Research on Demand Price Elasticity Based on Expressway ETC Data: A Case Study of Shanghai, China
Abstract
1. Introduction
2. Methodology
2.1. Demand Elasticity
2.2. Experimental Method
3. Case Studies and Discussion
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Olszewski, P.; Xie, L. Modelling the effects of road pricing on traffic in Singapore. Transp. Res. Part A Policy Pract. 2005, 39, 755–772. [Google Scholar] [CrossRef]
- TfL: Transport for London. 2003. Available online: http://www.cclondon.com/ (accessed on 16 March 2003).
- Burris, M.W. The toll-price component of travel demand elasticity. Int. J. Transport Econ./Riv. Internazionale Di Econ. Dei Trasp. 2003, 1, 45–59. [Google Scholar]
- Holguín-Veras, J.; Wang, Q.; Xu, N.; Ozbay, K.; Cetin, M.; Polimeni, J. The impacts of time of day pricing on the behavior of freight carriers in a congested urban area: Implications to road pricing. Transport. Res. Part A Policy Pract. 2006, 40, 744–766. [Google Scholar] [CrossRef]
- Holguín-Veras, J. Necessary conditions for off-hour deliveries and the effectiveness of urban freight road pricing and alternative financial policies in competitive markets. Transport. Res. Part A Policy Pract. 2008, 42, 392–413. [Google Scholar] [CrossRef]
- Holguín-Veras, J. The truth, the myths and the possible in freight road pricing in congested urban areas. Procedia-Social Behav. Sci. 2010, 2, 6366–6377. [Google Scholar] [CrossRef]
- Litman, T. Understanding Transport Demands and Elasticities. How Prices and Other Factors Affect Travel Behavior. (Victoria Transport Policy Institute: Litman). 2013. Available online: http://www.vtpi.org/elasticities.pdf (accessed on 22 November 2013).
- McKnight, C.E.; Hirschman, I.; Pucher, J.R.; Berechman, J.; Paaswell, R.E.; Hernandez, J.A.; Gamill, J. Optimal Toll Strategies for the Triborough Bridge and Tunnel Authority; Final Report; Triborough Bridge and Tunnel Authority: New York, NY, USA, 1992. [Google Scholar]
- Zou, W.; Wang, X.; Zhang, D. Truck crash severity in New York city: An investigation of the spatial and the time of day effects. Acc. Anal. Prevent. 2017, 99, 249–261. [Google Scholar] [CrossRef] [PubMed]
- Bari, M.E.; Burris, M.W.; Huang, C. The Impact of a Toll Reduction for Truck Traffic Using SH 130. Case Stud. Transp. Policy 2015, 2, 222–228. [Google Scholar] [CrossRef]
- Urbanek, A. Public Transport Fares as an Instrument of Impact on the Travel Behaviour: An Empirical Analysis of the Price Elasticity of Demand. In Challenges of Urban Mobility, Transport Companies and Systems; Springer Proceedings in Business and Economics: Berlin/Heidelberg, Germany, 2019. [Google Scholar]
- Sianturi, P.C.; Nasrudin, R.; Yudhistira, M.H. Estimating the price elasticity of demand for urban mass rapid transit ridership: A quasi-experimental evidence from Jakarta, Indonesia. Transp. Policy 2022, 10, 354–364. [Google Scholar] [CrossRef]
- Davis, L.W. Estimating the price elasticity of demand for subways: Evidence from Mexico. Reg. Sci. Urban Econ. 2021, 87, 103651. [Google Scholar] [CrossRef]
- Melo, P.C.; Sobreira, N.; Goulart, P. Estimating the long-run metro demand elasticities for Lisbon: A time-varying approach. Transp. Res. Part A 2019, 26, 360–376. [Google Scholar] [CrossRef]
- Holmgren, J. Meta-analysis of public transport demand. Transp. Res. Part A Policy Pract. 2017, 41, 1021–1035. [Google Scholar] [CrossRef]
OD Pairs | 2019 Charge/yuan | 2020 Charge/yuan | Distance/km | Charge Difference/yuan | Elasticity Value |
---|---|---|---|---|---|
S24-S19 | 4.75 | 0.95 | 1.58 | 3.8 | −0.42 |
S22-S24 | 4.75 | 1.46 | 2.43 | 3.29 | −0.46 |
S24-S22 | 4.75 | 1.46 | 2.43 | 3.29 | −0.37 |
S14-S15 | 4.75 | 1.9 | 3.17 | 2.85 | −0.38 |
S11-S16 | 4.75 | 1.9 | 3.17 | 2.85 | −0.50 |
S15-S14 | 4.75 | 1.9 | 3.17 | 2.85 | −0.23 |
S3-S21 | 4.75 | 3.8 | 6.30 | 0.95 | −1.78 |
S21-S3 | 4.75 | 3.8 | 6.30 | 0.95 | −1.29 |
S19-S26 | 4.75 | 5.23 | 8.72 | −0.48 | 2.17 |
S26-S19 | 4.75 | 5.23 | 8.72 | −0.48 | 1.40 |
S9-S10 | 9.5 | 5.48 | 9.13 | 4.02 | −0.81 |
S22-S23 | 9.5 | 6.21 | 10.35 | 3.29 | −0.93 |
S23-S22 | 9.5 | 6.21 | 10.35 | 3.29 | −0.86 |
S22-S25 | 9.5 | 6.21 | 10.35 | 3.29 | −0.69 |
S25-S22 | 9.5 | 6.21 | 10.35 | 3.29 | −0.71 |
S5-S6 | 9.5 | 6.65 | 11.08 | 2.85 | −0.75 |
S6-S5 | 9.5 | 6.65 | 11.08 | 2.85 | −0.33 |
S17-S18 | 4.75 | 7 | 11.66 | −2.25 | −0.27 |
S18-S17 | 4.75 | 7 | 11.66 | −2.25 | −0.28 |
S11-S12 | 14.25 | 9.5 | 15.83 | 4.75 | −0.90 |
S12-S11 | 14.25 | 9.5 | 15.83 | 4.75 | −0.54 |
S3-S4 | 14.25 | 10.45 | 17.41 | 3.8 | −1.59 |
S4-S3 | 14.25 | 10.45 | 17.41 | 3.8 | −1.30 |
S19-S20 | 14.25 | 11.23 | 18.71 | 3.02 | −1.78 |
S20-S19 | 14.25 | 11.23 | 18.71 | 3.02 | −1.36 |
S7-S8 | 14.25 | 11.4 | 19 | 2.85 | −1.91 |
S13-S11 | 14.25 | 11.4 | 19 | 2.85 | −1.41 |
S1-S2 | 19 | 15.2 | 25.33 | 3.8 | −1.85 |
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Li, Y.; Shao, M.; Sun, L.; Wang, X.; Song, S. Research on Demand Price Elasticity Based on Expressway ETC Data: A Case Study of Shanghai, China. Sustainability 2023, 15, 4379. https://doi.org/10.3390/su15054379
Li Y, Shao M, Sun L, Wang X, Song S. Research on Demand Price Elasticity Based on Expressway ETC Data: A Case Study of Shanghai, China. Sustainability. 2023; 15(5):4379. https://doi.org/10.3390/su15054379
Chicago/Turabian StyleLi, Yunyi, Minhua Shao, Lijun Sun, Xinmiao Wang, and Shizhao Song. 2023. "Research on Demand Price Elasticity Based on Expressway ETC Data: A Case Study of Shanghai, China" Sustainability 15, no. 5: 4379. https://doi.org/10.3390/su15054379
APA StyleLi, Y., Shao, M., Sun, L., Wang, X., & Song, S. (2023). Research on Demand Price Elasticity Based on Expressway ETC Data: A Case Study of Shanghai, China. Sustainability, 15(5), 4379. https://doi.org/10.3390/su15054379