arbiter
JournalsPricingAccount

Assessing the relationship between occupational stressors and accountants performance and burnout: a neural network approach with extreme learning machine

Abdulah Kürsat Merter et al.

Global Business and Economics Review2026https://doi.org/10.1504/gber.2027.10077293article
AJG 1ABDC C
Weight
0.50

What the paper says

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1504/gber.2027.10077293

Or copy a formatted citation

@article{abdulah2026,
  title        = {{Assessing the relationship between occupational stressors and accountants performance and burnout: a neural network approach with extreme learning machine}},
  author       = {Abdulah Kürsat Merter et al.},
  journal      = {Global Business and Economics Review},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1504/gber.2027.10077293},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Assessing the relationship between occupational stressors and accountants performance and burnout: a neural network approach with extreme learning machine

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.