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Record W2016166911 · doi:10.1108/00251740010360579

Anatomy of a merger: behavior of organizational factors and processes throughout the pre‐ during‐ post‐ stages (part 2)

2000· article· en· W2016166911 on OpenAlexaff
Steven H. Appelbaum, Joy Gandell, Barbara T. Shapiro, Pierre Bélisle, Eugene Hoeven

Bibliographic record

VenueManagement Decision · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsInternational Air Transport AssociationGouvernement du QuébecConcordia University
Fundersnot available
KeywordsMerge (version control)BusinessOrganizational cultureProcess (computing)Organizational changePublic relationsMarketingProcess managementManagementPolitical scienceComputer scienceEconomics

Abstract

fetched live from OpenAlex

The multiple organizational factors impacting upon a merger as well as those processes being impacted upon throughout the merger process will be examined. Part 1 of this article examined corporate culture and its affects on employees when two companies merge and considered the importance of lucid communication throughout the process. Part 2 of the article addresses the critical issue of stress, which is an outcome within the new and uncertain environment. Finally, the article concludes with the process of managing and strategy throughout the phases, giving guidelines that managers and CEOs should follow in the event of an M&A. Furthermore, the five major sections (communications, corporate culture, change, stress, and managing/strategy) are sub‐divided into three sub‐sections: pre‐merger; during the merger; post‐merger. This is intended to further assist managers and CEOs distinguish the important issues facing employees at each of the three junctures of the M&A process.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.243
Teacher spread0.233 · 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 designQualitative
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

Citations86
Published2000
Admission routes1
Has abstractyes

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