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Record W1581465663

Social Media Practices Among Small Business-to-Business Enterprises

2015· article· en· W1581465663 on OpenAlexaboutno aff
Greg M. Broekemier, Ngan N. Chau, Srivatsa Seshadri

Bibliographic record

VenueSmall Business Institute Journal · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Marketing and Social Media
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessSocial mediaMarketingSocial media marketingReputationSmall businessSample (material)Quarter (Canadian coin)AdvertisingDigital marketingSociologyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

A national sample of business-to-business (B2B) small businesses was surveyed regarding their attitudes toward and usage of social media in their marketing efforts. Results from this descriptive study show that many B2B small businesses utilize social media in their marketing efforts (54%). The four main purposes for using social media reported by the B2B small businesses were: (1) improving company reputation, (2) increasing customer interest, (3) increasing customer awareness, and (4) promoting business to new customers. Among the 46% not using social media, a substantial proportion (81%) had no intention to do so in the near future. Further, nearly a quarter of those who do use social media report that they do not know the effectiveness of their marketing efforts. Clearly there is still a need among small businesses to gain more knowledge of how to most effectively integrate social media into their marketing plans.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.122
GPT teacher head0.338
Teacher spread0.216 · 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 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

Citations50
Published2015
Admission routes1
Has abstractyes

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