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Record W2162528861 · doi:10.1093/wjaf/19.3.160

Consumer Willingness to Pay for a Naturally Decay-Resistant Wood Product

2004· article· en· W2162528861 on OpenAlexaff
Geoffrey H. Donovan, Hayley Hesseln

Bibliographic record

VenueWestern Journal of Applied Forestry · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsChromated copper arsenateWillingness to payContingent valuationBusinessPublicityProduct (mathematics)Agricultural economicsPulp and paper industryPreservativeMarketingEconomicsEngineeringChemistryMathematics

Abstract

fetched live from OpenAlex

Abstract Chromated copper arsenate (CCA) is the most widely used chemical wood preservative in the United States. Concerns about the safety of CCA led to an agreement between the Environmental Protection Agency and the wood treatment industry to withdraw CCA for nonindustrial uses by the end of 2003. In light of the publicity surrounding the withdrawal of CCA, this article evaluates consumers' willingness to pay a premium for products manufactured from naturally decay-resistant wood as opposed to chemically treated wood. We use a national contingent valuation survey to quantify consumer willingness to pay for a children's play structure made from Alaska yellow-cedar, as opposed to an identical play structure made from southern pine treated with ammonial copper quaternary, the likely replacement for CCA. Respondents' estimated mean willingness to pay for the Alaska yellow-cedar play structure is $2,013, compared to $1,000 for the treated southern pine structure. This study shows that manufacturers of products made from naturally decay-resistant wood may be able to capture a substantial premium for their products. West. J. Appl. For. 19(3):160–164.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.044
GPT teacher head0.222
Teacher spread0.179 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2004
Admission routes1
Has abstractyes

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