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Record W2581062728 · doi:10.5430/ijba.v8n1p106

Performance Evaluation and Measurement in Public Organizations: A Systematic Literature Review

2016· article· en· W2581062728 on OpenAlexvenueno aff
Orlando Troisi, Carlo Torre, Gennaro Maione

Bibliographic record

VenueInternational Journal of Business Administration · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsnot available
Fundersnot available
KeywordsOrder (exchange)Work (physics)Empirical researchPerformance measurementGeneralizationComputer scienceManagement scienceCompetitive advantageKnowledge managementPublic relationsBusinessMarketingEconomicsPolitical scienceEngineering

Abstract

fetched live from OpenAlex

The turbulence of the current competitive environment emphasizes the importance of the role played by performance measurement systems in generating an improvement of business results. Starting from this consideration, the work pursues a twofold goal: firstly, it tries to verify the existence and the degree of a research interest about this topic; secondly, it seeks to identify, in measurement and evaluation systems, which factors are capable of producing an effect on performances of public organizations. In order to well respond to the research purposes, the work begins with a systematic literature review, which highlights a growing attention of scholars on all those variables considered critical in conducting and managing public organizations. The study, highlighting the existence of six variables to be advantageously taken into account in managing public organizations, especially in light of the potential influence that they seem to exert on different types of business performances, could be considered as a useful tool for both practitioners (managers of public organizations) and scholars (professors, researchers, students, etc.) aimed at helping to become aware about the advantages arising from an adequate management of performances measures. The main research limitation is the lack of an empirical analysis of public companies performance plans, which should be thoroughly examined to allow a possible further generalization of the theoretical findings achieved.

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)0.005
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.645
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.085
GPT teacher head0.393
Teacher spread0.309 · 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.

Study designSystematic review
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

Citations11
Published2016
Admission routes1
Has abstractyes

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