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Record W2170524052 · doi:10.3390/su2051431

Beyond Abundance: Self-Interest Motives for Sustainable Consumption in Relation to Product Perception and Preferences

2010· article· en· W2170524052 on OpenAlexafffund
Anne Marchand, Stuart Walker, Tim Cooper

Bibliographic record

VenueSustainability · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSustainable consumptionConsumption (sociology)IncentiveProduct (mathematics)PerceptionMarketingRelation (database)SustainabilityEmpirical researchWarrantSustainable developmentBusinessEnvironmental economicsProduction (economics)EconomicsMicroeconomicsPsychologySociologyPolitical scienceComputer scienceEcology

Abstract

fetched live from OpenAlex

This paper presents results of a study that examined the perceptions and preferences of identified “responsible, sustainable consumers” with respect to functional products. The study is part of a larger research program that looks at material cultures and product design in relation to sustainable production and consumption. Based on empirical data gathered from among citizens attempting to follow sustainable lifestyles, the authors reflect on how the adoption of sustainable consumption patterns can not only be motivated by altruistic and environmental considerations, but also, significantly, by perceived personal benefits, including an expected increase in personal well-being. These motivations, together with how they unfold into preferences for particular product characteristics, are discussed. The paper concludes that the understanding of such motives, along with their implications for the ways in which products and services are conceived and positioned, may warrant further research as it can represent a key incentive for change towards a more sustainable future.

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)0.007
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.254
Teacher spread0.241 · 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

Citations18
Published2010
Admission routes2
Has abstractyes

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