IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v110y2021icp238-253.html
   My bibliography  Save this article

Impacts of service feature on vulnerability analysis of high-speed rail network

Author

Listed:
  • Li, Tao
  • Rong, Lili

Abstract

While previous literatures have analyzed the vulnerability of high-speed rail network (HSRN), they rarely consider its service feature. Obviously, one of the key features of HSRN is offering passengers fast travel services. This study selects the passenger flow and travel time to describe the service feature of HSRN, and constructs a multiple-weight HSRN. Then, the service performance is taken as the indicator of HSRN's vulnerability by innovatively integrating complex network theory and reliability theory. Using the daily operation data of China's HSRN (CHSRN) merged with the coordinate data and statistics data in November 2018, this study assesses its vulnerability under natural hazards and manmade accidents. Afterwards, the critical component and critical area within CHSRN are identified by the spatially localized failures (SLFs) model. Comparing with the results obtained by previous methods, this study finds that the vulnerability of CHSRN is always overestimated, and some critical components are overlooked regardless of its service feature. Furthermore, we also find that the critical areas within CHSRN mostly lie on the Yangtze River Delta as considering the service feature, while they are scattered along Beijing-Guangzhou railway line or Beijing-Shanghai railway line as ignoring the feature. These findings can help administrators develop different strategies to better prioritize the allocation of limited maintenance resources and mitigate the vulnerability of HSRN.

Suggested Citation

  • Li, Tao & Rong, Lili, 2021. "Impacts of service feature on vulnerability analysis of high-speed rail network," Transport Policy, Elsevier, vol. 110(C), pages 238-253.
    • Handle: RePEc:eee:trapol:v:110:y:2021:i:c:p:238-253
    DOI: 10.1016/j.tranpol.2021.05.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X21001566
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tranpol.2021.05.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Derrible, Sybil & Kennedy, Christopher, 2010. "The complexity and robustness of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3678-3691.
    2. Jiang, Ruoyun & Lu, Qing-Chang & Peng, Zhong-Ren, 2018. "A station-based rail transit network vulnerability measure considering land use dependency," Journal of Transport Geography, Elsevier, vol. 66(C), pages 10-18.
    3. Vickerman, Roger, 2018. "Can high-speed rail have a transformative effect on the economy?," Transport Policy, Elsevier, vol. 62(C), pages 31-37.
    4. Moyano, Amparo & Martínez, Héctor S. & Coronado, José M., 2018. "From network to services: A comparative accessibility analysis of the Spanish high-speed rail system," Transport Policy, Elsevier, vol. 63(C), pages 51-60.
    5. Zhang, Anming & Wan, Yulai & Yang, Hangjun, 2019. "Impacts of high-speed rail on airlines, airports and regional economies: A survey of recent research," Transport Policy, Elsevier, vol. 81(C), pages 1-19.
    6. Jiao, Jingjuan & Wang, Jiaoe & Jin, Fengjun, 2017. "Impacts of high-speed rail lines on the city network in China," Journal of Transport Geography, Elsevier, vol. 60(C), pages 257-266.
    7. Yang, Hangjun & Zhang, Anming, 2012. "Effects of high-speed rail and air transport competition on prices, profits and welfare," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1322-1333.
    8. Li, Yan & Chen, Zhenhua & Wang, Peng, 2020. "Impact of high-speed rail on urban economic efficiency in China," Transport Policy, Elsevier, vol. 97(C), pages 220-231.
    9. Cats, Oded & Jenelius, Erik, 2015. "Planning for the unexpected: The value of reserve capacity for public transport network robustness," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 47-61.
    10. Yang, Hangjun & Ma, Wenliang & Wang, Qiang & Wang, Kun & Zhang, Yahua, 2020. "Welfare implications for air passengers in China in the era of high-speed rail," Transport Policy, Elsevier, vol. 95(C), pages 1-13.
    11. Clewlow, Regina R. & Sussman, Joseph M. & Balakrishnan, Hamsa, 2014. "The impact of high-speed rail and low-cost carriers on European air passenger traffic," Transport Policy, Elsevier, vol. 33(C), pages 136-143.
    12. Yahua Zhang & Faqin Lin & Anming Zhang, 2018. "Gravity models in air transport research: a survey and an application," Chapters, in: Bruce A. Blonigen & Wesley W. Wilson (ed.), Handbook of International Trade and Transportation, chapter 4, pages 141-158, Edward Elgar Publishing.
    13. Kim, Hyojin & Sultana, Selima & Weber, Joe, 2018. "A geographic assessment of the economic development impact of Korean high-speed rail stations," Transport Policy, Elsevier, vol. 66(C), pages 127-137.
    14. Zhenhua Chen, 2019. "Measuring the regional economic impacts of high-speed rail using a dynamic SCGE model: the case of China," European Planning Studies, Taylor & Francis Journals, vol. 27(3), pages 483-512, March.
    15. Berdica, Katja, 2002. "An introduction to road vulnerability: what has been done, is done and should be done," Transport Policy, Elsevier, vol. 9(2), pages 117-127, April.
    16. López, Fernando A. & Páez, Antonio & Carrasco, Juan A. & Ruminot, Natalia A., 2017. "Vulnerability of nodes under controlled network topology and flow autocorrelation conditions," Journal of Transport Geography, Elsevier, vol. 59(C), pages 77-87.
    17. Zhang, Jianhua & Hu, Funian & Wang, Shuliang & Dai, Yang & Wang, Yixing, 2016. "Structural vulnerability and intervention of high speed railway networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 743-751.
    18. Laurino, Antonio & Ramella, Francesco & Beria, Paolo, 2015. "The economic regulation of railway networks: A worldwide survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 202-212.
    19. Sun, Xiaoqian & Wandelt, Sebastian & Zheng, Changhong & Zhang, Anming, 2021. "COVID-19 pandemic and air transportation: Successfully navigating the paper hurricane," Journal of Air Transport Management, Elsevier, vol. 94(C).
    20. Zhang, Fangni & Graham, Daniel J. & Wong, Mark Siu Chun, 2018. "Quantifying the substitutability and complementarity between high-speed rail and air transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 191-215.
    21. Zhang, Wenxin & Nian, Peihao & Lyu, Guowei, 2016. "A multimodal approach to assessing accessibility of a high-speed railway station," Journal of Transport Geography, Elsevier, vol. 54(C), pages 91-101.
    22. Zhou, Yaoming & Wang, Junwei & Huang, George Q., 2019. "Efficiency and robustness of weighted air transport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 14-26.
    23. Xu, Wangtu (Ato) & Zhou, Jiangping & Qiu, Guo, 2018. "China's high-speed rail network construction and planning over time: a network analysis," Journal of Transport Geography, Elsevier, vol. 70(C), pages 40-54.
    24. Szymula, Christopher & Bešinović, Nikola, 2020. "Passenger-centered vulnerability assessment of railway networks," Transportation Research Part B: Methodological, Elsevier, vol. 136(C), pages 30-61.
    25. Cats, Oded & Koppenol, Gert-Jaap & Warnier, Martijn, 2017. "Robustness assessment of link capacity reduction for complex networks: Application for public transport systems," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 544-553.
    26. Li, Tao & Rong, Lili & Zhang, Anming, 2021. "Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail," Transport Policy, Elsevier, vol. 106(C), pages 226-238.
    27. Campos, Javier & de Rus, Ginés, 2009. "Some stylized facts about high-speed rail: A review of HSR experiences around the world," Transport Policy, Elsevier, vol. 16(1), pages 19-28, January.
    28. Lu, Qing-Chang, 2018. "Modeling network resilience of rail transit under operational incidents," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 227-237.
    29. Snelder, M. & van Zuylen, H.J. & Immers, L.H., 2012. "A framework for robustness analysis of road networks for short term variations in supply," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(5), pages 828-842.
    30. Sun, Lishan & Huang, Yuchen & Chen, Yanyan & Yao, Liya, 2018. "Vulnerability assessment of urban rail transit based on multi-static weighted method in Beijing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 108(C), pages 12-24.
    31. Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2021. "Comparative accessibility of Chinese airports and high-speed railway stations: A high-resolution, yet scalable framework based on open data," Journal of Air Transport Management, Elsevier, vol. 92(C).
    32. Li, Tao & Rong, Lili & Yan, Kesheng, 2019. "Vulnerability analysis and critical area identification of public transport system: A case of high-speed rail and air transport coupling system in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 55-70.
    33. Reggiani, Aura & Nijkamp, Peter & Lanzi, Diego, 2015. "Transport resilience and vulnerability: The role of connectivity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 4-15.
    34. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    35. Angeloudis, Panagiotis & Fisk, David, 2006. "Large subway systems as complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 553-558.
    36. Li, Tao & Rong, Lili, 2020. "A comprehensive method for the robustness assessment of high-speed rail network with operation data: A case in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 666-681.
    37. Wang, Kun & Jiang, Changmin & Ng, Adolf K.Y. & Zhu, Zhenran, 2020. "Air and rail connectivity patterns of major city clusters in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 35-53.
    38. Zhang, Rui & Johnson, Daniel & Zhao, Weiming & Nash, Chris, 2019. "Competition of airline and high-speed rail in terms of price and frequency: Empirical study from China," Transport Policy, Elsevier, vol. 78(C), pages 8-18.
    39. Hsieh, Cheng-Hsien & Feng, Cheng-Min, 2020. "The highway resilience and vulnerability in Taiwan," Transport Policy, Elsevier, vol. 87(C), pages 1-9.
    40. Johansson, Jonas & Hassel, Henrik, 2010. "An approach for modelling interdependent infrastructures in the context of vulnerability analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1335-1344.
    41. Faturechi, Reza & Miller-Hooks, Elise, 2014. "Travel time resilience of roadway networks under disaster," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 47-64.
    42. Hong, Liu & Zhong, Xin & Ouyang, Min & Tian, Hui & He, Xiaozheng, 2019. "Vulnerability analysis of public transit systems from the perspective of urban residential communities," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 143-156.
    43. Wang, Kun & Xia, Wenyi & Zhang, Anming & Zhang, Qiong, 2018. "Effects of train speed on airline demand and price: Theory and empirical evidence from a natural experiment," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 99-130.
    44. Min Ouyang & Hui Tian & Zhenghua Wang & Liu Hong & Zijun Mao, 2019. "Critical Infrastructure Vulnerability to Spatially Localized Failures with Applications to Chinese Railway System," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 180-194, January.
    45. Xu, Wangtu (Ato) & Long, Ying & Zhang, Wei, 2019. "Prioritizing future funding and construction of the planned high-speed rail corridors of China – According to regional structure and urban land development potential indices," Transport Policy, Elsevier, vol. 81(C), pages 381-395.
    46. Chen, Zhenhua & Wang, Yuxuan & Zhou, Lei, 2021. "Predicting weather-induced delays of high-speed rail and aviation in China," Transport Policy, Elsevier, vol. 101(C), pages 1-13.
    47. Alexander Erath & Michael Löchl & Kay Axhausen, 2009. "Graph-Theoretical Analysis of the Swiss Road and Railway Networks Over Time," Networks and Spatial Economics, Springer, vol. 9(3), pages 379-400, September.
    48. Milan Janić, 2018. "Modelling the resilience of rail passenger transport networks affected by large-scale disruptive events: the case of HSR (high speed rail)," Transportation, Springer, vol. 45(4), pages 1101-1137, July.
    49. Ouyang, Min & Zhao, Lijing & Hong, Liu & Pan, Zhezhe, 2014. "Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 38-46.
    50. Huang, Yuxia & Jiang, Chenxin & Wang, Kun & Xiao, Yibin & Zhang, Anming, 2021. "Public-private partnership in high-speed rail financing: Case of uncertain regional economic spillovers in China," Transport Policy, Elsevier, vol. 106(C), pages 64-75.
    51. Ma, Wenliang & Wang, Qiang & Yang, Hangjun & Zhang, Anming & Zhang, Yahua, 2019. "Effects of Beijing-Shanghai high-speed rail on air travel: Passenger types, airline groups and tacit collusion," Research in Transportation Economics, Elsevier, vol. 74(C), pages 64-76.
    52. Wang, Lei, 2018. "High-speed rail services development and regional accessibility restructuring in megaregions: A case of the Yangtze River Delta, China," Transport Policy, Elsevier, vol. 72(C), pages 34-44.
    53. Zhang, Qiong & Yang, Hangjun & Wang, Qiang & Zhang, Anming & Zhang, Yahua, 2020. "Impact of high-speed rail on market concentration and Lerner index in China's airline market," Journal of Air Transport Management, Elsevier, vol. 83(C).
    54. Wang, Jiaoe & Mo, Huihui & Wang, Fahui & Jin, Fengjun, 2011. "Exploring the network structure and nodal centrality of China’s air transport network: A complex network approach," Journal of Transport Geography, Elsevier, vol. 19(4), pages 712-721.
    55. Li, Hongchang & Strauss, Jack & Lu, Liu, 2019. "The impact of high-speed rail on civil aviation in China," Transport Policy, Elsevier, vol. 74(C), pages 187-200.
    56. Ren, Xiaohong & Chen, Zhenhua & Wang, Fang & Dan, Ting & Wang, Wei & Guo, Xiaotong & Liu, Chunhua, 2020. "Impact of high-speed rail on social equity in China: Evidence from a mode choice survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 422-441.
    57. Wang, Feng & Wei, Xianjin & Liu, Juan & He, Lingyun & Gao, Mengnan, 2019. "Impact of high-speed rail on population mobility and urbanisation: A case study on Yangtze River Delta urban agglomeration, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 99-114.
    58. Ouyang, Min & Pan, ZheZhe & Hong, Liu & He, Yue, 2015. "Vulnerability analysis of complementary transportation systems with applications to railway and airline systems in China," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 248-257.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kopsidas, Athanasios & Kepaptsoglou, Konstantinos, 2022. "Identification of critical stations in a Metro System: A substitute complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    2. Zhang, Hui & Xu, Min & Ouyang, Min, 2024. "A multi-perspective functionality loss assessment of coupled railway and airline systems under extreme events," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Ilalokhoin, Ohis & Pant, Raghav & Hall, Jim W., 2023. "A model and methodology for resilience assessment of interdependent rail networks – Case study of Great Britain's rail network," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    4. Hong, Wei-Ting & Clifton, Geoffrey & Nelson, John D., 2024. "A data-driven conceptual framework for understanding the nature of hazards in railway accidents," Transport Policy, Elsevier, vol. 152(C), pages 102-117.
    5. Hu, Xinlei & Huang, Jie & Shi, Feng, 2022. "A robustness assessment with passenger flow data of high-speed rail network in China," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    6. Ma, Zhiao & Yang, Xin & Wu, Jianjun & Chen, Anthony & Wei, Yun & Gao, Ziyou, 2022. "Measuring the resilience of an urban rail transit network: A multi-dimensional evaluation model," Transport Policy, Elsevier, vol. 129(C), pages 38-50.
    7. Wang, Longjian & Zhang, Shuichao & Szűcs, Gábor & Wang, Yonggang, 2024. "Identifying the critical nodes in multi-modal transportation network with a traffic demand-based computational method," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    8. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Tao & Rong, Lili, 2022. "Spatiotemporally complementary effect of high-speed rail network on robustness of aviation network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 95-114.
    2. Li, Tao & Rong, Lili, 2020. "A comprehensive method for the robustness assessment of high-speed rail network with operation data: A case in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 666-681.
    3. Pan, Shouzheng & Yan, Hai & He, Jia & He, Zhengbing, 2021. "Vulnerability and resilience of transportation systems: A recent literature review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    4. Mohsen Momenitabar & Raj Bridgelall & Zhila Dehdari Ebrahimi & Mohammad Arani, 2021. "Literature Review of Socioeconomic and Environmental Impacts of High-Speed Rail in the World," Sustainability, MDPI, vol. 13(21), pages 1-27, November.
    5. Li, Tao & Rong, Lili & Yan, Kesheng, 2019. "Vulnerability analysis and critical area identification of public transport system: A case of high-speed rail and air transport coupling system in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 55-70.
    6. Mohsen Momenitabar & Zhila Dehdari Ebrahimi & Mohammad Arani, 2020. "A Systematic and Analytical Review of the Socioeconomic and Environmental Impact of the Deployed High-Speed Rail (HSR) Systems on the World," Papers 2003.04452, arXiv.org, revised Mar 2020.
    7. Hu, Xinlei & Huang, Jie & Shi, Feng, 2022. "A robustness assessment with passenger flow data of high-speed rail network in China," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    8. Hong, Liu & Ye, Bowen & Yan, Han & Zhang, Hui & Ouyang, Min & (Sean) He, Xiaozheng, 2019. "Spatiotemporal vulnerability analysis of railway systems with heterogeneous train flows," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 725-744.
    9. Feng, Xiao & He, Shiwei & Li, Guangye & Chi, Jushang, 2021. "Transfer network of high-speed rail and aviation: Structure and critical components," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    10. Jiao, Jingjuan & Wang, Jiaoe & Zhang, Fangni & Jin, Fengjun & Liu, Wei, 2020. "Roles of accessibility, connectivity and spatial interdependence in realizing the economic impact of high-speed rail: Evidence from China," Transport Policy, Elsevier, vol. 91(C), pages 1-15.
    11. Mizutani, Jun & Sakai, Hiroki, 2023. "The effects of frequent flyer programs in the competition with high speed rail: A case study of air passenger preference in Japan," Journal of Air Transport Management, Elsevier, vol. 106(C).
    12. Zhang, Anming & Wan, Yulai & Yang, Hangjun, 2019. "Impacts of high-speed rail on airlines, airports and regional economies: A survey of recent research," Transport Policy, Elsevier, vol. 81(C), pages 1-19.
    13. Huang, Yan & Zong, Huiming, 2020. "The spatial distribution and determinants of China’s high-speed train services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 56-70.
    14. Yang, Zhiwei & Li, Can & Jiao, Jingjuan & Liu, Wei & Zhang, Fangni, 2020. "On the joint impact of high-speed rail and megalopolis policy on regional economic growth in China," Transport Policy, Elsevier, vol. 99(C), pages 20-30.
    15. Wu, Bingyu & Levinson, David M., 2024. "A multi-modal analysis of the effect of transport on population and productivity in China," Journal of Transport Geography, Elsevier, vol. 116(C).
    16. Jiang, Changmin & Wang, Kun & Wang, Qiang & Yang, Hangjun, 2022. "The Impact of High-Speed Rail Competition on Airline On-Time Performance," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 109-127.
    17. Gonçalves, L.A.P.J. & Ribeiro, P.J.G., 2020. "Resilience of urban transportation systems. Concept, characteristics, and methods," Journal of Transport Geography, Elsevier, vol. 85(C).
    18. Zhang, Jianhua & Wang, Ziqi & Wang, Shuliang & Shao, Wenchao & Zhao, Xun & Liu, Weizhi, 2021. "Vulnerability assessments of weighted urban rail transit networks with integrated coupled map lattices," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    19. Lu, Qing-Chang & Zhang, Lei & Xu, Peng-Cheng & Cui, Xin & Li, Jing, 2022. "Modeling network vulnerability of urban rail transit under cascading failures: A Coupled Map Lattices approach," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    20. Zhu, Feng & Wu, Xu & Cao, Chengxuan, 2021. "High-speed rail and air transport competition under high flight delay conditions in China: A case study of the Beijing-Shanghai corridor," Utilities Policy, Elsevier, vol. 71(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:trapol:v:110:y:2021:i:c:p:238-253. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/30473/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.