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Record W2028816642 · doi:10.1509/jmkr.37.1.125.18724

Are Consumer Survey Results Distorted? Systematic Impact of Behavioral Frequency and Duration on Survey Response Errors

2000· article· en· W2028816642 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Marketing Research · 2000
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDuration (music)EconometricsTelephone surveyStatisticsHomogeneousCall durationScale (ratio)Non-sampling errorSurvey data collectionPsychologyAudiologyMathematicsComputer scienceMarketingMedicineTelecommunicationsAcousticsGeographyBusiness

Abstract

fetched live from OpenAlex

Using a large-scale consumer database created by AT&T, the authors investigate how actual behavioral frequency and duration systematically affect the direction of errors in consumer survey responses. By analyzing errors in consumers' reports on their frequency of using long-distance telephone calls, letters, cards, and visits for personal communication, the authors demonstrate that high-frequency groups underreported their behavioral frequencies, whereas low-frequency groups overreported them. Similarly, the results show that consumers underestimate the duration of lengthy telephone conversations, whereas they overestimate the duration of short ones. Overall, the authors find that people tend to overestimate both frequency and duration. These compressive regressive effects toward the mean and overall upward bias for both frequency and duration estimations result in a distorted view of the market, which will be incorrectly perceived to be more homogeneous and larger than it really is.

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.

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)0.322
metaresearch head score (Gemma)0.193
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 score0.129
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.3220.193
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.376
GPT teacher head0.522
Teacher spread0.146 · 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