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Record W751401484

ALO case study : entering a new market : getting back on track after getting lost

2014· dissertation· en· W751401484 on OpenAlexaboutno aff

Bibliographic record

VenueRepositório Institucional da Universidade Católica Portuguesa (Universidade Católica Portuguesa) · 2014
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategies and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsTrack (disk drive)BusinessComputer science
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this thesis is to study the influence of ALO’s positioning and targeting on its business, and how it can compromise the entire activity. ALO is an American brand, launched in 2008 in the USA, with the goal of selling natural beverages produced directly through the well-known Aloe Vera plant, providing the consumer with several health and dietary benefits, together with a great taste. In 2013 ALO was already the number 1 bestselling brand within the Aloe Vera beverage segment, and the number 2 bestselling brand within the functional beverage segment, among the markets of USA and Canada. It was also during this same year of 2013 that António Lopes decided to introduce ALO in Portugal and give the opportunity to the Portuguese population to include this amazing drink in their lives and daily activities. While people’s minds are changing towards a healthier and balanced life associated with healthier products’ consumption, the success and acceptance of ALO can’t be considered “black in white”. To make this thesis possible, a complex and thorough study and research was performed and tools used include a Literature Review where the concepts and theory were studied to better address the following parts of the thesis; a Case Study written including a proposal of analysis to be used during class discussions; and a Market Research involving interviews with the company, Survey and Focus Groups. Being ALO a 100% natural beverage with healthy and dietary benefits, António’s first approach was to focus on the part of the population that practise sports on a regular basis and on places dedicated to natural products, ending up with an unsustainable business. With the objective of giving people the opportunity of gathering the pleasure and taste together with the health and dietary benefits, ALO reached the conclusion that the consumer is the average Portuguese citizen, above 15, looking for a balanced life style, trying to keep a healthy life. ALO drink needs to be seen first as a great drink, with the bonus of being healthy and having great benefits – the consumer is more worried with the image, and benefits are the differentiation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0170.005
Scholarly communication0.0090.008
Open science0.0030.006
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0200.004

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 head0.020
GPT teacher head0.234
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2014
Admission routes1
Has abstractyes

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