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Record W2308536786

Mechanism of network marketing organizations expansion as pyramid structures

2004· article· en· W2308536786 on OpenAlexaff
Ming Ouyang, E. Stephen Grant

Bibliographic record

VenueJournal of Management and Research · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSecurities Regulation and Market Practices
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPyramid (geometry)Mechanism (biology)MarketingSales forceBusinessComputer scienceMathematics
DOInot available

Abstract

fetched live from OpenAlex

As a special retailing channel, network marketing organizations (NMO), also referred to as multilevel direct selling organizations (ML), have existed widely for decades. Although the marketing literature documents numerous studies on this popular but controversial practice, NMO’s functional mechanism has not yet been explored. This research presents a theoretical model in characterizing NMO’s behavioural rationale and illustrates how NMOs convert social networks into sales opportunities by incorporating the size of the sales force with individuals’ contacting rate and salespersons’ persuasive rate. In addition, when the factor of the quitting of salespersons is considered, the modeling dynamics demonstrates how and why down-stream salespersons are worse off. This paper provides insights into the inherent relationships within NMO’s pyramid levels and it advances our knowledge of NMO’s controversial practices.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.024
GPT teacher head0.303
Teacher spread0.279 · 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

Citations5
Published2004
Admission routes1
Has abstractyes

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