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Record W2397821348 · doi:10.5539/ijms.v8n3p145

A Model of Strategic Marketing Decision Premises

2016· article· en· W2397821348 on OpenAlexvenueno aff
Linus Osuagwu

Bibliographic record

VenueInternational Journal of Marketing Studies · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsExtant taxonMarketingMarketing managementBusinessProfit impact of marketing strategyMarketing researchMarketing strategyStrategic marketingEmpirical researchSketchRelationship marketingComputer science

Abstract

fetched live from OpenAlex

The paper utilized some relevant empirical and conceptual works in extant literature to sketch a model of the relations among marketing environment, strategic marketing decisions and effectiveness. The paper reveals that some forms of supports exist in extant literature regarding the impacts of marketing environment on strategic marketing decisions and effectiveness, and impacts of strategic marketing decisions on strategic marketing effectiveness. However, relevant extant literature seems to have ignored the impacts of strategic marketing decisions on marketing environment. Also, relevant extant literature contains some gaps regarding the impacts of strategic marketing effectiveness on marketing environment and strategic marketing decisions. The paper concludes that these important relationships in strategic marketing decisions, omitted in extant literature, should be incorporated for a more comprehensive understanding of the relevant issues in strategic management decisions. The paper proposes an empirical research agenda to test the model in some business functions, sectors, cultures, contexts or premises.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0060.006
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0290.005

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 head0.096
GPT teacher head0.327
Teacher spread0.231 · 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 designTheoretical or conceptual
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

Citations3
Published2016
Admission routes1
Has abstractyes

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