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Record W3027194072

The analysis of 4p's of marketing on coca-cola and rc cola with the objective to find why rc cola had failed in the international markets

2016· article· en· W3027194072 on OpenAlexaboutno aff
Rishab Telukunta, Surya Pratap Singh Rathore

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategies and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsCola (plant)Coca colaAdvertisingBusinessTasteLiberian dollarProduct (mathematics)MarketingFood scienceMathematics
DOInot available

Abstract

fetched live from OpenAlex

Asa Griggs Candler founded the Coca-Cola Company in the year 1889. the company is the No. 1 seller of sparking as well as still beverages. The famous tagline of the company “Open Happiness” has been changed to “Taste The Feeling”. The company's main competitors are Pepsi, Monster beverage and Dr. Pepper. The company has grown into such a great success in the global markets only because of their unique and creative marketing strategies that have attracted over millions of consumers over the century. There were even some somewhat diverting advertisements, incorporating one in which detainees sentenced to an existence of Coke or Pepsi snuck jars and containers of RC into their cells. RC cola is now more than 100 years old is traded all around the world. In 2001, every part of global RC-branded businesses were sold near Cott Beverages of Mississauga, Ontario, Canada, plus are operated to the same extent noble Crown Cola International, which handles RC Cola harvest exterior the United States. The company has around 20 billion-dollar brands that are Diet Coke, Coca-Cola Zero, Fanta, Minute Maid. The company has a different distribution system where the company only produces the syrup and it is transported to different bottlers throughout the world. To help our accomplices get the most out of these projects, RCCI keeps up a hands-on worldwide nearness with specialists in advertising, innovative work, specialized and quality administrations.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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 designObservational
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

Citations0
Published2016
Admission routes1
Has abstractyes

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