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Record W2253350919 · doi:10.5539/mas.v10n4p21

Investigating Online Consumer Behavior in Iran Based on the Theory of Planned Behavior

2016· article· en· W2253350919 on OpenAlexvenueno aff
Ramin Bagherzadeh, Rohullah Bayat

Bibliographic record

VenueModern Applied Science · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsTheory of planned behaviorStructural equation modelingDescriptive statisticsPurchasingTechnology acceptance modelControllabilityVariance (accounting)PsychologySample (material)Sample size determinationSimple random sampleSocial psychologyStatisticsMarketingApplied psychologyComputer scienceUsabilityMathematicsBusinessDemographyArtificial intelligenceControl (management)Sociology

Abstract

fetched live from OpenAlex

The aim of this research is to study the online consumer behavior in Iran using a combination of Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) with other variables. This study is objective, analytical, and descriptive. The subject of this research is online shoppers in the city of Shiraz. Sampling was simple random and was collected via the Internet. According to the conceptual model, the minimum required sample for this study was 80 samples; however, to ensure accuracy 390 questionnaires were collected. To analyze the data, structural equation modeling was used, using partial least squares (PLS) and analysis of one way variance (ANOVA). Results show that in online purchasing in Iran perceived ease of use (PEOU) has a positive effect on controllability and self-efficacy of individuals. Trust has a positive effect on the attitude and controllability of individuals. Media has a positive effect on subjective norms. Cost reduction has a positive effect on the attitude of individuals. Finally, age and income influence the intention of individuals in online purchasing. The other hypotheses of this study were not confirmed. It can be concluded that factors such as PEOU, trust, media, cost reduction, age and income affect online consumer behavior in Iran.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.158
GPT teacher head0.365
Teacher spread0.207 · 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.

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

Citations3
Published2016
Admission routes1
Has abstractyes

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