Do people spend travel time the way they think they would? a comparative study of generic and trip-specific travel time allocation using hybrid multiple discrete continuous (MDC) framework

References

• Akshay, V., and J. L. Walker. 2016. “How, When, and Why Integrated Choice and Latent Variable Models are Latently Useful.” Transportation Research Part B: Methodological 90: 192–217. doi:10.1016/j.trb.2016.04.021.
   Web of Science ®Google Scholar
• Auld, J., H. Ley, O. Verbas, N. Golshani, J. Bechara, and A. Fontes. 2020. “A Stated-Preference Intercept Survey of Transit-Rider Response to Service Disruptions.” Public Transport 12 (3): 557–585. doi:10.1007/s12469-020-00243-z.
   Web of Science ®Google Scholar
• Berliner, R. M., A. Malkin, G. Circella, and P. L. Mokhtarian. 2015. “Travel-Based Multitasking: Modeling the Propensity to Conduct Activities While Commuting.” Paper presented at the 95thannual meeting of the Transportation Research Board, Washington DC, USA.
   Google Scholar
• Bhat, C. R. 2008. “The Multiple Discrete-Continuous Extreme Value (MDCEV) Model: Role of Utility Function Parameters, Identification Considerations, and Model Extensions.” Transportation Research Part B: Methodological 42 (3): 274–303. doi:10.1016/j.trb.2007.06.002.
   Web of Science ®Google Scholar
• Bhat, C. R. 2018. “A New Flexible Multiple Discrete-Continuous Extreme Value (MDCEV) Choice Model.” Transportation Research Part B: Methodological 110: 261–279. doi:10.1016/j.trb.2018.02.011.
   Web of Science ®Google Scholar
• Bhat, C. R., M. Castro, and M. Khan. 2013. “A New Estimation Approach for the Multiple Discrete-Continuous Probits (MDCP) Choice Model.” Transportation Research Part B: Methodological 55: 1–22. doi:10.1016/j.trb.2013.04.005.
   Web of Science ®Google Scholar
• Bhat, C. R., and S. Sen. 2006. “Household Vehicle Type Holdings and Usage: An Application of the Multiple Discrete-Continuous Extreme Value (MDCEV) Model.” Transportation Research Part B: Methodological 40 (1): 35–53. doi:10.1016/j.trb.2005.01.003.
   Web of Science ®Google Scholar
• Bolduc, D., N. Boucher, and R. Alvarez-Daziano. 2008. “Hybrid Choice Modeling of New Technologies for Car Choice in Canada.” Transportation Research Record 2082 2082 (1): 63–71. doi:10.3141/2082-08.
   Google Scholar
• Calastri, C., J. Pawlak, and R. Batley. 2021. “Participation in Online Activities While Traveling: An Application of the MDCEV Model in the Context of Rail Travel.” Transportation 49 (1): 1–27. doi:10.1007/s11116-021-10166-8.
   Web of Science ®Google Scholar
• Charlotte, F., H. S. Mahmassani, and A. Frei. 2015. “Making Time Count: Traveler Activity Engagement on Urban Transit.” Transportation Research Part A: Policy and Practice 76: 58–70. doi:10.1016/j.tra.2014.12.007.
   Web of Science ®Google Scholar
• Choi, S., and P. L. Mokhtarian. 2020. “How Attractive is It to Use the Internet While Commuting? A Work-Attitude-Based Segmentation of Northern California Commuters.” Transportation Research Part A: Policy and Practice 138: 37–50. doi:10.1016/j.tra.2020.05.007.
   Web of Science ®Google Scholar
• 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.
   Web of Science ®Google Scholar
• Daziano, R. A., and D. Bolduc. 2013. “Incorporating Pro-Environmental Preferences Towards Green Automobile Technologies Through a Bayesian Hybrid Choice Model.” Transportmetrica A: Transport Science 9 (1): 74–106.
   Web of Science ®Google Scholar
• der Waerden, V., H. T. Peter, and R. van Neerven. 2009. “Extent, Nature, and Covariates of Multitasking of Rail Passengers in an Urban Corridor: A Dutch Case Study.” Transportation Research Record 2110 (1): 106–111. doi:10.3141/2110-13.
   Google Scholar
• Enam, A., K. C. Konduri, A. R. Pinjari, and N. Eluru. 2018. “An Integrated Choice and Latent Variable Model for Multiple Discrete-Continuous Choice Kernels: Application Exploring the Association Between Day Level Moods and Discretionary Activity Engagement Choices.” Journal of Choice Modeling 26: 80–100. doi:10.1016/j.jocm.2017.07.003.
   Web of Science ®Google Scholar
• Ettema, D., and L. Verschuren. 2007. “Multitasking and Value of Travel Time Savings.” Transportation Research Record 2010 (1): 19–25. doi:10.3141/2010-03.
   Web of Science ®Google Scholar
• Ferdousy, R., and P. A. Singleton. 2021. “What Factors are Associated with Travel Liking on a Recent Commute? Evidence from Commuters in Portland, Oregon.” Travel Behaviour and Society 23: 207–215. doi:10.1016/j.tbs.2021.01.004.
   Web of Science ®Google Scholar
• Gärling, T., R. Gillholm, and A. Gärling. 1998. “Reintroducing Attitude Theory in Travel Behavior Research: The Validity of an Interactive Interview Procedure to Predict Car Use.” Transportation 25 (2): 129–146. doi:10.1023/A:1005004311776.
   Web of Science ®Google Scholar
• Hess, S., G. Spitz, M. Bradley, and M. Coogan. 2018. “Analysis of Mode Choice for Intercity Travel: Application of a Hybrid Choice Model to Two Distinct US Corridors.” Transportation Research Part A: Policy and Practice 116: 547–567. doi:10.1016/j.tra.2018.05.019.
   Web of Science ®Google Scholar
• Jacek, P., J. W. Polak, and A. Sivakumar. 2017. “A Framework for Joint Modeling of Activity Choice, Duration, and Productivity While Travelling.” Transportation Research Part B: Methodological 106: 153–172. doi:10.1016/j.trb.2017.10.010.
   Web of Science ®Google Scholar
• Jian, S., T. Hossein Rashidi, and V. Dixit. 2017. “An Analysis of Carsharing Vehicle Choice and Utilization Patterns Using Multiple Discrete-Continuous Extreme Value (MDCEV) Models.” Transportation Research Part A: Policy and Practice 103: 362–376. doi:10.1016/j.tra.2017.06.012.
   Web of Science ®Google Scholar
• Kamargianni, M., and A. Polydoropoulou. 2013. “Hybrid Choice Model to Investigate Effects of teenagers’ Attitudes Toward Walking and Cycling on Mode Choice Behavior.” Transportation Research Record 2382 (1): 151–161. doi:10.3141/2382-17.
   Google Scholar
• Kaza, N., C. Towe, and Y. Xin. 2011. “A Hybrid Land Conversion Model Incorporating Multiple End Uses.” Agricultural and Resource Economics Review 40 (3): 341–359. doi:10.1017/S1068280500002823.
   Google Scholar
• Keseru, I., E. Heyndels, T. Dat Ton, and C. Macharis. 2020. “Multitasking on the Go: An Observation Study on Local Public Transport in Brussels.” Travel Behaviour and Society 18: 106–116. doi:10.1016/j.tbs.2019.10.003.
   Web of Science ®Google Scholar
• Keseru, I., and C. Macharis. 2018. “Travel-Based Multitasking: Review of the Empirical Evidence.” Transport Reviews 38 (2): 162–183. doi:10.1080/01441647.2017.1317048.
   Web of Science ®Google Scholar
• Kolarova, V., R. Cyganski, and B. Lenz. 2019. “Activities While Travelling? Travel Time Perception and Travel Time Use in an Era of Automated Driving.” Advances in Transport Policy and Planning 3: 171–206.
   Google Scholar
• Krizek, K. J., and A. El-Geneidy. 2007. “Segmenting Preferences and Habits of Transit Users and Non-Users.” Journal of Public Transportation 10 (3): 5. doi:10.5038/2375-0901.10.3.5.
   Google Scholar
• Kuppam, A. R., R. M. Pendyala, and S. Rahman. 1999. “Analysis of the Role of Traveler Attitudes and Perceptions in Explaining Mode-Choice Behavior.” Transportation Research Record 1676 (1): 68–76. doi:10.3141/1676-09.
   Google Scholar
• Mackie, P. J., S. Jara-Dıaz, and A. S. Fowkes. 2001. “The Value of Travel Time Savings in Evaluation.” Transportation Research Part E: Logistics and Transportation Review 37 (2–3): 91–106. doi:10.1016/S1366-5545(00)00013-2.
   Web of Science ®Google Scholar
• Malkin, A. “Pathways to improving traditional travel behavior models with travel-based multitasking and attitudinal data.” Ph.D. diss., Georgia Institute of Technology, 2019.
   Google Scholar
• Malokin, A., G. Circella, and P. L. Mokhtarian. 2021. “How Do Activities Conducted While Commuting Influence Mode Choice? Using Revealed Preference Models to Inform Public Transportation Advantage and Autonomous Vehicle Scenarios.” Transportation Research Part A: Policy and Practice 124: 82–114. doi:10.1016/j.tra.2018.12.015.
   Web of Science ®Google Scholar
• Marcel, P., D. Temme, A. Vij, and J. L. Walker. 2014. “Values, Attitudes and Travel Behavior: A Hierarchical Latent Variable Mixed Logit Model of Travel Mode Choice.” Transportation 41 (4): 873–888. doi:10.1007/s11116-013-9504-3.
   Web of Science ®Google Scholar
• Nostrand, V., V. S. Caleb, and A. Rawoof Pinjarra. 2013. “Analysis of Long-Distance Vacation Travel Demand in the United States: A Multiple Discrete-Continuous Choice Framework.” Transportation 40 (1): 151–171. doi:10.1007/s11116-012-9397-6.
   Web of Science ®Google Scholar
• Outwater, M. L., S. Castleberry, Y. Shiftan, M. Ben-Akiva, Y. Shuang Zhou, and A. Kuppam. 2003. “Attitudinal Market Segmentation Approach to Mode Choice and Ridership Forecasting: Structural Equation Modeling.” Transportation Research Record 1854 (1): 32–42. doi:10.3141/1854-04.
   Google Scholar
• Pawlak, J. 2020. “Travel-Based Multitasking: Review of the Role of Digital Activities and Connectivity.” Transport Reviews 40 (4): 429–456. doi:10.1080/01441647.2020.1728418.
   Web of Science ®Google Scholar
• Pellegrini, A., I. Sarman, and R. Maggi. 2021. “Understanding tourists’ Expenditure Patterns: A Stochastic Frontier Approach Within the Framework of Multiple Discrete–Continuous Choices.” Transportation 48 (2): 1–21. doi:10.1007/s11116-020-10083-2.
   Web of Science ®Google Scholar
• Peng, J., H. L. X. Jing Zhou, and J. T. Zhang. 2017. “Travelers’ Choice Behavior of Car Sharing Based on Hybrid Choice Model.” Journal of Transportation Systems Engineering and Information Technology 17: 7–13.
   Google Scholar
• Pinjari, A. R., B. Augustin, V. Sivaraman, A. Faghih Imani, N. Eluru, and R. M. Pendyala. 2016. “Stochastic Frontier Estimation of Budgets for Kuhn–Tucker Demand Systems: Application to Activity Time-Use Analysis.” Transportation Research Part A: Policy and Practice 88: 117–133. doi:10.1016/j.tra.2016.03.013.
   Web of Science ®Google Scholar
• Popuri, Y., K. Proussaloglou, C. Ayvalik, F. Koppelman, and A. Lee. 2011. “Importance of Traveler Attitudes in the Choice of Public Transportation to Work: Findings from the Regional Transportation Authority Attitudinal Survey.” Transportation 38 (4): 643–661. doi:10.1007/s11116-011-9336-y.
   Web of Science ®Google Scholar
• Pudāne, B., E. J. Molin, T. A. Arentze, Y. Maknoon, and C. G. Chorus. 2018. “A Time-Use Model for the Automated Vehicle Era.” Transportation Research Part C: Emerging Technologies 93: 102–114. doi:10.1016/j.trc.2018.05.022.
   Web of Science ®Google Scholar
• Raman, K. S. “Travel-based multitasking on the Mumbai Local and Metro: measurement, classification, and variation.” Ph.D. diss., Massachusetts Institute of Technology, 2019.
   Google Scholar
• Richards, T. J., and L. Mancino. 2014. “Demand for Food-Away-From-Home: A Multiple-Discrete–continuous Extreme Value Model.” European Review of Agricultural Economics 41 (1): 111–133. doi:10.1093/erae/jbt008.
   Web of Science ®Google Scholar
• Rico, K., T. H. Rashidi, and J. Auld. 2019. “Preferences for Travel-Based Multitasking: Evidence from a Survey Among Public Transit Users in the Chicago Metropolitan Area.” Transportation Research Part F, Traffic Psychology and Behaviour 65: 334–343. doi:10.1016/j.trf.2019.08.004.
   Web of Science ®Google Scholar
• Saxena, N., T. H. Rashidi, and J. Auld. 2019. “Studying the Tastes Affecting Mode Choice Behavior of Travelers Under Transit Service Disruptions.” Traveler Behavior and Society 17: 86–95. doi:10.1016/j.tbs.2019.07.004.
   Web of Science ®Google Scholar
• Shamshiripour, A., E. Rahimi, A. Kouros Mohammadian, and J. Auld. 2020. “Investigating the Influence of Latent Lifestyles on Productive Travels: Insights into Designing Autonomous Transit System.” Transportation Research Part A: Policy and Practice 141: 469–484. doi:10.1016/j.tra.2020.10.001.
   Web of Science ®Google Scholar
• Shaw, F. A., A. Malkin, P. L. Mokhtarian, and G. Circelli. 2019. “It’s Not All Fun and Games: An Investigation of the Reported Benefits and Disadvantages of Conducting Activities While Commuting.” Travel Behaviour and Society 17: 8–25. doi:10.1016/j.tbs.2019.05.008.
   Web of Science ®Google Scholar
• Singleton, P. A. 2018. “How Useful is Travel-Based Multitasking? Evidence from Commuters in Portland, Oregon.” Transportation Research Record 2672 2672 (50): 11–22. doi:10.1177/0361198118776151.
   Web of Science ®Google Scholar
• Singleton, P. A. 2019a. “Discussing the “Positive utilities” of Autonomous Vehicles: Will Travelers Really Use Their Time Productively?” Transport Reviews 39 (1): 50–65.
   Web of Science ®Google Scholar
• Singleton, P. A. 2019b. “Multimodal Travel-Based Multitasking During the Commute: Who Does What?” International Journal of Sustainable Transportation 14 (2): 150–162. doi:10.1080/15568318.2018.1536237.
   Web of Science ®Google Scholar
• Sobhani, A., N. Eluru, and A. Faghih-Imani. 2013. “A Latent Segmentation Based Multiple Discrete-Continuous Extreme Value Model.” Transportation Research Part B: Methodological 58: 154–169. doi:10.1016/j.trb.2013.07.009.
   Web of Science ®Google Scholar
• Stephane, H., M. Bierlaire, and J. W. Polak. 2005. “Estimation of the Value of Travel-Time Savings Using Mixed Logit Models.” Transportation Research Part A: Policy and Practice 39 (2–3): 221–236. doi:10.1016/j.tra.2004.09.007.
   Web of Science ®Google Scholar
• Varghese, V., M. Chikaraishi, and H. Kato. 2020. “Analysis of Travel-Time Use in Crowded Trains Using Discrete-Continuous Choices of Commuters in Tokyo, Japan.” Transportation Research Record 2674 (10): 189–198. doi:10.1177/0361198120934794.
   Web of Science ®Google Scholar
• Varghese, V., and A. Jana. 2019. “Multitasking During Travel in Mumbai, India: Effect of Satiation in Heterogeneous Urban Settings.” Journal of Urban Planning and Development 145 (2): 04019002. doi:10.1061/(ASCE)UP.1943-5444.0000504.
   Web of Science ®Google Scholar
• Walker, J., and M. Ben-Akiva. 2002. “Generalized Random Utility Model.” Mathematical Social Sciences 43 (3): 303–343. doi:10.1016/S0165-4896(02)00023-9.
   Web of Science ®Google Scholar
• Zhang, J., and H. Timmermans. 2010. “Scobie-Based Panel Analysis of Multitasking Behavior of Public Transport Users.” Transportation Research Record 2157 (1): 46–53. doi:10.3141/2157-06.
   Google Scholar