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Investigating the Service Quality of Kocaeli Tram Service Using Artificial Neural Networks

Year 2022, Volume: 33 Issue: 5, 12429 - 12456, 01.09.2022

Selim Dündar

https://doi.org/10.18400/tekderg.783110

Abstract

Service quality is one of the main issues that today's world. Firms operating in the transportation sector are also trying to improve the quality of the service they provide to their passengers. It is crucial to determine the passengers' service quality perceptions and priorities to evaluate and improve the service in this context. In this study, Kocaeli's tram service users' service quality perceptions have been evaluated by applying a survey consisting of 20 questions and user satisfaction levels from different service dimensions. Later, an artificial neural network model was developed using the users' demographic data and their responses to the survey questions to mimic their service quality satisfaction. The artificial neural network model developed has been examined to understand the importance that tram users give to service quality. Using the developed the “change of score” method, how the changes to be made in the tram system will affect the quality of service and how the opinions of different user groups will be affected can be examined in detail. The artificial neural network model's prediction capability was compared with the multiple linear regression model and found superior. According to the developed Change of Score Method, the most frequent user attaches the highest importance to the service dimensions of the convenience to pay for the tram, getting his/her destination on time, and reducing environmental pollution.

Keywords

Service Quality Public Transportation Artificial Neural Networks Tram Services Transportation Planning Transportation Modelling

Supporting Institution

-

Thanks

The author would like to thank the graduate thesis students Damla Yaşar and Cihan Bahadır Yaşar for their contribution in the process of collecting and evaluating the survey data.

References

  • Yaşar, D., Kocaeli tramvay sistemi kullanıcı memnuniyetinin incelenmesi, M.Sc. Thesis, İstanbul Okan Üniversitesi, 2020 (In Turkish).
  • Dell’Olio, L., Ibeas, A., Cecin, P., The quality of service desired by public transport users. Transport Policy., 18(1), 217-227, 2011.
  • Friman, M., Fellesson, M., Service supply and customer satisfaction in public transportation: The quality paradox. Journal of Public Transportation., 12(4), 57–69, 2009.
  • Benchmarking in European Service of public Transport (BEST), Results of the 2004 survey, http://benchmarkingpublictransport.org/content/download/292/1328/file/Report%20BEST%20Survey%20-%202004.pdf, 2004. Accessed 08 August 2020.
  • Eboli, L., Mazzulla, G., Service quality attributes affecting customer satisfaction for bus transit. Journal of public transportation., 10 (3), 21-34, 2007.
  • Noor, H.M., Nasrudin, N., Foo, J., Determinants of Customer Satisfaction of SQ: City Bus Service in Kota Kinabalu, Malaysia. Procedia - Social and Behavioural Sciences., 153, 595-605, 2014.
  • Islam, R., Chowdhury, M.S., Sarker, M.S., Ahmed, S., Measuring Customer’s Satisfaction on Bus Transportation. American Journal of Economics and Business Administration., 6(1), 34-41, 2014.
  • Directorate General Mobility and Transport and Co-ordinated by the Directorate General for Communication. Europeans’ Satisfaction with Urban Transport, England, Transport for NSW., https://ec.europa.eu/commfrontoffice/publicopinion/flash/fl_382b_en.pdf, 2014, Accessed 08 August 2020.
  • 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(1), 64-71, 2015.
  • Ardıç, K., Sadaklıoğlu, H., Şehirlerarası yolcu taşımacılığında hizmet kalitesinin ölçümü: Tokat örneği. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi., 23(3), 167-190, 2009 (In Turkish).
  • İmre, Ş., Çelebi, D., Measuring comfort in public transport: a case study for İstanbul. Transportation Research Procedia., 25, 2441-2449, 2017.
  • Özuysal, M., Tanyel, S., Oral, M.Y., Fayda esaslı erişilebilirliğin ulaşım türü seçimi üzerindeki etkisi. İMO Teknik Dergi., 23(113), 5987-6016, 2012 (In Turkish).
  • Doğan, G., Özuysal, M., Toplu ulaşımda bekleme süresini etkileyen faktörlerin incelenmesi: Güvenilirlik, yolcu bilgilendirme sistemi ve fiziksel koşullar. İMO Teknik Dergi., 28(3), 7927-7975, 2017 (In Turkish).
  • Kahraman, Ç., Yıldız, M.S., Şehirlerarası otobüs işletmelerinde hizmet kalitesinin ölçülmesi ve bir uygulama. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi., 23(2), 121-144, 2005 (In Turkish).
  • Koçoğlu, C.M., Aksoy, R., Hizmet kalitesinin servperf yöntemi ile ölçülmesi: otobüs işletmeleri üzerinde bir uygulama. Akademik Bakış Dergisi., 29(1), 1-25, 2012 (In Turkish).
  • Gökaşar, I., Dündar, S., Buran, B., Yolcu ihtiyaçlarının incelenmesi. İETT Örneği. İBB Transist 2017 Bildiri Kitabı., 2-4 Kasım, İstanbul, 386-395, 2017 (In Turkish).
  • Gökaşar, I., Buran, B., Dündar, S., Kent içi otobüs memnuniyet anketi verileri ve faktör analizinden yararlanılarak otobüslerin hizmet kalitesinin modellenmesi: İETT örneği. Pamukkale Üniv Müh Bilim Derg., 24(6), 1079-1086, 2018 (In Turkish).
  • Girginer, N., Cankuş, B., Tramvay yolcu memnuniyetinin lojistik regresyon analiziyle ölçülmesi: Estram örneği. Yönetim ve Ekonomi: Celal Bayar Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi., 15(1), 181-193, 2008 (In Turkish).
  • Hemedoğlu, E., Toplu taşımacılık sektöründe hizmet kalitesini ölçme: Algılanan hizmet kalitesi ve müşterinin arzuladığı hizmet kalitesi üzerindeki etkileri (Master Thesis). Yıldız Technical University, Graduate School of Natural and Applied Sciences, Istanbul, Turkey, 2010 (In Turkish).
  • Seçilmiş, C., Kaşlı, M., Kılıçlar, A., Sarı, Y., The effect of quality at railway services on customer satisfaction in terms of fee paid. Ege Academic Review., 11(4), 573-586, 2011 (In Turkish).
  • Akyıldız Alçura, G., Kuşakçı, S.Ş., Gölbaşı Şimşek, G., Gürsoy, M., Tanrıverdi, S.C., Impact score technique for analyzing the service quality of a high-speed rail system. Transportation Research Record: Journal of the Transportation Research Board., 2541(1): 64-72, 2016.
  • Šojat, D., Brcic, D., Slavulj, M., Analysis of public transport service improvements on tram network in the City of Zagreb. Tehnički vjesnik., 24, 217-223, 2017.
  • Vujičić, M., Prester, J., Assessing service quality of public tram transport in Zagreb city using P-TRANSQUAL mode. Zbornik Ekonomskog fakulteta u Zagrebu., 17, 19-31, 2019.
  • Khelf, M., Boukebbab, S., Bhouri, N., Boulahlib, M.S. Tram Service Quality and Its Impact on the Passengers’ Modal Choice in Constantine City (Algeria), Selected Papers from the 18th International Conference on Reliability and Statistics in Transportation and Communication, RelStat’18, 17-20 October 2018, Riga, Latvia, 2018.
  • De Oña, R., De Oña, J., Neural Networks for Analyzing Service Quality in Public Transportation. Expert Systems with Applications., 41(15), 6830–6838, 2014.
  • Islam, M.R., Hadiuzzaman, M., Banik, R., Hasnat, M.M., Musabbir, S.R, Hossain, S., Bus Service Quality Prediction and Attribute Ranking: a Neural Network Approach. Public Transport., 8(1), 295–313, 2016.
  • International Bus Benchmarking Group (IBBG), https://busbenchmarking.org. Accessed 08 August 2020.
  • Acar, S., Bilen Kazancık, L., Meydan, M.C., Işık, M., İllerin ve bölgelerin sosyo-ekonomik gelişmişlik sıralaması araştırması SEGE-2017., Kalkınma Ajansları Genel Müdürlüğü Yayını Sayı: 3 2018 (In Turkish).
  • KBB Ulaşım Dairesi Başkanlığı., Akçaray güzergay haritası, 2017
  • Turkish Statistical Institute TSI, Outcomes of Address Based Population Registration System 2018. TUIK, Ankara, Turkey, 2019 https://biruni.tuik.gov.tr/medas/?kn=95&locale=tr. Accessed 08 August 2020.
  • Meyer, J.T., Fundamental Research Statistics for the Behavioural Sciences., New York: Holt Rinehart & Winston, 1979.
  • Fox, N., Hunn, A., Mathers, N., Sampling and Sample Size Calculation. The NIHRRDS for the East Midlands / Yorkshire & the Humber, 2007.
  • Dündar, S., Şahin, İ., Train re-scheduling with genetic algorithms and artificial neural networks for single-track railways. Transportation Research Part C: Emerging Technologies Volume 27(1), 1-15, 2013.
  • Yardım, M.S., Değer Şitilbay, B., Dündar, S., Modelling the effects of hydrated lime additives on asphalt mixtures by fuzzy logic and ANN. Teknik Dergi, Vol. 30(6), 9533-9559, 2019.
  • Murat, Y.Ş., Başkan, Ö., Modelling vehicle delays at signalized junctions: Artificial neural networks approach. Journal of Scientific & Industrial Research, Vol. 65(1), 558-564,2006.
  • Osuna, R.G., CS790: Selected Topics in Computer Science, Lecture Notes, Texas A&M University, 2002.
  • Murat, Y.Ş., Comparison of fuzzy logic and artificial neural networks approaches in vehicle delay modeling. Transportation Research Part C Vol. 14(1), 316–334, 2006.
  • Kaya Uyanık, G., Güler, N., A study on multiple linear regression. Procedia - Social and Behavorial Sciences, Vol. 106, 234-240, 2013.

Investigating the Service Quality of Kocaeli Tram Service Using Artificial Neural Networks

Year 2022, Volume: 33 Issue: 5, 12429 - 12456, 01.09.2022

Selim Dündar

https://doi.org/10.18400/tekderg.783110

Abstract

Service quality is one of the main issues that today's world. Firms operating in the transportation sector are also trying to improve the quality of the service they provide to their passengers. It is crucial to determine the passengers' service quality perceptions and priorities to evaluate and improve the service in this context. In this study, Kocaeli's tram service users' service quality perceptions have been evaluated by applying a survey consisting of 20 questions and user satisfaction levels from different service dimensions. Later, an artificial neural network model was developed using the users' demographic data and their responses to the survey questions to mimic their service quality satisfaction. The artificial neural network model developed has been examined to understand the importance that tram users give to service quality. Using the developed the “change of score” method, how the changes to be made in the tram system will affect the quality of service and how the opinions of different user groups will be affected can be examined in detail. The artificial neural network model's prediction capability was compared with the multiple linear regression model and found superior. According to the developed Change of Score Method, the most frequent user attaches the highest importance to the service dimensions of the convenience to pay for the tram, getting his/her destination on time, and reducing environmental pollution.

Keywords

Service quality public transportation artificial neural networks tram services transportation planning transportation modelling

References

  • Yaşar, D., Kocaeli tramvay sistemi kullanıcı memnuniyetinin incelenmesi, M.Sc. Thesis, İstanbul Okan Üniversitesi, 2020 (In Turkish).
  • Dell’Olio, L., Ibeas, A., Cecin, P., The quality of service desired by public transport users. Transport Policy., 18(1), 217-227, 2011.
  • Friman, M., Fellesson, M., Service supply and customer satisfaction in public transportation: The quality paradox. Journal of Public Transportation., 12(4), 57–69, 2009.
  • Benchmarking in European Service of public Transport (BEST), Results of the 2004 survey, http://benchmarkingpublictransport.org/content/download/292/1328/file/Report%20BEST%20Survey%20-%202004.pdf, 2004. Accessed 08 August 2020.
  • Eboli, L., Mazzulla, G., Service quality attributes affecting customer satisfaction for bus transit. Journal of public transportation., 10 (3), 21-34, 2007.
  • Noor, H.M., Nasrudin, N., Foo, J., Determinants of Customer Satisfaction of SQ: City Bus Service in Kota Kinabalu, Malaysia. Procedia - Social and Behavioural Sciences., 153, 595-605, 2014.
  • Islam, R., Chowdhury, M.S., Sarker, M.S., Ahmed, S., Measuring Customer’s Satisfaction on Bus Transportation. American Journal of Economics and Business Administration., 6(1), 34-41, 2014.
  • Directorate General Mobility and Transport and Co-ordinated by the Directorate General for Communication. Europeans’ Satisfaction with Urban Transport, England, Transport for NSW., https://ec.europa.eu/commfrontoffice/publicopinion/flash/fl_382b_en.pdf, 2014, Accessed 08 August 2020.
  • 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(1), 64-71, 2015.
  • Ardıç, K., Sadaklıoğlu, H., Şehirlerarası yolcu taşımacılığında hizmet kalitesinin ölçümü: Tokat örneği. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi., 23(3), 167-190, 2009 (In Turkish).
  • İmre, Ş., Çelebi, D., Measuring comfort in public transport: a case study for İstanbul. Transportation Research Procedia., 25, 2441-2449, 2017.
  • Özuysal, M., Tanyel, S., Oral, M.Y., Fayda esaslı erişilebilirliğin ulaşım türü seçimi üzerindeki etkisi. İMO Teknik Dergi., 23(113), 5987-6016, 2012 (In Turkish).
  • Doğan, G., Özuysal, M., Toplu ulaşımda bekleme süresini etkileyen faktörlerin incelenmesi: Güvenilirlik, yolcu bilgilendirme sistemi ve fiziksel koşullar. İMO Teknik Dergi., 28(3), 7927-7975, 2017 (In Turkish).
  • Kahraman, Ç., Yıldız, M.S., Şehirlerarası otobüs işletmelerinde hizmet kalitesinin ölçülmesi ve bir uygulama. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi., 23(2), 121-144, 2005 (In Turkish).
  • Koçoğlu, C.M., Aksoy, R., Hizmet kalitesinin servperf yöntemi ile ölçülmesi: otobüs işletmeleri üzerinde bir uygulama. Akademik Bakış Dergisi., 29(1), 1-25, 2012 (In Turkish).
  • Gökaşar, I., Dündar, S., Buran, B., Yolcu ihtiyaçlarının incelenmesi. İETT Örneği. İBB Transist 2017 Bildiri Kitabı., 2-4 Kasım, İstanbul, 386-395, 2017 (In Turkish).
  • Gökaşar, I., Buran, B., Dündar, S., Kent içi otobüs memnuniyet anketi verileri ve faktör analizinden yararlanılarak otobüslerin hizmet kalitesinin modellenmesi: İETT örneği. Pamukkale Üniv Müh Bilim Derg., 24(6), 1079-1086, 2018 (In Turkish).
  • Girginer, N., Cankuş, B., Tramvay yolcu memnuniyetinin lojistik regresyon analiziyle ölçülmesi: Estram örneği. Yönetim ve Ekonomi: Celal Bayar Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi., 15(1), 181-193, 2008 (In Turkish).
  • Hemedoğlu, E., Toplu taşımacılık sektöründe hizmet kalitesini ölçme: Algılanan hizmet kalitesi ve müşterinin arzuladığı hizmet kalitesi üzerindeki etkileri (Master Thesis). Yıldız Technical University, Graduate School of Natural and Applied Sciences, Istanbul, Turkey, 2010 (In Turkish).
  • Seçilmiş, C., Kaşlı, M., Kılıçlar, A., Sarı, Y., The effect of quality at railway services on customer satisfaction in terms of fee paid. Ege Academic Review., 11(4), 573-586, 2011 (In Turkish).
  • Akyıldız Alçura, G., Kuşakçı, S.Ş., Gölbaşı Şimşek, G., Gürsoy, M., Tanrıverdi, S.C., Impact score technique for analyzing the service quality of a high-speed rail system. Transportation Research Record: Journal of the Transportation Research Board., 2541(1): 64-72, 2016.
  • Šojat, D., Brcic, D., Slavulj, M., Analysis of public transport service improvements on tram network in the City of Zagreb. Tehnički vjesnik., 24, 217-223, 2017.
  • Vujičić, M., Prester, J., Assessing service quality of public tram transport in Zagreb city using P-TRANSQUAL mode. Zbornik Ekonomskog fakulteta u Zagrebu., 17, 19-31, 2019.
  • Khelf, M., Boukebbab, S., Bhouri, N., Boulahlib, M.S. Tram Service Quality and Its Impact on the Passengers’ Modal Choice in Constantine City (Algeria), Selected Papers from the 18th International Conference on Reliability and Statistics in Transportation and Communication, RelStat’18, 17-20 October 2018, Riga, Latvia, 2018.
  • De Oña, R., De Oña, J., Neural Networks for Analyzing Service Quality in Public Transportation. Expert Systems with Applications., 41(15), 6830–6838, 2014.
  • Islam, M.R., Hadiuzzaman, M., Banik, R., Hasnat, M.M., Musabbir, S.R, Hossain, S., Bus Service Quality Prediction and Attribute Ranking: a Neural Network Approach. Public Transport., 8(1), 295–313, 2016.
  • International Bus Benchmarking Group (IBBG), https://busbenchmarking.org. Accessed 08 August 2020.
  • Acar, S., Bilen Kazancık, L., Meydan, M.C., Işık, M., İllerin ve bölgelerin sosyo-ekonomik gelişmişlik sıralaması araştırması SEGE-2017., Kalkınma Ajansları Genel Müdürlüğü Yayını Sayı: 3 2018 (In Turkish).
  • KBB Ulaşım Dairesi Başkanlığı., Akçaray güzergay haritası, 2017
  • Turkish Statistical Institute TSI, Outcomes of Address Based Population Registration System 2018. TUIK, Ankara, Turkey, 2019 https://biruni.tuik.gov.tr/medas/?kn=95&locale=tr. Accessed 08 August 2020.
  • Meyer, J.T., Fundamental Research Statistics for the Behavioural Sciences., New York: Holt Rinehart & Winston, 1979.
  • Fox, N., Hunn, A., Mathers, N., Sampling and Sample Size Calculation. The NIHRRDS for the East Midlands / Yorkshire & the Humber, 2007.
  • Dündar, S., Şahin, İ., Train re-scheduling with genetic algorithms and artificial neural networks for single-track railways. Transportation Research Part C: Emerging Technologies Volume 27(1), 1-15, 2013.
  • Yardım, M.S., Değer Şitilbay, B., Dündar, S., Modelling the effects of hydrated lime additives on asphalt mixtures by fuzzy logic and ANN. Teknik Dergi, Vol. 30(6), 9533-9559, 2019.
  • Murat, Y.Ş., Başkan, Ö., Modelling vehicle delays at signalized junctions: Artificial neural networks approach. Journal of Scientific & Industrial Research, Vol. 65(1), 558-564,2006.
  • Osuna, R.G., CS790: Selected Topics in Computer Science, Lecture Notes, Texas A&M University, 2002.
  • Murat, Y.Ş., Comparison of fuzzy logic and artificial neural networks approaches in vehicle delay modeling. Transportation Research Part C Vol. 14(1), 316–334, 2006.
  • Kaya Uyanık, G., Güler, N., A study on multiple linear regression. Procedia - Social and Behavorial Sciences, Vol. 106, 234-240, 2013.
There are 38 citations in total.

Details

Primary Language English
Subjects Civil Engineering
Journal Section Articles
Authors

Selim Dündar 0000-0003-4433-1998

Publication Date September 1, 2022
Submission Date August 20, 2020
Published in Issue Year 2022 Volume: 33 Issue: 5

Cite

APA Dündar, S. (2022). Investigating the Service Quality of Kocaeli Tram Service Using Artificial Neural Networks. Teknik Dergi, 33(5), 12429-12456. https://doi.org/10.18400/tekderg.783110
AMA Dündar S. Investigating the Service Quality of Kocaeli Tram Service Using Artificial Neural Networks. Teknik Dergi. September 2022;33(5):12429-12456. doi:10.18400/tekderg.783110
Chicago Dündar, Selim. “Investigating the Service Quality of Kocaeli Tram Service Using Artificial Neural Networks”. Teknik Dergi 33, no. 5 (September 2022): 12429-56. https://doi.org/10.18400/tekderg.783110.
EndNote Dündar S (September 1, 2022) Investigating the Service Quality of Kocaeli Tram Service Using Artificial Neural Networks. Teknik Dergi 33 5 12429–12456.
IEEE S. Dündar, “Investigating the Service Quality of Kocaeli Tram Service Using Artificial Neural Networks”, Teknik Dergi, vol. 33, no. 5, pp. 12429–12456, 2022, doi: 10.18400/tekderg.783110.
ISNAD Dündar, Selim. “Investigating the Service Quality of Kocaeli Tram Service Using Artificial Neural Networks”. Teknik Dergi 33/5 (September 2022), 12429-12456. https://doi.org/10.18400/tekderg.783110.
JAMA Dündar S. Investigating the Service Quality of Kocaeli Tram Service Using Artificial Neural Networks. Teknik Dergi. 2022;33:12429–12456.
MLA Dündar, Selim. “Investigating the Service Quality of Kocaeli Tram Service Using Artificial Neural Networks”. Teknik Dergi, vol. 33, no. 5, 2022, pp. 12429-56, doi:10.18400/tekderg.783110.
Vancouver Dündar S. Investigating the Service Quality of Kocaeli Tram Service Using Artificial Neural Networks. Teknik Dergi. 2022;33(5):12429-56.
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