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Record W4376869472 · doi:10.18280/isi.280209

The Effect of Motivating and Inhibitory Factors on Using the Electronic Commerce by Adopting UTAUT2 and SQB Models

2023· article· en· W4376869472 on OpenAlexvenueno aff
Dena Maan Ezzulddin Alsabbagh, Noor Dheyaa Azeez

Bibliographic record

VenueIngénierie des systèmes d information · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsInhibitory postsynaptic potentialOrder (exchange)PsychologyBusinessNeuroscience

Abstract

fetched live from OpenAlex

E-commerce is the practice of using information technology to do business online.Developing nations have not yet completely adapted to the use of e-commerce, despite wealthy countries having embraced and utilized it.To provide a framework that illustrates the influencing elements (enabling factors and discouraging factors) of e-commerce, this research aims to analyze the key variables that influence e-commerce adoption from the viewpoint of the two-factor theory.The Unified Expanded Technology Acceptance Theory (UTAUT2) components and the Status Quo Bias Theory (SQB) factors were both incorporated into the suggested model in this research.487 individuals were given a questionnaire to complete to gather data.The study's findings demonstrated that behavioral intention is favorably and substantially influenced by performance expectations, price value, effort expectations, and confidence.Therefore, the present research concluded that it is important to look at the enabling and inhibiting elements that affect e-commerce intention and adoption.Additionally, the last portion will cover the future directions for the research.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.620
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.052
GPT teacher head0.317
Teacher spread0.265 · 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 designSimulation or modeling
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

Citations5
Published2023
Admission routes1
Has abstractyes

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