The manager and the accounting information system in small companies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In very small organizations, the role of the manager in the choice and implementation of tools is predominant. In these entities, resources are scarce and accounting information systems are not very formalized. In this research work, we therefore sought to identify the typical profile of this manager and to understand his propensity to use accounting data. Several recent studies have highlighted the relevance of the concept of organizational bricolage to analyze the practices of small businesses. With this in mind, we have sought to explore the ways in which managers of small businesses use accounting information systems. For this, we opted for the qualitative research method based on semi-structured interviews with managers of small Tunisian companies. To conduct this study, we used a qualitative methodology. 36 companies were selected for study. The cross-site case study was favored because it maximizes generalization bias. Finally, the profile of the manager has an influence on the SIC and induces a type of MSE. The results of our research led to the conclusion that there are three types of small business leaders: survivalists, emerging and structured.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it