标题： 离散连续模型中对愿意作为众包配送员工作的选择性校正和出行时间容忍度 显示英文标题

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

摘要： 本研究的目的是了解影响人们参与众包配送市场的不同行为因素。 使用研究人员在美国收集的新数据，我们开发了离散-连续模型。 采用二元逻辑模型来估计众包配送员的工作意愿，采用普通最小二乘回归模型来计算众包配送员对配送时间和运输时间的最大容忍度。 在模型中包含了选择偏差项，以校正众包配送员工作意愿与其最大旅行时间容忍度之间的条件关系。 结果表明，社会人口特征（例如年龄、性别、种族、收入和教育水平）、运输货物经验以及社交媒体使用次数对参与众包配送市场的决策有显著影响。 此外，发现众包配送员的报酬期望是合理的，并与时间价值的相关文献一致。 本研究的发现有助于众包配送公司识别和吸引潜在的配送员。 此外，对众包配送员的行为、看法、人口统计特征、报酬期望以及他们在哪些情况下愿意改变路线的理解，对于制定如司机合作伙伴的匹配标准和补偿方案等商业策略具有重要价值。 显示英文摘要

摘要： The objective of this study is to understand the different behavioral considerations that govern the choice of people to engage in a crowd-shipping market. Using novel data collected by the researchers in the US, we develop discrete-continuous models. A binary logit model has been used to estimate crowd-shippers' willingness to work, and an ordinary least-square regression model has been employed to calculate crowd-shippers' maximum tolerance for shipping and delivery times. A selectivity-bias term has been included in the model to correct for the conditional relationships of the crowd-shipper's willingness to work and their maximum travel time tolerance. The results show socio-demographic characteristics (e.g. age, gender, race, income, and education level), transporting freight experience, and number of social media usages significant influence the decision to participate in the crowd-shipping market. In addition, crowd-shippers pay expectations were found to be reasonable and concurrent with the literature on value-of-time. Findings from this research are helpful for crowd-shipping companies to identify and attract potential shippers. In addition, an understanding of crowd-shippers - their behaviors, perceptions, demographics, pay expectations, and in which contexts they are willing to divert from their route - are valuable to the development of business strategies such as matching criteria and compensation schemes for driver-partners.