The aviation industry is a sector that is developing, changing and growing every day in terms of technological and legal framework. There are generally three factors that enable airlines to hold on to the market. These factors are safety, service quality and price. Airline companies can analyze the customers in the market with a focus on price and quality and develop a business model according to their expectations. For example, business class and economy class passenger expectations are different from each other, so the service and price to be offered to them will be different. However, all customers have one common expectation and that is safety. No matter how high quality the service is or how cheap the price is, no one wants to fly with an airline or plane that is not safe. From an airline company’s point of view, an accident or breakdown of one of the company’s aircraft can cause irreparable image loss and financial damage. If we look at past examples, we see that there are many airline companies or maintenance organizations that could not recover after an accident and went bankrupt. Safety is an indispensable factor. Therefore, there is a unit in the sector called the safety management system (SMS), which collects data by taking a proactive and reactive approach. The way and purpose of the safety management system is to take a proactive approach to recognize and prevent unsafe situations before they cause accidents or breakdowns, or to take a reactive approach to find the causes of accidents and breakdowns that have occurred as a result of certain factors and to take the necessary measures to prevent the same situations from happening again in the sector. The field of data mining, which is necessary to predict the future behavior of customers in the field of marketing, is an area that marketing also values. In this study, data mining studies to ensure safety in the aviation industry and the security of customer information in marketing will be emphasized, firstly, the concept and importance of data mining will be mentioned.
References
[1]
Adigüzel, S. (2019) Customer Service Design in Airline Companies and Its Effect on Performance. Master’s Thesis, Institute of Social Sciences.
[2]
Gerede, Y.D.D.E. (2011) Türkiye’deki Havayolu Taşimaciliğina İlişkin Ekonomik Düzenlemelerin Havayolu İşletmelerine Etkisinin Değerlendirilmesi. Manisa Celal Bayar ÜniversitesiSosyalBilimlerDergisi, 9, 505-537.
[3]
Wells, A.T. (2007) Air Transportation: A Management Perspective. Ashgate Publishing, Ltd.
[4]
Gerede, E. (2015) Havayolu taşimaciliği ve ekonomik düzenlemeler teori ve Türkiye uygulamasi. Sivil Havacilik Genel Müdürlüğü Yayinlari, Ankara.
[5]
İpek, S. (2019) Investigation of Student Attitudes and Opinions towards Human Factors Module and Their Achievements in Aircraft Maintenance High Schools. http://acikerisim.akdeniz.edu.tr:8080/bitstream/handle/123456789/6443/T07089.pdf?sequence=1&isAllowed=y
[6]
Hand, D.J. (2007) Principles of Data Mining. DrugSafety, 30, 621-622. https://doi.org/10.2165/00002018-200730070-00010
[7]
Grossman, R., Kasif, S., Moore, R., Rocke, D. and Ullman, J. (1999) Data Mining Research: Opportunities and Challenges. A Report of Three NSF Workshops on Mining Large, Massive, and Distributed Data.
[8]
Mollaoğullari, Z. (2020) Analyzing International Conflicts with Social Network Analysis. Master’s Thesis, Institute of Social Sciences.
[9]
Chen, I.J. and Popovich, K. (2003) Understanding Customer Relationship Management (CRM). BusinessProcessManagementJournal, 9, 672-688. https://doi.org/10.1108/14637150310496758
[10]
Bardak, T. and Sözen, E. (2018) Data Mining and Its Importance. 6th ASM International Congress of Agriculture and Environment, 2018 Proceeding Book, Vol. 19, 419-427.
[11]
Dontha, R. (2018) Data Mining Steps Digital Transformation for Professionals. https://digitaltransformationpro.com/data-mining-steps/
[12]
Kahvecioğlu, S. (2018) Data Mining and Its Applications in Aviation: A Brief Overview of Present and Future. JournalofSustainableAviationResearch, 3, 1-9.
[13]
Sjöblom, O. (2010) Data Mining in Aviation Safety. IWSEC (ShortPapers), 132-148.
[14]
Evans, B., Glendon, A.I. and Creed, P.A. (2007) Development and Initial Validation of an Aviation Safety Climate Scale. JournalofSafetyResearch, 38, 675-682. https://doi.org/10.1016/j.jsr.2007.09.005
[15]
Netjasov, F. and Janic, M. (2008) A Review of Research on Risk and Safety Modelling in Civil Aviation. JournalofAirTransportManagement, 14, 213-220. https://doi.org/10.1016/j.jairtraman.2008.04.008
[16]
European Commission. Enterprise DG (2000) European Competitiveness Report. Office for Official Publications of the European Communities.
[17]
Liu, T. and Hu, A. (2017) Model of Combined Transport of Perishable Foodstuffs and Safety Inspection Based on Data Mining. FoodandNutritionSciences, 8, 760-777. https://doi.org/10.4236/fns.2017.87054
[18]
Sharma, S. and Sabitha, A.S. (2016) Flight Crash Investigation Using Data Mining Techniques. 2016 1stIndiaInternationalConferenceonInformationProcessing (IICIP), Delhi, 12-14 August 2016, 1-7. https://doi.org/10.1109/iicip.2016.7975390
[19]
Asgary, A., Ansari, S., Duncan, R. and Pradhan, S. (2015) Mapping Potential Airplane Hazards and Risks Using Airline Traffic Data. InternationalJournalofDisasterRiskReduction, 13, 276-280. https://doi.org/10.1016/j.ijdrr.2015.07.002
[20]
Lukacova, A., Babic, F. and Paralic, J. (2014) Building the Prediction Model from the Aviation Incident Data. 2014 IEEE 12thInternationalSymposiumonAppliedMachineIntelligenceandInformatics (SAMI), Herl’any, 23-25 January 2014, 365-369. https://doi.org/10.1109/sami.2014.6822441
[21]
Zhu, D.W. and Ni, Y. (2012) The Application of Data Mining in the Civil Aviation Accident Analysis. AppliedMechanicsandMaterials, 241, 3000-3004. https://doi.org/10.4028/www.scientific.net/amm.241-244.3000
[22]
Christopher, A.B.A., Vivekanandam, V.S., Anderson, A.B.A., Markkandeyan, S. and Sivakumar, V. (2016) Large-Scale Data Analysis on Aviation Accident Database Using Different Data Mining Techniques. TheAeronauticalJournal, 120, 1849-1866. https://doi.org/10.1017/aer.2016.107
[23]
Duvvuri, M.D., Borra, S.K., Yarlagadda, P. and Jaume, S. (2017) Transportation Analytics: A Study of Aviation Accidents and Flight Incidents. International Journal of Data Analysis and Information Systems, 90, 11-23.
[24]
Xiong, J., Yu, G. and Zhang, X. (2017) Research on Governance Structure of Big Data of Civil Aviation. JournalofComputerandCommunications, 5, 112-118. https://doi.org/10.4236/jcc.2017.55009
[25]
Berg, J.E. and Rietz, T.A. (2003) Prediction Markets as Decision Support Systems. InformationSystemsFrontiers, 5, 79-93. https://doi.org/10.1023/a:1022002107255
[26]
Köktürk, M.S. and Dirsehan, T. (2012) Marketing Interaction with Data Mining. Nobel Publishing.
[27]
Tasci, M.T. and Dal, N.E. (2022) Algorithmic Marketing. In: Baş, M., Tarakçı, İ.E. and Aslan, R., Eds., Digitalization, Efeakademi Publications, 317-357.
[28]
Kashwan, K.R. and Velu, C.M. (2013) Customer Segmentation Using Clustering and Data Mining Techniques. InternationalJournalofComputerTheoryandEngineering, 5, 856-861. https://doi.org/10.7763/ijcte.2013.v5.811
[29]
Haşıloğlu, S.B. (2022) Marketing Research and Analytics. Nobel Bilimsel Eserler.
