TY - JOUR
T1 - To bid or not to bid
T2 - An empirical study of the supply determinants of crowd-shipping
AU - Ermagun, Alireza
AU - Stathopoulos, Amanda
N1 - Funding Information:
This material is based upon work supported by the US National Science Foundation Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) Grant No. 1534138 Smart CROwdsourced Urban Delivery ( CROUD ) System. The authors thank two reviewers for comments that helped improve the manuscript.
Funding Information:
This material is based upon work supported by the US National Science Foundation Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) Grant No. 1534138 Smart CROwdsourced Urban Delivery (CROUD) System. The authors thank two reviewers for comments that helped improve the manuscript.
Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/10
Y1 - 2018/10
N2 - This study makes three contributions to the literature of crowd-shipping. First, we represent a national data set incorporating 16,850 crowd-shipping requests across the United States for the 2-year period of January 2015 through December 2016. Second, we develop a two-part model of supply defined by both the probability of receiving a bid from a crowd-courier, and the bid count. Model results along with elasticity measurements summarize the effects of variation in shipping request and package, built environment, and socioeconomic characteristics. Third, we report the sensitivity of elasticities over different segmentations to understand whether and to what extent the supply responsiveness varies across segments. Our results show that (1) supply is unevenly distributed across the U.S. at the block group level, (2) this geographical disparity is a function of not only the shipping request and service characteristics, but also the socioeconomic and built-environment attributes, (3) the supply has denser pockets in areas with a higher percentage of African-American population, high wage workers, and families with two or more vehicles, (4) the supply peters off in areas with higher population and employment densities, while, it is accumulated in geographical areas with higher destination accessibility and regional employment diversity, and (5) the out-of-state and the business-to-customer shipments present the highest elasticity in receiving a bid, while posted requests with a delivery deadline is the most inelastic segment. Transportation planners and crowd-shipping companies can use these results to implement improved supply creation, geographically targeted growth, and price discrimination strategies.
AB - This study makes three contributions to the literature of crowd-shipping. First, we represent a national data set incorporating 16,850 crowd-shipping requests across the United States for the 2-year period of January 2015 through December 2016. Second, we develop a two-part model of supply defined by both the probability of receiving a bid from a crowd-courier, and the bid count. Model results along with elasticity measurements summarize the effects of variation in shipping request and package, built environment, and socioeconomic characteristics. Third, we report the sensitivity of elasticities over different segmentations to understand whether and to what extent the supply responsiveness varies across segments. Our results show that (1) supply is unevenly distributed across the U.S. at the block group level, (2) this geographical disparity is a function of not only the shipping request and service characteristics, but also the socioeconomic and built-environment attributes, (3) the supply has denser pockets in areas with a higher percentage of African-American population, high wage workers, and families with two or more vehicles, (4) the supply peters off in areas with higher population and employment densities, while, it is accumulated in geographical areas with higher destination accessibility and regional employment diversity, and (5) the out-of-state and the business-to-customer shipments present the highest elasticity in receiving a bid, while posted requests with a delivery deadline is the most inelastic segment. Transportation planners and crowd-shipping companies can use these results to implement improved supply creation, geographically targeted growth, and price discrimination strategies.
KW - Crowd-shipping
KW - On-demand mobility
KW - Policy and practice
KW - Sensitivity analysis
KW - Supply behavior
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U2 - 10.1016/j.tra.2018.06.019
DO - 10.1016/j.tra.2018.06.019
M3 - Article
AN - SCOPUS:85049618192
SN - 0965-8564
VL - 116
SP - 468
EP - 483
JO - Transportation Research Part A: Policy and Practice
JF - Transportation Research Part A: Policy and Practice
ER -