National Cultural Dimensions and Adoption of the International Financial Reporting Standard (IFRS) for Small and Medium-Sized Entities (SMEs)
Bibliographic record
Abstract
Synopsis The research problem This study investigates whether the adoption of the International Financial Reporting Standard (IFRS) for small- and medium-sized entities (SMEs) is linked to national culture. Motivation or theoretical reasoning Little is known about the role of cultural dimensions in explaining countries’ adoption of the IFRS for SMEs. Focusing on this topic could contribute to a better understanding of the adoption of the IFRS for SMEs and would enrich the international accounting literature. Conducting a specific empirical investigation into the IFRS for SMEs is motivated by the difference between the full IFRS and the IFRS for SMEs, by the inherent characteristics of SMEs, and by differences between the number of countries that adopted the full IFRS and those that have adopted the IFRS for SMEs. The test hypotheses We used Hofstede’s dimensions of national culture (Power Distance, Individualism, Masculinity, Uncertainty Avoidance, Long-term Orientation, and Indulgence) to capture a country’s culture. We expected that these six dimensions would play a crucial role in countries’ decision to adopt the IFRS for SMEs. Based on previous relevant studies, we developed a research hypothesis for each of the mentioned cultural dimensions. Target population We selected the 101 countries included in Hofstede’s study. For each country, we looked at the data available on the IFRS website to identify its position in relation to the IFRS for SMEs. The final sample included 97 countries. Adopted methodology After classifying countries in three groups (Non-Adopters, Voluntary Adopters, and Mandatory Adopters), we performed several statistical regressions with adoption of the IFRS for SMEs as the dependent variable and the cultural dimensions as the relevant independent variables. Analyses Among others, we used several logistic regressions to estimate the association between national culture and the use of the IFRS for SMEs. We initially performed a statistical estimation for each of the six dimensions of national culture. Then, we included all cultural dimensions simultaneously. Finally, we performed robustness tests by applying multinomial regressions and focusing on the group of full IFRS adopters. Findings Empirical results revealed that the adoption of the IFRS for SMEs was less likely in countries with the highest levels of individualism. This conclusion held for both Mandatory and Voluntary Adopters. In contrast, the other dimensions of national culture were not significant in explaining the adoption of the IFRS for SMEs by national accounting regulators.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".