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Record W2415874771 · doi:10.1108/md-01-2015-0001

Measuring the actionability of evidence for evidence-based management

2016· article· en· W2415874771 on OpenAlexaff
Farimah HakemZadeh, Vishwanath V. Baba

Bibliographic record

VenueManagement Decision · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsVarimax rotationFormative assessmentPsychologyIndex (typography)Metric (unit)Relevance (law)Variance (accounting)Knowledge managementComputer sciencePsychometricsCronbach's alphaMarketingBusinessPolitical science

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to address the gap between management research and management practice by suggesting that, in addition to rigor and relevance, management knowledge should be actionable to be of practical value. To this end, an index for evaluating actionability is proposed and empirically tested. Design/methodology/approach – Based on reflective and formative conceptualizations of actionability and a critical review of both evidence-based management (EBMgt) and evidence-based medicine literature, the authors developed 40 items that would best represent attributes of actionable research. The authors asked 187 management scholars, members of the editorial boards of influential management journals, and practicing managers to rank the extent to which each item was important to their perceptions of research to be actionable in practice. The authors treated actionability as a two-level construct consisting of first-order reflective factors and second-order formative ones. Findings – Using principal component analysis with varimax rotation six factors were extracted, explaining 68 percent of variance in actionability: operationality, which also included items from causality; contextuality; comprehensiveness; persuasiveness, which split into two dimensions of rigor and unbiasedness; and lastly comprehensibility. Using partial least squares analysis, the authors demonstrated that these six factors formatively contribute to an overall index of actionability of management research. Research limitations/implications – The index offers an empirical measure to advance research on EBMgt by facilitating theory testing in different management contexts. Practical implications – The developed index promotes EBMgt by providing producers, disseminators, and users of management knowledge with a metric to appraise actionability of management knowledge. Originality/value – This index is the first theory-based and empirically tested tool for effectively evaluating the practical value of management research.

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 imitation

Not 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.

metaresearch head score (Codex)0.469
metaresearch head score (Gemma)0.771
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.655

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4690.771
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0260.011
Science and technology studies0.0030.008
Scholarly communication0.0150.015
Open science0.0030.010
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0020.000

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 head0.196
GPT teacher head0.309
Teacher spread0.113 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
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

Citations19
Published2016
Admission routes1
Has abstractyes

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