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Assessing the impacts of collection-delivery points to individual’s activity-travel patterns: A greener last mile alternative?

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  • Liu, Chengxi
  • Wang, Qian
  • Susilo, Yusak O.

Abstract

The transport impacts of collection-delivery points (CDPs), as an alternative to home delivery, are rarely studied. As e-shopping becomes increasingly popular, trips to collect deliveries at CDP, especially by car travel, may generate a considerable amount of external effects, such as emissions. Therefore, this paper analysed the “picking up/leaving goods” trips selected from the Swedish National Travel Survey and jointly modelled the individuals’ mode choice and trip chaining decisions using a panel cross-nested logit model. The roles of trip chain characteristics, individual socio-demographics and land use characteristics on each trip chain and mode choice combination are investigated. The results indicate observed and unobserved heterogeneities of trip chaining and mode choice decisions among populations. Young adults living with partners/spouses, single adults with children and partnered adults with children have the preference of using cars in collection-delivery trips compared to other life-cycle groups. A sensitivity analysis is carried out to estimate the effect of distance to CDPs on vehicle kilometres travelled. The calibrated model is used to estimate the VKT of collection-delivery trips in the greater Stockholm area. The results indicate a 22.5% reduction of VKT from collection-delivery trips by relocating 5% CDPs from urban areas to suburban and rural areas.

Suggested Citation

  • Liu, Chengxi & Wang, Qian & Susilo, Yusak O., 2019. "Assessing the impacts of collection-delivery points to individual’s activity-travel patterns: A greener last mile alternative?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 121(C), pages 84-99.
    • Handle: RePEc:eee:transe:v:121:y:2019:i:c:p:84-99
    DOI: 10.1016/j.tre.2017.08.007
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    1. Agostino Nuzzolo & Antonio Comi & Luca Rosati, 2014. "City logistics long-term planning: simulation of shopping mobility and goods restocking and related support systems," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 18(2), pages 201-217, July.
    2. Nurul Habib, Khandker M. & Day, Nicholas & Miller, Eric J., 2009. "An investigation of commuting trip timing and mode choice in the Greater Toronto Area: Application of a joint discrete-continuous model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(7), pages 639-653, August.
    3. Jesus Gonzalez-Feliu & Christian Ambrosini & Jean-Louis Routhier, 2012. "New trends on urban goods movement: Modelling and simulation of e-commerce distribution," Post-Print halshs-00626152, HAL.
    4. Bhat, Chandra R. & Sivakumar, Aruna & Axhausen, Kay W., 2003. "An analysis of the impact of information and communication technologies on non-maintenance shopping activities," Transportation Research Part B: Methodological, Elsevier, vol. 37(10), pages 857-881, December.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    6. Jan-Dirk Schmöcker & Fengming Su & Robert Noland, 2010. "An analysis of trip chaining among older London residents," Transportation, Springer, vol. 37(1), pages 105-123, January.
    7. Yusak Susilo & Kees Maat, 2007. "The influence of built environment to the trends in commuting journeys in the Netherlands," Transportation, Springer, vol. 34(5), pages 589-609, September.
    8. Gonzalez Feliu, Jesus & Ambrosini, Christian & Routhier, Jean-Louis, 2012. "New trends on urban goods movement modelling: proximity delivery versus shopping trips," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 50, pages 1-2.
    9. Eléonora Morganti & Laetitia Dablanc & François Fortin, 2014. "Final deliveries for online shopping: the deployment of pickup point networks in urban and suburban areas," Post-Print hal-01067223, HAL.
    10. Ye, Xin & Pendyala, Ram M. & Gottardi, Giovanni, 2007. "An exploration of the relationship between mode choice and complexity of trip chaining patterns," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 96-113, January.
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