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Record W3013326753 · doi:10.14596/pisb.324

Il ruolo del capitale intellettuale nel successo delle strategie di merger & acquisition delle start-up

2020· article· it· W3013326753 on OpenAlexaff
Francesca Masciarelli, Francesca Di Pietro, Greta Serpente

Bibliographic record

VenueBOA (University of Milano-Bicocca) · 2020
Typearticle
Languageit
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsTrinity College
Fundersnot available
KeywordsAgency (philosophy)BusinessIntellectual capitalBusiness administrationHuman capitalService (business)Capital (architecture)ManagementMarketingFinanceSociologyEconomicsEconomic growthGeography

Abstract

fetched live from OpenAlex

The article proposes a case study of a Merger and Acquisition (M&A) processes in Italy between a temporary agency and an innovative start-up. The aim of the study is to investigate which component of the intellectual capital affects the trust of the companies involved in the M&A process. Results show the key role of trust in start-up’s human capital for the integration of the innovative service into the acquiring company. We suggest that the success of the M&A is given by our model named “circular vision of intellectual capital”.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.043
GPT teacher head0.193
Teacher spread0.150 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2020
Admission routes1
Has abstractyes

Explore more

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