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Record W2164208465 · doi:10.5539/ibr.v5n3p2

The Effect of Peer Communication Influence on the Development of Materialistic Values among Young Urban Adult Consumers

2012· article· en· W2164208465 on OpenAlexvenueno aff
Eric Bindah, Md. Nor Othman

Bibliographic record

VenueInternational Business Research · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaMaterialismPsychologyConstruct (python library)Internal consistencySocial psychologyDemographyDevelopmental psychologySociologyPsychometricsTheology

Abstract

fetched live from OpenAlex

The study attempts to uncover the characteristics of materialism groups in Malaysia among young adult consumers. It assesses the differences between materialism groups, i.e., low and high materialistic groups, using demographic and peer communication dimensions. The data was collected through self-administered questionnaires. The sample consisted of 956 respondents. The majority of the respondents were Malays followed by Chinese and Indians. The proportion of female respondents was higher than the male respondents. Most of the respondents were single and in the age group of between 19-29 years old. Independent sample t-tests were used to compare mean scores for the study variables between ‘high’ materialism and ‘low’ materialism groups and significant mean differences were found between ‘high’ and ‘low’ materialism groups in terms of peer communication construct. Specifically, it was found that the ‘high’ materialism group has considerably greater ratings on the construct. Internal consistency reliability assessment using Cronbach coefficient alpha revealed that the two dimensions had high reliability. A stepwise discriminant analysis performed on peer communication variable found that peer communication variable was significant in differentiating the two materialism groups. The implications, significance and limitations of the study are discussed.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.017
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.347
Teacher spread0.294 · 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.

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

Citations11
Published2012
Admission routes1
Has abstractyes

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