A survey on existing challenges of BSC implementation for performance measurement
Bibliographic record
Abstract
The balanced scorecard (BSC) is a strategic oriented tool used comprehensively in profit and nonprofit organizations all over the world to synchronize routine processes of organizations to the mission and strategy, improve inner and outter communications, control organization performance toward strategic targets.BSC has emerged from a simple performance measurement framework to a comprehensive strategic management system.It changes an organization's strategic plan from a passive document to an active guideline for the organization on a daily basis and provides a helpful assistance that not only enables performance measurements, but also helps planners identify what should be accomplished and measured.This study focuses on how BSC is adopted as a tool for measuring effectiveness of strategy implementation in these organizations.This study adapts the BSC as a powerful tool for reaching an organization's performance in four significant areas: Financial perspective, Customer-Market perspective, Internal Processes perspective and Learning & Growth perspective.The results suggest that governmental organizations are somehow successful in achieving their objectives in various degrees.
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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 | 0.143 | 0.263 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.022 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".