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Record W2493621679 · doi:10.5539/mas.v10n9p263

Assessment of Modern Banking Services to Achieve and Realization of E-Commerce and Its Impact on the Profitability of Banks Listed on the Tehran Stock Exchange

2016· article· en· W2493621679 on OpenAlexvenueno aff
Sadeqh Mahmoodi, Hossein Naderi

Bibliographic record

VenueModern Applied Science · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexStock exchangeBusinessDescriptive statisticsPanel dataOrder (exchange)VariablesPearson product-moment correlation coefficientActuarial scienceFinanceEconometricsStatisticsEconomicsMathematics

Abstract

fetched live from OpenAlex

The aim of this study was to investigate new banking services in order to achieve and the realization of e-commerce and its impact on banks' profitability listed on the stock exchange. This study is an applied research and from the logic implementation is descriptive survey study and the relationship between variables is correlation. In this study, data collection is by using library and field method, according to research hypotheses simple two-variable linear regression model was used. In this study, panel data is used to estimate and analyze quantitative and analytical and descriptive models by using Spss software. Among 3,000 delegates, managers and employees eight banks listed on the Tehran Stock Exchange using cluster sampling of 300 randomly selected as a population, and has been done during the period 2014-2015.The results of Pearson correlation coefficient between the variables of new services banking and e-commerce and profitability is equal to (0.144), which indicates that new services bank has positive impact significant on the Tehran Stock Exchange in order to fulfill ecommerce and profitability of listed banks, which means that a variety of modern banking services and increasing their use not only further caused the fulfill of e-commerce, but also increased the profitability of banks and has a direct impact on the profitability of them.

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)0.000
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 score0.682
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.035
GPT teacher head0.283
Teacher spread0.248 · 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

Citations6
Published2016
Admission routes1
Has abstractyes

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