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Record W7117718019 · doi:10.1080/00036846.2025.2601333

Sliding doors: Alitalia–ITA transition impact on pricing strategies

2025· article· en· W7117718019 on OpenAlexaff
Angela Stefania Bergantino, Ada Spiru, Mario Intini

Bibliographic record

VenueApplied Economics · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicItaly: Economic History and Contemporary Issues
Canadian institutionsInstitute on Governance
FundersEuropean Commission
KeywordsTransition (genetics)Stability (learning theory)Series (stratigraphy)Work (physics)

Abstract

fetched live from OpenAlex

This article investigates the short-term impact of the Alitalia–ITA Airways transition on pricing strategies and market competition in the Italian domestic air transport sector. Using a novel dataset simulating over 21,000 ticket purchases before and after ITA’s market entry, we apply a difference-in-difference approach combined with propensity score matching to estimate the causal effect of this ownership transition. Our results show a significant fare reduction of approximately 25% on affected routes, driven by ITA’s more competitive pricing and reduced intertemporal price dispersion. The study also documents heterogeneous reactions among competing airlines, particularly Ryanair. These findings provide new empirical evidence on how structural changes in flag carrier ownership affect market dynamics, raising important considerations for competition policy and future regulatory design.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.228
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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