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Record W2209674773 · doi:10.5430/ijba.v7n1p12

Themes and Topics of Research in Marketing: A Content Analysis of the Articles Published in Three Marketing Journals

2016· article· en· W2209674773 on OpenAlexvenueno aff
Mahmoud Abdel Hamid Saleh

Bibliographic record

VenueInternational Journal of Business Administration · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsnot available
Fundersnot available
KeywordsMarketingMarketing researchMarketing scienceMarketing managementRelationship marketingReturn on marketing investmentBusinessMarketing mixDigital marketingMarketing strategyQuantitative marketing research

Abstract

fetched live from OpenAlex

This study aimed at classifying the themes of marketing in the articles published in three top journals in the field of marketing from 2010 to 2014. At the same time, the study aimed at identifying the researchers’ interest and topics in each theme. The study findings demonstrated that the Journal of Marketing Research has got a share of 39% of the total published articles of those three journals, compared to 35% for the Marketing Science journal, and 26% for the Journal of Marketing. With respect to the research themes, extensive interest has been given to consumer behavior at 22%, e-marketing at 10%, advertising at 7%, promotion and pricing at 7% each, product development at 5%, and marketing management at 4%. The study also concluded the researchers’ negligence of important themes in marketing theory, such as: marketing ethics, international marketing, social responsibility, service marketing, competitive analysis, and customer relationship management. Moreover, The study found that each of the three journals has extensively published on some specific themes compared to the other two journals. The journal of Marketing Science has published more articles on e-marketing, channels of distribution, competitive analysis, and marketing ethics. The Journal of Marketing has published more articles on branding, sales and sales management, value creation, services and service quality, customer relationship management, international marketing, social responsibility, and customer loyalty. The Journal of Marketing Research has published more articles on consumer behavior, branding, pricing, retailing, and customer satisfaction.

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)0.004
metaresearch head score (Gemma)0.002
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 score0.106
Threshold uncertainty score0.257

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.154
GPT teacher head0.357
Teacher spread0.203 · 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

Citations9
Published2016
Admission routes1
Has abstractyes

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