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Record W2169880791 · doi:10.5267/j.msl.2012.06.014

Theoretical construct of strategic control systems

2012· article· en· W2169880791 on OpenAlexvenueno aff
Zulnaidi Yaacob

Bibliographic record

VenueManagement Science Letters · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsnot available
Fundersnot available
KeywordsConstruct (python library)Process managementControl (management)Computer scienceConstruct validityProcess (computing)Quality (philosophy)Strategic planningResource (disambiguation)Measure (data warehouse)Management scienceKnowledge managementRisk analysis (engineering)Operations managementBusinessMarketingEngineeringData miningArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents the development of an instrument for measuring strategic control systems (SCS). Although SCS has received considerable attention in the literature, most of the discussions, on the elements that constitute SCS, are limited to descriptive statements. Thus, the theoretical construct of SCS suffers from lack of extensive statistical validation procedures. However, there are a few authors that had initiated the development of an instrument to measure the SCS. Their small effort had also been criticized due to the inconsistency among authors in defining SCS, which would likely affect the validity of the instrument being developed. Given this lacuna, this paper has developed and validated an instrument for conceptualizing SCS, specifically under the environment of Quality Management strategy. Based on a careful and systematic process of instrument development, this paper revealed that SCS consists of two important dimensions, namely strategy implementation and strategic resource allocation. In developing this instrument, a total number of 205 respondents were involved. The findings reported in this paper would benefit future researchers in measuring SCS, particularly for survey-based 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 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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.011
GPT teacher head0.204
Teacher spread0.192 · 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 designTheoretical or conceptual
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

Citations3
Published2012
Admission routes1
Has abstractyes

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