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Record W3008486894 · doi:10.5267/j.msl.2020.2.015

The mediating effect of organizational factors between multidimensional performance measures and performance management systems

2020· article· en· W3008486894 on OpenAlexvenueno aff
Kien Pham Van, Phong Nguyen Dinh, Tung Tran Anh, Linh Nguyen Tran Cam

Bibliographic record

VenueManagement Science Letters · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsnot available
Fundersnot available
KeywordsProcess managementKnowledge managementComputer scienceMeasure (data warehouse)Organizational performancePsychologyBusinessData mining

Abstract

fetched live from OpenAlex

There are many studies on the effectiveness by employing management systems and this paper tries to point out the critical components that embodied the obstacles on system deployment on the context of the emerging markets in Viet Nam.The study is conducted as an exploratory research project which uses a quantitative approach to gain insight and information of the businesses in question.The data was collected via a survey questionnaire derived from experts and focus groups.The findings of this study indicated the significant role of organizational factors such as employee participation and communication, demonstrating they were critical mediators in the given context.Upon completion of the research, we advanced the study of these factors that directly and indirectly affect the success of PMS implementation throughout the empirical approach on Vietnamese firms.

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)0.005
metaresearch head score (Gemma)0.021
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 score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.009
GPT teacher head0.184
Teacher spread0.175 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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