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Record W129871017

Communication about Planned Obsolescence as an Atypical Two-sided Message

2012· article· en· W129871017 on OpenAlexaff
Frank Goethals, Shamel Addas, Isabelle Fagnot

Bibliographic record

VenueJournal of the Association for Information Systems · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsMcGill University
Fundersnot available
KeywordsObsolescenceFriendshipMarketingPsychologyBusinessAdvertisingInternet privacyComputer scienceSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

While many information technology vendors deliberately cut their products’ lifecycles to elicit repeat purchases, consumers are often unaware of such planned obsolescence. This paper investigates the effects of atypical two-sided communication about planned obsolescence on consumers’ beliefs and buying intentions. Drawing upon insights from inoculation theory, we hypothesize that trust and intent to buy initially decrease after individuals are exposed to communication about planned obsolescence, but that they partly bounce back after some time during which the inoculated individuals get a chance to discuss and practice counter-arguing the two-sided message. Through a repeated measures survey design, we confirm the study’s main hypotheses. We also show that the drop in intent to buy depends on gender, the importance given to friendship, and the weighted average decrease in friends’ intent to buy.

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)0.006
metaresearch head score (Gemma)0.047
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 score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.002
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 head0.026
GPT teacher head0.283
Teacher spread0.257 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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