Determination of Factors Affecting Transportation Mode Choice of Turkish Domestic Airline Passengers

Yıl 2024, Cilt: 8 Sayı: 2, 166 - 174, 27.06.2024

Mevlüt Üzülmez , Ali Emre Sarılgan

https://doi.org/10.30518/jav.1443263

Öz

Increasing demand in the transportation sector is closely related to the level of meeting passengers' demands. For this reason, many studies are being carried out in many parts of the world, especially in European and Far Eastern countries, aiming to determine the factors that affect passengers' choice of transportation mode. The aim of this study is to determine the main and sub factors affecting the choice of transportation mode for domestic airline passengers traveling in Türkiye. Within the scope of the study, a face-to-face survey was conducted to 407 passengers at Sabiha Gökçen Airport. Then, exploratory factor analysis was performed with the obtained data. Three main factors that emerged as a result of the analysis were named "Trip Factor", "Transportation Mode Factor" and "Safety and Comfort Factor", taking into account the literature review, expert opinions and the characteristics of the items. While on-time departure / punctuality, total travel time and travel at the requested time are the variables that have the highest impact on the choice of transportation mode. Previous accidents/incidents, transportation cost to airport/station and entertainment service in the cabin/wagon emerged as the variables with the lowest impact.

Anahtar Kelimeler

Transportation Mode Choice, Airline Passenger, Aviation Safety, Aviation Management, Exploratory Factor Analysis

Kaynakça

• Alpar, C. R. (2016). Applied Statistics and Validity Reliability with Examples from Sports, Health and Educational Sciences. Detay Publish.
• Banister, D., & Berechman, J. (2000). Transport Investment and EconomicDevelopment. London: UCL Press.
• Belobaba, P., Odoni, A., & Barnhart, C. (2015). The global airline industry. John Wiley & Sons.
• Behrens, C., & Pels, E. (2012). Intermodal competition in the London–Paris passenger market: High-Speed Rail and air transport. Journal of Urban Economics, 71(3), 278-288.
• Boonekamp, T., Zuidberg, J., & Burghouwt, G. (2018). Determinants of air travel demand: the role of low-cost carriers, ethnic links and aviation-dependent employment. Transport. Res. Pol. Pract, 18-28.
• Boonekamp, T., Zuidberg, J., & Burghouwt, G. (2018). Determinants of air travel demand: the role of low-cost carriers, ethnic links and aviation-dependent employment. Transport. Res. Pol. Pract, 18-28.
• Budd, L., & Ison, S. (2017). Air transport management. Routledge.
• Buehler, R. (2011). Determinants of transport mode choice: a comparison of Germany and the USA. Journal of transport geography, 19(4), 644-657.
• Buhalis, D., & Law, R. (2008). Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research. Tourism management, 29(4), 609-623.
• Capik, C., Gozum, S., & Aksayan, S. (2002). A guide for trans-cultural scale adaptation, I: steps of a scale adaptation and psycholinguistic adaptation. Turkish J Nurs. Res, 9-14.
• Chang, Y. C. (2013). Factors affecting airport access mode choice for elderly air passengers. Transportation research part E: logistics and transportation review, 57, 105-112.
• Chen, Z., Liu, X., Chin, K., Pedrycz, W., Tsui, K., & Skibniewski, M. (2021). Online-review analysis based large-scale group decision-making for determining passenger demands and evaluating passenger satisfaction: Case study of high-speed rail system in China. Information Fusion, 22-39.
• Chen, Z.-S., Liu, X.-L., Rodríguez, R., Wang, X.-J., Chin, K.-S., Tsui, K.-L., & Martínez, L. (2020). Identifying and prioritizing factors affecting in-cabin passenger comfort on high-speed rail in China: A fuzzy-based linguistic approach. Applied Soft Computing.
• Conroy, R. M. (2018). The RCSI Sample size handbook A rough guide.
• Dalkic, G., Balaban, O., Tuydes-Yaman, H., & Celikkol-Kocak, T. (2017). An assessment of the CO2 emissions reduction in high speed rail lines: Two case studies from Turkey. Journal of Cleaner Production, 746-761.
• David Mc A, B. (2013). Service quality and customer satisfaction in the airline industry: A comparison between legacy airlines and low-cost airlines. American journal of tourism research, 2(1), 67-77.
• Demirsoy, Ç. (2012). Analysis of stimulated domestic air transport demand in turkey. Rotterdam: Erasmus University, Master Thesis.
• Duval, D., & Schiff, A. (2011). Effect of air services availability on international visitors to New Zealand. J. Air Transport. Manag., 17 (3), 175-180.
• Field, A. (2005). Discovering Statistics, 1st. Ed. London: Sage Publication.
• Field, A. (2013). Discovering statistics using IBM SPSS statistics. sage.
• Findlay, C. C., Chia, L., & Singh, K. (1997). Asia Pacific Air Transport: Challenges and Policy Reforms. Singapore: Institue of southeast asian studies.
• Francis, G., Humphreys, I., Ison, S., & Aicken, M. (2006). Where next for low cost airlines? A spatial and temporal comparative study. Journal of Transport Geography, 14(2), 83-94.
• George, D., & Mallery, M. (2010). SPSS for Windows Step by Step: A Simple Guide and Reference, 17.0 update (10a ed.). Boston: Pearson.
• Ghosh, R., & Terekhov, I. (2015). Future passenger air traffic modelling: trend analysis of the global passenger air travel demand network. In: 53rd AIAA Aerospace Sciences Meeting, (January).
• Gürsoy, M., Kuşakcı, S., Tanrıverdi, S., & Akyıldız, G. (2020). An Analysis for Mode Choice Preferences Between Ankara and Istanbul. Sigma Journal of Engineering and Natural Sciences, 727-739.
• Hazledine, T. (2017). An augmented gravity model for forecasting passenger air traffic on city-pair routes. J. Transport Econ. Dresnerand Pol., 208–224.
• Hensher, D. A. (2001). The valuation of commuter travel time savings for car drivers: evaluating alternative model specifications. Transportation, 28, 101-118.
• Islamoglu, H., & Alniacik, U. (2019). Research Methods in Social Sciences 6th edition. Beta.
• Karasar, N. (2005). Scientific Research Methods. Nobel Publish.
• Kline, P. (1994). An Easy Guide to Factor Analysis, 1st. Ed. New York: British Library.
• Kline, R. B. (2016). Principles and Practice of Structural Equation Modeling. Newyork: The Guilford Press.
• Koo, T., Lim, C., & Dobruszkes, F. (2017). Causality in direct air services and tourism demand. Ann. Tourism Res., 67 (9), 67-77.
• Koo, T., Tan, D., & Duval, D. (2013). Direct air transport capacity and demand interaction: a vector error correction approach. J. Air Transport. Manag., 28 (5), 14-19.
• Kopsch, F. (2012). A demand model for domestic air travel in Sweden. J. Air Transport. management, 46-48.
• Lee, J., Kim, S., & Sim, G. (2019). Mode choice behavior analysis of air transport on the introduction of remotely piloted passenger aircraft. Journal of Air Transport Management, 76, 48-55.
• Li, Z., & Sheng, D. (2016). Forecasting passenger travel demand for air and high-speed rail integration service: a case study of Beijing-Guangzhou corridor, China. Transport Res. Pol. Pract., 397–410.
• Li, X., Tian, X., & Li, X. (2016). Multi-mode choice behavior for passenger in comprehensive transportation corridor. Procedia engineering, 137, 849-857.
• Liu, C. P. (2017). Understanding the factors influencing public transport mode choice in Taiwan (Doctoral dissertation, UCL (University College London)).
• Loo, B. P. (2008). Passengers’ airport choice within multi-airport regions (MARs): some insights from a stated preference survey at Hong Kong International Airport. Journal of transport geography, 16(2), 117-125.
• Macit, A. (2020). Creating Loyal Customers by Pricing with Unit Cost in Airline Business: A Strategy Proposal for Business Purposes Traveling Passengers. Ordu University Social Sciences Institute Journal of Social Sciences Research, 10(3), 931-940.
• Marzuoli, A., Emmanuel, B., Feron, E., van Erp, P., Alexis, U., Bayen, A., & Hansen, M. (2014). Anatomy of a Crash. arXiv.
• Nadeeshan, S. R., & Mudunkotuwa, M. R. S. (2018). Factors affecting the selection of a mode of passenger transportation in the Colombo metropolitan area.
• Pagliara, F., Vassallo, J., & Román, C. (2012). High-Speed Rail versus Air Transportation: Case Study of Madrid– Barcelona, Spain. Journal of the Transportation Research Board, 10-17.
• Park, Y., & Ha, H.-K. (2006). Analysis of the impact of high-speed railroad service on air transport demand. Transportation Research Part E 42, 95–104.
• Phang, S.-Y. (2003). Strategic development of airport and rail infrastructure: the case of Singapore. Transport Policy 10, 27–33.
• Proussaloglou, K., & Koppelman, F. (1999). The choice of air carrier, flight, and fare class. Journal of Air Transport Management, 193-201.
• Proussaloglou, K., & Koppelman, F. (1999). The choice of air carrier, flight, and fare class. Journal of Air Transport Management, 193-201.
• Rimjha, M., Hotle, S., Trani, A., Hinze, N., & Smith, J. C. (2021, April). Urban air mobility demand estimation for airport access: A Los Angeles international airport case study. In 2021 Integrated Communications Navigation and Surveillance Conference (ICNS) (pp. 1-15). IEEE.
• Saatcioglu, C., & Yasarlar, Y. (2012). Public Transportation Systems in Urban Transport: In the Case of Istanbul. Kafkas University, Journal of Economics and Administrative Sciences Faculty, 117-144.
• Shi, J., Hussain, M., & Kong, X. (2022). Factors Affecting Travel Mode Choice between High-speed Railway and Air Transportation among University Students for Tourism-Evidence from China. Journal of China Tourism Research, 18(1), 106-120.
• Silla, A., & Kallberg, V. (2012). (). The development of railway safety in Finland. Accident Analysis & Prevention, 45, 737-744.
• Sofany, A. (2016). Determinants of Domestic Air Transport Demand in Ethiopia. Ethiopia: Addis Ababa University.
• Su, M., Luan, W., Yuan, L., Zhang, R., & Zhang, Z. (2019). Sustainability Development of High-Speed Rail and Airline—Understanding Passengers’ Preferences：A Case Study of the Beijing–Shanghai Corridor. Sustainability.
• Szatmári, M. (2021). Proposal AHP method for increasing the security level in the railway station. D, 55, 1681- 1688. Transportation research procedia, 55, 1681-1688.
• Tavsancil, E. (2019). Measurement of Attitudes and Data Analysis with SPSS 6. edition. Nobel Academic Publish.
• Tengilimoglu, E., & Ozturk, Y. (2021). The Effect of Price Justice and Consumption Emotions on PWOM Intentions in Leisure and Business Travels. Journal of Turkish Tourism Research, 1815-1832.
• Tveteras, S., & Roll, K. (2014). Non-stop flights and tourist arrivals. Tourism Econ., 20 (1), 5-20.
• Tyrinopoulos, Y., & Antoniou, C. (2013). Factors affecting modal choice in urban mobility. European Transport Research Review, 5, 27-39.
• Wang, S., & Gao, Y. (2021). A literature review and citation analyses of air travel demand studies published between 2010 and 2020. Journal of Air Transport Management, 1-15.
• Wang, S., & Gao, Y. (2021). A literature review and citation analyses of air travel demand studies published between 2010 and 2020. Journal of Air Transport Management, 1-15.
• Wei, Y., Guo, Y., Dong, D., & Li, D. (2012). Public places safety management evaluation of railway stations. Procedia Engineering, 240-247.
• Wensveen, J. (2023). Air Transportation: A Global Management Perspective. Routledge.
• Xia, W., & Zhang, A. (2016). High-speed rail and air transport competition and cooperation: A vertical differentiation approach. Transportation Research Part B: Methodological, 456-481.
• Yang, H., & Zhang, A. (2012). Effects of high-speed rail and air transport competition on prices, profits and welfare. Transportation Research Part B: Methodological, 1322-1333.
• Yoo, K. E. (1995). A study of Korean air passengers' choice behaviour utilising stated preference and revealed preference methods. İngiltere: Loughborough University of Technology.
• Zhang, Y., & Findlay, C. (2014). Air transport policy and its impacts on passenger traffic and tourist flows. J. Air Transport. Manag., 42-48.
• Zhang, A., Wan, Y., & Yang, H. (2019). Impacts of high-speed rail on airlines, airports and regional economies: A survey of recent research. Transport Policy, 1-19.