Importance of Diversified Marketing Strategies for Fast Food Restaurant Chains
Bibliographic record
Abstract
Every organization needs to consistently adjust operations and marketing strategies in order to perpetually satisfy consumers and reinforce dedication to the vision and mission of the company. The adjustments need to be made over time, according to situational influences as well as internal and external trends affecting consumer behavior. Without a proper marketing strategy, a company may go out of business due to internal and external organizational pressures. Nowadays, as the economies of countries worldwide show signs of crisis, fast food industry players need to adjust their marketing strategies in order to overcome the competition within new circumstances. This literature review demonstrates that in order to succeed in this competition, food chain companies need to combine multiple approaches and use omni-channel marketing campaigns. This article summarizes the research made over the last two decades and suggests topics in this area that can be further researched. The research documents, reviewed in chronological order, are peer-reviewed articles, conference papers, corporate websites and major media resources. Keywords: consumer behavior, McDonald’s, decision-making process, business strategy, marketing strategy
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 | 0.002 | 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 | 0.001 | 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".