Implementing Modeling Techniques to Formulate a Strategy for Organizational Change Management in Enterprises' Sustainable Development Systems
Bibliographic record
Abstract
The primary aim of this article is to graphically construct change management strategies within the system of enterprise sustainable development.The study focuses on the sustainable development system of an enterprise.The scientific task is the implementation of a new methodological approach to building strategies for managing changes in sustainable development system of enterprise.The research methods involve the use of technologies for constructing two variants of IDEF3 strategies.The IDEF3 method was utilized to capture descriptions of action sequences, enabling a specialist to construct change management strategies within the enterprise's sustainable development system.As a result, two unique examples of change management strategies in enterprise sustainable development system were presented.Consequently, we formed process-oriented and object-oriented strategies for managing changes in the machine-building enterprise's sustainable development system.These strategies allow for the inclusion of all elements of the enterprise's sustainable development in strategy formation.The implications of the study are the formation of a specific methodological approach to the presentation of the strategy for managing changes in the system of sustainable development of an enterprise.The study is limited as it only takes into account the specifics of the sustainable development system within an engineering enterprise.Prospects for further research should be devoted to the analysis of the change management system in the framework of security.The practical value of the results obtained lies in the possibility of using strategy models for top managers.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".