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Record W4361801754 · doi:10.55365/1923.x2023.21.12

Procurement Fraud In The Public Sector: An Analysis Of Fraud Triangle Elements And Workplace Spirituality

2023· article· en· W4361801754 on OpenAlexvenueno aff
Razana Johari, Nur Faudzi, S. Hussin, Ida Rosnidah, Ayatulloh Michael Musyaffi

Bibliographic record

VenueReview of Economics and Finance · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Spirituality and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsProcurementRationalisationPublic sectorBusinessGovernment procurementGovernment (linguistics)AccountingPublic relationsMarketingPolitical scienceLaw

Abstract

fetched live from OpenAlex

This study's objective is to identify the elements that lead to public procurement fraud among Malaysian public sector employees.In order to comprehend and analyse procurement fraud in Malaysia, this study uses four distinct factors: pressure, opportunity, rationalisation, and workplace spirituality.The Statistical Package for Social Science (SPSS) version 25 software was used for analysis of the data, which were collected by sending questionnaires to Malaysia's 25 ministries.The results of this study show that opportunity and rationalisation have a significant positive relationship with the incidence of procurement fraud among public sector employees, but that there is a significant negative relationship between workplace spirituality and the incidence of procurement fraud.However, there is no solid evidence linking pressures on Malaysian public sector employees to procurement fraud.The findings offer important details on the theoretical and practical aspects of procurement fraud, as well as on its occurrences in the government and administrative sector, as well as in ministries and academic institutions.

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)0.006
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.103
GPT teacher head0.344
Teacher spread0.241 · 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 designNot applicable
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

Citations6
Published2023
Admission routes1
Has abstractyes

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