Built for Speed: The Hidden Costs of Last-Mile Delivery

By: Samantha K. McGovern

Edited by: Rose Kores

A friendly, flashing button appears on your screen: “order within two hours to receive this delivery today!” With a single click, your online delivery arrives within just hours of being ordered. What appears to be a seamless convenience is, in reality, the product of a tightly bound system built on speed, constant connectivity, and occupational hazards for drivers who take your package from a local distribution center straight to your front door. This final stage, known as “last-mile delivery”, sits at the center of that promise. Beneath this efficiency lies a structure that generates new forms of risk for the workers who sustain this system. 

The rise of e-commerce, and concurrently, last-mile delivery drivers, has completely transformed consumer expectations, making next-day and even same-day delivery on items ranging from stickers to heavy bags of kitty litter the standard. To meet that demand, last-mile drivers and their “employers” have shifted toward a new, decentralized model. Smiley-faced packages now arrive at our doors thanks to drivers classified as either independent or third-party contractors, while larger platforms and logistics companies retain control over the routing systems, delivery timelines, and customer expectations. For drivers, operating within a highly monitored and algorithmically managed system introduces new operational pressures. By shifting between fixed and flexible labor sources, firms can manage cost variability and maintain service levels.1 However, this flexibility comes at the cost of clarity in responsibility.

At the same time, the “last-mile” has become one of the most expensive segments of the logistics chain, creating strong incentives for firms to optimize both speed and labor costs.2 Thanks to advances in tracking technologies and real-time data systems that monitor both packages and drivers, firms are able to reassert pressure on drivers. Unfortunately, regulatory frameworks have struggled to keep pace with this everchanging economy, leaving many of these working conditions insufficiently regulated.

This article conceptualizes risk in last-mile delivery as system-produced, emerging from the interaction of speed, algorithmic control, and fragmented responsibility between the consumer, the driver, and their many employers. 

Speed Intensifies Risk to Drivers

Speed is the organizing principle of last-mile delivery.2 Drivers are routinely exposed to high stop volumes, compressed delivery windows, and strict performance metrics, all of which define the pace necessary to fulfill a shift. These conditions make time the dominant constraint shaping driver behavior. In this context, unsafe practices become rational responses to structurally imposed pressures.

Fatigue, musculoskeletal strain, and traffic-related hazards are all exacerbated by the demands of last-mile delivery.3 The non-stop motion leaves little room for rest and caution. In this context, unsafe practices become rational responses to structurally imposed time constraints.

The Fragmentation of Responsibility

The current structure of last-mile delivery spreads responsibility across a network, separating control from accountability. Through the subcontracting or pseudo-franchising of last-mile delivery operations, the firms that design delivery systems, establish performance expectations, and determine delivery timelines are often not the same entities that bear the legal responsibility for protecting drivers.4 Instead, these obligations are shifted to smaller third-party contractors that directly employ or contract with drivers and are responsible for complying with workplace safety regulations. As a result, the organizations that exert the greatest influence over the pace and conditions of work may not be the ones held accountable when injuries or accidents occur.3 When responsibility for safety is fragmented in this way, identifying who is responsible for workplace dangers becomes increasingly difficult.

By separating operational control from legal responsibility, the organizations that shape the pace and conditions of delivery can shift many workplace safety obligations onto smaller contractors. Drivers, in turn, operate within a tightly controlled system without many of the protections traditionally associated with direct employment—particularly those that historically accompanied delivery work before the expansion of subcontracted and platform-based labor models.5 As a result, the workplace hazards generated by demands for speed and efficiency are increasingly borne by workers rather than by the firms that benefit from the system.

Algorithmic Management as Behavioral Control, Not Safety Standards

Advances in routing software and real-time performance monitoring enable firms to optimize delivery sequences while evaluating drivers at increasingly granular levels.6 Small delays may trigger penalties that affect future work opportunities, including reduced access to scheduled shifts. Over time, this creates pressure for drivers to leave their positions. To avoid these consequences, workers adjust their behavior to meet delivery expectations, even when doing so requires prioritizing speed over safety.7

The result is a unique paradox: the larger delivery firm can exercise significant control over how delivery work is performed through surveillance, yet defer responsibility to difficult-to-trace third-party subcontractors.

Policy Mismatch in an Everchanging System

Workplace safety standards were developed around steady employment and fixed workspaces. Existing regulatory frameworks rely on clearly identifiable employers, but last-mile delivery workers often fall through the cracks.5 Current transportation regulations largely focus on long-haul trucking and do not reflect the fast-paced, high-density conditions of urban delivery. As a result, key hazards such as fatigue, compressed routes, and inadequate vehicle oversight often fall outside effective regulatory monitoring.8 Taken together, this mismatch between past regulatory design and operational reality leaves workers exposed to hazards generated by the structure of the delivery system itself, which existing regulatory frameworks neither fully recognize nor adequately monitor.

Policy Solutions: Aligning Control, Responsibility, and Safety

Addressing system-produced hazards requires policy interventions that target the structure of last-mile delivery itself rather than its stated problems:

  1. Align responsibility with operational control: Legal frameworks must reflect the realities of gig work. Existing franchising law provides a precedent for extending liability to firms that exert operational control, and similar standards should be applied to subcontracted delivery systems to better protect its workforce.5
  2. Regulate algorithmic management systems: Transparency requirements should be established, requiring delivery firms to disclose the basis of their routing strategies, performance metrics, and resulting penalties. An audit of this data could determine if these systems encourage people to behave unsafely, and in such cases, firms should be obliged to make the necessary corrections.
  3. Modernize safety standards for urban delivery: Regulations should be adapted to reflect the operational realities of last-mile delivery work. This could include work capacity limits based on the number of stops, integrating breaks with delivery routes, and developing safety standards specific to high-density delivery work.

The Tradeoffs

From a firm perspective, the current system represents a response to uncertainty, both in the economy and the nature of delivery. Crowdsourcing labor and related responsibility reduces overhead costs while meeting ever-increasing service levels. When both demand and labor are unpredictable, the last-mile employment model surfaces as a rational solution.1

Unfortunately, this model is full of invisible tradeoffs. By optimizing cost and responsiveness for the consumer, the burden has been disproportionately externalized back to the worker, where customers effectively act as informal managers through rating systems tied to platform oversight.9 Without proper safety interventions, these dynamics can intensify as market-based competition pressures firms to optimize delivery standards.

The goal of an employment policy should be to enhance, not hinder efficiency or flexibility. At the same time, businesses’ success should not come at the cost of workers’ safety. Implementing the right incentives for safe behavior can both preserve the advantages of modern delivery logistics and lessen its negative effects.

Conclusion: Stability in an Everchanging System

Last-mile delivery represents the most visible manifestation of a broader transformation in the organization of work. As systems become increasingly dynamic, decentralized, and technologically mediated, stability must be constructed through intentional governance, coordination, and institutional design.10 Risk in last-mile delivery is not a mere accident of innovation. Rather, it emerges from systems designed to maximize speed, manage uncertainty, and spread responsibility. Instead of concentrating only on individual behavior or single firms, regulation needs to tackle the very systems that influence both. As e-commerce continues to expand, the challenge is not simply adapting to change, but ensuring that the systems driving that change align with basic standards of safety and accountability.

 

 

Works Cited

  1. Ohio State University. 2024. “Ohio State Research Helping Retailers Close the Gap in Last-Mile Delivery.” Max M. Fisher College of Business. https://fisher.osu.edu/news/ohio-state-research-helping-retailers-close-gap-last-mile-delivery.
  2. European University Institute. n.d. “Addicted to Speed but at What Cost?” Florence School of Regulation. https://fsr.eui.eu/wp-content/uploads/2021/10/3B-01-Stanford-Houck.pdf.
  3. Strategic Organization Center. 2022. “The Worst Mile”. https://thesoc.org/wp-content/uploads/sites/342/The-Worst-Mile-1.pdf.
  4. Johnston, Hannah, Yana Mommadova, Steven Vallas, and Juliet Schor. 2023. “Delivering Difference: ‘Unbelonging’ Among US Platform Parcel Delivery Workers.” Cambridge Journal of Regions, Economy and Society 16 (2): 303–318. https://academic.oup.com/cjres/article/16/2/303/7024795.
  5. Levine, Sarah M. 2025. “Gig-Economy Myths and Missteps.” Yale Law Journal. https://yalelawjournal.org/pdf/LevineYLJForumEssay_z2cftu78.pdf.
  6. Camden, Matthew, Laurel Glenn, Aditi Manke, and Richard J. Hanowski. 2022. “Fleet-Based Driver Monitoring Systems”. Virginia Tech Works. https://vtechworks.lib.vt.edu/items/58c28fd5-94dc-4ebd-8016-e5a6fef13677.
  7. Wood, Alex, Mark Graham, Vili Lehdonvirta, and Isis Hjorth. 2019. “Good Gig, Bad Gig: Autonomy and Algorithmic Control in the Global Gig Economy.” Work, Employment and Society 33 (1): 56–75.
  8. Brown, Nellie. 2025. Personal interview by author regarding occupational hygiene and workplace safety. July 21, 2025.
  9. Cameron, Lindsey D., and Hatim Rahman. 2022. “Expanding the Locus of Resistance: Understanding the Co-constitution of Control and Resistance in the Gig Economy.” Organization Science 33 (1): 38–58.
  10.  Davis, Gerald. 2016. “What Might Replace the Modern Corporation? Uberization and the Web Page Enterprise.” Seattle University Law Review 39 (2). https://digitalcommons.law.seattleu.edu/sulr/vol39/iss2/13/. 

Author BioHeadshot of Samantha McGovern

Samantha McGovern is a graduate of Cornell University’s Executive Master of Public Administration (EMPA) program at the Jeb E. Brooks School of Public Policy, where she concentrated in Public and Nonprofit Management. She serves as Program Manager for Pre-Apprenticeship at the Center for Economic Growth (CEG), the regional economic development organization affiliated with the Capital Region Chamber, where she develops workforce pathways into advanced manufacturing through no-cost pre-apprenticeship programs that connect individuals with high-quality careers. This article builds on her capstone research examining occupational safety and employment structures in last-mile delivery. The project was developed through the Institute for Compensation Studies (ICS) at Cornell’s ILR School as part of its broader research on changing employment models in the small-package delivery industry. Samantha is especially grateful to Dr. M. Diane Burton for her mentorship throughout the capstone process and for her teaching on job quality, compensation, and the distinction between “good jobs” and “bad jobs,” which helped shape the framework for this analysis. She hopes this research contributes to ongoing conversations about worker safety, organizational accountability, and the creation of safe, high-quality jobs.

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