The US Cigarette Industry: An Economic and Marketing Perspective
Bibliographic record
Abstract
OBJECTIVES: Tobacco company conduct has been a central concern in tobacco control. Nevertheless, the public health community has not taken full advantage of the large economics and marketing literature on market competition in the cigarette industry. METHODS: We conducted an unstructured narrative review of the economics and marketing literature using an antitrust framework that considers: 1) market; definition, 2) market concentration; 3) entry barriers; and 4) firm conduct. RESULTS: Since the 1960s, U.S. cigarette market concentration has increased primarily due to mergers and growth in the Marlboro brand. Entry barriers have included brand proliferation, slotting allowance contracts with retailers and government regulation. While cigarette sales have declined, established firms have used coordinated price increases, predatory pricing and price discrimination to sustain their market power and profits. CONCLUSIONS: Although the major cigarette firms have exercised market power to increase prices and profits, the market could be radically changing, with consumers more likely to use several different types of tobacco products rather than just smoking a single cigarette brand. Better understanding of the interaction between market structure and government regulation can help develop effective policies in this changing tobacco product market.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".