Construction of a Strategic Business Process Reengineering Model: Empirical Research on the After-sale Service Process of SH
Bibliographic record
Abstract
For the past decade, business process reengineering (BPR) has gradually evolved from a revolutionary principle, which provided enterprises with methods to eliminate problems, into a set of management approaches for enterprises to face unpredictable and uncontrollable circumstances. This study puts forward an integrated model, strategic business process reengineering model,, which focuses on analysis of the three stages of BPR, and explores how BPR develops into competitive advantage with strategic basic factors – positioning, unique activities, trade-offs and fit. The authors undertake SH, a famous Taiwanese brand of small appliance, for case study and analysis. The research results show that the process reengineering activities held after strategic positioning should be improved through unique activities and trade-offs, such as technology-oriented, cross-departmental labor integration and trade-offs, cross-departmental rotation and talent cultivation, and cross-organizational support for channel manufacturers in their training of technicians. During the activities, mutual fit would lead to a set of behavior system, where construction plays an essential role, as it is difficult to imitate in competitive advantage.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".