Joint analysis of urban shopping destination and travel mode choice accounting for potential spatial correlation between alternatives
来源期刊：中南大学学报(英文版)2014年第8期
论文作者：LIN Yao-yu(林姚宇) DING Chuan(丁川) WANG Yao-wu(王耀武) 刘超 CUI Yu-chen(崔愉晨) Sabyasachee Mishra
文章页码：3378 - 3385
Key words：shopping destination; travel mode choice; joint choice; cross-nested logit; Monte Carlo simulation
Abstract: In recent years, there have been important developments in the joint analysis of the travel behavior based on discrete choice models as well as in the formulation of increasingly flexible closed-form models belonging to the generalized extreme value class. The objective of this work is to describe the simultaneous choice of shopping destination and travel-to-shop mode in downtown area by making use of the cross-nested logit (CNL) structure that allows for potential spatial correlation. The analysis uses data collected in the downtown areas of Maryland-Washington, D.C. region for shopping trips, considering household, individual, land use, and travel-related characteristics. The estimation results show that the dissimilarity parameter in the CNL model is 0.37 and significant at the 95% level, indicating that the alternatives have high spatial correlation for the short shopping distance. The results of analysis reveal detailed significant influences on travel behavior of joint choice shopping destination and travel mode. Moreover, a Monte Carlo simulation for a group of scenarios arising from transportation policies and parking fees in downtown area, was undertaken to examine the impact of a change in car travel cost on the shopping destination and travel mode switching. These findings have important implications for transportation demand management and urban planning.
LIN Yao-yu(林姚宇)1, DING Chuan(丁川)1, 2, WANG Yao-wu(王耀武)1, LIU Chao(刘超)3, CUI Yu-chen(崔愉晨)3, Sabyasachee Mishra4
(1. Shenzhen Key Laboratory of Urban Planning and Decision Making Simulation
(Shenzhen Graduate School, Harbin Institute of Technology), Shenzhen 518055, China;
2. School of Architecture, Harbin Institute of Technology, Harbin 150006, China;
3. National Center for Smart Growth Research and Education, University of Maryland,
College Park 20742, United States;
4. Department of Civil Engineering, University of Memphis, Memphis 38152, United States)
Abstract:In recent years, there have been important developments in the joint analysis of the travel behavior based on discrete choice models as well as in the formulation of increasingly flexible closed-form models belonging to the generalized extreme value class. The objective of this work is to describe the simultaneous choice of shopping destination and travel-to-shop mode in downtown area by making use of the cross-nested logit (CNL) structure that allows for potential spatial correlation. The analysis uses data collected in the downtown areas of Maryland-Washington, D.C. region for shopping trips, considering household, individual, land use, and travel-related characteristics. The estimation results show that the dissimilarity parameter in the CNL model is 0.37 and significant at the 95% level, indicating that the alternatives have high spatial correlation for the short shopping distance. The results of analysis reveal detailed significant influences on travel behavior of joint choice shopping destination and travel mode. Moreover, a Monte Carlo simulation for a group of scenarios arising from transportation policies and parking fees in downtown area, was undertaken to examine the impact of a change in car travel cost on the shopping destination and travel mode switching. These findings have important implications for transportation demand management and urban planning.
Key words:shopping destination; travel mode choice; joint choice; cross-nested logit; Monte Carlo simulation
