Crowd-Shipping Services for Last Mile Delivery: Analysis from Survey Data in Two Countries

The e-commerce boom has led to overwhelming demand for personalized delivery services. Accordingly, various start-ups and tech companies provide crowd-shipping services that aim to be more efficient and effective than traditional logistics options. These services are fueled by technological innovation, improved internet infrastructure, and increased smartphone use. However, the field of on-demand delivery faces several challenges, including specified pickup and delivery times and locations. Therefore, market demand and prospective crowd-shipper supply must be well understood to ensure industry success. This research analyzes current and future shipping behaviors, as well as potential employees' willingness to work (WTW) as crowd-shippers. Revealed and stated preference survey questionnaires were designed. The surveys were implemented in Vietnam and the US. This descriptive study makes use of the survey data sets to understand the behavior of requesters and potential crowd-shippers in the logistics market and assumes that crowd-sourced delivery is available. The results show requesters' various behaviors and expectations as well as prospective crowd-shippers' WTW in the two countries. The results can be used to recruit potential crowd-shippers and create business strategies that match requesters' and potential crowd-shippers' expectations.

[1]  N. Sanko Guidelines for Stated Preference Experiment Design , 2001 .

[2]  Aashwinikumar Devari,et al.  Crowdsourced last mile delivery using social network , 2016 .

[3]  Yu Nie,et al.  Crowdsourced Urban Package Delivery , 2017 .

[4]  A. Stathopoulos,et al.  Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects , 2017 .

[5]  Andrew M Amey Real-time ridesharing : exploring the opportunities and challenges of designing a technology-based rideshare trial for the MIT community , 2010 .

[6]  T. Nemoto,et al.  E-­commerce and City Logistics Solution , 2014 .

[7]  K. Train,et al.  Estimation on stated-preference experiments constructed from revealed-preference choices , 2008 .

[8]  Satish V. Ukkusuri,et al.  Selectivity Correction in Discrete-Continuous Models for the Willingness to Work as Crowd-Shippers and Travel Time Tolerance , 2018, 1810.00985.

[9]  Romeo Danielis,et al.  Attribute cut-offs in freight service selection , 2007 .

[10]  D. Hensher,et al.  Stated Choice Methods: Analysis and Applications , 2000 .

[11]  Rainer Alt,et al.  Sharing Economy , 2016, Bus. Inf. Syst. Eng..

[12]  E P Kroes,et al.  STATED PREFERENCE TECHNIQUES: A GUIDE TO PRACTICE , 1990 .

[13]  Michael Lettenmeier,et al.  Transport reduction by crowdsourced deliveries – a library case in Finland , 2016 .

[14]  Mickael Briffaz,et al.  Crowd-shipping in Geneva Exploratory and descriptive study of Crowd-shipping , 2016 .

[15]  Matthew J. Roorda,et al.  Shipper/Carrier Interactions Data Collection: Web-Based Respondent Customized Stated Preference (WRCSP) Survey , 2013 .