Reframing Airport Choice in Platform Logistics: The Case of Amazon Air
Xiaofu Fan et al.
What the paper says
ABSTRACT While the substantial growth of e‐commerce has transformed air cargo from a peripheral service into a major revenue source in air transportation, airports, key nodes in this network, have increasingly benefited from this shift. The emergence of new players such as Amazon Air has significantly influenced the revenue growth trajectories of many airports. Despite this trend, the determinants guiding Amazon's airport selection strategy remain poorly understood. By analyzing data from 62 U.S. airports between 2010 and 2023, this study employs an Instrumental Variables Probit model to shed light on the key factors that influence Amazon's airport choices, thereby providing insights to help airports better align with the operational needs of major e‐commerce carriers. The results reveal that Amazon prefers to choose airports that are non‐hub, have good freight infrastructure, are far from urban centers, have low ground delays, and have a large scale of regional employment, while the per capita income has no significant level. These findings indicate the core logic of the “decentralized” layout of e‐commerce logistics: by avoiding the high cost and congestion of traditional hubs, relying on professional facilities and flexible scheduling to achieve efficient performance, which confirms its high sensitivity to operational efficiency and scheduling freedom.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.