The Link between Business Process Management and Quality Management
Bibliographic record
Abstract
In an environment of intense globalization and digitalization, business organizations are increasingly faced with various challenges such as rising costs, strong competition, rapidly evolving technologies, increasingly demanding and whimsical consumers, and, in social terms, changing societal demands. It is within this context that the effectiveness and efficiency of the management of business organizations is actualized. The paper addresses the following fundamental questions regarding the scientific problem at the theoretical level: What is the place of Business Process Management (BPM) in the context of Quality Management (QM)? Should BPM be the axis of QM? There is a lack of interdisciplinary research on the link between Business Process Management and Quality Management, and this study aims to ground this link. Methods of the research are literature review and the critical analysis of the scientific sources on the issue. The findings show that there exists confusion, overlaps among different paradigms of QM and BPM. The BPM paradigm might be considered as an integral part of almost all essential quality management paradigms. BPM is like a horizontal area “crossing” different paradigms of quality management (e.g., TQM, SMS, Lean, Six Sigma). The conclusions drawn are useful for organizations that implement quality management systems. The integration of BPM into quality management systems and tools creates preconditions for the development of an effective and efficient organization.
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 | 0.023 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".