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Hub‐and‐Spoke Collusion With a Third‐Party Pricing Algorithm

Joseph E. Harrington

The Journal of Industrial Economics2026https://doi.org/10.1111/joie.70017article
AJG 3ABDC A*
Weight
0.50

What the paper says

A data analytics company delivers an efficiency by supplying a pricing algorithm that allows prices to more effectively respond to demand variation. In this setting, I consider a new form of hub‐and‐spoke collusion: A data analytics company (hub) coordinates the prices of competitors (spokes) through its pricing algorithm. A novel finding is that the data analytics company's efficiency is a facilitating factor for collusion; a rise in this efficiency increases the supracompetitive markup and the incremental profit from collusion. Thus, markets in which a third party's services are solidly grounded in efficiency still warrant scrutiny by competition authorities because they are more prone to the emergence of collusion and anticompetitive harm.

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https://doi.org/https://doi.org/10.1111/joie.70017

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@article{joseph2026,
  title        = {{Hub‐and‐Spoke Collusion With a Third‐Party Pricing Algorithm}},
  author       = {Joseph E. Harrington},
  journal      = {The Journal of Industrial Economics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/joie.70017},
}

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Hub‐and‐Spoke Collusion With a Third‐Party Pricing Algorithm

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 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.