TY - JOUR T1 - Assessment of Profitability of Small-Scale Traditional Taxi Services: A Case Study of a Taxi Stand AU - Karabulut, Nihat Can AU - Özen, Halit PY - 2024 DA - November Y2 - 2024 DO - 10.26650/JTL.2024.1429951 JF - Journal of Transportation and Logistics JO - JTL PB - Istanbul University WT - DergiPark SN - 2459-1718 SP - 298 EP - 310 VL - 9 IS - 2 LA - en AB - Taxis play a pivotal role in urban mobility by offering passengers flexible, comfortable, and door-to-door services. Despite the advent of the sharing economy, ensuring the continuity of traditional taxi services necessitates profitability analyses. For this reason, this study focuses on the economic profitability of trips made at a taxi stand serving the urban arteries of Istanbul. With the aim this, a survey was conducted among the drivers of a taxi stand. Subsequently, a model was developed, incorporating factors such as the number of trips (TRP), total trip distance (DST) and efficiency (EFF), which impact the profitability of taxi services. The modeling approach employed in this study is Response Surface Methodology (RSM). Additionally, contour plots were utilized to provide a more accurate assessment of the effects of factors. The results indicate that the EFF factor is the crucial factor influencing the profitability of traditional taxi services. This underscores the significance of the distance covered with passengers, highlighting its importance for both the economic success of taxi services and the broader network context of urban transportation. KW - Traditional taxis KW - profitability analysis KW - response surface methodology KW - contour plot KW - sustainability CR - Aarhaug, J., & Skollerud, K. (2014). Taxi: different solutions in different segments. Transportation Research Procedia, 1(1), 276-283. DOI: 10.1016/j.trpro.2014.07.027 google scholar CR - Berger, T., Chen, C., & Frey, C. B. (2018). Drivers of disruption? Estimating the Uber effect. European Economic Review, 110, 197-210. DOI: 10.1016/j.euroecorev.2018.05.006 google scholar CR - Bi, H., & Ye, Z. (2021). Exploring ridesourcing trip patterns by fusing multi-source data: A big data approach. Sustainable Cities and Society, 64, 102499. DOI: 10.1016/j.scs.2020.102499 google scholar CR - Brodeur, A., & Nield, K. (2018). An empirical analysis of taxi, Lyft and Uber rides: Evidence from weather shocks in NYC. Journal of Economic Behavior & Organization, 152, 1-16. DOI: 10.1016/j.jebo.2018.06.004 google scholar CR - Chen, F., Yin, Z., Ye, Y., & Sun, D. J. (2020). Taxi hailing choice behavior and economic benefit analysis of emission reduction based on multi-mode travel big data. Transport Policy, 97, 73-84. DOI: 10.1016/j.tranpol.2020.04.001 google scholar CR - Choi, Y., Guhathakurta, S., & Pande, A. (2022). An empirical Bayes approach to quantifying the impact of transportation net-work companies (TNCs) operations on travel demand. Transportation Research Part A: Policy and Practice, 161, 269-283. DOI: https://doi.org/10.1016/j.tra.2022.04.008 google scholar CR - Christoforou, Z., Milioti, C., Perperidou, D., & Karlaftis, M. G. (2012). Investigation of taxi travel time characteristics. Advances in Transportation Studies, (27). google scholar CR - Cochran, W. G. (1977). Sampling techniques. Canada: John Wiley & Sons. google scholar CR - Cramer, J., & Krueger, A. B. (2016). Disruptive change in the taxi business: The case of Uber. American Economic Review, 106(5), 177-182. DOI: 10.1257/aer.p20161002 google scholar CR - Ghaffar, A., Mitra, S., & Hyland, M. (2020). Modeling determinants of ridesourcing usage: A census tract-level analysis of Chicago. Transportation Research Part C: Emerging Technologies, 119, 102769. DOI: https://doi.org/10.1016/j.trc.2020.102769 google scholar CR - IBB (2023a), Istanbul Transportation Bulletin. Istanbul Metropolitan Municipality, Retrieved May 21, 2024. https://cdn-uym.ibb.gov.tr/cdn/uym/Bultenlerimiz/istanbul-ulasim-bulteni-2023-2.pdf google scholar CR - IBB (2023b), Taxi Transportation Segments and Fee Tariff. Istanbul Metropolitan Municipality, Retrieved May 21, 2024. https://tuhim.ibb.gov.tr/media/2573/taksi-yay%C4%B1nlama.pdf google scholar CR - Jiang, S., Chen, L., Mislove, A., & Wilson, C. (2018, April). On ridesharing competition and accessibility: Evidence from uber, lyft, and taxi. In Proceedings of the 2018 World Wide Web Conference (pp. 863-872). DOI: https://doi.org/10.1145/3178876.3186134 google scholar CR - Kattan, L., de Barros, A., & Wirasinghe, S. C. (2010). Analysis of work trips made by taxi in Canadian cities. Journal of Advanced Transportation, 44(1), 11-18. DOI: 10.1002/atr.102 google scholar CR - Kong, H., Zhang, X., & Zhao, J. (2020). Is ridesourcing more efficient than taxis?. Applied Geography, 125, 102301. DOI: 10.1016/j.apgeog.2020.102301 google scholar CR - Liu, F., Gao, F., Yang, L., Han, C., Hao, W., & Tang, J. (2022). Exploring the spatially heterogeneous effect of the built environment on ride-hailing travel demand: A geo.graphically weighted quantile regression model. Travel Behaviour and Society, 29, 22-33. DOI: 10.1016/j.tbs.2022.05.004 google scholar CR - Milioti, C., Kepaptsoglou, K., Kouretas, K., & Vlahogianni, E. I. (2022). Driver perceptions on taxi-sharing and dynamic pricing in taxi services: Evidence from Athens, Greece. Journal of Public Transportation, 24, 100022. DOI: 10.5038/2375-0901.23.2.4 google scholar CR - Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response surface methodology: process and product optimization using designed experiments. John Wiley & Sons. google scholar CR - Nguyen-Phuoc, D. Q., Tran, P. T. K., Su, D. N., Oviedo-Trespalacios, O., & Johnson, L. W. (2021). The formation of passenger loyalty: Differences between ride-hailing and traditional taxi services. Travel Behaviour and Society, 24, 218-230. DOI: 10.1016/j.tbs.2021.04.006 google scholar CR - Nian, G., Huang, J., & Sun, D. (2022). Exploring built environment influence on taxi vacant time in megacities: A case study of Chongqing, China. Journal of Advanced Transportation, 2022, 1-14. DOI: 10.1155/2022/3096901 google scholar CR - Pan, Y., Chen, S., Li, T., Niu, S., Tang, K., 2019a. Exploring spatial variation of the bus stop in fl uence zone with multi-source data: a case study inZhenjiang, China. J. Transp. Geogr. 76, 166-177. DOI: 10.1016/j.jtrangeo.2019.03.012 google scholar CR - Shaheen, S., Cohen, A., Chan, N., & Bansal, A. (2020). Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes. In Transportation, land use, and environmental planning (pp. 237-262). Elsevier. DOI: 10.1016/B978-0-12-815167-9.00013-X google scholar CR - Szeto, W. Y., Wong, R. C. P., & Yang, W. H. (2019). Guiding vacant taxi drivers to demand locations by taxi-calling signals: A sequential binary logistic regression modeling approach and policy implications. Transport Policy, 76, 100-110. DOI: 10.1016/j.tranpol.2018.06.009 google scholar CR - Qian, X., Ukkusuri, S.V., 2015. Spatial variation of the urban taxi ridership using GPS data. Appl. Geogr. 59, 31-42. DOI: 10.1016/j.apgeog.2015.02.011 google scholar CR - Qian, X., & Ukkusuri, S. V. (2017). Time-of-day pricing in taxi markets. IEEE Transactions on Intelligent Transportation Systems, 18(6), 1610-1622. DOI: 10.1109/TITS.2016.2614621 google scholar CR - Yuan, J., Zheng, Y., Zhang, L., Xie, X., & Sun, G. (2011, September). Where to find my next passenger. In Proceedings of the 13th international conference on Ubiquitous computing (pp. 109-118). DOI: 10.1145/2030112.2030128 google scholar CR - Welch, T. F., Gehrke, S. R., & Widita, A. (2020). Shared-use mobility competition: a trip-level analysis of taxi, bike share, and transit mode choice in Washington, DC. Transportmetrica A: Transport Science, 16(1), 43-55. DOI: 10.1080/23249935.2018.1523250 google scholar CR - Wu, T., Shen, Q., Xu, M., Peng, T., & Ou, X. (2018). Development and application of an energy use and CO2 emissions reduction evaluation model for China’s online car hailing services. Energy, 154, 298-307. DOI: 10.1016/j.energy.2018.04.130 google scholar CR - Zhang, W., Ukkusuri, S. V., & Lu, J. J. (2017). Impacts of urban built environment on empty taxi trips using limited geolocation data. Transportation, 44, 1445-1473. DOI: https://doi.org/10.1007/s11116-016-9709-3 google scholar CR - Zong, F., Wu, T., & Jia, H. (2018). Taxi drivers’ cruising patterns—Insights from taxi GPS traces. IEEE Transactions on Intelligent Transportation Systems, 20(2), 571-582. DOI: 10.1109/TITS.2018.2816938 google scholar UR - https://doi.org/10.26650/JTL.2024.1429951 L1 - https://dergipark.org.tr/en/download/article-file/3699989 ER -