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Record W1987469176 · doi:10.1109/dest.2010.5610622

Business network orchestration in digital ecosystems

2010· article· en· W1987469176 on OpenAlexaff
Diederik W. van Liere, Otto Koppius, Peter Vervest

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOrchestrationDigital ecosystemPortfolioBusiness ecosystemBusinessKnowledge managementNetwork theoryComputer sciencePosition (finance)Industrial organizationProcess managementFinance

Abstract

fetched live from OpenAlex

The ongoing evolution of interorganizational information systems (IOS) into industry-wide systems (IIOS) or digital ecosystem platforms raises new questions for researchers and practitioners alike, in particular the question of how organizations can gain advantage of these new ecosystems by orchestrating their business network. In an empirical study of the Dutch insurance industry, we use network theory and interorganizational systems theory to show that participation in a digital ecosystem leads to organizations orchestrating their network position into a larger portfolio of suppliers as well as a more differentiated portfolio of suppliers. A more differentiated supplier portfolio in turn leads to superior organizational performance.

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)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0040.007
Open science0.0010.003
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.203
Teacher spread0.189 · 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 designTheoretical or conceptual
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
Published2010
Admission routes1
Has abstractyes

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