Comprehensive service quality evaluation of public transit based on extension cloud model

Authors

DOI:

https://doi.org/10.5604/01.3001.0015.8198

Keywords:

traffic engineering, public transit, urban traffic congestion, service quality, optimization, sustainable development

Abstract

Prioritizing the development of public transit and enhancing its attractiveness is an important way to solve the problem of urban traffic congestion and achieve sustainable development. To improve the service quality and overall operational efficiency of urban public transit, an evaluation index system related to the comprehensive experience of passengers, service supply quality of public transit enterprises, and supervision of management departments was introduced from both the demand and the supply of public transit travel services. Based on the data distribution characteristics of the boxplot in statistics, the evaluation level and corresponding value range of each index were determined, and the comprehensive weight of the index was determined using the linear weighting method combining the analytic hierarchy process and the entropy weight method, so as to reduce the influence of single weighting method on the evaluation results of comprehensive service quality of public transit. An evaluation method of public transit comprehensive service quality based on the extension cloud model was established. The evaluation results of the model were obtained by calculating the cloud affiliation and comprehensive certainty, and a reliability factor was used to test the evaluation results, which solved the problem of randomness and fuzziness in the process of comprehensive service quality evaluation of public transportation and made the evaluation results closer to the reality. Finally, the established comprehensive evaluation model was applied to a city for example analysis, and the corresponding evaluation level was obtained as good. The value of the reliability factor in the model was less than 0.01, indicating that the model has good applicability and a certain application value for the comprehensive service quality evaluation of public transit. The evaluation method fully considered a variety of evaluation indicators, specified the evaluation level of comprehensive service quality of public transit, and the evaluation results provide a theoretical basis for public transport enterprise to make targeted improvement measures.

References

Lai, X., Teng, J., & Ling, L. (2020). Evaluating Public Transportation Service in a Transit Hub based on Passengers Energy Cost. In 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), 1-7, IEEE.

Awasthi, A., Chauhan, S. S., Omrani, H., & Panahi, A. (2011). A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality. Computers & Industrial Engineering, 61(3), 637-646. doi: 10.1016/j.cie.2021.04.019.

Liou, J. J., Hsu, C. C., & Chen, Y. S. (2014). Improving transportation service quality based on information fusion. Transportation Research Part A: Policy and Practice, 67(3), 225- 239. doi: 10.1016/j.tra.2018.07.007.

Sendek-Matysiak, E., & Pyza, D. (2018). The assigment of vehicle assesment based on multi criteria decision making. Archives of Transport, 48(4), 77-85. doi: 10.5604/01.3001.0012.8367.

Moslem, S., Alkharabsheh, A., Ismael, K., & Duleba, S. (2020). An integrated decision support model for evaluating public transport quality. Applied Sciences, 10(12), 41-54. doi: 10.3390/app10124158.

Sercan KESTEN, A., & Selçuk Öğüt, K. (2014). A new passenger oriented performance measurement framework for public rail transportation systems. Promet-Traffic&Transportation, 26(4), 299-311. doi: 10.7307/ptt.v26i4.1314.

Morton, C., Caulfield, B., & Anable, J. (2016). Customer perceptions of quality of service in public transport: Evidence for bus transit in Scotland. Case Studies on Transport Policy, 4(3), 199-207. doi: 10.1016/j.cstp.2016.03.002.

Stojic, D., Ciric, Z., Sedlak, O., & Marcikic Horvat, A. (2020). Students’ views on public transport: satisfaction and emission. Sustainability, 12(20), 84-98. doi: 10.3390/su12208470.

Rajsman, M., & Škorput, P. (2022). Methodo logical approach for evaluation and improvement of quality transport service in public road passenger transport. Tehnički vjesnik, 29(1), 139-148. doi: 10.17559/TV-20201031104641.

Moslem, S., & Çelikbilek, Y. (2020). An integrated grey AHP-MOORA model for ameliorating public transport service quality. European Transport Research Review, 12(1), 1-13. [11] Soza-Parra, J., Raveau, S., Muñoz, J. C., & Cats, O. (2019). The underlying effect of public transport reliability on users’ satisfaction. Transportation Research Part A: Policy and Practice, 12(6), 83-93. doi: 10.1016/j.tra.2019.06.004.

Sam, E. F., Hamidu, O., & Daniels, S. (2018). SERVQUAL analysis of public bus transport services in Kumasi metropolis, Ghana: Core user perspectives. Case studies on transport policy, 6(1), 25-31. doi: 10.1016/j.cstp.2017.12.004.

Chocholac, J., Sommerauerova, D., Hyrslova, J., Kucera, T., Hruska, R., & Machalik, S. (2020). Service quality of the urban public transport companies and sustainable city logistics. Open Engineering, 10(1), 86-97. doi: 10.1515/eng-2020-0010.

Noor, H. M., & Foo, J. (2014). Determinants of customer satisfaction of service quality: City bus service in Kota Kinabalu, Malaysia. Procedia-Social and Behavioral Sciences, 15(3), 595-605. doi: 10.1016/j.sbspro.2019.10.092.

Rajsman, M., & Škorput, P. (2022). Methodological approach for evaluation and improvement of quality transport service in public road passenger transport. Tehnički vjesnik, 29(1), 139-148. doi: 10.17559/TV-20201031104641.

Kisilowski, M., & Stypułkowski, K. (2021). Thermal imaging for the operator's comfort assessment in the aspect of the COVID-19 pandemic. Archives of Transport, 59(3), 149-163. doi: 10.5604/01.3001.0015.3275.

Deng, H., & Qing, J. (2020). Comprehensive Evaluation of Urban Bus Satisfaction Based on Service Level Survey. Journal of Chongqing University of Technology (Natural Science), 34(5): 226-232. doi: 10.3969/j.issn.1674-8425 (z).2020.05.029.

Stanevičiūtė, I., & Grigonis, V. (2018). Analysis and Evaluation of Public Transport Safety in Vilnius. In Conference Vision Zero for Sustainable Road Safety in Baltic Sea Region (pp. 140-145). Springer, Cham. doi: 10.1007/978-3-030-22375-5_16.

Öztürk, F. (2021). A Hybrid Type-2 Fuzzy Performance Evaluation Model for Public Transport Services. Arabian Journal for Science and Engineering, 46(10), 10261-1 DOI: 10.1007/s13369-021-05687-4.

Podolski, P., Rohatynski, K., & Wnukowska, B. (2011). AHP method in process of choice vendor of energy. Przeglad Elektrotechniczny, 87(11), 68-71.

Harte, J., & Newman, E. A. (2014). Maximum information entropy: a foundation for ecological theory. Trends in ecology & evolution, 29(7), 384-389. doi: 10.1016/j.tree.2014.04.009.

Yao, X., Liu, J., & Zhang, Y. (2018). Level of Service Evaluation of Urban Commuter Travel Mode. Journal of Transportation Systems Engineering and Information, 11(5), 97-103. doi: 10.3969/j.issn.1009-6744.2011.z1.015.

Cigoli, A. S., & Metere, G. (2016). Extension theory and the calculus of butterflies. Journal of Algebra, 45(8), 87-119. doi: 10.1016/j.jalge bra.2016.03.015.

Yang, Y., Liu, R., Chen, Y., Li, T., & Tang, Y. (2018). Normal cloud model-based algorithm for multi-attribute trusted cloud service selection. IEEE Access, 6, 37644-37652. doi: 10.1109/ACCESS.2018.2850050.

Wu, H. W., Zhen, J., & Zhang, J. (2020). Urban rail transit operation safety evaluation based on an improved CRITIC method and cloud model. Journal of Rail Transport Planning & Management, 16(4), 100-114. doi: 10.1016/j.jrtpm.2020.100206.

Zhu, X., Yao, L., & Ye, L. (2021). Evaluation of Competitiveness of Highway Hub Cities Carrier Based on ANP and Extension Cloud Model. Highway, 66(10): 235-242

Downloads

Published

2022-01-31

Issue

Section

Original articles

How to Cite

Hu, X., Chen, X., Zhao, J., Yu, K., Long, B., & Dai, G. (2022). Comprehensive service quality evaluation of public transit based on extension cloud model. Archives of Transport, 61(1), 103-115. https://doi.org/10.5604/01.3001.0015.8198

Share

Most read articles by the same author(s)

<< < 30 31 32 33 34 35 36 37 38 39 > >> 

Similar Articles

1-10 of 383

You may also start an advanced similarity search for this article.

Assessment of options to meet transport needs using the MAJA multi-criteria method

Jerzy Małachowski, Jarosław Ziółkowski, Mateusz Oszczypała, Joanna Szkutnik-Rogoż, Aleksandra...