Exploring drivers' willingness to pay for safer roads in Iran: a discrete choice experiment on reducing injury and mortality risks
-
Leila Zarei
,
Farimah Rahimi
,
Najmeh Moradi
,
Ali Majidpour Azad Shirazi
,
Yaser Sarikhani
,
Seyyed Taghi Heydari
,
Kamran Bagheri Lankarani
Abstract
Background: Road traffic injuries (RTIs) are a leading global health challenge, with Iran facing significant economic and social costs due to these incidents. This study investigates Iranian drivers' preferences for road safety and their willingness to pay (WTP) to reduce injury and mortality risks. It also examines the influence of demographic and driving-related factors on these preferences. Method: A discrete choice experiment (DCE) was conducted among Shiraz residents to analyze route preferences. Participants evaluated hypothetical commuting scenarios characterized by variations in travel time, cost, injury risk, and fatality risk. Using a D-efficient fractional factorial design, 10 two-alternative choice scenarios were developed. Data were collected through interviews in five districts, achieving an 81% response rate. A mixed logit regression model was employed to assess how route attributes influenced participants' decisions. Results: Key factors driving route choices included the number of deaths, injury rates, travel time, and cost, with fatalities being the most influential. Participants were willing to pay $7.07 extra for routes with travel times under 30 minutes, $8.98 for routes with fewer than 10 annual injuries, and $11.83 for routes with fewer than 5 annual deaths. WTP varied significantly across demographic groups: men prioritized reduced travel time, while women emphasized safety. Personal-use drivers exhibited higher WTP compared to professional drivers like taxi operators. Larger family sizes correlated with lower WTP, whereas individuals in excellent health or with supplementary health insurance displayed higher WTP for safer and faster routes. Conclusion: This study underscores the utility of DCEs in capturing drivers' preferences for road safety and efficiency in Iran. By highlighting the trade-offs drivers are willing to make and identifying key factors, these findings offer actionable insights for policymakers to design transportation systems that align with public safety and mobility priorities.
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36. Schoeters A, Large M, Koning M, Carnis L, Daniels S, Mignot D, et al. Economic valuation of preventing fatal and serious road injuries. Results of a willingness-to-pay study in four European countries. Accid Anal Prev. 2022;173:106705.
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38. Beli E, Nalmpantis D, editors. Estimation of the willingness to pay for road safety improvements and its correlation with specific demographic, psychological, and behavioral factors. Conference on Sustainable Urban Mobility. Springer; 2020.
39. Phanikumar C, Maitra B, editors. Modeling willingness-to-pay values for rural bus attributes under different trip purposes. J Transp Res Forum. 2006.
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42. Karmarkar OD, Jana A, Velaga NR. Willingness to pay for reduced travel time: case study of Mumbai-Ahmedabad jigh Speed railway. Case studies on transport policy. 2023;12:100974.
43. Poudel N, Singleton PA. Willingness to pay for changes in travel time and work time: a stated choice experiment of US commuters. Res Transp Econ. 2024;103:101381.
2. Xu Y, Chen M, Yang R, Wumaierjiang M, Huang S. Global, regional, and national burden of road injuries from 1990 to 2019. International journal of environmental research and public health. 2022;19(24):16479.
3. James SL, Lucchesi LR, Bisignano C, Castle CD, Dingels ZV, Fox JT, et al. The global burden of falls: global, regional and national estimates of morbidity and mortality from the global burden of disease Study 2017. Injury prevention. 2020;26(Suppl 2):i3–i11.
4. Ahmed SK, Mohammed MG, Abdulqadir SO, El‐Kader RGA, El‐Shall NA, Chandran D, et al. Road traffic accidental injuries and deaths: a neglected global health issue. Health science reports. 2023;6(5):e1240.
5. Hashempour R, Tahmasebi A, Veysi M, Amini M, Tavakoli N. Cost analysis of accidents according to demographic factors in Iran. Iranian journal of public health. 2019;48(7):1346.
6. Tafti MRS, Ostovar A, Moghaddam SS, Shobeiri P, Ehrampoush MH, Salmani I, et al. Burden of road traffic injuries in Iran: a national and subnational perspective, 1990− 2019. Injury prevention. 2023;29(2):101-10.
7. Seif M, Edalat S, Shirazi AMA, Alipouri S, Bayati M. Prediction of the burden of road traffic injuries in Iran by 2030: prevalence, death, and disability-adjusted life years. Chinese journal of traumatology. 2024.
8. Peden MM. World report on road traffic injury prevention: world health organization; 2004.
9. Honavar SG. Should visual function tests be mandatory for a driving license?. Indian J Ophthalmol. 2022;70(6):1871-4..
10. Rezaei S, Arab M, Matin BK, Sari AA. Extent, consequences and economic burden of road traffic crashes in Iran. Journal of injury and violence research. 2014;6(2):57.
11. Ismail MA, Abdelmageed SM. Cost of road traffic accidents in Egypt. International Journal of Humanities and Social Sciences. 2010;4(6):1219-25.
12. Anh TT, Dao NX, Anh TT, editors. The cost of road traffic accident in Vietnam. Proceedings of the Eastern Asia Society for Transportation Studies.Tokyo, Japan: J-Stage; 2005.
13. Deresse E, Komicha MA, Lema T, Abdulkadir S, Roba KT. Road traffic accident and management outcome among in Adama Hospital Medical College, Central Ethiopia. Pan African medical journal. 2021;38(1).
14. Rahmati F, Doosti M, Bahreini M. The cost analysis of patients with traffic traumatic injuries presenting to emergency department; a cross-sectional study. Adv J Emerg Med. 2018;3(1):e2.
15. Prakash I, Neves O, Cumbe E, Hamadani F, Razek T, Fata P, et al. The financial burden of road traffic injuries in Mozambique: a hospital‐related cost‐of‐illness study of Maputo Central Hospital. World J Surg. 2019;43(12):2959-66.
16. Kristianssen A-C. Towards a potential paradigm shift: the role of vision zero in global road safety policy making. The Vision Zero Handbook: Theory, Technology and Management for a Zero Casualty Policy. Springer; 2022:647-72.
17. Mekonnen AA, Beza AD, Sipos T. Estimating the value of statistical life in a road safety context based on the contingent valuation method. J Adv Transp. 2022;2022(1):3047794.
18. Niroomand N, Jenkins GP. A comparison of stated preference methods for the valuation of improvement in road safety. Econ Anal Policy. 2018;59:138-49.
19. Ainy E, Soori H, Ganjali M, Le H, Baghfalaki T. Estimating cost of road traffic injuries in Iran using willingness to pay (WTP) method. PLoS one. 2014;9(12):e112721.
20. Nankunda C, Evdorides H. A systematic review of the application of road safety valuation methods in assessing the economic impact of road traffic injuries. Future Transportation. 2023;3(4):1253-71.
21. Clark MD, Determann D, Petrou S, Moro D, de Bekker-Grob EW. Discrete choice experiments in health economics: a review of the literature. Pharmacoeconomics. 2014;32:883-902.
22. Bateman IJ. Economic valuation with stated preference techniques: a manual. Edward Elgar; 2002.
23. Jaździk-Osmólska A. Willingness to pay for road safety improvements in Poland. 2021.
24. Andersson H. Consistency in preferences for road safety: an analysis of precautionary and stated behavior. Research in transportation economics. 2013;43(1):41-9.
25. Akhundi A. Instructions on how to identify and prioritize high-accident road locations in Iran. 2020. Available from: https://transportsafety.ir/.
26. (CBI) TCBoI. The central bank of Iran (CBI) - foreign exchange rates: the central bank of Iran (CBI). 2022. Available from: https://www.cbi.ir/ExRates/rates_en.aspx.
27. Train KE. Discrete choice methods with simulation: Cambridge university press; 2009.
28. Ryan M, Gerard K, Amaya-Amaya M. Using discrete choice experiments to value health and health care. New York, NY: Springer Science & Business Media; 2007
29. Daly A, Hess S, de Dios Ortúzar J. Estimating willingness-to-pay from discrete choice models: setting the record straight. Transportation Research Part A: policy and practice. 2023;176:103828.
30. Han H, Sun S. Identifying heterogeneous willingness to pay for new energy vehicles attributes: a discrete choice experiment in China. Sustainability. 2024;16(7):2949.
31. Liu K, Xu Y. Route choice behavior: Understanding the impact of asymmetric preference on travelers’ decision making. Symmetry. 2019;11(1):66.
32. Fayyaz M, Bliemer MC, Beck MJ, Hess S, Van Lint J. Stated choices and simulated experiences: differences in the value of travel time and reliability. Transportation Research Part C: Emerging Technologies. 2021;128:103145.
33. Andersson Järnberg L, Andrén D, Hultkrantz L, Rutström EE, Vimefall E. Willingness to pay for private and public traffic safety improvements: the importance of the underlying good. Applied Economics. 2024:1-14.
34. Rousseau S, Franck M, De Jaeger S. The impact of spatial patterns in road traffic externalities on willingness-to-pay estimates. Environmental and Resource Economics. 2020;75:271-95.
35. Brownstone D, Ghosh A, Golob TF, Kazimi C, Van Amelsfort D. Drivers’ willingness-to-pay to reduce travel time: evidence from the San Diego I-15 congestion pricing project. Transportation Research Part A: Policy and Practice. 2003;37(4):373-87.
36. Schoeters A, Large M, Koning M, Carnis L, Daniels S, Mignot D, et al. Economic valuation of preventing fatal and serious road injuries. Results of a willingness-to-pay study in four European countries. Accid Anal Prev. 2022;173:106705.
37. Niroomand N, Jenkins GP. Estimating the value of life, injury, and travel time saved using a stated preference framework. Accid Anal Prev. 2016;91:216-25.
38. Beli E, Nalmpantis D, editors. Estimation of the willingness to pay for road safety improvements and its correlation with specific demographic, psychological, and behavioral factors. Conference on Sustainable Urban Mobility. Springer; 2020.
39. Phanikumar C, Maitra B, editors. Modeling willingness-to-pay values for rural bus attributes under different trip purposes. J Transp Res Forum. 2006.
40. Yang Z, Zhang Y, Bai X, Wu D, editors. Estimation of value of travel time savings using willingness-to-pay method. In: 18th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers; 2018.41. Wisutwattanasak P, Jomnonkwao S, Se C, Champahom T, Ratanavaraha V. Correlated random parameters model with heterogeneity in means for analysis of factors affecting the perceived value of road accidents and travel time. J Transp Res Forum. 2023;183:106992.
42. Karmarkar OD, Jana A, Velaga NR. Willingness to pay for reduced travel time: case study of Mumbai-Ahmedabad jigh Speed railway. Case studies on transport policy. 2023;12:100974.
43. Poudel N, Singleton PA. Willingness to pay for changes in travel time and work time: a stated choice experiment of US commuters. Res Transp Econ. 2024;103:101381.
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| Issue | In press | |
| Section | Original article | |
| Keywords | ||
| Discrete Choice Experiment Risk Reduction Behavior Road Safety Road Traffic Accident Willingness to Pay | ||
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How to Cite
1.
Zarei L, Rahimi F, Moradi N, Majidpour Azad Shirazi A, Sarikhani Y, Heydari ST, Bagheri Lankarani K. Exploring drivers’ willingness to pay for safer roads in Iran: a discrete choice experiment on reducing injury and mortality risks. Front Emerg Med. 2025;.
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