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Record W1524486899 · doi:10.1108/01443571111126328

Exploring the impact of national culture on investments in manufacturing practices and performance

2011· article· en· W1524486899 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Operations & Production Management · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsYork University
Fundersnot available
KeywordsHofstede's cultural dimensions theoryOriginalityBusinessMarketingOrganizational cultureValue (mathematics)Uncertainty avoidanceAffect (linguistics)Operations managementManagementSociologyEconomicsComputer scienceQualitative researchSocial science

Abstract

fetched live from OpenAlex

Purpose The purpose of this study is to assess how differences in national culture influence the impact of investments in manufacturing practices on operational performance. The paper addresses the following research question: does national culture affect the efficacy of investments in manufacturing practices? Design/methodology/approach Hofstede's model of national culture is used to test whether there are operational performance differences when organisations in different cultural contexts invest in identical manufacturing practices. The research question is explored and answered by assessing the moderating role of national culture using ordinary least square analysis. Findings The results suggest that some dimensions of national culture significantly moderate the impact of investments in manufacturing practices on manufacturing performance. Originality/value This study represents a comprehensive attempt to explain differences in the impact of manufacturing practices investments on operational performance improvements in terms of cultural differences.

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.

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 score0.822
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.162
GPT teacher head0.328
Teacher spread0.166 · 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