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Record W1573607008 · doi:10.2145/20080305

Porter’s model of generic competitive strategies

2008· article· en· W1573607008 on OpenAlex
Orges Ormanidhi, Omer Stringa

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRePEc: Research Papers in Economics · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCLARITYGeneralityPopularityCompetitive advantageComplementarity (molecular biology)EconomicsIndustrial organizationSimplicityMicroeconomicsNeoclassical economicsManagementEpistemology

Abstract

fetched live from OpenAlex

A firm's competitive behavior is an important topic for practitioners, theorists, and policy makers. Among the explanations of firms' behavior is Michael Porter's model. We have presented this model along with some alternative approaches: Structure-Conduct-Performance, the New Industrial Organization and Game Theory, the Resource-Based Perspective, and Market Process Economics. These approaches are discussed in terms of their relations, similarities, and differences relative to Porter's model. In our comparative discussion, we support the use of Porter's model to evaluate firms' competitive behavior. Our reasons for this support are this model's popularity, well-defined structure, feasibility, clarity, simplicity, generality, and its complementarity to two other main approaches. We find the Porter model to be a convenient approach to the firm's competitive advantage and strategy.Business Economics (2008) 43, 55–64; doi:10.2145/20080305

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.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.065
GPT teacher head0.277
Teacher spread0.213 · 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