دانشگاه مازندران

 آمار

تعداد نشریات32
تعداد شماره‌ها591
تعداد مقالات5,779
تعداد مشاهده مقاله8,660,887
تعداد دریافت فایل اصل مقاله6,342,767
Nosrati, Mahdi, Rassafi, Amir Abbas, Rahimi Farahani, Hossein. (1406). Determinants of Ride-Hailing Adoption in Developing Urban Contexts: Evidence from Western Districts of Mashhad, Iran. پژوهشنامه مدیریت اجرایی, 3(2), 69-86. doi: 10.22080/ceas.2026.31910.1103
Mahdi Nosrati; Amir Abbas Rassafi; Hossein Rahimi Farahani. "Determinants of Ride-Hailing Adoption in Developing Urban Contexts: Evidence from Western Districts of Mashhad, Iran". پژوهشنامه مدیریت اجرایی, 3, 2, 1406, 69-86. doi: 10.22080/ceas.2026.31910.1103
Nosrati, Mahdi, Rassafi, Amir Abbas, Rahimi Farahani, Hossein. (1406). 'Determinants of Ride-Hailing Adoption in Developing Urban Contexts: Evidence from Western Districts of Mashhad, Iran', پژوهشنامه مدیریت اجرایی, 3(2), pp. 69-86. doi: 10.22080/ceas.2026.31910.1103
Nosrati, Mahdi, Rassafi, Amir Abbas, Rahimi Farahani, Hossein. Determinants of Ride-Hailing Adoption in Developing Urban Contexts: Evidence from Western Districts of Mashhad, Iran. پژوهشنامه مدیریت اجرایی, 1406; 3(2): 69-86. doi: 10.22080/ceas.2026.31910.1103

Determinants of Ride-Hailing Adoption in Developing Urban Contexts: Evidence from Western Districts of Mashhad, Iran

Civil Engineering and Applied Solutions
دوره 3، شماره 2، تیر 2027، صفحه 69-86    اصل مقاله (998.44 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22080/ceas.2026.31910.1103
نویسندگان
Mahdi Nosrati؛ Amir Abbas Rassafi* ؛ Hossein Rahimi Farahani
Department of Transportation Planning, Faculty of Engineering, Imam Khomeini International University, Qazvin, Iran
تاریخ دریافت: 04 خرداد 1405،  تاریخ بازنگری: 03 تیر 1405،  تاریخ پذیرش: 10 مرداد 1405 
چکیده
Ride-Hailing (RH) services have emerged as a preferred non-shared mobility option, contributing to a notable increase in their volume and modal share within urban transportation systems in Iranian cities. Despite this trend, limited empirical research exists on RH adoption in Iran and other developing countries. This study investigates the factors influencing RH usage in Iran, focusing on Mashhad, the nation’s second-largest metropolis. Data were collected in 2022 through 619 valid questionnaires encompassing four categories of variables: demographic, travel-related, environmental, and latent psychological factors. Exploratory factor analysis was first used to derive factor scores, followed by the development of an ordered probit discrete choice model. Findings reveal that variables such as marital status, employment, physical disability, household size, and social media use showed no significant effect. However, travel purpose, limited public transit access, proximity to traffic-restricted area, and trip characteristics such as duration and time of day significantly influenced usage. Among latent variables, privacy concerns and dissatisfaction with public transportation positively affected RH preference. Whereas pandemic-related apprehensions and economic constraints diminished it. The study offers insights into urban mobility behavior in developing contexts and highlights the multifaceted factors shaping RH demand.
کلیدواژه‌ها
Ride-hailing adoption؛ Travel behavior؛ Mode choice؛ Pandemic-related impacts؛ Discrete choice modeling؛ Public transportation
مراجع
  1. Soltanzadeh, J., Blind, K., Elyasi, M. Exploring how regulators face platform business issues in the lifecycle stages: Evidence of Iranian ride-hailing platform business. Telecommunications Policy, 2023; 47: 102582. doi:10.1016/j.telpol.2023.102582.
  2. Oviedo, D., Sabogal-Cardona, O., Scholl, L. Transport and social (dis)advantage in ride-hailing. Area Development and Policy, 2025; 10: 295–325. doi:10.1080/23792949.2024.2404024.
  3. Martins, D. L., Meira, L. H., Costa, C. S., Pitombo, C. S. An overview of the impacts of ridesourcing in developing countries: Main topics and questions for future research. Latin American Transport Studies, 2024; 2: 100017. doi:10.1016/j.latran.2024.100017.
  4. Etminani-Ghasrodashti, R., Hamidi, S. Individuals’ Demand for Ride-hailing Services: Investigating the Combined Effects of Attitudinal Factors, Land Use, and Travel Attributes on Demand for App-based Taxis in Tehran, Iran. Sustainability, 2019; 11: 5755. doi:10.3390/su11205755.
  5. Nie, Y. How can the taxi industry survive the tide of ridesourcing? Evidence from Shenzhen, China. Transportation Research Part C: Emerging Technologies, 2017; 79: 242–256. doi:10.1016/j.trc.2017.03.017.
  6. Tirachini, A. Ride-hailing, travel behaviour and sustainable mobility: an international review. Transportation, 2020; 47: 2011–2047. doi:10.1007/s11116-019-10070-2.
  7. Rayle, L., Dai, D., Chan, N., Cervero, R., Shaheen, S. Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco. Transport Policy, 2016; 45: 168–178. doi:10.1016/j.tranpol.2015.10.004.
  8. Snapp group annual report. Tehran (IR): Snapp; 2020. Report No.: 2.
  9. Said, M., Soria, J., Stathopoulos, A. Shifting Mobility Behaviors in Unprecedented Times: A Multigroup MIMIC Model Investigating Intentions to Use On-Demand Ride Services During the COVID-19 Pandemic. Transportation Research Record, 2023; 2677: 704–722. doi:10.1177/03611981221147520.
  10. Ke, J., Yang, H., Zheng, H., Chen, X., Jia, Y., Gong, P., Ye, J. Hexagon-Based Convolutional Neural Network for Supply-Demand Forecasting of Ride-Sourcing Services. IEEE Transactions on Intelligent Transportation Systems, 2019; 20: 4160–4173. doi:10.1109/TITS.2018.2882861.
  11. Weyl, E. G. A Price Theory of Multi-sided Platforms. American Economic Review, 2010; 100: 1642–72. doi:10.1257/aer.100.4.1642.
  12. Armstrong, M. Competition in Two-Sided Markets. RAND Journal of Economics, 2006; 37: 668–691. doi:10.1111/j.1756-2171.2006.tb00037.x.
  13. Wang, H., Yang, H. Ridesourcing systems: A framework and review. Transportation Research Part B: Methodological, 2019; 129: 122–155. doi:10.1016/j.trb.2019.07.009.
  14. Alemi, F., Circella, G., Mokhtarian, P., Handy, S. What drives the use of ride-hailing in California? Ordered probit models of the usage frequency of Uber and Lyft. Transportation Research Part C: Emerging Technologies, 2019; 102: 233–248. doi:10.1016/j.trc.2018.12.016.
  15. Greene, W. H. Econometric Analysis. 7th ed. Boston (MA): Pearson; 2012.
  16. Train, K. Discrete choice methods with simulation. 2nd ed. Cambridge (UK): Cambridge University Press; 2009.
  17. Acheampong, R. A., Siiba, A., Okyere, D. K., Tuffour, J. P. Mobility-on-demand: An empirical study of internet-based ride-hailing adoption factors, travel characteristics and mode substitution effects. Transportation Research Part C: Emerging Technologies, 2020; 115: 102638. doi:10.1016/j.trc.2020.102638.
  18. Tirachini, A., del Río, M. Ride-hailing in Santiago de Chile: Users’ characterisation and effects on travel behaviour. Transport Policy, 2019; 82: 46–57. doi:10.1016/j.tranpol.2019.07.008.
  19. Dias, F. F., Lavieri, P. S., Garikapati, V. M., Astroza, S., Pendyala, R. M., Bhat, C. R. A behavioral choice model of the use of car-sharing and ride-sourcing services. Transportation, 2017; 44: 1307–1323. doi:10.1007/s11116-017-9797-8.
  20. Vinayak, P., Dias, F. F., Astroza, S., Bhat, C. R., Pendyala, R. M., Garikapati, V. M. Accounting for multi-dimensional dependencies among decision-makers within a generalized model framework: An application to understanding shared mobility service usage levels. Transport Policy, 2018; 72: 129–137. doi:10.1016/j.tranpol.2018.09.013.
  21. Tang, B.-J., Li, X.-Y., Yu, B., Wei, Y.-M. How app-based ride-hailing services influence travel behavior: An empirical study from China. International Journal of Sustainable Transportation, 2020; 14: 554–568. doi:10.1080/15568318.2019.1584932.
  22. Atkinson-Palombo, C., Varone, L., Garrick, N. W. Understanding the Surprising and Oversized Use of Ridesourcing Services in Poor Neighborhoods in New York City. Transportation Research Record, 2019; 2673: 185–194. doi:10.1177/0361198119835809.
  23. Nugroho, S. B., Zusman, E., Nakano, R. Explaining the spread of online taxi services in Semarang, Bogor and Bandung, Indonesia; a discrete choice analysis. Travel Behaviour and Society, 2020; 20: 358–369. doi:10.1016/j.tbs.2020.04.008.
  24. Lesteven, G., Samadzad, M. Ride-hailing, a new mode to commute? Evidence from Tehran, Iran. Travel Behaviour and Society, 2021; 22: 175–185. doi:10.1016/j.tbs.2020.09.006.
  25. Smith, A. Shared, Collaborative and On Demand: The New Digital Economy. Washington, D.C. (US): Pew Research Center; 2016. Report No.: 02.
  26. Hussain, I., Hussain, Q., Dias, C., Bargi, W. A., Ali, N., Abdullah, M., Cheng, L. Exploring Commuter’s Preferences and Future Intentions to Use Ride-Sharing: A Case Study From a Developing Country. Journal of Advanced Transportation, 2025; 2025: 5516034. doi:10.1155/atr/5516034.
  27. Sabouri, S., Brewer, S., Ewing, R. Exploring the relationship between ride-sourcing services and vehicle ownership, using both inferential and machine learning approaches. Landscape and Urban Planning, 2020; 198: 103797. doi:10.1016/j.landurbplan.2020.103797.
  28. Circella, G., Alemi, F., Tiedeman, K., Handy, S., Mokhtarian, P. L. The Adoption of Shared Mobility in California and Its Relationship with Other Components of Travel Behavior. Davis (CA): National Center for Sustainable Transportation; 2018. Report No.: 03.
  29. Wali, B., Santi, P., Ratti, C. Modeling ride-hailing and carsharing adoption & use patterns: deciphering the substitutive and complementary impacts of built environment, transit accessibility, & active travel. Sustainable Cities and Society, 2025; 120: 105931. doi:10.1016/j.scs.2024.105931.
  30. Li, W., Ma, J., Cai, H., Chen, F., Qin, W. The role of built environment in shaping reserved ride-hailing services: Insights from interpretable machine learning approach. Research in Transportation Business & Management, 2024; 56: 101173. doi:10.1016/j.rtbm.2024.101173.
  31. Alemi, F., Circella, G., Mokhtarian, P., Handy, S. Exploring the latent constructs behind the use of ride-hailing in California. Journal of Choice Modelling, 2018; 29: 47–62. doi:10.1016/j.jocm.2018.08.003.
  32. Wang, S., Noland, R. B. Variation in ride-hailing trips in Chengdu, China. Transportation Research Part D: Transport and Environment, 2021; 90: 102596. doi:10.1016/j.trd.2020.102596.
  33. Sarjana, S., Ramadan, O., Sisiopiku, V. Analysis of Transportation Users’ Preferences and Attitudes for Identifying Micro-Level Determinants of Transportation Network Companies’ (TNCs) Growth. Journal of Transportation Technologies, 2020; 10: 251–264. doi:10.4236/jtts.2020.103016.
  34. Bhaduri, E., Pal, S., Goswami, A. K. Analysing heterogeneity in factors affecting adoption of ride-hailing services: a stepwise LCCA-MCDM modelling approach. Transportation, 2024; doi:10.1007/s11116-024-10563-9.
  35. Sikder, S. Who Uses Ride-Hailing Services in the United States? Transportation Research Record, 2019; 2673: 40–54. doi:10.1177/0361198119859302.
  36. Nguyen-Phuoc, D. Q., Su, D. N., Tran, P. T. K., Le, D.-T. T., Johnson, L. W. Factors influencing customer's loyalty towards ride-hailing taxi services – A case study of Vietnam. Transportation Research Part A: Policy and Practice, 2020; 134: 96–112. doi:10.1016/j.tra.2020.02.008.
  37. Anser, M., Ahmed, F., Ali, A. Investigating Factors Impacting the Use of Ride-Hailing Service Applications. International Journal of Management Research and Emerging Sciences, 2024; 14: doi:10.56536/ijmres.v14i3.637.
  38. Ghaffar, A., Mitra, S., Hyland, M. Modeling determinants of ridesourcing usage: A census tract-level analysis of Chicago. Transportation Research Part C: Emerging Technologies, 2020; 119: 102769. doi:10.1016/j.trc.2020.102769.
  39. Azimi, G., Rahimi, A., Asgari, H., Jin, X. Role of Attitudes in Transit and Auto Users’ Mode Choice of Ridesourcing. Transportation Research Record, 2020; 2674: 1–16. doi:10.1177/0361198120941841.
  40. Tohidimehr, H., Bakhtiarizadeh, H. Money on the Way: Analyzing the Impact of Ride-Sharing on Labor, Income, and Expenditure in Iran. Income, and Expenditure in Iran (October 22, 2024), 2024; doi:10.2139/ssrn.5166284.
  41. Akbari, M., Amiri, N. S., Zúñiga, M. Á., Padash, H., Shakiba, H. Evidence for Acceptance of Ride-Hailing Services in Iran. Transportation Research Record, 2020; 2674: 289–303. doi:10.1177/0361198120942224.
  42. Edrisi, A., Rezaei, H. Assessment of how Ride-Hailing services affect individuals' travel mode choice in urban transportation. International Journal of Human Capital in Urban Management, 2021; 6: 81–96. doi:10.22034/IJHCUM.2021.01.07.
  43. Koppelman, F., Bhat, C. A Self-Instructing Course in Mode Choice Modelling: Multinomial and Nested Logit Models. Washington, D.C. (US): US Federal Transit Administration - Department of Transportation; 2006. Report No.: 04.
  44. Daykin, A. R., Moffatt, P. G. Analyzing Ordered Responses: A Review of the Ordered Probit Model. Understanding Statistics, 2002; 1: 157–166. doi:10.1207/S15328031US0103_02.
  45. Tabachnick, B. G., Fidell, L. S. Using Multivariate Statistics. 6th ed. Boston (MA): Pearson; 2013.
  46. Williams, B., Onsman, A., Brown, T. Exploratory Factor Analysis: A Five-Step Guide for Novices. Australasian Journal of Paramedicine, 2010; 8: 1–13. doi:10.33151/ajp.8.3.93.
  47. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E. Multivariate data analysis. 8th ed. Boston (MA): CENGATE; 2019.
  48. Mirkatouli, J., Samadi, R., Hosseini, A. Evaluating and analysis of socio-economic variables on land and housing prices in Mashhad, Iran. Sustainable Cities and Society, 2018; 41: 695–705. doi:10.1016/j.scs.2018.06.022.
  49. Talebian, K., Riza, M. Mashhad, City of Light. Cities, 2020; 101: 102674. doi:10.1016/j.cities.2020.102674.
  50. Soltanifard, H., Roshandel, T., Ghodrati, S. Assessment and ranking of influencing factors in the relationship between spatial patterns of urban green spaces and socioeconomic indices in Mashhad urban districts, Iran. Modeling Earth Systems and Environment, 2020; 6: 1589–1605. doi:10.1007/s40808-020-00776-z.
  51. Jing, P., Chen, Y., Wang, X., Pan, K., Yuan, D. Evaluating the effectiveness of Didi ride-hailing security measures: An integration model. Transportation Research Part F: Traffic Psychology and Behaviour, 2021; 76: 139–166. doi:10.1016/j.trf.2020.11.004.
  52. Sedighi, M., Parsaeiyan, H., Araghi, Y. An Empirical Study of Intention to Continue Using of Digital Ride-hailing Platforms. The Review of Socionetwork Strategies, 2021; 15: 489–515. doi:10.1007/s12626-021-00098-1.
  53. Baghestani, A., Heshami, S., Mahpour, A. The impact of pandemic experiences on future similar situations: analysis of latent variables and trip purposes in ride-hailing choice. Transportation Planning and Technology, 2026; 49: 691–710. doi:10.1080/03081060.2025.2458606.
  54. Conway, M. W., Salon, D., King, D. A. Trends in Taxi Use and the Advent of Ridehailing, 1995–2017: Evidence from the US National Household Travel Survey. Urban Science, 2018; 2: 79. doi:10.3390/urbansci2030079.
  55. Habib, K. N. Mode choice modelling for hailable rides: An investigation of the competition of Uber with other modes by using an integrated non-compensatory choice model with probabilistic choice set formation. Transportation Research Part A: Policy and Practice, 2019; 129: 205–216. doi:10.1016/j.tra.2019.08.014.
  56. Loa, P., Nurul Habib, K. Examining the influence of attitudinal factors on the use of ride-hailing services in Toronto. Transportation Research Part A: Policy and Practice, 2021; 146: 13–28. doi:10.1016/j.tra.2021.02.002.
  57. Sabogal-Cardona, O., Oviedo, D., Scholl, L., Crotte, A., Bedoya-Maya, F. Not my usual trip: Ride-hailing characterization in Mexico City. Travel Behaviour and Society, 2021; 25: 233–245. doi:10.1016/j.tbs.2021.07.010.
  58. Firoozi Yeganeh, S., Khademi, N., Farahani, H., Besharat, M. A. A qualitative exploration of factors influencing women's intention to use shared taxis: A study on the characteristics of urban commuting behavior in Iran. Transport Policy, 2022; 129: 90–104. doi:10.1016/j.tranpol.2022.10.001.
  59. Zhen, C. Impact of ride-sourcing services on travel habits and transportation planning [Master's Thesis]. Pittsburgh (PA): University of Pittsburgh; 2015.
آمار
تعداد مشاهده مقاله: 170
تعداد دریافت فایل اصل مقاله: 29


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب