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Record W2164106225 · doi:10.5267/j.msl.2014.2.016

A survey on existing challenges of BSC implementation for performance measurement

2014· article· en· W2164106225 on OpenAlexvenueno aff
Behdad Gitinejad, Mohammad Ali Keramati

Bibliographic record

VenueManagement Science Letters · 2014
Typearticle
Languageen
FieldPsychology
TopicOutdoor and Experiential Education
Canadian institutionsnot available
Fundersnot available
KeywordsBalanced scorecardProcess managementPerformance measurementStrategic planningStrategy implementationStrategy mapPerspective (graphical)Computer scienceControl (management)Knowledge managementBusinessStrategic managementPerformance managementStrategic alignmentMarketingStrategic financial management

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.132
GPT teacher head0.392
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2014
Admission routes1
Has abstractyes

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