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The objective of this study is to understand the different behavioralconsiderations that govern the choice of people to engage in a crowd-shippingmarket. Using novel data collected by the researchers in the US, we developdiscrete-continuous models. A binary logit model has been used to estimatecrowd-shippers' willingness to work, and an ordinary least-square regressionmodel has been employed to calculate crowd-shippers' maximum tolerance forshipping and delivery times. A selectivity-bias term has been included in themodel to correct for the conditional relationships of the crowd-shipper'swillingness to work and their maximum travel time tolerance. The results showsocio-demographic characteristics (e.g. age, gender, race, income, andeducation level), transporting freight experience, and number of social mediausages significant influence the decision to participate in the crowd-shippingmarket. In addition, crowd-shippers pay expectations were found to bereasonable and concurrent with the literature on value-of-time. Findings fromthis research are helpful for crowd-shipping companies to identify and attractpotential shippers. In addition, an understanding of crowd-shippers - theirbehaviors, perceptions, demographics, pay expectations, and in which contextsthey are willing to divert from their route - are valuable to the developmentof business strategies such as matching criteria and compensation schemes fordriver-partners.

Selectivity correction in discrete-continuous models for the willingness to work as crowd-shippers and travel time tolerance