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Record W2325172568 · doi:10.5539/ijms.v8n2p147

Internal Marketing: Employee Satisfaction and Word of Mouth in Guilan’s Saderat Bank

2016· article· en· W2325172568 on OpenAlexvenueno aff
Maryam Haghighikhah, Mahdieh Khadang, Masoud Arabi

Bibliographic record

VenueInternational Journal of Marketing Studies · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsInternal marketingMarketingStructural equation modelingVariance (accounting)BusinessWord of mouthEmpowermentBanking industryBusiness administrationEconomicsMathematicsStatisticsFinanceAccounting

Abstract

fetched live from OpenAlex

<p>Internal marketing is too important for all organizations and it’s especially critical for a people intensive industry such as banking. This paper examines the effects of internal marketing on satisfaction of employees and employee’s word of mouth. Dimensions of internal marketing, which were studied are training, supervisory support, empowerment, communication and compensation. The study has been done in Saderat Bank of Iran in Gulian and we used the technique of Structural Equation Modeling to provide a model. The analytical results demonstrate that approximately 88% of the variance Satisfaction (R<sup>2</sup> = 0.88) is explained by Internal marketing and approximately, 82% of the variance word of mouth (R<sup>2</sup> = 0.82) is explained by Satisfaction and Internal marketing.</p>

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.031
GPT teacher head0.295
Teacher spread0.264 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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