Zavadskas EK, Škare M. “An overview of fuzzy multi-criteria decision-making methods in hospitality and tourism industries: bibliometrics, methodologies, applications and future directions”. Economic Research-Ekonomska Istraživanja, 36(3), 2150871, 2023.
- [10] MacCrimmon KR. Decision Making Among Multiple-Attribute Alternatives: A Survey and Consolidated Approach. California, USD, Advanced Research Projects Agency, 1968.
- [11] Kaya İ, Çolak M, Terzi F. “A comprehensive review of fuzzy multi criteria decision making methodologies for energy policy making”. Energy Strategy Reviews, 24, 207-228, 2019.
- [12] Hacibektaşoğlu SE, Mertoğlu B, Tozan H. “Application of a risk analysis with fuzzy multi-criteria decision making methods”. International Journal of Advances in Engineering and Pure Sciences, 34(3), 403-414, 2022.
- [13] Otay İ. “Intuitive fuzzy multi-expert & multi-criteria decision making methodology: An application in healthcare industry”. Journal of the Faculty of Engineering and Architecture of Gazi University, 37(2), 1047-1062, 2022.
- [14] Yel İ, Baysal ME. “An application on the use of fuzzy multi criteria decision making methods for software project development process selection”. Journal of the Faculty of Engineering and Architecture of Gazi University, 38(4), 2325-2337, 2023.
- [15] Görçün ÖF, Küçükönder H. “Integrated fuzzy multi-criteria decision-making approach for seaport selection”. Dokuz Eylül University Maritime Faculty Journal, 15(1), 1-34, 2023.
- [16] Avşar İİ. “Evaluation of Turkish aviation sector with multi-criteria decision making methods: 2002-2022 period”. Bingöl University Journal of Social Sciences Institute, 26, 153-169, 2023.
- [17] Huang JJ, Tzeng GH, Liu HH. A Revised VIKOR Model for Multiple Criteria Decision Making-The Perspective of Regret Theory. Editors: Shi Y, Wang S, Peng Y, Li J, Zeng Y. Communications in Computer and Information Science, 761-768, Berlin Heidelberg, Germany, Springer, 2009.
- [18] Chang CL. “A modified VIKOR method for multiple criteria analysis”. Environmental Monitoring and Assessment, 168, 339-344, 2010.
- [19] Devi K. “Extension of VIKOR method in intuitionistic fuzzy environment for robot selection”. Expert Systems with Applications, 38(11), 14163-14168, 2011.
- [20] Kaya N. “A reviewon manufacturing applications of theVIKOR approach”. Bmij, 9(4), 1673-1695, 2021.
- [21] Gupta H. “Evaluating service quality of airline industry using hybrid best worst method and VIKOR”. Journal of Air Transport Management, 68, 35-47, 2018.
- [22] Shojaei P, Haeri SAS, Mohammadi S. “Airports evaluation and ranking model using taguchi loss function, best-worst method and VIKOR technique”. Journal of Air Transport Management, 68, 4-13, 2018.
- [23] Uçakcıoğlu B, Eren T. “Investment selection project in air defense industry with analytic hierarchy process and VIKOR methods”. Harran University Journal of Engineering, 2, 35-53, 2017.
- [24] Bellman RE, Zadeh LA.”Decision-making in a fuzzy environment”. Management Science, 17(4), B-141-B-164, (1970).
- [25] Opricovic S. “Fuzzy VIKOR with an application to water resources planning”. Expert Systems with Applications, 38(10), 12983-12990, 2011.
- [26] Çekiç C, Gül NN, Güneri AF. “Managing supplier selection problem with integrated fuzzy AHP and fuzzy VIKOR: A manufacturing company case”. Journal of Advances in Manufacturing Engineering, 3(1), 1-13, 2022.
- [27] Faydalı R, Erkan EF. “A Fuzzy VIKOR method for machine selection”. Journal of Intelligent Systems: Theory and Applications, 3(1), 7-12, 2020.
- [28] Bhalaji RKA, Sankaranarayanan S, Saravanasankar S. “A Fuzzy VIKOR method to analyze the risks in lean manufacturing implementation”. Materialstoday: Proceedings, 45, 1294-1299, 2021.
- [29] Mustapha MT, Uzun Ozsahin D, Uzun B, Ozsahin İ. “Evaluation of the thyroid cancer treatment techniques with fuzzy VIKOR”. Advances in Science and Engineering Technology International Conferences (ASET), Dubai, United Arab Emirates, 21-24 February 2022.
- [30] Gupta P, Mehlawat MK, Ahemad F. “Selection of renewable energy sources: a novel VIKOR approach in an intuitionistic fuzzy linguistic environment”. Environment, Development and Sustainability, 25(4), 3429-3467, 2023.
- [31] Vahdani B, Hadipour H, Sadaghiani JS, Amiri M. “Extension of VIKOR method based on interval-valued fuzzy sets”. The International Journal of Advanced Manufacturing Technology, 47(9-12), 1231-1239, 2010.
- [32] Dinçer H, Görener A. “Dynamic performance analysis via analytic hierarchy process and Vikor technique: An application for banking sector”. Istanbul Commerce University Journal of Social Sciences, 10(19), 109-127, 2011.
- [33] Cengiz G. Evaluation of Airline Service Quality in Terms of Gender With New Integrated Approach. Master's Thesis, Baskent University Institute of Science and Technology, Ankara, Türkiye, 2019.
- [34] Tatlı M, Akın HB. “Relationship between burnout and work load: a research on Aksaray revenue office”. Journal of Aksaray University Faculty of Economics and Administrative Sciences, 9(3), 49-62, 2017.
- [35] Hart SG. “NASA-task load index (NASA-TLX); 20 years later”. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 50(9), 904-908, 2006.
- [36] Cain B. “A Review of the Mental Workload Literature”. Human System Integration Section, Defence Research and Development, Toronto, Canada, RTO-TR-HFM-121-Part-II, 2007.
- [37] Emeç Ş, Akkaya G. “Evaluation of mental work on the health sector and an application”. Ergonomics, 1(3), 156-162, 2018.
- [38] Çalımfidan E. A Study to Enhance Night Flying Safety for Rotary Wing Pilots. Master's Thesis, Gazi University Institute of Science and Technology, Ankara, Türkiye, 2015.
- [39] Mamak Ekinci EB, Can GF. “Evaluation of workers’ ergonomic risk levels considering working postures and perceived workload with multi-criteria decision making approach”. Ergonomics, 1(2), 77-91, 2018.
- [40] Yener Y, Can GF, Toktaş P. “A job rotation proposal considering physical strain and perceived workload level”. Journal of Engineering and Architecture Faculty of Eskisehir Osmangazi University, 27(1), 9-20, 2019.
- [41] Chen LY, Wang TC. “Optimizing partners’ choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR”. International Journal of Production Economics, 120(1), 233–242, 2009.
- [42] Al-Hawari T, Naji A, Alshraideh H, Bataineh O. “Extending the WEDBA to the fuzzy multi-criteria decision-making environment”. International Journal of Computer Applications in Technology, 59(4), 330-346, 2019.
- [43] Wang TC, Liang JL, Ho CY. "Multi-criteria decision analysis by using fuzzy VIKOR". ICSSSM '06: 2006 International Conference on Service Systems and Service Management, Troyes, France, 25-27 October 2006.