Sustaining Growth or Boosting Profit: Accounting Tools under Process-Based Management in a Transition Economy
Bibliographic record
Abstract
Over the past three decades, economic transformations in Eastern Europe and Russia have substantially affected the use of management technologies. More and more businesses prioritize sustaining growth and development in the long run instead of maximizing profits in the short term. The shift in the business paradigm requires the implementation of new management tools along with the improvement of management accounting. Through the example of seven Russian boiler manufacturers, this study examines the main reasons for the transition to process-based management. The study identifies patterns of using management accounting tools in process-based management by employing the literature analysis, conducting an expert survey, and studying the accounting documents of selected companies. The authors analyze features of management accounting tools at different stages of implementation of the process-based management system, in enterprises with different life cycles and different sizes. A total of 53 employees were surveyed, which included senior managers, accountants, and middle-level managers. It is found that the main reason for the transition to process-based management is a shift in the focus of managers’ attention from cutting costs to creating value. By adding new features of business process classification, developing new classification groups, and proposing the optimal structure of the core, auxiliary, and controlling business processes, this study contributes to the optimization of management accounting when organizational change requires implementing process-based management.
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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 | 0.002 | 0.005 |
| 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 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".