AN EXAMINATION FACTORS INFLUENCING THE INTENTION TO ADOPT INTERNET BANKING AMONG SMES IN YEMEN: USING AN EXTENSION OF THE TECHNOLOGY ACCEPTANCE MODEL (TAM)
Bibliographic record
Abstract
Although the wide adoption of Internet banking service in developed countries, its application is still low in developing countries like Yemen. Moreover, there is a dearth of empirical research on Internet banking services in Yemen and this makes it necessary to carry out research on adoption of Internet banking service. The purpose of this study is to examine and investigate the main factors which influence the adoption of Internet banking services by Small and Medium Enterprise (SME) managers or owners in Yemen. The research framework consists of seven latent variables, four exogenous variables and three endogenous variables. Out of 920 SME managers or owners located in Sana’a (capital city), 311 respondents (35% response rate) were eventually used to analyze the data using Structural Equation Modeling (SEM) to examine causal and mediating relationship between the latent variables. The results of the study indicate that usefulness and ease of use are significant and positive effect towards Internet banking services adoption (IBSA). It also reveals that ICT readiness, financial institution support and competitive pressure are significant and positive effect towards usefulness and ease of use. It is found that usefulness, ease of use and regulatory support are significant towards (Internet Banking Services Adoption (IBSA). It can be concluded that TAM is found to be a good and suitable underpinning theory to explain IBSA factors in Yemen by achievement of model goodness of fit for the GOF index. The study also discussed implications for Yemeni contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".