Crowdsourcing Last Mile Delivery: Strategic Implications and Future Research Directions

Abstract

The rise of e‐commerce over the past 20 years has created an increased need for responsive omnichannel distribution to meet the last mile challenge. Some companies are experimenting with the use of the sharing economy business model to augment distribution strategies. The use of so‐called “Crowdsourced Logistics” (CSL) is becoming more prevalent in practice, but the role in logistics strategy of this new phenomenon has not been thoroughly investigated and understood. Using a contingency theory lens, this research contributes a nascent understanding of how CSL performs in terms of logistics effectiveness by simulating same‐day delivery services from a distribution center to 1,000 customer locations throughout New York City under dynamic market conditions and by comparing the results to those of a traditional dedicated fleet of delivery drivers. The findings are analyzed to suggest how firms may find strategic benefit using CSL. An agenda for future research is provided to explore these strategic implications and to deepen knowledge about the CSL phenomenon.

Logistics Innovation and Social Sustainability: How to Prevent an Artificial Divide in Human–Computer Interaction

“…; Castillo et al. ). A key question that comes along with these developments concerns the future form and performance of human‐computer interaction (HCI) .…”

“…Logistics and supply chain management are subject to rapid changes as a result of technological, social, and market evolutions within the global economy, see, for example, Bloemhof et al (2015), Hilger et al (2016), Sternberg and Norrman (2017), Bertazzi and Mogre (2018), or Fors et al (2015). In response to increasing customer demands (cost effectiveness, sustainability, speed, tailored problem solutions), automation in production and distribution has migrated from the execution of programmed tasks to a level, in which software agents and robots act (partly) autonomously using artificial intelligence (AI)-based algorithms (Gunsekaran and Ngai 2014; Lee et al 2014;LeCun et al 2015;Torabi et al 2015;Kong et al 2016;Castillo et al 2017). A key question that comes along with these developments concerns the future form and performance of human-computer interaction (HCI).…”

Crowd Logistics Platform’s Informative Support to Logistics Performance: Scale Development and Empirical Examination

“…Crowd logistics is an innovative business model in sharing economy. In crowd logistics, drivers use their own vehicles to provide logistics services as independent contractors, and shippers outsource logistics tasks to a large number of drivers through technology platforms [1]. The crowd logistics platforms integrate enormous logistics tasks, contributing to optimal allocation of logistics resources by providing drivers with informative support.…”

A Tribute to Our Founding Father, Professor Bernard J. “Bud” LaLonde

“…Castillo et al. () describe how the sharing economy is influencing logistics activity and decision making. They present the following research question: “How does a crowdsourced fleet compare to a traditional dedicated courier fleet in terms of logistics effectiveness under dynamic task environment conditions?” To address the question, they simulate the operations of a crowdsourced logistics provision in New York City.…”

“…In this issue, we open with an interesting analysis of a modern phenomenon, crowdsourced logistics (CSL). Castillo et al (2018a) describe how the sharing economy is influencing logistics activity and decision making. They present the following research question: "How does a crowdsourced fleet compare to a traditional dedicated courier fleet in terms of logistics effectiveness under dynamic task environment conditions?"…”