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Record W4386274179 · doi:10.33423/jabe.v25i3.6336

An Exploratory Examination of The Threshold Concepts in Strategic Management

2023· article· en· W4386274179 on OpenAlexvenueno aff
Geoffrey G. Bell, Linda Rochford

Bibliographic record

VenueJournal of Applied Business and Economics · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Marketing Education
Canadian institutionsnot available
Fundersnot available
KeywordsTransformative learningBalanced scorecardDiversification (marketing strategy)PerceptionCore (optical fiber)Corporate governanceExploratory researchField (mathematics)Knowledge managementPsychologyComputer scienceMathematics educationSociologyProcess managementBusinessMarketingManagementMathematicsPedagogyEconomics

Abstract

fetched live from OpenAlex

Threshold concepts are core concepts in a field that students find particularly troublesome to understand, often because they integrate what students previously believed were discrete concepts or because they span boundaries between concepts or fields. Consequently, they are often transformative in nature and irreversible once fully understood. Therefore, they should form the core of our pedagogy. Threshold concepts have yet to be identified in strategic management. In this exploratory study, we examine student perceptions to determine which strategy concepts are likely threshold and identify four candidates: vertical integration, corporate diversification, innovation, and governance. In addition, we identify three non-core concepts - PESTEL, global strategies, and the balanced scorecard – that possess threshold-like characteristics, suggesting we rethink their curricular value. Finally, we identify active learning strategies that help students understand threshold concepts: applying/using the concept, discussing it with peers, and exploring examples. Class time devoted to such learning activities facilitates students “crossing the threshold.”

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.026
GPT teacher head0.229
Teacher spread0.203 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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