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Record W2272691074 · doi:10.14288/1.0091454

Emerging B2B electronic marketplaces : explaining organizational participation with transaction cost perspective

2009· article· en· W2272691074 on OpenAlexaboutno aff
Rong Tang

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsTransaction costPerspective (graphical)BusinessElectronic marketsDatabase transactionIndustrial organizationMarketingKnowledge managementComputer scienceThe InternetFinanceWorld Wide Web

Abstract

fetched live from OpenAlex

With the growing popularity of B2B e-marketplaces, increasing numbers of organizations are endeavouring to utilize this medium in their business activities. However, the present knowledge regarding B2B e-marketplace adoption processes is still limited. Therefore, the present study investigates circumstances under which organizations adopt B2B e-marketplaces. More specifically, it is primarily concerned with the factors motivating an organization's participation in B2B e-marketplaces from the purchasing manager's perspective, based on insights and observations obtained from transaction cost economics. A single unified framework was developed based on previous findings to investigate the emergence of efficiency motive within organizations, and to analyze the role of this motivation in organizational participation processes. A large-scale cross-sectional survey study targeted the membership of the Purchasing Management Association of Canada (PMAC) was used for empirical validation of this framework. Partial Least Squares (PLS) analysis was chosen to test the measurement model and the conceptual model based on 466 usable responses obtained. The results demonstrate that efficiency motive exerts a significant influence on intentions to adopt B2B e-marketplaces, and reveal three transaction characteristics that significantly contribute to the formulation of efficiency motive: frequency uncertainty of demand, asset specificity, and market fragmentation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.950
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.004
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 head0.006
GPT teacher head0.162
Teacher spread0.156 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

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