Demand-shock characteristics and pricing behavior: A natural experiment from UEFA Euro 2016

Claudio A. Piga et al.

Economics of Transportation2025https://doi.org/10.1016/j.ecotra.2025.100393article
AJG 1ABDC B
Weight
0.41

Abstract

We consider a multi-period, limited capacity, unsegmented airline pricing model whose solution returns a sequence of increasing prices based on the order of sale. We show that a positive demand shock corresponding to an increase in the arrival rate reduces within-period price dispersion and has a minor impact on the sequence’s maximum prices. Alternatively, upward shifts in customers’ willingness-to-pay lead to higher maximum prices but do not affect within-period price dispersion. Demand shocks are identified in our sample by the draw that created the stage groups for the UEFA Euro 2016 soccer tournament. After the draw, some flights became suitable to transport foreign supporters to the location where matches were scheduled. Consistent with the theory, a different price behavior is observed between UK and continental European routes. • Demand shocks may modify customers’ willingness to pay, or market size, or both. • Large sport events create demand shocks in some airline markets. • Airlines’ pricing consists of sequences that pair the i th fare with the i th seat. • Sequences in flights affected by a shock change in response to new conditions. • The impact of shocks on sequences depend on route characteristics.

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https://doi.org/https://doi.org/10.1016/j.ecotra.2025.100393

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@article{claudio2025,
  title        = {{Demand-shock characteristics and pricing behavior: A natural experiment from UEFA Euro 2016}},
  author       = {Claudio A. Piga et al.},
  journal      = {Economics of Transportation},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1016/j.ecotra.2025.100393},
}

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Evidence weight

0.41

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

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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