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Record W3090239347 · doi:10.17722/ijme.v12i1.1038

National Private Banks’ Organizational Culture and Organizational Commitment Analysis

2018· article· en· W3090239347 on OpenAlexvenueno aff
Dikdik Supriyadi

Bibliographic record

VenueInternational Journal of Management Excellence · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEmployee Performance and Management
Canadian institutionsnot available
Fundersnot available
KeywordsOrganizational commitmentOrganizational cultureBusinessOrganizational learningOrganizational behavior and human resourcesOrganization developmentOrganizational studiesOrganizational engineeringBusiness administrationOrganizational performancePublic relationsMarketingManagementPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The acceleration of environmental change results in changes in corporate culture, the success of an organization is not only supported by the organizational culture but also how the organization fosters organizational commitment that is understood as an individual's psychological bond to the organization. The purpose of this study is to analyze the Organizational Culture and Organizational Commitment in Private Banks in Bandung. Descriptive method was used in this study for employees of some private banks. The total number of respondents were 80 employees. The result shown that Organizational Culture produces the level of effort and subordinate Organizational Commitment beyond what will happen, when viewed from the average weight of Organizational Culture. Based on the analysis of Organizational Commitment, it can be said that employees of Private Bank in Bandung as a whole have a high Organizational Commitment based on the weight generated from the questionnaires that the authors distribute.

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)0.003
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.013
GPT teacher head0.295
Teacher spread0.282 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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