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Record W1963917014 · doi:10.1108/00251740710745043

Strategizing through the capability lens: sources and outcomes of integration

2007· article· en· W1963917014 on OpenAlex

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

VenueManagement Decision · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsGRASPCompetitive advantageCoherence (philosophical gambling strategy)Computer scienceContext (archaeology)Consistency (knowledge bases)Process managementRisk analysis (engineering)Knowledge managementBusinessMarketingArtificial intelligence

Abstract

fetched live from OpenAlex

Purpose This paper aims to explore the concept of capabilities and where they come from as well as their impact on integration and performance. Design/methodology/approach The paper is presented in the form of a theoretical development and literature review. Findings This paper proposes a theory of capability development and discusses the conditions under which a capability is effective. In particular, for a capability to be effective both local and global coherence are required. But a capability effectiveness and coherence has an inverted U shape. It increases with coherence up to a certain threshold then decreases. As a result, the development of capability is a powerful integration mechanism that crosses levels and functions. Research limitations/implications This is a theoretical paper; the propositions offered have still to be empirically tested. Practical implications Opening up the capability black box might help managers better grasp how to develop and shape organizational capabilities that are deemed to contribute to competitive advantage (e.g. the pricing capability). First, capabilities are not to be equated with competitive advantage. They may lead to a competitive advantage only where the context is favorable. Thus consistency with the environment challenges is an important factor to watch. This suggests that managers should give attention to the relationships between what they perceive to be their capabilities and the nature of the challenges faced by the organization. Further this research might promote the development of tools to measure coherence within a context and manage appropriate levels of dissent to trigger the re‐shaping of existing capabilities or the emergence of new one. Originality/value The paper bridges highly theoretical questions with practical considerations.

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)0.002
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: none
Teacher disagreement score0.647
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.033
GPT teacher head0.279
Teacher spread0.246 · 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