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Record W3015377966

Sustainable Competitiveness of Companies: It Is Difficult to Maintain, Easy to Lose

2019· article· en· W3015377966 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEconomics of Contemporary Russia · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsDiversification (marketing strategy)ReputationPhenomenonChinaBusinessIndustrial organizationMarket economyEconomic systemEconomicsMarketingPolitical science
DOInot available

Abstract

fetched live from OpenAlex

The loss of competitiveness by global companies that held leading positions in their industries and had significant core competencies for a very long time highlights a need for the analysis of such a phenomenon as long-term competitiveness. The aim of the research is to discover major causes of the loss of competitiveness. The goals include the detection of breaking points that force companies to remold their business activities aswell as the determination of factors that bring about the emergence of breaking points. The subject of sustainable competitiveness relates to both economics and management. That is why numerous theories including the neoclassical one, the institutional one etc. are applied to the study. The research methods include the case-study method as well as structural and comparative analysis. The study of 33 companies (from the USA, Canada, Germany, Sweden, China, South Korea and Japan) in five industries helps to reveal the most common breaking points as well as to determine and classify the internal and external factors that lead to them. The internal factors include crises of growth, diversification crises, innovation crises, reputation crises etc. The external ones include political, technological, economic and natural problems. The authors of the paper reach the conclusion that the loss of competitiveness by a company happens as a result of combined influence of internal and external factors.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.812
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.215
Teacher spread0.199 · 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