Image Factors Which Determine the Choice of the Bank
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study of priorities of the bank image scientific researches make it possible to consider that there is the lack of the bank image scientific researches. The main reason is that there are not concrete proposals regarding factors which can be used for the bank image evaluation. The priority is allocated to researches of industry and trade enterprises image, because those enterprises are working with tangible products. Thus it is more easier to study the image of such enterprises. Also there is the lack of researches. These considerations let prepare recommendations regarding the position the competitive bank should cover. Basing on these propositions the problem is formulated- what are the main image factors determining the competitiveness of the bank? The objective of this article is to name factors of the competitive bank image, determining the choice of the bank. Findings will be based on survey of empirical researches of banks’ image results in foreign countries and in Lithuania. Scientists discuss the factors which are containing the image of the bank, which of them are the main and becoming determinants in choosing the bank. There is no one opinion on this question. Determinants-components of the bank image and their weightiness are mostly based on researches that have been done in foreign countries. Thus the main problem that is arising in evaluation of the concrete bank position in the market is the factors of the bank evaluation. For example, Swedish scientists have excluded 5 factors, which are used in the bank evaluation, i.e. services quality, facilities of credit receiving, distribution system, promotion, reputation and differentiation. Canadian scientists have presented even 19 factors: reputation, recommendations of other people, interesting advertising, the convenience of the place, working hours, help of personnel, friendliness, etc. Danish scientists have looked at this problem more narrowly and have estimated factors, that are important only for business clients of the bank. According them, there are 9 main factors: connections, price policy, quality, rating, technology, the net of the subdivisions, commitment and compensation of other services. The main difference of earlier made researches is that business clients prefer the quality of services more than the bank reputation. USA scientists have presented the reduced list of factors, containing 5 search factors, 7 experience factors and 5 confidence factors that are the main for bank clients. Conclusions of accomplished research in Lithuania have identified that desirable characteristics of Lithuanian banks’ image are confidentiality of clients data, respectability of the bank, technical facilities of the bank, the bank management and the bank competence in the market.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it