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Record W2136398737 · doi:10.5267/j.msl.2015.1.013

Application of accrual accounting in Iran municipalities

2015· article· en· W2136398737 on OpenAlexvenueno aff
Ali Eamaeilzade Maghariee, Zahra Houshmand Neghabi, Rahele Abdi

Bibliographic record

VenueManagement Science Letters · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAccrualAccountingBusinessComputer scienceEarnings

Abstract

fetched live from OpenAlex

Accrual accounting is a technique for recognizing expenses when incurred and revenue when earned rather than when payment is made or received. In the cash method of accounting, on the other hand, cash receipts and disbursements technique of accounting or cash accounting records revenue when cash is earned, and expenses when they are paid in cash. In this paper, we present an empirical investigation to study the effect of implementing accrual accounting in municipality of Amol, Iran. The survey investigates whether or not financial reporting based on accrual accounting compared with a cash basis could provide a better method for promoting accountability. Using, regression analysis, the study compares the performance of accrual accounting versus cash accounting and the results have indicated that accrual accounting could improve the performance of accounting in municipality system. In addition, the study has examined whether or not converting cash to accrual accounting basis in municipalities could improve qualitative characteristics of accounting information. To examine this hypothesis, the study has designed a questionnaire in Likert scale to measure the quality of information and, using some statistical tests, the survey has concluded accrual accounting indeed provided better quality characteristics information.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.193
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0010.001
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 head0.021
GPT teacher head0.237
Teacher spread0.217 · 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 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

Citations2
Published2015
Admission routes1
Has abstractyes

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