HİZMET SEKTÖRÜNDE KONTROL KARTLARI KULLANIMI: KENT İÇİ TOPLU TAŞIMA SEKTÖRÜNDE BİR UYGULAMA

Yıl 2024, Cilt: 26 Sayı: 3, 1200 - 1221, 15.09.2024

Umit Kuvvetli

https://doi.org/10.16953/deusosbil.1420663

Öz

Üretim sektörünün aksine istatistiksel kalite kontrol kartlarının hizmet sektöründe kullanımı oldukça sınırlıdır. Bu çalışmada, bir kentteki yaşam kalitesini etkileyen en önemli hizmet sektörlerinden olan kent içi toplu taşıma sektöründe farklı kalite kontrol kartlarının nasıl ve ne amaçla kullanılabileceği araştırılmıştır. Bu doğrultuda, örnek bir otobüs hattında 55 güne ait 715 seferdeki otobüs içi yolcu sayısı değişkeni ile 55 güne ait toplam biniş sayısı değişkenlerinin izlenmesinde Shewhart, EWMA ve CUSUM kontrol kartları kullanılmıştır. Elde edilen sonuçlar, kent içi toplu taşıma sektöründe taktiksel planlamalar için Shewhart, operasyonel planlamalar için ise EWMA ve CUSUM kartlarının, kalite izleme ve iyileştirme amaçlı çalışmalarda faydalı olabileceğini göstermektedir.

Anahtar Kelimeler

: İstatistiksel Kontrol Kartları, Kent İçi Toplu Taşıma, Hizmet Kalitesi, Akıllı Kart Biniş Verisi

THE USE OF CONTROL CHARTS IN THE SERVICE SECTOR: A CASE STUDY IN THE URBAN PUBLIC TRANSPORT SECTOR

Öz

Contrary to the production sector, the use of statistical quality control charts is quite limited in the service sector. In this study, it was investigated how and for what purpose different quality control charts can be used in the urban public transportation sector, which is one of the most important service sectors affecting the quality of life in a city. In this regard, Shewhart, EWMA and CUSUM control charts have been used to monitor the variables of the number of passengers on the bus in 715 trips of 55 days and the total number of boardings for 55 days on a sample bus route. The results show that Shewhart charts for tactical planning, EWMA and CUSUM charts for operational planning can be useful for quality monitoring and improvement in urban public transportation sector.

Anahtar Kelimeler

Statistical Quality Control, Urban Public Transport, Service Quality, Smart Card Boarding Data

Kaynakça

• Altuntas S., Dereli T. & Kaya İ. (2020). Monitoring patient dissatisfaction: a methodology based on SERVQUAL scale and statistical process control charts, Total Quality Management & Business Excellence, 31 (9-10), 978-1008, DOI:10.1080/14783363.2018.1457434.
• Aykroyd R.G., Leiva V., & Ruggeri F. (2019). Recent developments of control charts, identification of big data sources and future trends of current research, Technological Forecasting and Social Change, 144, 221-232.
• Baesen, B. (2014). Analytics in a Big Data World: The Essential Guide to Data Science and Its Applications. New York: Wiley.
• Baradaran, V., & Dashtbani, H. (2014). A decision support system for monitoring traffic by statistical control charts. Management Science Letters, 4, 1661-1670.
• Barnard, G. A. (1959). Control charts and stochastic processes. Journal of the Royal Statistical Society. B (Methodological), 21 (2), 239–271.
• Bi, H.H. (2018). A robust interpretation of teaching evaluation ratings. Assessment and Evaluation in Higher Education, 43 (1), 79-93.
• Carlucci, D., Renna, P., Izzo, C. & Schiuma, G. (2019). Assessing teaching performance in higher education: a framework for continuous improvement. Management Decision, 57 (2), 461-479.
• Carson P. K. & Yeh A. B. (2008). Exponentially weighted moving average (EWMA) control charts for monitoring an analytical process. Industrial & Engineering Chemistry Research, 47 (2), 405-411.
• Cerqueira, S., Arsenio, E. & Henriques, R. (2022). Inference of dynamic origin–destination matrices with trip and transfer status from individual smart card data. European Transport Research Review, 14, 42. https://doi.org/10.1186/s12544-022-00562-1.
• Chen K.S., Chang T.C., Wang K.J. & Huang C.T. (2015). Developing control charts in monitoring service quality based on the number of customer complaints, Total Quality Management & Business Excellence, 26 (5-6), 675-689, DOI:10.1080/14783363.2013.874198
• Colosimo, B.M. & Semeraro, Q. (2002). A Bayesian control chart for service quality control. Proceeding of the Joint Statistical Meetings, Section on Quality and Productivity, 57, Arizona, US.
• de Oña, J., de Oña, R. & Calvo, F. (2012). A classification tree approach to identify key factors of transit service quality. Expert Systems with Applications. 39, 11164–11171. http://dx.doi.org/10.1016/j.eswa.2012.03.037.
• Debnath, R.M. & Shankar, R. (2014). Emerging trend of customer satisfaction in academic process. The TQM Journal, 26 (1), 14-29.
• dell’Olio, L., Ibeas, A., de Oña, J. & de Oña, R. (2018). Chapter 9 - Data mining approaches. In: dell’Olio, L., Ibeas, A., de Oña, J., de Oña, R. (Eds.), Public Transportation Quality of Service. Elsevier, (ss. 155–179). http://dx.doi.org/10.1016/B978-0-08-102080-7.00009-4.
• Dey, M.L., Sluyter, G.V. & Keating J.E. (1994). Statistical process control and direct care staff performance. Mental Health Administration, 21 (2), 201-209.
• Doğan İ. & Doğan N. (2019). EWMA kontrol çizelgeleri ve sağlık alanında kullanımına genel bir bakış. Türkiye Klinikleri Journal of Biostatistics, 11 (1), 72-82.
• Firuzan A.R., Alpaykut S. & Kuvvetli Ü. (2012). Bulanık servqual yaklaşımıyla toplu taşımada kalitenin ölçülmesi. Muğla Sıtkı Koçman Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 29, 78-94.
• Firuzan, A.R. & Kuvvetli, Ü. (2012). 1.5 sigma kaymanın istatistiksel nedenleri üzerine bir araştırma. İstanbul University Econometrics and Statistics e-Journal, 0 (16), 1-11.
• Garrido, C., de Oña, R. & de Oña, J. (2014). Neural networks for analyzing service quality in public transportation. Expert Systems with Applications, 41, 6830–6838. http://dx.doi.org/10.1016/j.eswa.2014.04.045.
• Gessa A., Marin E. & Sancha P. (2022). A practical application of statistical process control to evaluate the performance rate of academic programmes: implications and suggestions, Quality Assurance in Education, 30 (4), 571-588.
• Gökaşar I, Buran B. & Dündar D. (2018). Kent içi otobüs memnuniyet anketi verileri ve faktör analizinden yararlanılarak otobüslerin hizmet kalitesinin modellenmesi: İETT örneği. Pamukkale Universitesi Muhendislik Bilimleri Dergisi, 24 (6), 1079-1086.
• Gündoğdu F. K., Duleba S., Moslem S. & Aydın S. (2021). Evaluating public transport service quality using Picture fuzzy analytic hierarchy process and linear assigment model, Applied Soft Computing, 100, 106920.
• Hanslik, T., Boelle, P. & Flahault, A. (2001). The control chart: An epidemiological tool for public health monitoring. Public Health, 115, 277–281.
• Huang, D., Jun Y., Shiyu S., Zhekang L., Luyun Z. & Cheng G. (2020). A Method for Bus OD Matrix Estimation Using Multisource Data, Journal of Advanced Transportation, 5740521, https://doi.org/10.1155/2020/5740521.
• Jomnonkwao, S., & Ratanavaraha, V. (2016). Measurement modelling of the perceived service quality of a sightseeing bus service: An application of hierarchical confirmatory factor analysis. Transport Policy, 45, 240–252. https://doi.org/10.1016/j.tranpol.2015.04.001
• Jumah, J. A. B., Burt, R. P. & Buttram, B. (2012). An exploration of quality control in banking and finance. International Journal of Business and Social Science, 3, 273–277.
• Kang J.M., Ataeian, S. & Amiripour, S.M.M. (2021). A procedure for public transit OD matrix generation using smart card transaction data. Public Transportation, 13, 81–100. https://doi.org/10.1007/s12469-020-00257-7.
• Kim K. & Lee I. (2017). Public transportation alighting estimation method using smart card data. Journal of Korean Socirty for Railway, 20 (5), 692-702.
• Krishnakumari P., Lint H.v., Djukic T. & Cats O. (2019). A data driven method for OD matrix estimation. Transportation Research Procedia, 38, 139-159.
• Kuvvetli, Ü., Diker, A.C., Eliiyi, U., Ozkılcık, M. & Nasiboğlu, E. (2014a) Akıllı Kart Verileri ile OD Matrisi Oluşturmada Kullanılan BölgeBazlı ve Hat Bazlı Yaklaşımların Karşılaştırılması: İzmir Örneği. Yöneylem Araştırması ve Endüstri Mühendisliği 34. Ulusal Kongresi, Bursa, Türkiye. (Temmuz 2014)
• Kuvvetli, Ü., Eliiyi, U., Nasiboğlu, E., Diker, A.C., Osmanoğulları, E. & Ozkılcık, M. (2014b). İniş Duraklarının Akıllı Kart Verileri Kullanılarak Tahmin Edilmesi İçin Hat Bazlı Yaklaşım İzmir Örneği, TRANSİST, 7. Uluslararası Ulaşım Teknolojileri Sempozyumu ve Fuarı. (107-113), İstanbul, Türkiye. (Aralık 2014)
• Kuvvetli, U., & Firuzan, A. R. (2021). Kent İçi Toplu Taşımada Belediye Otobüslerinin Karıştığı Trafik Kazalarının Lojistik Regresyon ile İncelenmesi. Trakya Üniversitesi Sosyal Bilimler Dergisi, 23 (1), 321-336. https://doi.org/10.26468/trakyasobed.773099
• Laisak, A. H., Rosli, A., & Sa’adi, N. (2021). The effect of service quality on customers’ satisfaction of Inter-District Public bus companies in the Central Region of Sarawak, Malaysia. International Journal of Marketing Studies, 13 (2), 53–67. https://doi.org/10.5539/ijms.v13n2p53
• Leiva, V., Marchant, C., Ruggeri, F. & Saulo, H. (2015). A criterion for environmental assessment using Birnbaum-Saunders attribute control charts. Environmetrics, 26, 463–476.
• Leiva, V., Lillo, C. & Morrás, R., (2018). On a business confidence index and its data analytics: a Chilean case. In: Oliveira, T., Kitsos, C., Oliveira, A., Grilo, L.M. (Eds.), Recent Studies on Risk Analysis and Statistical Modeling. Springer, Switzerland, (ss.61–78).
• Montgomery, D. C. (2009). Introduction to Statistical Quality Control. New York: Wiley.
• Münz, G., & Carle, G. (2008). Application of Forecasting Techniques and Control Charts for Traffic Anomaly Detection.
• Nasiboglu E., Kuvvetli U, Ozkilcik M. & Eliiyi, U. (2012). Origin-destination matrix generation using smart card data: Case study for Izmir. 2012 IV International Conference. Problems of Cybernetics and Informatics (PCI), Baku, Azerbaijan, (1-4). DOI:10.1109/ICPCI.2012.6486315.
• Novoa N. M. & Varela G. (2020). Monitoring surgical quality: the cumulative sum (CUSUM) approach, Mediastinum, 4 (4), 35118272.
• Oktay, E. (1994). Shewart, Cusum ve Ewma kontrol grafiklerinin şeker sanayiine uygulanması üzerine bir deneme. (Doktora Tezi). Atatürk Üniversitesi, Sosyal Bilimler Enstitüsü, Erzurum.
• Orme, J.G. & Cox, M.E. (2001). Analyzing single-subject design data using statistical process control charts. Social Work Research, 25 (2), 115-127.
• Ou, Y., Hu, J., Li, X. & Le, T. (2014). MIMO EWMA-CUSUM condition-based statistical process control in manufacturing processes. Proceedings of IEEE Emerging Technology and Factory Automation. IEEE, pp. 1–8.
• Özkan B. & Alp S. (2020). Toplu ulaşımda hizmet kalitesi: İstanbul’da yolcu memnuniyeti araştırması, Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, 3 (2), 94-111.
• Öztürk H. Murat N. & Elevli S. (2019). Quality Control Charts for Monitoring Performance of Hospital Call Center. Sigma, 37 (4), 1396-410.
• Page E.S. (1954). Continuous Inspection Schemes. Biometrika, 41(1), 100-115.
• Pelletier, M. P., Trépanier, M., & Morency, C. (2011). Smart card data use in public transit: A literature review, Transportation Research Part C: Emerging Technologies, 19 (4), 557–568.
• Perucca, G., & Salini, S. (2014). Travellers’ Satisfaction with Railway Transport: A Bayesian Network Approach. Quality Technology & Quantitative Management, 11 (1), 71–84. https://doi.org/10.1080/16843703.2014.11673326
• Rafique M.Z., Rahman M.N., Saibani N., Arsad N., Mughal I.A. & Hanif S. (2016). Quality check for customer benefit in bus transport system through statistical control charts and gauge R&R. International Journal of Applied Engineering Research, 11 (1), 101-104.
• Rebisz B. (2013). The Study of the Dynamics of Traffic Accidents using The control charts. Modern Management Review, 20 (3), 135-144.
• Roberts, S.W. (1959). Control charts test based on geometric moving averages. Tech- nometrics: A Journal of Statistics for the Physical, Chemical, and Engineering Sciences, 1, 239–250.
• Ruiz E., Yushimito W. F., Aburto L. & Cruz R. (2024). Predicting passenger satisfaction in public transportation using machine learning models. Transportation research Part A: Policy and Practice, 181,103995.
• Shewhart, W.A. (1931). Economic control of quality of manufactured product. New York: D. Van Nostrand Company.
• Sivena, S., & Nikolaidis, Y. (2019). Improving the quality of Higher Education teaching through the exploitation of student evaluations and the use of control charts. Communications in Statistics - Simulation and Computation, 51 (3), 1289–1312. https://doi.org/10.1080/03610918.2019.1667390.
• Schuh A, Canham-Chervak M. & Jones B.H. (2017). Statistical process control charts for monitoring military injuries. Injury Prevention, 23, 416-422.
• Schuh A., Camelio J.A. & Woodall W.H. (2014). Control charts for accident frequency: a motivation for real-time occupational safety monitoring, International Journal of Injury Control and Safety Promotion, 21 (2), 154-162, DOI: 10.1080/17457300.2013.792285.
• Türk Standartları Enstitüsü. (2014). TS EN 13816: 2002, Ulaştırma-Lojistik ve Hizmetler Toplu taşıma-Hizmet Kalitesinin Tarifi, Hedefi ve Ölçümü Standardı. Ankara, Türkiye.
• Türkmen B.C. & Akyurt İ.Z. (2018). Çanakkale kale seramik işletmesi karo üretiminde X ̅-S, cusum ve ewma kalite kontrol grafiklerinin uygulanması. Akademik Bakış Dergisi, 66, 376-395.
• van Cranenburgh, S., Wang, S., Vij, A., Pereira, F., & Walker, J. (2022). Choice modelling in the age of machine learning - Discussion paper. Journal of Choice Model. 42, 100340. http://dx.doi.org/10.1016/j.jocm.2021.100340.
• Wang, Y., Zhang, Z., Zhu, M., & Wang, H. (2020). The impact of service quality and customer satisfaction on reuse intention in urban rail transit in Tianjin, China. SAGE Open, 10 (1). https://doi.org/10.1177/215824401989880.
• Weng, J., Yu, J., Di, X., Lin, P., Wang, J.-J. & Mao, L.-Z.. (2023). How does the state of bus operations influence passengers’ service satisfaction? A method considering the differences in passenger preferences. Transport. Research. Part A: Policy Practice 174, 103734.
• Woodall, W. (2014). Discussion of “latent structures-based multivariate statistical process control: a paradigm shift”. Quality Engineering, 26, 92–95.
• Yap M., Cats O. & Arem B.v. (2018). Crowding valuation in urban tram and bus transportation based on smart card data. Transportmetrica A: Transport Science 16 (1), 23-42.
• Yazid, M. F., Ali, A. M., & Manaf, S. A. (2020). Customer satisfaction in public transport service. European Journal of Molecular & Clinical Medicine, 7 (3), 4108–4127.