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Record W2154374169 · doi:10.1177/014920630102700610

The resource-based view and marketing: The role of market-based assets in gaining competitive advantage

2001· article· en· W2154374169 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

VenueJournal of Management · 2001
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsCompetitive advantageShareholder valueMarketingBusinessResource-based viewContext (archaeology)Resource (disambiguation)Value propositionCore (optical fiber)Value (mathematics)Industrial organizationSet (abstract data type)Process managementComputer scienceShareholderCorporate governance

Abstract

fetched live from OpenAlex

This article posits a framework that shows how market-based assets and capabilities are leveraged via market-facing or core business processes to deliver superior customer value and competitive advantages. These value elements and competitive advantages can be leveraged to result in superior corporate performance and shareholder value and reinvested to nurture market-based assets and capabilities in the future. The article also illustrates how resource-based view (RBV) and marketing considerations in the context of generating and sustaining customer value can refine and extend each other’s traditional frames of analysis. Finally, the article posits a set of research directions designed to enable scholars to further advance the integration of RBV and marketing from both theory-driven practice management as well as a problem-driven theory development perspectives.

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)0.006
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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