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Record W2056370415 · doi:10.1016/s0272-6963(02)00022-0

Effective case research in operations management: a process perspective

2002· article· en· W2056370415 on OpenAlexaff
Ian Stuart, David McCutcheon, Robert Handfield, Ron McLachlin, Daniel Samson

Bibliographic record

VenueJournal of Operations Management · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPerspective (graphical)Process (computing)Computer scienceProcess managementManagement scienceOperations managementBusinessEngineering

Abstract

fetched live from OpenAlex

Abstract Despite many calls for case‐based operations management research, the successful publication rate of such articles in top‐tier journals has been less than stellar. A five step case‐based research and dissemination process is presented. Guidance is given to future researchers for each step in the process. In addition, areas of weakness are examined and discussed in detail. Future potential research questions in operations management considered to be appropriate for the case‐based method are highlighted.

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)0.112
metaresearch head score (Gemma)0.115
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.112
Threshold uncertainty score0.592

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1120.115
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0120.010
Science and technology studies0.0060.027
Scholarly communication0.0220.023
Open science0.0050.007
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0100.001

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 head0.066
GPT teacher head0.360
Teacher spread0.293 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1,026
Published2002
Admission routes1
Has abstractyes

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