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Record W2497097457

The U.S. Airline Industry in 2015

2015· article· en· W2497097457 on OpenAlexaboutno aff
Duane Helleloid, Seong‐Hyun Nam, Patrick Schultz, John Vitton

Bibliographic record

VenueJournal of the International Academy of Case Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Aviation
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexRevenueBusinessCompetitor analysisFinanceProfit (economics)Profit marginEconomicsMarketing
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION [T]he airline business has been extraordinary. It has eaten up capital over the past century like almost no other business because people seem to keep coming back to it and putting fresh money in. You've got huge fixed costs, you've got strong labor unions and you've got commodity pricing. That is not a great recipe for success. (Warren Buffett, Berkshire Hathaway CEO, as quoted in Reed, 2013) The U.S. airline industry has been plagued by financial losses, bankruptcies, union disputes, and expensive mergers over the past decade. Since 2009, profitability has returned for most airlines (MIT, 2015). The International Air Transport Association projected combined profits for North American airlines (predominantly U.S. airlines, but also including Canadian and Mexican airlines) of almost $12 billion in 2014 and over $13 billion in 2015 (IATA, 2014 a). Four large U.S.-based airlines (American, United, Southwest, and Delta) each reported 2104 operating profits of over $2 billion (MIT, 2015). A combination of an improving economy, lower oil prices, reduction in the number of competitors, increases in ancillary revenue, and cost cutting efforts all contributed to this improved profit picture. It was unclear, however, whether these changes were structural in nature and would lead to a period of higher profitability, or whether the airlines might again face financial losses and another round of bankruptcies. Regardless, the record profitability had attracted the attention of regulators and politicians. In July 2015, the U.S. Department of Justice announced it was initiating an investigation to determine whether airlines had colluded to keep airfares high (Harwell, Halsey, and Moore, 2015). New York's Senator Schumer issued a statement questioning why fares weren't falling in accordance with oil prices, while an industry group responded that competition remained intense, to the benefit of consumers (Naylor, 2015). REGULATION OF THE U.S. AIRLINE INDUSTRY The history of the U.S. airline industry has been influenced throughout the past 100 years by changing regulation. The Air Mail Act of 1925 authorized the postmaster general to enter into contracts for the transportation of mail by air. This was rewritten by the Air Mail Act of 1934, which required that aircraft manufacturers divest their ownership in airlines and required that rates be set by the Interstate Commerce Commission. Until 1936, airlines earned more revenue from carrying mail than they did from carrying passengers. The Civil Aeronautics Act of 1938 created a system whereby all passenger routes between city-pairs (e.g., Chicago-Philadelphia, Washington-Boston) were regulated by the federal government, which could decide which airlines would be allowed to fly which routes, and what fares could be charged. This regulatory environment remained in place until the Airline Deregulation Act of 1978. The 1978 legislation, which was phased in over 5 years, allowed airlines to determine their own routes and rates. It also allowed new airlines to enter the market, competing with existing airlines on some routes, and opening routes on previously unserved city-pairs. Existing airlines also took advantage of the new freedom to restructure their routes, open service on new routes, and discontinue service on undesirable routes. (Dana, 2004; Dempsey, 1984; Kou and McGahan, 1995; Millbrooke, 2006) The impact of regulation, and changing regulation, has and continues to impact the airline industry. Up until the 1978 deregulation, airlines' routes and fares were strictly regulated, which minimized competition between airlines. In order to maintain air safety, significant regulation still remains, with unions, companies, and consumer groups all trying to influence regulations to their advantage. BANKRUPTCIES, NEW ENTRANTS, AND CONSOLIDATIONS As deregulation was phased in from 1978-1984, existing U.S. airlines included six major network firms--American, United, Delta, Eastern, Braniff and Continental. …

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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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.091
GPT teacher head0.429
Teacher spread0.338 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2015
Admission routes1
Has abstractyes

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