Crowdsourced Urban Package Delivery: Modeling Traveler Willingness to Work as Crowdshippers. Issue 1 (January 2017)

• Record Type: Journal Article
• Authors: Miller, John; Nie, Yu (Marco); Stathopoulos, Amanda
• Is Part Of: Transportation research record. Volume 2610:Issue 1(2017)
• Page Start: 67
• Page End: 75
• Publication Date: 2017-01
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.3141/2610-08
• Languages: English
• ISSNs: 0361-1981

Abstract

Crowdsourced shipping presents an innovative shipping alternative that is expected to improve shipping efficiency, increase service, and decrease cost to the customer, and such shipping promises to enhance the sustainability of the transportation system. This study collected data on behavioral responses to choose from available crowdsourced shipping jobs. The goal of the study was to measure the potential willingness of individuals to change status from pure commuters to traveler–shippers. In particular, the study quantified potential crowdsourced shippers' value of free time, or willingness to work (WTW) in a hypothetical scenario in which crowdsourced shipping jobs were available in a variety of settings. This WTW calculation is unique compared with the traditional willingness to pay (WTP) in that it measured the trade-off of making a profit and giving up time instead of spending money to save time. This work provides a foundation to analyze the application and effectiveness of crowdsourced shipping by exploring the WTW propensity of ordinary travelers. The analysis was based on a newly developed stated preference survey and analyzed choice across three potential shipping jobs and the option to choose none of the three (i.e., the status quo). Results showed that the experiment was successful in recovering reasonable WTW values that are higher than the normal WTP metrics. The results also identified many significant sociodemographic variables that could help crowdsourced shipping companies better target potential part-time drivers.