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Record W3001153224 · doi:10.1177/2051570719891037

The destiny of replaced technological products: The influence of perceived residual value

2020· article· en· W3001153224 on OpenAlexaff
Dominique Kréziak, Isabelle Prim‐Allaz, Élisabeth Robinot

Bibliographic record

VenueRecherche et Applications en Marketing (English Edition) · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsDestiny (ISS module)Product (mathematics)Possession (linguistics)PopulationValue (mathematics)DispositionSample (material)Perspective (graphical)BusinessMarketingPsychologyEngineeringSocial psychologyStatisticsComputer scienceMathematicsMedicineEnvironmental healthChemistry

Abstract

fetched live from OpenAlex

Technological products are being replaced at an increased rate, inducing the disposition of still functioning devices and generating a growing flow of electronic waste. Following the perspective of the circular economy, this research uses perceived residual value (PRV) to shed new light on the destiny of replaced products. Considering simultaneously consumers’ evaluation of a product in a specific situation, PRV is the value consumers ascribe to post-use possession. A measurement tool of PRV is developed and used to measure its effects on a sample of 1,302 respondents representative of the French population. Results show that the three dimensions of PRV (utilitarian, financial, and affective) influence whether or not a replaced technological product is kept. PRV has a major impact on disposition channels when the replaced product is not kept. These results lead to managerial recommendations, as PRV can be used to foster product recirculation and contribute to reducing the wastage of natural resources.

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 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)0.012
metaresearch head score (Gemma)0.063
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.063
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.039
GPT teacher head0.278
Teacher spread0.239 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations6
Published2020
Admission routes1
Has abstractyes

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