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Record W4306967679 · doi:10.1108/cr-03-2022-0045

The comparative advantages in the wooden furniture industry: does the export price matter?

2022· article· en· W4306967679 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

VenueCompetitiveness Review An International Business Journal incorporating Journal of Global Competitiveness · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsComparative advantageRevealed comparative advantageCompetition (biology)Competitive advantageIndustrial organizationIndex (typography)Government (linguistics)BusinessEconomicsInternational tradeMarketingComputer science

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to evaluate the global competitiveness of the top ten wooden furniture exporting countries with several approaches and to test the effect of export prices (EXPRs) on the global competition. Design/methodology/approach Countries' competitiveness levels were measured with revealed comparative advantage (RCA), normalised RCA (NRCA), revealed symmetric comparative advantage (RSCA) and trade balance index. Furthermore, panel regression analysis techniques were used to test the effects of EXPR on RCA, NRCA and RSCA in the wooden furniture industry (WFI). Findings Although the comparative advantage approaches give different results, the global competitiveness of Poland and Vietnam is at a high level in all approaches. Canada has been the country with the weakest global competitiveness in all approaches. According to the results of the analysis, EXPRs positively affect all the competitive advantage indexes. As a result, the competitiveness of the WFI is affected by the non-price factors instead of the EXPR. Research limitations/implications The framework allows us to measure and illustrate the export competitiveness of the WFI and permits a global comparison. Similar analyses can be made for different labour-intensive sectors. In addition, analysis can be made to identify non-price factors for the WFI sector. Thus, more specific inferences can be made. Practical implications This study is useful for policymakers, government officials, the industry associations and the company executives to assess their export competitiveness in the WFI. Thus, they can determine whether to shift scarce resources to this industry or other industries. In addition, this study may affect the price competition policy of the sector representatives in the global market. Originality/value This study deals with the competitiveness of the WFI with different approaches. And this study determines the importance of price for global competition in this sector.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0030.001
Scholarly communication0.0020.003
Open science0.0050.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.302
Teacher spread0.273 · 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