Shared Mobility for Last-Mile Delivery: Design, Operational Prescriptions, and Environmental Impact

Cities around the world are experiencing two socioeconomic transformations: First, the boom of the so-called sharing economy engage people to be more collaborative in sharing access to goods and services and less obsessed with ownership. PWC projects that the market size of the sharing economy will reach $335 billion by 2025. One of the most profoundly impacted sectors is transportation. Companies such as Uber and Lyft are disrupting the traditional business of people-riding transit. Second, we have long witnessed retail e-commerce change our way of shopping. According to eMarketer, worldwide sales of business-to-consumer (B2C) online retail has been over $2 trillion with an annual growth rate of around 20%. To maintain their logistics competitive edge, major players in the arena of online retail launched various new shipping services (e.g., Amazon Prime Now and Google Express, etc.) for faster and more cost-effective package delivery.

These phenomena naturally lead to a question: Is it a smart idea for online retailers to crowdsource shared mobility for home delivery services? Botsman (2014) expressed optimism about this delivery mode that “it does not require the asset-heavy infrastructure of warehouses, vehicle fleets, fuel costs and employed drivers that traditional logistics companies have to pay for and manage. . . . It’s an asset-light model, akin to the likes of Uber and Airbnb, with low overheads meaning it can scale relatively fast depending on demand.” Will this marriage of the sharing economy and e-commerce really hold all these promises? Until recently, this business model is still in its early stage. On the one hand, most of the companies in the courier industry still primarily use professional drivers and dedicated fleets. On the other hand, some companies have started trying crowdsourcing mobility for delivery services. Examples include UberEATS, Amazon Flex, and start-ups such as Deliv. However, those services are mainly for express deliveries and/or specific product types.

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Source: wavebreakmedia under Creative Commons.

Will crowdsourcing shared mobility also be beneficial for large-scale last-mile package delivery? If yes, how to improve the cost efficiency of its operations? These questions were addressed in a research article (Qi et al. 2018) recently published in Manufacturing & Service Operations Management. From the perspective of a logistics service provider, the researchers evaluated the cost of providing such delivery services. They considered a logistics setting in which a fleet of short-haul trucks are dispatched from a depot and unload packages at a set of transshipment locations. Passenger car drivers (e.g., Uber drivers) that are near each transshipment location and not in ride-share service are offered wages to commit to a last-mile delivery trip. The trip-specific wages are competitive with what drivers can otherwise expect to earn from the ride-share service market. Each driver committed to an on-demand delivery trip will move to the transshipment location, pick up a ration of packages, and deliver them to the doorsteps of customers. Combining mathematical modeling and parameter calibration based on various sources of empirical estimates, the researchers evaluated this business model in a setting of 15 zip-code areas in the East San Francisco Bay Area.

The article reveals several findings. First, it turns out that crowdsourcing shared mobility is not as scalable as the conventional dedicated delivery system in terms of the operating cost. For areas with high volume of delivery demands, the logistics service provider may find it still favorable to exclusively rely on its conventional dedicated delivery capacity. On the other hand, shared mobility can be more cost effective where the delivery demands are sparse. The difference in scalability is owing to the difference in payment structures under these two delivery modes: Unlike the dedicated delivery system where professional drivers are hired and paid a fixed rate, the wages to crowdsourced drivers are trip-specific and reflect the competition with the ride-share service market. As a result, the conventional system has more economies of scale with respect to demand density.

Second, though not necessarily implying immediate savings in operating cost, crowdsourcing shared mobility creates value in other dimensions. With shared mobility taking care of the last mile, the fleet size of the dedicated delivery vans can be significantly smaller. Moreover, shared mobility has its operational flexibilities. Based on the analysis of scalability and flexibilities, the article suggests four operating strategies/tactics:

  1. Launch this delivery mode in low-demand-density areas.
  2. Adopt heavy-duty trucks in place of regular-size delivery vans. (This is to enhance the inbound-trucking efficiency.)
  3. Schedule deliveries when ride-share demands subside. (During those hours, shared mobility becomes less expensive to crowdsource.)
  4. If possible, load more packages in cars to exploit the economies of scale of last-mile trips.

The researchers showed that adopting the last three prescriptions can reduce the operating cost by about 24% in their case study. They also tested that these insights remain valid in the presence of surge pricing (i.e., ride-share service platforms dynamically adjust wages and prices of rides).

Finally, the researchers examined the environmental implication of this business model in terms of greenhouse gas (GHG) emissions. Their analysis showed that crowdsourcing gas-powered passenger cars for last-mile delivery may incur more GHG emissions. Although passenger cars have higher per-km emission efficiency, they are of much smaller loading capacity and thus incur much longer total trip distance than dedicated delivery vans.

In summary, crowdsourcing shared mobility for last-mile home delivery on a large scale may not be immediately a cost saver for logistics service providers, nor an emission saver for society. However, crowdsourcing shared mobility opens many possibilities for logistics service providers to enhance their overall performance. The business model is also aligned with a smart-city vision to promote multi-model integrated freight and transit systems and car sharing programs. We hope to see more practice and research to shed light upon this new delivery mode.

References

Botsman R (2014) Crowdshipping: Using the crowd to transform delivery. AFR Boss Magazine (September 12), http://www.afr.com/it-pro/crowdshipping-using-the-crowd-to-transform-delivery-20140911-jyk63.

Qi W, Li L, Liu S, Shen S-JM (2018) Shared mobility for last-mile delivery: Design, operational prescriptions, and environmental impact. Manufacturing Service Operations Management 20(4):737–751.

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