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Record W2133323206 · doi:10.5539/ass.v11n3p135

Technology Adoption and Innovation of E-Government in Republic of Iraq

2014· article· en· W2133323206 on OpenAlexvenueno aff
Munadil K. Faaeq, Khaled Alqasa, Ebrahim Mohammed Al‐Matari

Bibliographic record

VenueAsian Social Science · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsnot available
Fundersnot available
KeywordsUnified theory of acceptance and use of technologyExpectancy theoryGovernment (linguistics)Social influenceContext (archaeology)BusinessE-GovernmentVariablesPublic relationsPsychologyMarketingSocial psychologyInformation and Communications TechnologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Electronic government (EG) refers to a computer application employed in government activities and operations,where both government and the public are enabled to interact and transact online. The practicability of EG hasnot been largely explored in the context of Iraq, owing to the conflicting activities it has been experiencing in thepast few years. Prior to EG adoption, variables have to be examined such as infrastructure, social factors,security, skills, users’ behavior etc. The present study aims at examining the related variables that couldpotentially bar the EG services adoption in Iraq with the help of the Unified Theory of Acceptance and Use ofTechnology (UTAUT). Three independent variables are examined namely effort expectancy, performanceexpectancy, and social influence – the influence of these variables on the EG services uses as the dependentvariable is examined. The study proposes a quantitative examination of the EG services usage behavior with datagathered from Iraq. The study findings are then 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.007
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.054
GPT teacher head0.362
Teacher spread0.308 · 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

Citations33
Published2014
Admission routes1
Has abstractyes

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