An analysis of operating efficiency and policy implications in last-mile transportation following Amazon's integration

Research output: Contribution to journalArticlepeer-review

Abstract

We examine how Amazon's decision to vertically integrate its retail platform and last-mile delivery operations can lead to anti-competitive outcomes as a result of a deterioration in the operating efficiency in the routes served by a last-mile transportation firm. Based on an operational analysis of the last-mile transportation firm, we find that Amazon's decision to vertically integrate increases significantly the mileage necessary to deliver parcels in the ZIP code areas where this integration occurs. Moreover, this increase is significantly amplified by the remoteness and proportion of fast deliveries in these areas. These effects translate, on average, into $1.36 in additional costs necessary to cover extra vehicular and labor expenditures per parcel delivered. Because at the root of these outcomes are interactions among multiple organizations with significant market power asymmetries, we expand on a variety of potential anti-competitive service and pricing outcomes stemming from the impact of Amazon's vertical integration on the last-mile delivery firm's costs. We then put forth different public policy remedies that could be implemented to address these potential sources of anti-competitiveness in the last-mile delivery industry.

Original languageEnglish (US)
JournalJournal of Operations Management
DOIs
StateAccepted/In press - 2022
Externally publishedYes

Keywords

  • competitive dynamics
  • econometric analysis
  • last-mile transportation
  • online retailing
  • operating efficiency
  • platforms
  • public policy
  • vertical integration

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

Fingerprint

Dive into the research topics of 'An analysis of operating efficiency and policy implications in last-mile transportation following Amazon's integration'. Together they form a unique fingerprint.

Cite this