Kent içi otobüs memnuniyet anketi verileri ve faktör analizinden yararlanılarak otobüslerin hizmet kalitesinin modellenmesi: İETT örneği

Abstract

Hizmet kalitesi, 1980’lerden bu yana, önemli bir konu olarak değerlendirilmektedir. Kişiden kişiye farklılık gösterebildiği ve somut bir çıktı üretmediği için, hizmet kalitesinin ölçümü, ürün kalitesine kıyasla daha zordur. Hizmet kalitesinin değerlendirilmesi için, literatürde çok sayıda model geliştirilmiştir. Ulaştırma iş kolu, hizmet iş kolunun önde gelen bileşenlerinden birisidir. Toplu taşımanın kalitesinin arttırılması, kentlerin gelişiminde ve özel araç kullanımının toplu ulaşıma yönlendirilmesinde kuvvetli bir etkendir. Otobüs hizmetlerinin kalitesi, toplu ulaşımın kalitesinin ölçülmesine olanak sağlayan TS-EN 13816 Standardına göre tanımlanmıştır. İstanbul’da otobüsler için hizmet kalite ölçütleri belirlenmiş olup performansları sistematik bir şekilde ölçülmektedir. Bu çalışma kapsamında, otobüs hizmetlerinin kalitesinin değerlendirmek için, İETT tarafından internet üzerinden kullanıcılara uygulanan memnuniyet anketlerinin 2177 tanesinin sonuçları kullanılarak faktör analizi uygulanmış ve çoklu doğrusal regresyon modeli oluşturulmuştur. Ortaya çıkan 2 faktör incelendiğinde, kullanıcıların hizmete erişime, konfordan daha fazla önem verdikleri ortaya çıkmıştır. Ayrıca, kullanıcı anketlerinin sonuçları, hizmet sağlayıcıların görüşleri ile karşılaştırılmış, iki kesimin görüşü arasında yalnızca %1.733’lik fark gözlemlenmiştir.

Keywords

• Otobüs hizmetleri,Kalite değerlendirilmesi,Hizmet kalitesi,Faktör analizi,Çoklu doğrusal regresyon

Modelling the quality of bus services by using factor analysis on urban bus satisfaction survey data: Case of IETT

Abstract

Service quality has been regarded as an important issue since the 1980s. The measurement of service quality is harder than the quality of the product, since it varies from person to person and produces no concrete output. A number of models have been developed in the literature to assess service quality. The transportation sector is one of the leading components of the service sector. Increasing the quality of public transport has a strong influence in the development of cities and decreasing the usage of private cars. The quality of bus services is defined in accordance with TS-EN 13816 Standard, which allows measurement of the quality of public transport. In Istanbul, service quality criteria for buses are determined and their performance is measured systematically. In this study, factor analysis was applied to evaluate the quality of the bus services using the results of the Satisfaction Surveys applied by IETT to 2177 users on the internet and a multiple linear regression model was developed. When the two emerging factors are examined, it is seen that users pay more importance to access to the service than the comfort. In addition, the results of user surveys were compared with the views of service providers, and a difference of only 1.733% was observed between the two groups’ views.

Keywords

• Bus services,Quality evaluation,Service quality,Factor analysis,Multiple linear regression

References

1. Department of Territory and Municipal Services. “Delivery of Action, Bus Services Report”. Department of Territory and Municipal Services, Australia, 5, 2010.
2. Noor HM, Nasrudin N, Foo J. “Determinants of customer satisfaction of service quality: City bus service in Kota Kinabalu, Malaysia”. Social and Behavioral Sciences, 153, 595-605, 2014.
3. Islam R, Chowdhury MS, Sarker MS, Ahmed S. “Measuring customer’s satisfaction on bus transportation”. American Journal of Economics and Business Administration, 6(1), 34-41, 2014.
4. Directorate-General Mobility and Transport and Co-ordinated by the Directorate General for Communication, “Europeans’ Satisfaction with Urban Transport”. Transport for NSW, England, 59739, 2014.
5. Liu R, Sinha S. ‘’Modelling urban bus service and passenger reliability". 3rd International Symposium on Transportation Network Reliability (INSTR), Delft, Holland, 19-20 June 2007.
6. Chen X, Yu L, Zhang Y, Guo J. "Analyzing urban bus service reliability at the stop, route, and network levels". Transportation Research Part A, 43, 722-734, 2009.
7. Özuysal M, Uzunoğlu UZK, Akpulat N, Çalışkanelli SP, Tanyel S, Ceylan H. 2015. “Akıllı Kart Verilerine Dayalı Güvenilirlik Ölçütlerinin Toplu Ulaşım Atama Modellerine Entegrasyonu”. TÜBİTAK Projesi Final Raporu, Ankara, Türkiye, 112M117, 2015.
8. Verbich D, Geneidy A. “The pursuit of satisfaction: Variation in satisfaction with bus transit service among riders with encumbrances and riders with disabilities using a large-scale survey from London, UK”. Transport Policy, 47, 64-71, 2015.

9. Rohani MM, Wijeyesekera DC, Karim AT. “Bus operation, quality service and the role of bus provider and diver”. Procedia Engineering, 53, 167-178, 2013.
10. Luhua S, Yin H, Xinkai J. “Study on method of bus service frequency optimal model based on genetic algorithm”. Procedia Environmental Sciences, 10, 869-874, 2011.
11. Bais NS, Pitale N, Thorat S. “Optimal schedule modeling for public transportation system”. International Journal of Science and Research (IJSR), 4(4), 2053-2056, 2013.
12. Hema DD, Angeline R. “Frequency of buses determination model and bus schedule in Chennai metro transport for ITS based system”. International Journal of Emerging Technology and Advanced Engineering, 4, 118-124, 2014.
13. Scottish Government. “Bus Punctuality Improvement Partnerships (BPIPs) Guidance”. Scottish Government, Edinburgh, Scotland, RR Donnelley, 2009.
14. Urban Transport Group (Pteg). “Bus Punctuality”. Urban Transport Group, London, UK, 2014.
15. Napiah M, Kamaruddin I, Suwardo . “Punctuality index and expected average waiting time of stage buses in mixed traffic”. Urban Transport, 116, 215-226, 2015.
16. McKnight CE, Levinson HS, Ozbay K, Kamga C, Paaswell RE. “Impact of traffic congestion on bus travel time in Northern New Jersey”. Transportation Research Record, 1884, 27-35, 2004.
17. Department for Transport Framework for Transport Related Technical Engineering Advice and Research. “Bus Journey Time Variability in Urban Areas”. Department for Transport Framework for Transport Related Technical Engineering Advice and Research, BK, 2015.
18. Amita J, Singh JS, Kumar GP. “Prediction of bus travel time using artificial neural network”. International Journal for Traffic and Transport Engineering, 4, 410-424, 2015
19. Victoria Transport Policy Institute. “Transportation Cost and Benefit Analysis II-Travel Time Costs”. Victoria Transport Policy Institute, Canada, 2017.
20. Joewono TB, Kubota H. “Safety and security improvement in public transportation based on public perception in developing countries”. IATSS Research, 30(1), 86-100, 2006.
21. American Public Transportation Association (APTA). “The Hidden Traffic Safety Solution: Public Transportation”. American Public Transportation Association, Washington, USA, 2016
22. European Transport Safety Council. “Transport Safety Performance in the EU, a Statistical Overview”. European Transport Safety Council, Bruxelles, Belgium, 2003.
23. Federal Transit Administration (FTA). “Review and Evaluation of Public Transportation Safety Standards”. Federal Transit Administration, Washington, USA, 2017.
24. Gökaşar I, Dündar S, Buran B. “Yolcu ihtiyaçlarının incelenmesi, İETT örneği”. Transist 2017 Uluslararası İstanbul Ulaşım Kongresi ve Fuarı, İstanbul, Türkiye, 2-4 Kasım, 2017.
25. Albayrak AS. Lojistik Regresyon Analizi. Editör: Kalaycı Ş. SPSS Uygulamalı Çok Değişkenli İstatistik Teknikleri, 273-300, Ankara, Türkiye, Asil Yayın Dağıtım, 2014.
26. Kalaycı Ş. Faktör Analizi. Editör: Kalaycı Ş. SPSS Uygulamalı Çok Değişkenli İstatistik Teknikleri, 321-334, Ankara, Türkiye, Asil Yayın Dağıtım, 2014.
27. Hair JF, Anderson RE, Tatham RL, Black WC. Multivariate Data Analysis, Prentice Hall, New Jersey, USA, 1998.
28. Sharma S. Applied Multivariate Techniques, John Wiley & Sons Inc., New York, USA, 1996.
29. Büyüköztürk Ş. “Faktör analizi: Temel kavramlar ve ölçek geliştirmede kullanımı”. Kuram ve Uygulamada Eğitim Yönetimi, 32, 470-483, 2002.
30. Dunteman GH. Principal Components Analysis. Thousand Oaks, CA, USA, Sage Publications, 1989.