A multilevel spatial interaction model of transit flows incorporating spatial and network autocorrelation |
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| Affiliation: | 1. Institute for Management Research, Radboud University, P.O. Box 9108, Nijmegen 6500 HK, The Netherlands;2. Leona Chanin Career Development Chair, Faculty of Architecture and Town Planning, Technion - Israel Institute of Technology, Amado Building, Technion City, 32000 Haifa, Israel;1. Transport and Planning Department, Delft University of Technology, Netherlands;2. Operations Research and Logistics Group, Wageningen University, Netherlands;3. Rotterdam School of Management, Erasmus University, Netherlands;1. Department of Transport and Regional Economics, University of Antwerp, Prinsstraat 13, 2000 Antwerpen, Belgium;2. Open Lab, Newcastle University, 89 Sandyford Rd, Newcastle upon Tyne NE1 8HW, UK;3. Departement SENSE, Orange Labs, 44 Avenue de la République, 92320 Châtillon, France;1. 777 Glades Road, Building SO 44 Room 284, School of Urban and Regional Planning, Florida Atlantic University, United States;2. School of Architecture and Urban Planning, University of Wisconsin – Milwaukee, PO Box 413, Milwaukee, WI 5320, United States;1. Department of Mathematics, University of Arizona, 617 N. Santa Rita Avenue, Tucson, AZ 85718, United States of America;2. School of Geographical Sciences and Urban Planning, Arizona State University, 975 S Myrtle Ave, Tempe, AZ 85281, United States of America;3. Mel and Enid Zuckerman College of Public Health, University of Arizona, 1295 N. Martin Ave., Tucson, AZ 85724, United States of America;1. Department of Industrial Engineering, Ghent University, Valentin Vaerwyckweg 1, 9000 Ghent, Belgium;2. Department of Geography, Ghent University, Krijgslaan 281 S8, 9000 Ghent, Belgium;3. Department of Human Geography, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, Canada |
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| Abstract: | While it is well known that ignoring spatial dependence often results in misspecification of models, travel demand models almost never account for this phenomenon. The aim of this paper is to empirically demonstrate the importance of accounting for potential spatial dependence between observations in the specification of spatial interaction models. As a case study, we analyze travel flows on the public transport system in an urban region in the Netherlands. We develop five distinct spatial interaction models (SIMs) of increasing complexity, each encompassing a lower and upper level model. At the lower level, the attractiveness of neighborhoods for boarding and alighting is modeled based on spatial and transit supply characteristics. At the upper level, spatial interactions among zones are modeled taking into account competing origins, competing destinations as well as network characteristics. We systematically compare more traditional SIM formulations with a SIM that explicitly accounts for spatial and network autocorrelation. The results show a substantial difference between the former models and the latter, in terms of the estimated total marginal impacts of the different variables and the pattern of the error terms. The results of our study underscore that the failure to incorporate autocorrelation effects in travel models is likely to influence model outcomes, which in turn may have profound implications for the very design of public transport networks in cities and regions. |
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