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Record W3159371427 · doi:10.1145/3462766.3462771

Understanding Customers' Continuance Intention

2021· article· en· W3159371427 on OpenAlexaff
Bangaly Kaba

Bibliographic record

VenueACM SIGMIS Database the DATABASE for Advances in Information Systems · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicTechnology Adoption and User Behaviour
Canadian institutionsAthabasca University
Fundersnot available
KeywordsContinuanceInformation and Communications TechnologyContext (archaeology)Structural equation modelingNormativeThe InternetInequalitySalientDigital divideKnowledge managementPsychologyBusinessMarketingSocial psychologyComputer sciencePolitical scienceWorld Wide WebGeographyMathematics

Abstract

fetched live from OpenAlex

The purpose of this study is to understand the difference between Internet users' continuing use behavior in the context of digital inequality. Data were collected through a survey of Internet users in the Ivory Coast. The structural equation modeling technique was used to test the research hypothesis. This study showed empirically that concern over information and communication technologies (ICT) access as an explanation for digital inequality should be toned down. This research suggests emphasizing alternative factors to explain Internet sustained use intention by underprivileged individuals, including normative beliefs. The results will help internet service providers, governments, and international aid agencies to better understand users' behaviors or reactions to ICT available to them. This understanding provides a foundational platform upon which viable and effective information technology-enabled solutions and policies can be conceptualized and implemented. This study is one of the few that integrate three salient beliefs to differentiate ICT use continuance intention in the context of digital inequality.

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)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.967
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.009
Open science0.0020.001
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 head0.193
GPT teacher head0.397
Teacher spread0.203 · 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 designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

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