Havayolları İçin Karar Vermenin Değeri: Check-in'lerde Yolcu Tercihlerinin Bir Analizi

Year 2017, , 1 - 10, 28.04.2017

Doğuş Aygün , İlker Yılmaz , Sevinç Gülseçen

https://doi.org/10.22532/jtl.299879

Abstract

Havalimanlarındaki iş ortamının doğası operasyonların hızını önemli hale getirmiştir. Bu noktadan hareketle, havalimanlarındaki check-in alanları operasyonların hızının gözlemlenmesi için en önemli yer haline gelmiştir. Havayolu şirketleri check-in işlemleri için yolculara birçok yöntem sunmakla beraber self-check-in’lerde büyük bir artış söz konusudur. Bu aşamada karar verme devreye girmektedir. Bu çalışma, check-in’lerde yolcu tercihlerini analiz ederek havayolları için karar vermenin değerini ortaya koymaya yönelik bir girişimdir. Sayısal veriye dayanarak korelasyonel analiz yöntemi uygulanmış ve tüm hesaplamalarda RStudio kullanılmıştır. Sonuç olarak, bu analize dayanarak bazı kararlar verilmiştir.

Keywords

Karar Verme, Havayolu, Check-In

The Value of Decision Making to the Airlines: An Analysis of Passenger Preferences on Check-ins

Abstract

The nature of business environment in airports has made speed of operations crucial. From this standpoint, check-in areas in airports have become the most important place for monitoring the speed of operations. Airline companies offer many methods for check-in processes to the passengers and along with that there has been a huge increase in usage of self-check-ins. In this phase, decision making comes into play. This study is an attempt to reveal the value decision making for the airlines by analysing the passenger preferences on check-ins. Based on the quantitative data, correlational analysis method is performed and RStudio is used for all computations. Hence, some decisions are made based on that analysis.

Keywords

Decision Making, Airline, Check-In

References

• Adeoti‐Adekeye, W. B. (1997). The importance of management information systems. Library Review, 46(5), 318–327. https://doi.org/10.1108/00242539710178452
• Asemi, A., Safari, A., & Zavareh, A. A. (2011). The Role of Management Information System (MIS) and Decision Support System (DSS) for Manager’s Decision Making Process. International Journal of Business and Management, 6(7), 164–173. https://doi.org/10.5539/ijbm.v6n7p164
• Banerjee, A. (2005). Financial Accounting. New Delhi: Excel Books India.
• Barich, F. (2011). Guide to the Decision-Making Tool for Evaluating Passenger Self-Tagging (Airport Cooperative Research Program (ACRP) No. 41). Washington, D.C.: Transportation Research Board.
• Bewick, V., Cheek, L., & Ball, J. (2003). Statistics review 7: Correlation and regression. Critical Care, 7(6), 451. https://doi.org/10.1186/cc2401
• Bruce, P. J. (2016). Understanding Decision-making Processes in Airline Operations Control. New York, NY: Routledge.
• Chang, H.-L., & Yang, C.-H. (2008). Do airline self-service check-in kiosks meet the needs of passengers? Tourism Management, 29(5), 980–993. https://doi.org/10.1016/j.tourman.2007.12.002
• Curry, A., Flett, P., & Hollingsworth, I. (2006). Managing Information and Systems: The business perspective. London&New York: Routledge.
• Edwards, B. (2005). The Modern Airport Terminal: New Approaches to Airport Architecture. London: Spon Press.
• Gross, S., & Schröder, A. (2007). Handbook of Low Cost Airlines: Strategies, Business Processes and Market Environment. Berlin: Erich Schmidt Verlag GmbH & Co.
• Halpern, N., & Graham, A. (2013). Airport Marketing. New York, NY: Routledge.
• Hauke, J., & Kossowski, T. (2011). Comparison of Values of Pearson’s and Spearman’s Correlation Coefficients on the Same Sets of Data. Quaestiones Geographicae, 30(2). https://doi.org/10.2478/v10117-011-0021-1
• Helsel, D. R., & Hirsch, R. M. (1992). Statistical Methods in Mater Resources. Amsterdam: Elsevier.
• Holmes, W. H., & Rinaman, W. C. (2014). Statistical Literacy for Clinical Practitioners. Switzerland: Springer.
• Hung, Y.-F., & Chen, C.-H. (2013). An effective dynamic decision policy for the revenue management of an airline flight. International Journal of Production Economics, 144(2), 440–450. https://doi.org/10.1016/j.ijpe.2013.03.012
• Jawadekar, W. S. (2013). Management Information Systems: Text and Cases: a Global Digital Enterprise Perspective (5th ed.). New Delhi: McGraw Hill Education.
• Kisielnicki, J. A., & Gwiazda, E. (2007). How the Application of Management Information System (MIS) Affects Business Value (BV) in the Airline Industry. In Managing Worldwide Operations and Communications with Information Technology (pp. 691–696). Retrieved from http://www.irma-international.org/viewtitle/33166/
• Lee, W., Castellanos, C., & Chris Choi, H. S. (2012). The Effect of Technology Readiness on Customers’ Attitudes toward Self-Service Technology and Its Adoption; The Empirical Study of U.S. Airline Self-Service Check-In Kiosks. Journal of Travel & Tourism Marketing, 29(8), 731–743. https://doi.org/10.1080/10548408.2012.730934
• Lee-Partridge, J. E., & Law, D. L. F. (2004). Enterprise Modelling and Organizational Learning: An Interpretative Study. In Innovations Through Information Technology. Idea Group Inc (IGI).
• Lin, J.-S. C., & Hsieh, P.-L. (2006). The role of technology readiness in customers’ perception and adoption of self-service technologies. International Journal of Service Industry Management, 17(5), 497–517. https://doi.org/10.1108/09564230610689795
• Lipaj, D., & Davidavičienė, V. (2013). Influence of Information Systems on Business Performance. Science–Future of Lithuania/Mokslas–Lietuvos Ateitis, 5(1), 38–45. https://doi.org/10.3846/mla.2013.06
• Lucey, T. (2005). Management Information Systems (9th ed.). London: Thomson Learning.
• Mukaka, M. M. (2012). A guide to appropriate use of correlation coefficient in medical research. Malawi Medical Journal, 24(3), 69–71.
• O’Connell, J. F. (2016). Air Transport in the 21st Century: Key Strategic Developments. New York, NY: Routledge.
• Purnell, J. (2012). Information Technology Systems at Airports-A Primer (Airport Cooperative Research Program (ACRP) No. 59). Washington, D.C.: Transportation Research Board. Retrieved from http://www.trb.org/Publications/Blurbs/166592.aspx
• Royston, J. P. (1983). Some Techniques for Assessing Multivarate Normality Based on the Shapiro-Wilk W. Journal of the Royal Statistical Society. Series C (Applied Statistics), 32(2), 121–133. https://doi.org/10.2307/2347291
• RStudio Team. (2015). RStudio (Version 0.99.891). Boston, MA: RStudio Inc.
• Schultz, M., Schulz, C., & Fricke, H. (2010). Passenger Dynamics at Airport Terminal Environment. In Pedestrian and Evacuation Dynamics 2008 (pp. 381–396). Springer. Retrieved from http://link.springer.com/chapter/10.1007/978-3-642-04504-2_33
• Sedgwick, P. (2012). Pearson’s correlation coefficient. BMJ, 345, e4483. https://doi.org/10.1136/bmj.e4483
• Stair, R., & Reynolds, G. (2013). Principles of Information Systems (11th ed.). Boston, MA: Cengage Learning.
• Ueda, K., & Kurahashi, S. (2014). How passenger decides a check-in option in an airport: Self-Service Technology Adoption model in passenger process. In Proceedings of the Social Simulation Conference. Barcelona, Catalunya (Spain). Retrieved from http://ddd.uab.cat/pub/poncom/2014/125597/advcomsocsci_a2014.pdf
• Weisburd, D., & Britt, C. (2007). Statistics in Criminal Justice (3rd ed.). New York, NY: Springer Science & Business Media.
• Wright, A. (2004). Reward Management in Context. London: CIPD.
• Wu, H.-C., & Cheng, C.-C. (2013). A hierarchical model of service quality in the airline industry. Journal of Hospitality and Tourism Management, 20, 13–22. https://doi.org/10.1016/j.jhtm.2013.05.001