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

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.

[1]  L. Sim,et al.  Singapore's Internet shoppers and their impact on traditional shopping patterns , 2002 .

[2]  K. Train Discrete Choice Methods with Simulation , 2003 .

[3]  Yaping Wei,et al.  Influence of Land-Use on Travel Pattern of Shopping-Mall: A Subdivided Method of Multinomial Logistic Model and Case Study in Nine Sub-Districts of Hangzhou, China , 2012 .

[4]  J. Weltevreden Substitution or complementarity? How the Internet changes city centre shopping , 2007 .

[5]  Kay W. Axhausen,et al.  An Analysis of the Impact of Information and Communication Technologies on Non- Maintenance Shopping Activities , 2003 .

[6]  A. McKinnon,et al.  The development of e-tail logistics , 2009 .

[7]  Eleonora Morganti,et al.  Final Deliveries for Online Shopping: The Deployment of Pickup Point Networks in Urban and Suburban Areas , 2014 .

[8]  Alan C. McKinnon,et al.  Unattended delivery to the home: an assessment of the security implications , 2003 .

[9]  Kenneth K. Boyer,et al.  THE LAST MILE CHALLENGE: EVALUATING THE EFFECTS OF CUSTOMER DENSITY AND DELIVERY WINDOW PATTERNS , 2009 .

[10]  Xin Ye,et al.  An Exploration of the Relationship Between Mode Choice and Complexity of Trip Chaining Patterns , 2007 .

[11]  J. Weltevreden B2c e‐commerce logistics: the rise of collection‐and‐delivery points in The Netherlands , 2008 .

[12]  Tom Cherrett,et al.  Transport impacts of local collection/delivery points , 2006 .

[13]  Anders Karlström,et al.  Day-to-day variability in travellers’ activity-travel patterns in the Jakarta metropolitan area , 2016 .

[14]  Julian Allen,et al.  Overview of home deliveries in the UK , 2001 .

[15]  Y. Susilo,et al.  The influence of built environment to the trends in commuting journeys in the Netherlands , 2007 .

[16]  Christian Ambrosini,et al.  New trends on urban goods movement: Modelling and simulation of e-commerce distribution , 2012 .

[17]  Fengming Su,et al.  An analysis of trip chaining among older London residents , 2010 .

[18]  Khandker Nurul Habib,et al.  An investigation of commuting trip timing and mode choice in the Greater Toronto Area: Application of a joint discrete-continuous model , 2009 .

[19]  K. Esser,et al.  B2C E-Commerce: Impact on Transport in Urban Areas , 2006 .

[20]  Agostino Nuzzolo,et al.  City logistics long-term planning: simulation of shopping mobility and goods restocking and related support systems , 2014 .

[21]  Tom Cherrett,et al.  Addressing the Last Mile Problem , 2009 .