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Record W4310238085 · doi:10.5539/ibr.v15n12p86

Collaborative Consumption and Institutional Theory: Bibliometric Analysis of Scientific Production from 2011 to 2021

2022· article· en· W4310238085 on OpenAlexvenueno aff
Maiara N Cardoso, Rogerio T O Lacerda, Michel Becker

Bibliographic record

VenueInternational Business Research · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsnot available
Fundersnot available
KeywordsScopusRelevance (law)Consumption (sociology)PortfolioBibliometricsField (mathematics)Sample (material)Process (computing)Computer scienceSociologyPolitical scienceSocial scienceBusinessLibrary scienceMEDLINE

Abstract

fetched live from OpenAlex

Owing to the interest in investigating how institutional theory can be used according to collaborative consumption, this study presents a process for the selection of articles of scientific relevance to these themes, published between 2011 and 2021. Thus, 27 articles were identified to compose the final bibliographic portfolio with relevant articles and aligned with the themes after using the Scopus international database. Articles were selected, and a bibliometric analysis was performed, which led to the description of the most relevant articles, authors, and journals. Given the results presented, this research intends to contribute to studies on collaborative consumption and institutional theory and present a process for selecting and disclosing the most relevant articles, authors, and journals in the area that can serve academic and future scientific research. As a suggestion for future research, it is possible to carry out a systemic analysis of the portfolio presented in this study to identify gaps and research opportunities. A limitation of this study is that the sample field was restricted to the Scopus database.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designmedium
models splitAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0600.083
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.079
GPT teacher head0.342
Teacher spread0.263 · 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

Labeled directly by 2 models reading the full record.

Bibliometrics

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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

Citations1
Published2022
Admission routes1
Has abstractyes

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