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Record W4409603237 · doi:10.61091/jcmcc127b-092

Constructing a Corporate Demand Model for Brand Design of Financial Central Enterprises Based on the Grounded Theory

2025· article· en· W4409603237 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Combinatorial Mathematics and Combinatorial Computing · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Topics in Contemporary Research
Canadian institutionsnot available
Fundersnot available
KeywordsGrounded theoryBusinessFinanceMarketingIndustrial organizationQualitative researchSociology

Abstract

fetched live from OpenAlex

This study aims to construct a corporate demand model of brand design for financial central enterprises based on grounded theory, providing a systematic theoretical framework to help financial central enterprises effectively meet their brand design needs.The method of grounded theory is used to extract relevant information from public information and in-depth interviews, and to demonstrate the rationality of the corporate demand model by combining quantitative research.Through an indepth analysis of the subsystems of demand motivation generation, demand factor analysis and demand design realisation, a feasible theoretical framework is provided for financial central enterprises to achieve effective satisfaction of brand design corporate demands.The problem of accurately grasping requirements in the practice of brand design for financial central enterprises is solved.Useful reference and support are provided for the brand design of financial central enterprises.The innovative practice of brand design is promoted for financial central enterprises.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.066
GPT teacher head0.313
Teacher spread0.247 · 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
Published2025
Admission routes1
Has abstractyes

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Same venueJournal of Combinatorial Mathematics and Combinatorial ComputingSame topicDiverse Topics in Contemporary ResearchFrench-language works237,207