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Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2016. Intercity Passenger Rail in the Context of Dynamic Travel Markets. Washington, DC: The National Academies Press. doi: 10.17226/22072.
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Page 117
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2016. Intercity Passenger Rail in the Context of Dynamic Travel Markets. Washington, DC: The National Academies Press. doi: 10.17226/22072.
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Page 117
Page 118
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2016. Intercity Passenger Rail in the Context of Dynamic Travel Markets. Washington, DC: The National Academies Press. doi: 10.17226/22072.
×
Page 118
Page 119
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2016. Intercity Passenger Rail in the Context of Dynamic Travel Markets. Washington, DC: The National Academies Press. doi: 10.17226/22072.
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116 Aarts, H., B. Verplanken, and A. Van Knippenberg (1997). “Habit and Information Use in Travel Mode Choices.” Acta Psychologica 96(1): 1–14. Abou-Zeid, M., M. Ben-Akiva, M. Bierlaire, C. Choudhury, and S. Hess (2010). “Attitudes and Value of Time Heterogeneity.” In: E. Van de Voorde, and T. Vanelslander (eds.), Applied Transport Economics: A Management and Policy Perspective, De Boeck Publishing, pp. 523–545. Amrosell (2008). “The Travelsmart Model: How to Think People out of Their Vehicles.” Twin Cities Streets for People. Website. http://www.tcstreetsforpeople.org/node/341. Reprint of J. Jowit, “Inside Track: How to Think People out of Their Vehicles,” Financial Times, September 2001. Anable, J. (2005). “‘Complacent Car Addicts’ or ‘Aspiring Environmentalists’? Identifying Travel Behaviour Segments Using Attitude Theory.” Transport Policy 12(1): 65–78. http://dx.doi.org/10.1016/j.tranpol.2004.11.004. Ashok, K., W. R. Dillon, and S. Yuan (2002). “Extending Discrete Choice Models to Incorporate Attitudinal and Other Latent Variables.” Journal of Marketing Research 39(1): 31–46. Ayvalik, C., K. Prossaligou, R. Greene-Roesel, and C. Wornum (2008). “TOD Choices Study—Market Segmentation Results.” Metropolitan Transportation Commission. MTC Library. Bamberg, S., I. Ajzen, and P. Schmidt (2003). “Choice of Travel Mode in the Theory of Planned Behavior: The Roles of Past Behavior, Habit, and Reasoned Action.” Basic and Applied Social Psychology 25(3): 175–187. Ben-Akiva, M., D. McFadden, T. Gärling, D. Gopinath, J. Walker, D. Bolduc, A. Börsch-Supan, P. Delquié, O. Larichev, and T. Morikawa (1999). “Extended Framework for Modeling Choice Behavior.” Marketing Letters 10(3): 187–203. Ben-Akiva, M., D. McFadden, K. Train, J. Walker, C. Bhat, M. Bierlaire, D. Bolduc, A. Boersch-Supan, D. Brownstone, D. S. Bunch, A. Daly, A. de Palma, D. Gopinath, A. Karlstrom, and M. A. Munizaga (2002). “Hybrid Choice Models: Progress and Challenges.” Marketing Letters 13(3):163–75. Ben-Akiva, M., J. Walker, A. T. Bernardino, D. A. Gopinath, T. Morikawa, and A. Polydoropoulou (1999). “Integra- tion of Choice and Latent Variable Models.” Massachusetts Institute of Technology, Cambridge. http://www. joanwalker.com/uploads/3/6/9/5/3695513/benakivawalkeretal_iclv_chapter_2002.pdf. Ben-Akiva, M., J. L. Walker, A. T. Bernardino, D. A. Gopinath, T. Morikawa, and A. Polydoropoulou (2002). “Integration of Choice and Latent Variable Models.” In: H. S. Mahmassani (ed.), In Perpetual Motion: Travel Behavior Research Opportunities and Application Challenges, Elsevier, Amsterdam, pp. 431–470. Blumenberg, E., M. Wander, B. Taylor, and M. Smart (2013). “The Times Are They A-Changin’? Youth, Travel Mode, and the Journey to Work.” TRB 92nd Annual Meeting Compendium of Papers. Bolduc, D., M. Ben-Akiva, J. Walker, and A. Michaud (2005). “Hybrid Choice Models with Logit Kernel: Applicabil- ity to Large Scale Models.” In: M. Lee-Gosselin and S. Doherty (eds.), Integrated Land-Use and Transportation Models: Behavioural Foundations. Elsevier, Oxford, p. 275–302. Catawba Riverkeeper Foundation v. NC Department of Transportation (2015). No. 5:15 CV-00029-D (W.D.N.C. Mar. 13, 2015). Retrieved from https://www.southernenvironment.org/uploads/words_docs/03-13-15_ Order_-_Granting_Plaintiffs_Motion_for_SJ_-_Dkt_71.PDF. Chakraborty, A. and A. McMillan (2015). “Scenario Planning for Urban Planners: Toward a Practitioner’s Guide.” Journal of the American Planning Association 81(1): 1–12. doi:10.1080/01944363.2015.1038576. Chalom, A. and P.I.K.L de Prado (2015). Documentation for Parameter Space Exploration with Latin Hyper- cubes, Version 0.4.3. http://cran.r-project.org/web/packages/pse/pse.pdf. Chorus, C. G. and M. Kroesen (2014). “On the (Im-)Possibility of Deriving Transport Policy Implications from Hybrid Choice Models.” Transport Policy 36: 217–222. doi:10.1016/j.tranpol.2014.09.001. Coogan, M. A., M. Campbell, T. J. Adler, S. Forward, and J. P. Assailly (2011). “Latent Class Cluster Analysis of Driver Attitudes Towards Risky Driving in Northern New England: Is There a Rural Culture of Unsafe Driving Attitudes and Behavior?” Presented at 90th Annual Meeting of the Transportation Research Board, Washington, DC. References

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118 Intercity Passenger Rail in the Context of Dynamic Travel Markets Le Vine, S. and P. Jones (2012). “On the Move: Making Sense of Car and Train Travel Trends in Britain.” RAC Foundation, London. Le Vine, S., P. Jones, M. E. H. Lee-Gosselin, and J. Polak (2014). “Is Heightened Environmental Sensitivity Respon- sible for Drop in Young Adults’ Rates of Driver’s License Acquisition?” Transportation Research Record: Journal of the Transportation Research Board, No. 2465, Transportation Research Board of the National Academies, pp. 73–78. Le Vine, S., C. Latinopoulos, and J. Polak (2014a). “Establishing the Links Between Online Activity and Car Use: Evidence from a Combined Travel Diary and Online-Activity Pseudo-Diary Data Set.” Transportation Research Record: Journal of the Transportation Research Board, No. 2405, Transportation Research Board of the National Academies, pp. 68–77. Le Vine, S., C. Latinopoulos, and J. 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TRB’s National Cooperative Rail Research Program (NCRRP) Report 4: Intercity Passenger Rail in the Context of Dynamic Travel Markets explains the analytical framework and models developed to improve understanding of how current or potential intercity travelers make the choice to travel by rail. NCRRP Web-Only Document 2: Bibliography and Technical Appendices to Intercity Passenger Rail in the Context of Dynamic Travel Markets outlines materials used to develop NCRRP Report 4.

The Integrated Choice/Latent Variable (ICLV) model explores how demand for rail is influenced by not only traditional times and costs but also cultural and psychological variables. The spreadsheet-based scenario analysis tool helps users translate the data generated from the ICLV model into possible future scenarios that take into account changing consumer demand in the context of changing levels of service by competing travel modes.

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