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Record W4391062584 · doi:10.5267/j.uscm.2023.12.005

Determinants of sustainable performance: The mediating role of organizational culture

2024· article· en· W4391062584 on OpenAlexvenueno aff
Eri Marlapa, Tine Yuliantini, Junaedi Junaedi, Merdiyanti Rika Kusuma, Citra Shahnia, Endri Endri

Bibliographic record

VenueUncertain Supply Chain Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEmployee Performance and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsIncentiveBusinessStructural equation modelingOrganizational cultureOrganizational performanceMarketingKnowledge managementPublic relationsEconomicsPolitical scienceMicroeconomicsComputer science

Abstract

fetched live from OpenAlex

This study aims to determine the effect of the relationship between the application of fingerprints, work discipline, and the provision of incentives on the Sustainable Performance of the Jakarta Institute of the Arts Film and Television Faculty with organizational Culture as a mediating variable. The population in this study were 53 employees of the Faculty of Film and Television, Jakarta Art Institute. The sampling technique used is total sampling/saturation sampling. This study used an exploratory approach with structural equation modeling data analysis techniques with SmartPLS software, which was tested on 53 respondents. The research results show that Fingerprint application does not affect Organizational Culture, Application of Fingerprint has a positive effect on Sustainable Performance, Application of Fingerprint has no considerable impact on Organizational Culture, Work discipline has no substantial effect on Sustainable Performance, Provision of Incentives has a positive impact on Organizational Culture. Provision of Incentives has a positive effect on Sustainable Performance, Provision of Incentives has a positive impact on Sustainable Performance.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.225
Teacher spread0.215 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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