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Cristian Angelo Guevara

Personal Details

First Name:Cristian
Middle Name:Angelo
Last Name:Guevara
Suffix:
RePEc Short-ID:pgu425
[This author has chosen not to make the email address public]
https://scholar.google.com/citations?user=3vUZQDkAAAAJ&hl=es

Affiliation

Universidad de Chile, Departamento de Ingeniería Civil

http://ingenieria.uchile.cl/departamentos/87707/ingenieria-civil
Chile, Santiago

Research output

as
Jump to: Articles

Articles

  1. C. Angelo Guevara, 2017. "Mode-valued differences of in-vehicle travel time Savings," Transportation, Springer, vol. 44(5), pages 977-997, September.
  2. C. Angelo Guevara & Caspar G. Chorus & Moshe E. Ben-Akiva, 2016. "Sampling of Alternatives in Random Regret Minimization Models," Transportation Science, INFORMS, vol. 50(1), pages 306-321, February.
  3. Guevara, C. Angelo & Fukushi, Mitsuyoshi, 2016. "Modeling the decoy effect with context-RUM Models: Diagrammatic analysis and empirical evidence from route choice SP and mode choice RP case studies," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 318-337.
  4. Palma, David & Ortúzar, Juan de Dios & Rizzi, Luis Ignacio & Guevara, Cristian Angelo & Casaubon, Gerard & Ma, Huiqin, 2016. "Modelling choice when price is a cue for quality: a case study with Chinese consumers," Journal of choice modelling, Elsevier, vol. 19(C), pages 24-39.
  5. Fernández-Antolín, Anna & Guevara, C. Angelo & de Lapparent, Matthieu & Bierlaire, Michel, 2016. "Correcting for endogeneity due to omitted attitudes: Empirical assessment of a modified MIS method using RP mode choice data," Journal of choice modelling, Elsevier, vol. 20(C), pages 1-15.
  6. Guevara, C. Angelo, 2015. "Critical assessment of five methods to correct for endogeneity in discrete-choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 240-254.
  7. van Cranenburgh, Sander & Guevara, Cristian Angelo & Chorus, Caspar G., 2015. "New insights on random regret minimization models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 91-109.
  8. Guevara, C. Angelo & Donoso, Gonzalo A., 2014. "Tactical design of high-demand bus transfers," Transport Policy, Elsevier, vol. 32(C), pages 16-24.
  9. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Logit Mixture models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 185-198.
  10. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Multivariate Extreme Value (MEV) models," Transportation Research Part B: Methodological, Elsevier, vol. 48(C), pages 31-52.
  11. Cristian Angelo Guevara & Moshe E. Ben-Akiva, 2012. "Change of Scale and Forecasting with the Control-Function Method in Logit Models," Transportation Science, INFORMS, vol. 46(3), pages 425-437, August.
  12. Cherchi, Elisabetta & Guevara, Cristian Angelo, 2012. "A Monte Carlo experiment to analyze the curse of dimensionality in estimating random coefficients models with a full variance–covariance matrix," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 321-332.
  13. Basso, Leonardo J. & Guevara, Cristián Angelo & Gschwender, Antonio & Fuster, Marcelo, 2011. "Congestion pricing, transit subsidies and dedicated bus lanes: Efficient and practical solutions to congestion," Transport Policy, Elsevier, vol. 18(5), pages 676-684, September.
  14. Guevara, Cristian Angelo & Thomas, Alan, 2007. "Multiple classification analysis in trip production models," Transport Policy, Elsevier, vol. 14(6), pages 514-522, November.
  15. Sergio R. Jara-Diaz & Cristián A. Guevara, 2003. "Behind the Subjective Value of Travel Time Savings," Journal of Transport Economics and Policy, University of Bath, vol. 37(1), pages 29-46, January.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. C. Angelo Guevara, 2017. "Mode-valued differences of in-vehicle travel time Savings," Transportation, Springer, vol. 44(5), pages 977-997, September.

    Cited by:

    1. Pawlak, Jacek & Polak, John W. & Sivakumar, Aruna, 2017. "A framework for joint modelling of activity choice, duration, and productivity while travelling," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 153-172.

  2. C. Angelo Guevara & Caspar G. Chorus & Moshe E. Ben-Akiva, 2016. "Sampling of Alternatives in Random Regret Minimization Models," Transportation Science, INFORMS, vol. 50(1), pages 306-321, February.

    Cited by:

    1. Caspar G. Chorus, 2014. "Capturing alternative decision rules in travel choice models: a critical discussion," Chapters,in: Handbook of Choice Modelling, chapter 13, pages 290-310 Edward Elgar Publishing.

  3. Guevara, C. Angelo & Fukushi, Mitsuyoshi, 2016. "Modeling the decoy effect with context-RUM Models: Diagrammatic analysis and empirical evidence from route choice SP and mode choice RP case studies," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 318-337.

    Cited by:

    1. Hancock, Thomas O. & Hess, Stephane & Choudhury, Charisma F., 2018. "Decision field theory: Improvements to current methodology and comparisons with standard choice modelling techniques," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 18-40.

  4. Guevara, C. Angelo, 2015. "Critical assessment of five methods to correct for endogeneity in discrete-choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 240-254.

    Cited by:

    1. Vij, Akshay & Walker, Joan L., 2016. "How, when and why integrated choice and latent variable models are latently useful," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 192-217.
    2. Lurkin, Virginie & Garrow, Laurie A. & Higgins, Matthew J. & Newman, Jeffrey P. & Schyns, Michael, 2017. "Accounting for price endogeneity in airline itinerary choice models: An application to Continental U.S. markets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 228-246.
    3. Palma, David & Ortúzar, Juan de Dios & Rizzi, Luis Ignacio & Guevara, Cristian Angelo & Casaubon, Gerard & Ma, Huiqin, 2016. "Modelling choice when price is a cue for quality: a case study with Chinese consumers," Journal of choice modelling, Elsevier, vol. 19(C), pages 24-39.
    4. Virginie Lurkin & Laurie A. Garrow & Matthew J. Higgins & Jeffrey P. Newman & Michael Schyns, 2016. "Accounting for Price Endogeneity in Airline Itinerary Choice Models: An Application to Continental U.S. Markets," NBER Working Papers 22730, National Bureau of Economic Research, Inc.
    5. Wen, Chieh-Hua & Chen, Po-Hung, 2017. "Passenger booking timing for low-cost airlines: A continuous logit approach," Journal of Air Transport Management, Elsevier, vol. 64(PA), pages 91-99.
    6. Johannes Dahlin & Verena Halbherr & Peter Kurz & Michael Nelles & Carsten Herbes, 2016. "Marketing Green Fertilizers: Insights into Consumer Preferences," Sustainability, MDPI, Open Access Journal, vol. 8(11), pages 1-15, November.
    7. Fernández-Antolín, Anna & Guevara, C. Angelo & de Lapparent, Matthieu & Bierlaire, Michel, 2016. "Correcting for endogeneity due to omitted attitudes: Empirical assessment of a modified MIS method using RP mode choice data," Journal of choice modelling, Elsevier, vol. 20(C), pages 1-15.
    8. C. Angelo Guevara, 2017. "Mode-valued differences of in-vehicle travel time Savings," Transportation, Springer, vol. 44(5), pages 977-997, September.

  5. van Cranenburgh, Sander & Guevara, Cristian Angelo & Chorus, Caspar G., 2015. "New insights on random regret minimization models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 91-109.

    Cited by:

    1. Chorus, Caspar G., 2015. "Models of moral decision making: Literature review and research agenda for discrete choice analysis," Journal of choice modelling, Elsevier, vol. 16(C), pages 69-85.
    2. van Cranenburgh, Sander & Prato, Carlo G., 2016. "On the robustness of random regret minimization modelling outcomes towards omitted attributes," Journal of choice modelling, Elsevier, vol. 18(C), pages 51-70.
    3. Marley, A.A.J. & Swait, J., 2017. "Goal-based models for discrete choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 72-88.
    4. Caspar G. Chorus & Sander Cranenburgh, 2018. "Specification of regret-based models of choice behaviour: formal analyses and experimental design based evidence—commentary," Transportation, Springer, vol. 45(1), pages 247-256, January.
    5. Balbontin, Camila & Hensher, David A. & Collins, Andrew T., 2017. "Is there a systematic relationship between random parameters and process heuristics?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 160-177.
    6. Guevara, C. Angelo & Fukushi, Mitsuyoshi, 2016. "Modeling the decoy effect with context-RUM Models: Diagrammatic analysis and empirical evidence from route choice SP and mode choice RP case studies," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 318-337.
    7. Bliemer, Michiel C.J. & Rose, John M. & Chorus, Caspar G., 2017. "Detecting dominance in stated choice data and accounting for dominance-based scale differences in logit models," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 83-104.
    8. Boeri, Marco & Longo, Alberto, 2017. "The importance of regret minimization in the choice for renewable energy programmes: Evidence from a discrete choice experiment," Energy Economics, Elsevier, vol. 63(C), pages 253-260.
    9. Hancock, Thomas O. & Hess, Stephane & Choudhury, Charisma F., 2018. "Decision field theory: Improvements to current methodology and comparisons with standard choice modelling techniques," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 18-40.
    10. Mai, Tien & Bastin, Fabian & Frejinger, Emma, 2017. "On the similarities between random regret minimization and mother logit: The case of recursive route choice models," Journal of choice modelling, Elsevier, vol. 23(C), pages 21-33.

  6. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Logit Mixture models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 185-198.

    Cited by:

    1. Paleti, Rajesh & Faghih Imani, Ahmadreza & Eluru, Naveen & Hu, Hsi-Hwa & Huang, Guoxiong, 2017. "An integrated model of intensity of activity opportunities on supply side and tour destination & departure time choices on demand side," Journal of choice modelling, Elsevier, vol. 24(C), pages 63-74.
    2. Fadaei Oshyani, Masoud & Sundberg, Marcus & Karlström, Anders, 2013. "Estimating flexible route choice models using sparse data," Working papers in Transport Economics 2013:11, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    3. Mai, Tien & Frejinger, Emma & Fosgerau, Mogens, 2015. "A nested recursive logit model for route choice analysis," MPRA Paper 63161, University Library of Munich, Germany.
    4. Keane, Michael P. & Wasi, Nada, 2016. "How to model consumer heterogeneity? Lessons from three case studies on SP and RP data," Research in Economics, Elsevier, vol. 70(2), pages 197-231.
    5. Melstrom, Richard T., 2017. "Where to drill? The petroleum industry's response to an endangered species listing," Energy Economics, Elsevier, vol. 66(C), pages 320-327.
    6. Blom Västberg, Oskar & Karlström, Anders & Jonsson, Daniel & Sundberg, Marcus, 2016. "Including time in a travel demand model using dynamic discrete choice," MPRA Paper 75336, University Library of Munich, Germany, revised 11 Nov 2016.
    7. Lai, Xinjun & Bierlaire, Michel, 2015. "Specification of the cross-nested logit model with sampling of alternatives for route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 220-234.
    8. Rajesh Paleti & Peter Vovsha & Gaurav Vyas & Rebekah Anderson & Gregory Giaimo, 2017. "Activity sequencing, location, and formation of individual non-mandatory tours: application to the activity-based models for Columbus, Cincinnati, and Cleveland, OH," Transportation, Springer, vol. 44(3), pages 615-640, May.

  7. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Multivariate Extreme Value (MEV) models," Transportation Research Part B: Methodological, Elsevier, vol. 48(C), pages 31-52.

    Cited by:

    1. Jeppe Rich & Stefan L. Mabit, 2016. "Cost damping and functional form in transport models," Transportation, Springer, vol. 43(5), pages 889-912, September.
    2. Mai, Tien & Frejinger, Emma & Fosgerau, Mogens, 2015. "A nested recursive logit model for route choice analysis," MPRA Paper 63161, University Library of Munich, Germany.
    3. Melstrom, Richard T., 2017. "Where to drill? The petroleum industry's response to an endangered species listing," Energy Economics, Elsevier, vol. 66(C), pages 320-327.
    4. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Logit Mixture models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 185-198.
    5. Mai, Tien & Frejinger, Emma & Fosgerau, Mogens & Bastin, Fabian, 2017. "A dynamic programming approach for quickly estimating large network-based MEV models," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 179-197.
    6. Fosgerau, Mogens & Frejinger, Emma & Karlström, Anders, 2013. "A link based network route choice model with unrestricted choice set," Working papers in Transport Economics 2013:10, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    7. Bhat, Chandra R., 2015. "A comprehensive dwelling unit choice model accommodating psychological constructs within a search strategy for consideration set formation," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 161-188.
    8. Kazagli, Evanthia & Bierlaire, Michel & Flötteröd, Gunnar, 2016. "Revisiting the route choice problem: A modeling framework based on mental representations," Journal of choice modelling, Elsevier, vol. 19(C), pages 1-23.
    9. Lai, Xinjun & Bierlaire, Michel, 2015. "Specification of the cross-nested logit model with sampling of alternatives for route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 220-234.
    10. Papola, Andrea, 2016. "A new random utility model with flexible correlation pattern and closed-form covariance expression: The CoRUM," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 80-96.
    11. C. Jacobs-Crisioni & C. C. Koopmans, 2016. "Transport link scanner: simulating geographic transport network expansion through individual investments," Journal of Geographical Systems, Springer, vol. 18(3), pages 265-301, July.
    12. Marzano, Vittorio & Papola, Andrea & Simonelli, Fulvio & Vitillo, Roberta, 2013. "A practically tractable expression of the covariances of the Cross-Nested Logit model," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 1-11.

  8. Cristian Angelo Guevara & Moshe E. Ben-Akiva, 2012. "Change of Scale and Forecasting with the Control-Function Method in Logit Models," Transportation Science, INFORMS, vol. 46(3), pages 425-437, August.

    Cited by:

    1. Lurkin, Virginie & Garrow, Laurie A. & Higgins, Matthew J. & Newman, Jeffrey P. & Schyns, Michael, 2017. "Accounting for price endogeneity in airline itinerary choice models: An application to Continental U.S. markets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 228-246.
    2. Virginie Lurkin & Laurie A. Garrow & Matthew J. Higgins & Jeffrey P. Newman & Michael Schyns, 2016. "Accounting for Price Endogeneity in Airline Itinerary Choice Models: An Application to Continental U.S. Markets," NBER Working Papers 22730, National Bureau of Economic Research, Inc.
    3. Fernández-Antolín, Anna & Guevara, C. Angelo & de Lapparent, Matthieu & Bierlaire, Michel, 2016. "Correcting for endogeneity due to omitted attitudes: Empirical assessment of a modified MIS method using RP mode choice data," Journal of choice modelling, Elsevier, vol. 20(C), pages 1-15.
    4. José Francisco Tudón Maldonado, 2017. "Congestion v Content Provision in Net Neutrality: The Case of Amazon's Twitch.tv," 2017 Papers ptu168, Job Market Papers.
    5. C. Angelo Guevara, 2017. "Mode-valued differences of in-vehicle travel time Savings," Transportation, Springer, vol. 44(5), pages 977-997, September.

  9. Cherchi, Elisabetta & Guevara, Cristian Angelo, 2012. "A Monte Carlo experiment to analyze the curse of dimensionality in estimating random coefficients models with a full variance–covariance matrix," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 321-332.

    Cited by:

    1. Vij, Akshay & Krueger, Rico, 2017. "Random taste heterogeneity in discrete choice models: Flexible nonparametric finite mixture distributions," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 76-101.
    2. Guevara, C. Angelo, 2015. "Critical assessment of five methods to correct for endogeneity in discrete-choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 240-254.
    3. Yuan, Yuan & You, Wen & Boyle, Kevin J., 2015. "A guide to heterogeneity features captured by parametric and nonparametric mixing distributions for the mixed logit model," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205733, Agricultural and Applied Economics Association;Western Agricultural Economics Association.
    4. Sobhani, Anae & Eluru, Naveen & Faghih-Imani, Ahmadreza, 2013. "A latent segmentation based multiple discrete continuous extreme value model," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 154-169.
    5. Akshay Vij & Rico Krueger, 2018. "Random taste heterogeneity in discrete choice models: Flexible nonparametric finite mixture distributions," Papers 1802.02299, arXiv.org.
    6. Chenfeng Xiong & Xiqun Chen & Xiang He & Wei Guo & Lei Zhang, 2015. "The analysis of dynamic travel mode choice: a heterogeneous hidden Markov approach," Transportation, Springer, vol. 42(6), pages 985-1002, November.
    7. Hess, Stephane & Train, Kenneth E., 2011. "Recovery of inter- and intra-personal heterogeneity using mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 973-990, August.
    8. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Logit Mixture models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 185-198.

  10. Basso, Leonardo J. & Guevara, Cristián Angelo & Gschwender, Antonio & Fuster, Marcelo, 2011. "Congestion pricing, transit subsidies and dedicated bus lanes: Efficient and practical solutions to congestion," Transport Policy, Elsevier, vol. 18(5), pages 676-684, September.

    Cited by:

    1. Tscharaktschiew, Stefan & Hirte, Georg, 2012. "Should subsidies to urban passenger transport be increased? A spatial CGE analysis for a German metropolitan area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 285-309.
    2. Basso, Leonardo J. & Jara-Díaz, Sergio R., 2012. "Integrating congestion pricing, transit subsidies and mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(6), pages 890-900.
    3. Wang, Wei (Walker) & Wang, David Z.W. & Zhang, Fangni & Sun, Huijun & Zhang, Wenyi & Wu, Jianjun, 2017. "Overcoming the Downs-Thomson Paradox by transit subsidy policies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 126-147.
    4. Tirachini, Alejandro & Hensher, David A. & Rose, John M., 2014. "Multimodal pricing and optimal design of urban public transport: The interplay between traffic congestion and bus crowding," Transportation Research Part B: Methodological, Elsevier, vol. 61(C), pages 33-54.
    5. Simone Borghesi & Chiara Calastri & Giorgio Fagiolo, 2014. "How do people choose their commuting mode? An evolutionary approach to transport choices," LEM Papers Series 2014/15, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Tirachini, Alejandro, 2014. "The economics and engineering of bus stops: Spacing, design and congestion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 37-57.
    7. Ihab Kaddoura & Benjamin Kickhöfer & Andreas Neumann & Alejandro Tirachini, 2015. "Agent-based optimisation of public transport supply and pricing: impacts of activity scheduling decisions and simulation randomness," Transportation, Springer, vol. 42(6), pages 1039-1061, November.
    8. Daniels, Margaret J. & Harmon, Laurlyn K. & Vese, Rodney & Park, Minkyung & Brayley, Russell E., 2018. "Spatial dynamics of tour bus transport within urban destinations," Tourism Management, Elsevier, vol. 64(C), pages 129-141.

  11. Guevara, Cristian Angelo & Thomas, Alan, 2007. "Multiple classification analysis in trip production models," Transport Policy, Elsevier, vol. 14(6), pages 514-522, November.

    Cited by:

    1. André Romano Alho & João Abreu e Silva, 2017. "Modeling retail establishments’ freight trip generation: a comparison of methodologies to predict total weekly deliveries," Transportation, Springer, vol. 44(5), pages 1195-1212, September.
    2. Guevara, C. Angelo, 2015. "Critical assessment of five methods to correct for endogeneity in discrete-choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 240-254.
    3. Lucas, Karen & Bates, John & Moore, José & Carrasco, Juan Antonio, 2016. "Modelling the relationship between travel behaviours and social disadvantage," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 157-173.
    4. Mwakalonge, Judith L. & Badoe, Daniel A., 2012. "Comparison of Alternative Methods for Estimating Household Trip Rates of Cross-Classification Cells with Inadequate Data," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 51(2).
    5. de Grange, Louis & Troncoso, Rodrigo & González, Felipe, 2012. "An empirical evaluation of the impact of three urban transportation policies on transit use," Transport Policy, Elsevier, vol. 22(C), pages 11-19.
    6. C. Angelo Guevara, 2017. "Mode-valued differences of in-vehicle travel time Savings," Transportation, Springer, vol. 44(5), pages 977-997, September.

  12. Sergio R. Jara-Diaz & Cristián A. Guevara, 2003. "Behind the Subjective Value of Travel Time Savings," Journal of Transport Economics and Policy, University of Bath, vol. 37(1), pages 29-46, January.

    Cited by:

    1. Evert Jan van de Kaa, 2017. "Establishing the relevance of non-compensatory choice algorithms from stated choice surveys – an exploration," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 12(3), pages 260-279, May.
    2. Pawlak, Jacek & Polak, John W. & Sivakumar, Aruna, 2017. "A framework for joint modelling of activity choice, duration, and productivity while travelling," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 153-172.
    3. Héctor López-Ospina & Francisco Martínez & Cristián Cortés, 2015. "A time-hierarchical microeconomic model of activities," Transportation, Springer, vol. 42(2), pages 211-236, March.
    4. Banerjee, Ipsita & Kanafani, Adib, 2008. "The Value of Wireless Internet Connection on Trains: Implications for Mode-Choice Models," University of California Transportation Center, Working Papers qt3bv6g5pm, University of California Transportation Center.
    5. Batarce, Marco & Ivaldi, Marc, 2014. "Urban travel demand model with endogenous congestion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 331-345.
    6. Larson, Douglas M. & Lew, Daniel K., 2005. "Measuring the utility of ancillary travel: revealed preferences in recreation site demand and trips taken," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 237-255.
    7. Jara-Díaz, Sergio R. & Astroza, Sebastian & Bhat, Chandra R. & Castro, Marisol, 2016. "Introducing relations between activities and goods consumption in microeconomic time use models," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 162-180.
    8. Tscharaktschiew, Stefan & Hirte, Georg, 2009. "An urban general equilibrium model with multiple household structures and travel mode choice," Dresden Discussion Paper Series in Economics 06/09, Technische Universität Dresden, Faculty of Business and Economics, Department of Economics.
    9. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    10. Börjesson, Maria & Eliasson, Jonas, 2012. "The value of time and external benefits in bicycle appraisal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 673-683.
    11. Xinkai Wu & David Levinson & Henry Liu, 2008. "Perception of Waiting Time at Signalized Intersections," Working Papers 200909, University of Minnesota: Nexus Research Group.
    12. Börjesson, Maria & Eliasson, Jonas, 2012. "Experiences from the Swedish Value of Time study," Working papers in Transport Economics 2012:8, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    13. Nagel Kai & Grether Dominik & Beuck Ulrike & Chen Yu & Rieser Marcel & Axhausen Kay W., 2008. "Multi-Agent Transport Simulations and Economic Evaluation," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 173-194, April.
    14. C. Angelo Guevara, 2017. "Mode-valued differences of in-vehicle travel time Savings," Transportation, Springer, vol. 44(5), pages 977-997, September.
    15. Yao, Mingzhu & Wang, Donggen & Yang, Hai, 2017. "A game-theoretic model of car ownership and household time allocation," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 667-685.

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