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Record W2770399963 · doi:10.1139/cjfr-2017-0219

Firm-level competitiveness in the forest industries: review and research implications in the context of bioeconomy strategies

2017· article· en· W2770399963 on OpenAlex
Jaana Korhonen, Elias Hurmekoski, Eric Hansen, Anne Toppinen

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.

venuePublished in a venue whose home country is Canada.
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

VenueCanadian Journal of Forest Research · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioeconomy and Sustainability Development
Canadian institutionsnot available
FundersAcademy of Finland
KeywordsCompetitor analysisContext (archaeology)BusinessIndustrial organizationCompetitive advantageValue (mathematics)Economic geographyEconomicsMarketingGeography

Abstract

fetched live from OpenAlex

The operational environment of the forest sector is becoming more complex, and maintaining competitiveness has become increasingly complicated. At the industry or firm level, competitiveness is seen as the ability to perform better than competitors in terms of value creation over time. Relatively little is known about changes in firm-level competitiveness caused by the shifting dynamics of the competitive situation in the forest sector toward the bioeconomy. A systematic literature review is conducted to examine how competitiveness of the sector is analyzed at the firm level and what are seen as its most influential drivers. Furthermore, these findings are discussed in the context of the bioeconomy transition. The results show that strategies and firm characteristics related to innovation and differentiation provide the key for understanding competitiveness at the firm level. Literature focuses on describing the competitive dynamics between firms within an industry rather than across sectors, despite that substitution between materials as well as intersectoral R&D collaboration are strongly advocated by national and international bioeconomy strategies.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.209
GPT teacher head0.380
Teacher spread0.171 · 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