Internet Banking in Emergency MarketsThe Case of Jordon - A Note
Bibliographic record
Abstract
The goal of this paper is to replicate the Diniz (1998) survey using the case of Jordan as an example of an emerging market. The Diniz framework was developed in order to learn about Web banking models and their adoption in the United States. The findings clearly indicate a gap between Jordanian bank web application and American bank web application. In a more general framework we can extrapolate this commentary to the gap between web usage in developing and developed countries. Kurtas (2000) found that American banks use their web sites not only to provide classical operations such as fund transfer or account details, but also to provide stock trading in the world markets, financial calculators, investment advice, and bill payments. American bank are now using very high technology in encryption in order to provide safety and privacy. They have reached a stage where a number of banks are operating entirely via web without any need for physical location. On the other hand, very limited evidence of web usage at this level was found among Jordanian banks. Both American and Jordanian banking industries do however exhibit weaknesses in the advanced levels of all web opportunities, particularly with regards to customer relationships. Our preliminary results indicate that Jordanian banks have been successful in the introductory phase of web banking. What is now required is to focus on moving Jordanian web banking usage forward with a view to conducting real financial transactions and improving electronic customer relations. This objective can be generalized to banks in developing economies who can no longer ignore the internet as a strategic weapon and distribution channel for their services.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".