A Bivariate Multinomial Probit Model for Trip Scheduling: Bayesian Analysis of the Work Tour
Published Online:8 Feb 2012https://doi.org/10.1287/trsc.1110.0397
References
- AASHTO Combatting congestion through leadership, innovation, and resources: A summary report on the 2007 National Congestion Summits. (2007) . American Association of State Highway and Transportation Officials (AASHTO). Accessed July 2010, http://downloads.transportation.org/CTL-1.pdfGoogle Scholar
- An analysis of the commuter departure time decision. Transportation (1981) 10(3):283–297Crossref, Google Scholar
- Modeling time of day choice in the context of tour and activity based models. Transportation Res. Record (2006) 1981:42–49Crossref, Google Scholar
- Bayesian analysis of binary and polychotomous response data. J. Amer. Statist. Assoc. (1993) 88(422):669–679Crossref, Google Scholar
- Utility of schedules: Theoretical model of departure-time choice and activity-time allocation with application to individual activity schedules. Transportation Res. Record (2004) 1894:84–98Crossref, Google Scholar
- Analysis of travel mode and departure time choice for urban shopping trips. Transportation Res. Part B (1998) 32(6):361–371Crossref, Google Scholar
- A continuous-time model of departure time choice for urban shopping trips. Transportation Res. Part B (2002) 36(3):207–224Crossref, Google Scholar
- BIOGEME: A free package for the estimation of discrete choice models. (2003) Presentation 3rd Swiss Transportation Research ConferenceMarch 19–21Ascona, SwitzerlandGoogle Scholar
- The Sacramento activity-based travel demand model: Estimation and validation results. (2006) Presentation 2006 European Transport ConferenceSeptember 18–20Strasbourg, FranceGoogle Scholar
- Analysis of multivariate probit models. Biometrika (1998) 85(2):347–361Crossref, Google Scholar
- Influences on commuter trip departure time decisions in Singapore. Transportation Res. Part A (1990) 24(5):321–333Crossref, Google Scholar
- Bayesian smoothing of rates in small geographic areas. J. Regional Sci. (1995) 35(4):659–673Crossref, Google Scholar
- The logsum as an evaluation measure: Review of the literature and new results. Transportation Res. Part A (2007) 41(9):874–889Google Scholar
- Modeling departure time choice in the context of activity scheduling behavior. Transportation Res. Record (2003) 1831:39–46Crossref, Google Scholar
- Modeling timing and duration of activities and trips in response to road-pricing policies. Transportation Res. Record (2004) 1894:1–10Crossref, Google Scholar
- Modeling the joint choice of activity timing and duration. Transportation Res. Part A (2007) 41(9):827–841Google Scholar
- Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference (2006) 2nd ed.(Chapman and Hall/CRC, Boca Raton, FL) Google Scholar
- Alternative computational approaches to inference in the multinomial probit model. Rev. Econom. Statist. (1994) 76(4):609–632Crossref, Google Scholar
- Trucking industry adoption of information technology: A multivariate discrete choice model. Transportation Res. Part C (2002) 10(3):205–228Crossref, Google Scholar
- Time Series Analysis (1994) (Princeton University Press, Princeton, NJ) Crossref, Google Scholar
- The flexibility of departure times for work trips. Transportation Res. Part A (1984) 18(1):25–36Crossref, Google Scholar
- Adaptive independent metropolis-hastings. Ann. Appl. Probab. (2009) 19(1):395–413Crossref, Google Scholar
- On the similarity of classical and Bayesian estimates of individual mean partworths. Marketing Lett. (2001) 12:259–269Crossref, Google Scholar
- Spatial autocorrelation and the selection of simultaneous autoregressive models. Global Ecology and Biogeography (2008) 17(1):59–71Google Scholar
- Anticipating new-highway impacts: Opportunities for welfare analysis and credit-based congestion pricing. Transportation Res. Part A (2011) 45(8):825–838Google Scholar
- A latent class accelerated hazard model of activity episode durations. Transportation Res. Part B (2007) 41(4):426–447Crossref, Google Scholar
- Capturing random utility maximization behavior in continuous choice data: Application to work tour scheduling. (2009) . Doctoral Dissertation, Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, AustinGoogle Scholar
- Understanding and accommodating risk and uncertainty in toll road projects: A review of the literature. Transportation Res. Record (2009) 2132:106–112Crossref, Google Scholar
- Empirical investigation of continuous logit for departure time choice with Bayesian methods. Transportation Res. Record (2010) 2165:59–68Crossref, Google Scholar
- The continuous cross-nested logit model: Formulation and application for departure time choice. Transportation Res. Part B (2010) 44(5):646–661Crossref, Google Scholar
- Spatial autocorrelation and autoregressive models in ecology. Ecological Monographs (2002) 72(3):445–463Crossref, Google Scholar
- An exact likelihood analysis of the multinomial probit model. J. Econometrics (1994) 64(1–2):207–240Crossref, Google Scholar
- , Karlquist A., Jundgquist L., Snickbars F., Weibull J. W. Modeling the choice of residential location. Spatial Interaction Theory and Planning Models (1978) (North-Holland, Amsterdam) 75–96Google Scholar
- A method of simulated moments for estimation of discrete response models without numerical integration. Econometrica (1989) 57(5):995–1026Crossref, Google Scholar
- Departure time choice for recreational activities by elderly non-workers. Transportation Res. Record (2003) 1848:86–93Crossref, Google Scholar
- Using the variance structure of the conditional autoregressive spatial specification to model knowledge spillovers. J. Appl. Econometrics (2008) 23(2):235–256Crossref, Google Scholar
- PB Consult The MORPC travel demand model: Validation and final report. (2005) . Prepared for the Mid-Ohio Regional Planning Commission as part of the MORPC Model Improvement Project, Columbus, OHGoogle Scholar
- Time of day modeling in a tour-based context: The Tel-Aviv experience. Transportation Res. Board (2008) 2076:88–96Crossref, Google Scholar
- Bayesian Statistics and Marketing (2005) (John Wiley and Sons, Hoboken, NJ) Crossref, Google Scholar
- Summary statement. Proc. USDOT Expert Forum on Road Pricing and Travel Demand Modeling (2005) Alexandria, VA:3–12Google Scholar
- The scheduling of consumer activities: Work trips. Amer. Econom. Rev. (1982) 72(3):467–479Google Scholar
- A discrete choice model for ordered alternatives. Econometrica (1987) 55(2):409–424Crossref, Google Scholar
- Applied welfare economics with discrete choice models. Econometrica (1981) 49(1):105–130Crossref, Google Scholar
- Valuation of travel-time savings and predictability in congested conditions for highway user-cost estimation. (1999) . National Cooperative Highway Research Program Report 431, National Academy Press, Washington, DCGoogle Scholar
- , LeSage J. P., Pace R. K. A Bayesian probit model with spatial dependencies. Spatial and Spatiotemporal Econometrics (2004) (Elsevier, Amsterdam) 127–160Crossref, Google Scholar
- On modeling the departure time choice for home-based social/recreational and shopping trips. Transportation Res. Record (2000) 1706:152–159Crossref, Google Scholar
- Transportation Research Board Metropolitan travel forecasting: Current practice and future direction. (2007) . TRB Special Report 288, Committee for Determination of the State of the Practice in Metropolitan Area Travel Forecasting, Washington, DCGoogle Scholar
- A hybrid discrete choice departure time and duration model for scheduling travel tours. Transportation Res. Record (2004) 1894:46–56Crossref, Google Scholar
- Making the state of the art the state of the practice: advanced modeling techniques for road pricing. Proc. USDOT Expert Forum on Road Pricing and Travel Demand Modeling (2005) Alexandria, VA:95–122Google Scholar
- Timing utility of daily activities and its impact on travel. Transportation Res. Part A (1996) 30(3):189–206Crossref, Google Scholar
- Analysis of activity duration using the Puget sound transportation panel. Transportation Res. Part A (2000) 34(8):607–624Google Scholar
- Bayesian analysis of multivariate nominal measures using multivariate multinomial probit models. Computational Statist. Data Anal. (2008) 52(7):3697–3708Crossref, Google Scholar

