  The objective of this study is to understand how senders choose shipping
services for different products, given the availability of both emerging
crowd-shipping (CS) and traditional carriers in a logistics market. Using data
collected from a US survey, Random Utility Maximization (RUM) and Random Regret
Minimization (RRM) models have been employed to reveal factors that influence
the diversity of decisions made by senders. Shipping costs, along with
additional real-time services such as courier reputations, tracking info,
e-notifications, and customized delivery time and location, have been found to
have remarkable impacts on senders' choices. Interestingly, potential senders
were willing to pay more to ship grocery items such as food, beverages, and
medicines by CS services. Moreover, the real-time services have low
elasticities, meaning that only a slight change in those services will lead to
a change in sender-behavior. Finally, data-science techniques were used to
assess the performance of the RUM and RRM models and found to have similar
accuracies. The findings from this research will help logistics firms address
potential market segments, prepare service configurations to fulfill senders'
expectations, and develop effective business operations strategies.
