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Record W917772247

The impact of national culture on the effectiveness of interorganizational knowledge transfer

2005· dissertation· en· W917772247 on OpenAlexaboutno aff
Yie Li

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2005
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsKnowledge transferKnowledge managementOrganizational learningOrganizational cultureMultinational corporationMiddle managementBusinessChampionPolitical sciencePublic relationsComputer science
DOInot available

Abstract

fetched live from OpenAlex

In today's business climate, organizational knowledge has been widely accepted as a principle organizational source for sustainable advantages for global competitiveness. Inter-organizational knowledge transfer lays a significant foundation for obtaining new organizational knowledge. The role of middle managers in inter-organizational knowledge transfer is getting more and more attentions nowadays, although it cannot be more than enough. In addition, considerable evidence supports the importance of culture in the success or failure of knowledge transfer within organizations. The main purpose of this research is to identify what roles of middle managers play in each stage of inter-organizational knowledge transfer as well as the impact of national culture on such roles. The research used a case study methodology and was conducted among Canadian, American and Chinese middle managers in two well-known multinational organizations. The findings suggest that first, middle managers play the roles of Radar, Filter and Champion in the initiation stage, the role of Coordinator in the interrelation stage and the role of Problem solver in the implementation stage; second, Chinese middle managers are involved less than those from North America in the activity 'Suggesting and prioritizing the different courses of action to acquire new knowledge', 'Defining and justifying the importance of new knowledge transfer proposals to upper-level managers' and 'Embedding the newly acquired knowledge in organizational processes and routines'. This study opens new insights of research in knowledge transfer that link up the roles of middle managers, national culture, and the effectiveness of knowledge transfer.

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 score0.596
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.289
Teacher spread0.267 · 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
Published2005
Admission routes1
Has abstractyes

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