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Record W2148456478 · doi:10.7819/rbgn.v9i23.74

Accounting Marketing by Accounting Offices in the State of Sao Paulo

2007· article· en· W2148456478 on OpenAlexaboutno aff
Ivam Ricardo Peleias, Danieli Cristina Ramos Hernandes, Mauro Neves Garcia, Dirceu da Silva

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2007
Typearticle
Languageen
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMarketingQuarter (Canadian coin)BusinessAccountingMarketing researchValuation (finance)

Abstract

fetched live from OpenAlex

This article presents a portion of the result of a research carried through between the last quarter of 2004 and the first quarter of 2005, to identify as 259 accounting services offices in the State of Sao Paulo use or not the Marketing tools. The study executed combined empirical research to identify excellent aspects about the reality of the offices, bibliographical revision, and field research, in its first stage by means of a depth interview with the partners of five offices, and later with the use of a questionnaire with 49 assertive, answered by the partners of the 259 accounting offices. The revision of literature disclosed international experiences in the use of the Marketing that can contribute the offices have one better image for its customers, and for the development of its businesses. The data collected with the questionnaires have been treated by the Descriptive Statistics and analyzed by the use of Mean, because the collected data was not adherent to the normal curve. The achieved results have disclosed that the use of the Marketing tools is intuitive and embryonic in the sector. The research supplies information that will serve of subsidy so that the accounting entrepreneurs adopt the Marketing tools as an alternative for bigger valuation of its services for the market, and an element of support to its business.Key-words: Marketing. Services marketing. Accounting marketing. Accounting services offices. Services. Accounting.

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)0.015
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.035
GPT teacher head0.291
Teacher spread0.256 · 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.

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

Citations0
Published2007
Admission routes1
Has abstractyes

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