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Record W4319596390 · doi:10.3390/jrfm16020102

The Usefulness of Accounting Information and Management Accounting Practices under Environmental Uncertainty

2023· article· en· W4319596390 on OpenAlexvenueno aff
Rui Alexandre R. Pires, Maria do Céu Gaspar Alves, Catarina Fernandes

Bibliographic record

VenueJournal of risk and financial management · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsScope (computer science)Management accountingAccounting information systemAccountingCost accountingBusinessKnowledge managementComputer science

Abstract

fetched live from OpenAlex

The purpose of this paper is twofold. Firstly, we aim to investigate the relationships among environmental uncertainty, broad-scope and timely management accounting information usefulness, and (traditional and contemporary) management accounting practices (MAPs) usage. Secondly, we intend to explore how these relationships influence decision-makers’ satisfaction with management accounting information. Survey data were obtained through an online questionnaire from 114 large manufacturing companies operating in Portugal. The findings indicate a positive relationship between environmental uncertainty and timely management accounting information usefulness and between (broad-scope and timely) management accounting information usefulness and (traditional and contemporary) MAPs usage. The findings also show that decision-makers’ satisfaction with management accounting information improves when there is a good fit between environmental uncertainty, broad-scope and timely management accounting information usefulness, and MAPs usage. In this way, organisations need to adjust the implementation and usage of MAPs to contextual factors, using both contemporary and traditional MAPs, to achieve greater decision-makers’ satisfaction with management accounting information. Thus, the results achieved in this study are useful for both theory and practice and have several implications for professionals engaged in MAPs implementation and decision-making activities.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.001
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 head0.009
GPT teacher head0.201
Teacher spread0.192 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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