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Record W2950787380 · doi:10.5430/ijfr.v10n5p301

Are SMEs Ready for Integrated Reporting? The Malaysian Experience of Accountability

2019· article· en· W2950787380 on OpenAlexvenueno aff
Mira Susanti Amirrudin, Mazni Abdullah, Nooraslinda Abdul Aris, Nor Farizal Mohammed

Bibliographic record

VenueInternational Journal of Financial Research · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
FundersUniversiti Teknologi MARA
KeywordsAccountabilityBusinessIntegrated reportingReputationMarketingUsabilityValue (mathematics)CorporationAccountingPublic relationsFinanceSustainability

Abstract

fetched live from OpenAlex

The Integrated Reporting (IR) provides businesses with a reporting approach that is conducive to the understanding and articulating their business strategy. By doing so, businesses will be able to drive performance internally and attract financial capital for investment, as well as helping investors to understand how the strategy being pursued that creates value over time. Changing market trends due to technology advancement had jeopardized the traditional way of reporting performance. Small and medium-sized enterprises (SMEs) are typically vulnerable entities against such changes and therefore challenged to sustain their life spans. This paper offers an introduction of IR, as well as assessing IR usability and benefits for SMEs in Malaysia. Furthermore, the paper discusses relevant literature and opportunities available for SMEs regarding the applicability of such reporting philosophy. Applying the qualitative method, themes and key success factors were identified using NVivo application software. The annual reports of SME Corporation Malaysian from the year 2014 to 2016 were analysed showcase growing evidence of integrated communications to SMEs in the areas of access to markets, better business understanding and enhancing reputation. IR offers invaluable benefits to SMEs, shifting their focus from merely financial performance measures to a more holistic integrated approach to accountability, which emphasises on value creation.

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)0.009
metaresearch head score (Gemma)0.046
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.148
GPT teacher head0.429
Teacher spread0.281 · 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.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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