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Research Article

A commodity-based production and distribution road freight model with application to urban and regional New South Wales

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Pages 566-592 | Received 11 Oct 2019, Accepted 17 Mar 2020, Published online: 10 Aug 2020

References

  • Anand, N., J. R. Van Duin, H. Quak, and L. A. Tavasszy. 2015. “Relevance of City Logistics Modelling Efforts: A Review.” Transport Reviews, doi:https://doi.org/10.1080/01441647.2015.1052112.
  • Anas, A. 1983. “Discrete Choice Theory, Information Theory and the Multinomial Logit and Gravity Models.” Transportation Research Part B: Methodological 17 (1): 13–23.
  • Australian Bureau of Statistics. 2018. Australian Statistical Geography Standard (ASGS). http://www.abs.gov.au.
  • Ben-Akiva, M. E., and S. R. Lerman. 1985. Discrete Choice Analysis: Theory and Application to Travel Demand. Cambridge, MA: The MIT Press.
  • Bergstrand, J. H., P. Egger, and M. Larch. 2013. “Gravity Redux: Estimation of Gravity-Equation Coefficients, Elasticities of Substitution, and General Equilibrium Comparative Statics Under Asymmetric Bilateral Trade Costs.” Journal of International Economics 89: 110–121.
  • Bröcker, J. 1998. “Operational Spatial Computable General Equilibrium Modelling.” The Annals of Regional Science 32: 367–387.
  • Cambridge Systematics, Inc. 1997. A Guidebook for Forecasting Freight Transportation Demand. NCHRP Report 388. Washington, DC: Transportation Research Board, National Research Council.
  • Cascetta, E. 1997. “National Modelling in Italy; Simulation and Evaluation Models for the Italian DSS.” Paper presented at the Seminar on National Transport Models: The State of the Art, Noordwijk.
  • de Bok, M., and L. Tavasszy. 2018. “An Empirical Agent-Based Simulation System for Urban Goods Transport (MASS-GT).” Procedia Computer Science. 130: 126–133.
  • de Jong, G., and M. Ben-Akiva. 2007. “A Micro-Simulation Model of Shipment Size and Transport Chain Choice.” Transportation Research Part B: Methodological 41 (9): 950–965. http://linkinghub.elsevier.com/retrieve/pii/S0191261507000549.
  • de Jong, G., H. Gunn, and W. Walker. 2004. “National and International Freight Transport Models: An Overview and Ideas for Future Development.” Transport Reviews 24 (1): 103–124. doi:https://doi.org/10.1080/0144164032000080494.
  • Ellison, R., C. Teye, and D. A. Hensher. 2017. “Commodity-Based Heavy Vehicle Model for Greater Sydney.” Paper presented at The Fifth International Choice Modelling Conference 3–5 April 2017, Cape Town, South Africa.
  • Erlander, S., and N. F. Stewart. 1990. The Gravity Model in Transportation Analysis: Theory and Extensions. Utrecht: Vsp.
  • Expedite Consortium. 2000. Review of European and National Passenger and Freight Market Forecasting Systems. Deliverable 2 for the European Commission DGTREN. The Hague: HCG.
  • Garrido, R. A. 2000. “Spatial Interaction Between Trucks Flows Through the Mexico–Texas Border.” Transportation Research Part A 33: 23–33.
  • Harker, P., and T. L. Friesz. 1986a. “Prediction of Intercity Freight Flows I: Theory.” Transportation Research Part B 20 (2): 139–153.
  • Harker, P., and T. L. Friesz. 1986b. “Prediction of Intercity Freight Flows I: Mathematical Formulations.” Transportation Research Part B 20 (2): 155–174.
  • Hensher, D., and M. A. Figliozzi. 2007. “Behavioural Insights Into the Modeling of Freight Transportation and Distribution Systems.” Transportation Research Part B 41 (9): 921–923.
  • Hensher, D. A., and S. M. Puckett. 2005. “Refocusing the Modeling of Freight Distribution: Development of an Economic Based Framework to Evaluate Supply Chain Behavior in Response to Congestion Charging.” Transportation 32 (6): 573–602.
  • Hensher, D. A., J. M. Rose, and W. H. Greene. 2015. Applied Choice Analysis. Cambridge: Cambridge University Press.
  • Holguín-Veras, J., and G. R. Patil. 2008. “A Multicommodity Integrated Freight Origin-Destination Synthesis Model.” Networks and Spatial Economics 8: 309.
  • Holmgren, J., P. Davidsson, J. A. Persson, and L. Ramstedt. 2012. “TAPAS: A Multi-Agent-Based Model for Simulation of Transport Chains.” Simulation Modelling Practice and Theory 23: 1–18.
  • Hyman, G. M. 1969. “The Calibration of Trip Distribution Models.” Environment and Planning 1: 105–112.
  • ITE (Institute of Transportation Engineers). 2003. Trip Generation. ISBN No: 0.935403-79-5, Washington, DC.
  • Ivanova, O., A. Vold, and V. Jean-Hansen. 2002. PINGO – A Model for Prediction of Regional and Interregional Freight Transport (Version 1). TØI Report 578/2000. Oslo: Institute of Transport Economics (TØI).
  • Jaynes, E. T. 1957. “Information Theory and Statistical Mechanics.” Physical Review 106 (4): 620–630.
  • Lam, W. H. K., and H. P. Lo. 1991. “Estimation of Origin–Destination Matrix From Traffic Counts: A Comparison of Entropy Maximizing and Information Minimizing Models.” Transportation Planning and Technology 16 (2): 85–104. doi:https://doi.org/10.1080/03081069108717474.
  • Lamond, B., and N. F. Stewart. 1981. “Bregman’s Balancing Method.” Transportation Research Part B 15: 239–248.
  • Leitham, S., J. Downing, A. Martino, and D. Fiorelli. 1999. “European Transport Forecasts for 2020: The Streams Model Results.” Paper presented at 1999 European Transport Conference, Cambridge.
  • Leontief, W. 1936. “Quantitative Input and Output Relations in the Economic System of the United States.” Review of Economic Statistics 18 (3): 105–125.
  • Le Pira, M., E. Marcucci, V. Gatta, G. Inturri, M. Ignaccolo, and A. Pluchino. 2017. “Integrating Discrete Choice Models and Agent-Based Models for Ex-Ante Evaluation of Stakeholder Policy Acceptability in Urban Freight Transport.” Research in Transportation Economy. 64: 13–25.
  • Lowry, L. S. 1964. I.S. A Model of Metropolis. Santa Monica, CA: RAND Corporation.
  • Marco, Boeri, and Masiero Lorenzo. 2014. “Regret Minimisation and Utility Maximisation in a Freight Transport Context.” Transportmetrica A: Transport Science 10 (6): 548–560. doi:https://doi.org/10.1080/23249935.2013.809818.
  • McFadden, D. 1974. “Conditional Logit Analysis of Qualitative Choice Behavior.” In Frontiers in Econometrics, edited by P. Zarembka, 105–142. New York: Academic Press.
  • Novak, D. C., C. Hodgdon, F. Guo, and L. Aultman-Hall. 2011. “Nationwide Freight Generation Models: A Spatial Regression Approach.” Network and Spatial Economics 11: 23–41.
  • Nuzzolo, A., P. Coppola, and A. Comi. 2013. “Freight Transport Modeling: Review and Future Challenges.” International Journal of Transport Economics XL (2): 151.
  • Nuzzolo, A., U. Crisalli, and A. Comi. 2015. “An Aggregate Transport Demand Model for Import and Export Flow Simulation.” Transport 30 (1): 43–54. doi:https://doi.org/10.3846/16484142.2013.820215.
  • Oosterhaven, J. 1988. “On the Plausibility of the Supply-Driven Model.” Journal of Regional Science 28: 203–217.
  • Puckett, S. M., D. A. Hensher, J. M. Rose, and A. Collins. 2007. “Design and Development of a Stated Choice Experiment for Interdependent Agents: Accounting for Interactions Between Buyers and Sellers of Urban Freight Services.” Transportation 34: 429–451.
  • Roorda, M. J., R. Cavalcante, S. McCabe, and H. Kwan. 2010. “A Conceptual Framework for Agent-Based Modelling of Logistics Services.” Transportation Research Part E 46 (1): 18–31.
  • Sakai, T., K. B. Bhavathrathan, A. Alho, T. Hyodo, and M. Ben-Akiva. 2018. “Urban Freight Distribution considering Logistics Chain Structure: Selection of Supplier with Distribution Channel.” The 97th Annual Meeting of the Transportation Research Board, Washington D.C., January 7–11.
  • Sakai, T., K. B. Bhavathrathan, A. Alho, T. Hyodo, and M. Ben-Akiva. 2019. “Modeling Freight Generation, Commodity Contracts, and Shipments for SimMobility Freight – A Disaggregate Agent-Based Urban Freight Simulator.” Submitted to the 98th Annual Meeting of the Transportation Research Board.
  • Shannon, CE. 1948. “A mathematical theory of communication.” Bell System Technical Journal 27 (3): 379–423.
  • Sivakumar, A., and C. Bhat. 2002. “Fractional Split-Distribution Model for Statewide Commodity-Flow Analysis.” Transportation Research Record 1790: 80–88.
  • Soyoung, Iris You, Joseph Y. J. Chow, and Stephen G. Ritchie. 2016. “Inverse Vehicle Routing for Activity-Based Urban Freight Forecast Modeling and City Logistics.” Transportmetrica A: Transport Science 12 (7): 650–673. doi:https://doi.org/10.1080/23249935.2016.1189723.
  • Tavasszy, L., M.J.P.M. Thissen, and J. Oosterhaven. 2011. “Challenges in the application of spatial computable general equilibrium models for transport appraisal.” Res.Transp. Econ. 31 (1): 12–18.
  • Teye, C. 2017. “The Siting of Multi-User Inland Intermodal Container Terminals in Transport Networks.” PhD. Thesis, The Institute of Transport and Logistics Studies (ITLS), University of Sydney.
  • Teye, C., M. G. H. Bell, and M. Bliemer. 2017a. “Urban Intermodal Container Terminals: The Entropy Maximisation Facility Location Problem.” Transportation Research Part B 100: 64–81.
  • Teye, C., M. G. H. Bell, and M. Bliemer. 2017b. “Locating Urban and Regional Container Terminals in Competitive Environment: An Entropy Maximising Approach.” Transportation Research Part B 117: 971–985. doi:https://doi.org/10.1016/j.trb.2017.08.017.
  • Train, K. 2009. Discrete Choice Methods and Simulation: Second Edition. Berkeley, California: Cambridge University Press.
  • Williams, H. C. W. L. 1977. “On the Formation of Travel Demand Models and Economic Evaluation Measures of User Benefit.” Environment and Planning 9A: 285–344.
  • Wilson, A. G. 1969. “The Use of Entropy Maximising Models, in the Theory of Trip Distribution, Mode Split and Route Split.” Journal of Transport Economics and Policy 3: 108–126.
  • Wilson, A. G. 1970. Entropy in Urban and Regional Modelling. London: Pion.
  • Wisetjindawat, W., K. Sano, and S. Matsumoto. 2006. “Commodity Distribution Model Incorporating Spatial Interactions for Urban Freight Movement.” Transportation Research Record 1966: 41–50.
  • Zhong, R. X., K. Y. Fu, A. Sumalee, D. Ngoduy, and W. H. K. Lam. 2016. “A Cross-Entropy Method and Probabilistic Sensitivity Analysis Framework for Calibrating Microscopic Traffic Models.” Transportation Research Part C 63: 147–169. doi:https://doi.org/10.1016/j.trc.2015.12.006.

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