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Record W1551854931 · doi:10.1108/17506120910989679

Considering implementing major strategic change?

2009· article· en· W1551854931 on OpenAlexaff
Michel Rod, Nicholas J. Ashill, Sarena Saunders

Bibliographic record

VenueInternational Journal of Pharmaceutical and Healthcare Marketing · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Change and Leadership
Canadian institutionsCarleton University
Fundersnot available
KeywordsJoint ventureOriginalityBusinessValue (mathematics)Process managementJoint (building)Strategic managementChange management (ITSM)Knowledge managementMarketingComputer scienceSociologyQualitative researchBusiness administrationEngineering

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to identify and illustrate those factors that influence successful implementation of major strategic change drawing on the example of a joint venture between two small firms in the health technology sector. Design/methodology/approach The methodological approach involves a selective review of the strategic change implementation literature in conjunction with personal reflections on the part of the lead author regarding his involvement in the development and first year of operations of this joint venture. Findings The authors provide an illustration of the sorts of factors that influence major strategic change implementation from the literature integrated with the findings from the focal joint venture in developing a taxonomic framework and several propositions with accompanying managerial action points to help guide the development and management of a small joint venture as one example of major strategic change implementation. Originality/value The paper provides managers with a framework that identifies the sorts of issues that need to be considered when implementing this type of major strategic change.

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)0.001
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 score0.577
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.161
GPT teacher head0.375
Teacher spread0.214 · 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

Citations2
Published2009
Admission routes1
Has abstractyes

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