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Record W2107461833 · doi:10.1086/513048

Explaining Cognitive Lock-In: The Role of Skill-Based Habits of Use in Consumer Choice

2007· article· en· W2107461833 on OpenAlexaff
Kyle B. Murray, Gerald Häubl

Bibliographic record

VenueJournal of Consumer Research · 2007
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsProduct (mathematics)Consumption (sociology)PreferenceConsumer choiceCognitionCognitive psychologyNew product developmentPsychologyComputer scienceMicroeconomicsMarketingEconomicsBusinessMathematics

Abstract

fetched live from OpenAlex

We introduce and test a theory of how the choices consumers make are influenced by skill-based habits of use—goal-activated automated behaviors that develop through the repeated consumption or use of a particular product. Such habits can explain how consumers become locked in to an incumbent product. The proposed theory characterizes how the amount of experience with the incumbent product, the occurrence of usage errors while learning to use that product, and the goal that is activated at the time a choice is made interrelate to influence consumer preference. The results of three experiments support the theory's predictions.

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)0.032
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0320.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.315
GPT teacher head0.515
Teacher spread0.200 · 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; both teacher heads agree on what is shown here.

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

Citations26
Published2007
Admission routes1
Has abstractyes

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