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Record W2160974611 · doi:10.5267/j.msl.2012.05.013

An empirical study on the relationship between effective organizational communication and the performance of central office staff

2012· article· en· W2160974611 on OpenAlexvenueno aff
Abbas Monavvarian

Bibliographic record

VenueManagement Science Letters · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsOrganizational performanceEmpirical researchBusinessKnowledge managementPsychologyComputer scienceMarketing

Abstract

fetched live from OpenAlex

Inter-organizational communication plays an important role in promoting strategic collaboration among firms. It can improve productivity and increases collaboration among employees. In this paper, we present an empirical study to measure the role of interorganizational communication on efficiency among administration employees who work for one the oldest banks in Iran, Bank Melli Iran. The study uses 380 full time employees who work for 28 different administration divisions of this bank. The survey uses a questionnaire consists of 19 questions about inter-organizational communication and 25 questions about efficiency of employees. The reliability of the survey has been approved using an initial survey and Cronbach alpha was calculated as 0.87, which is well above the minimum acceptable level. The result of our survey confirms there is a meaningful relationship between interorganizational communication and efficiency of all administration employees who work for this bank. There is also a meaningful relationship between age and efficiency and the maximum efficiency belongs to people aged 31 to 40. According to our survey, men have more interorganizational efficiency than women do. The result of our survey also confirms that positivism impacts more than other factors on efficiency. Among five effective factors, empathy has the most impact and responsiveness 6 efficiency dimensions.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.623

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.036
GPT teacher head0.289
Teacher spread0.253 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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