Proceedings of the International Scientific Conference "Far East Con" (ISCFEC 2020)

Employee Performance Assessment in a Large Enterprise

Authors
I Tarasova, N Asanova, O Avdeyuk
Corresponding Author
I Tarasova
Available Online 17 March 2020.
DOI
10.2991/aebmr.k.200312.259How to use a DOI?
Abstract

Employee performance assessment is a complex process which aims to identify the effectiveness of the staff’s daily activity and to provide information that will help in decision-making. In this article, employee performance is viewed as a complex structure which is comprised of four criteria groups (qualification, staff morale, productivity, discipline). In its turn, each criterion is comprised of sub-criteria. We have developed an adaptable assessment structure that can be easily adjusted to the specific nature of any enterprise. We have used a convolution method to combine criteria into a generalized parameter. We suggest a methodology for employee performance assessment as well as an automated program. The suggested convolution of the staff performance criteria can be used in the systems for optimization and decision-making.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the International Scientific Conference "Far East Con" (ISCFEC 2020)
Series
Advances in Economics, Business and Management Research
Publication Date
17 March 2020
ISBN
978-94-6252-929-8
ISSN
2352-5428
DOI
10.2991/aebmr.k.200312.259How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - I Tarasova
AU  - N Asanova
AU  - O Avdeyuk
PY  - 2020
DA  - 2020/03/17
TI  - Employee Performance Assessment in a Large Enterprise
BT  - Proceedings of the International Scientific Conference "Far East Con" (ISCFEC 2020)
PB  - Atlantis Press
SP  - 1859
EP  - 1864
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.200312.259
DO  - 10.2991/aebmr.k.200312.259
ID  - Tarasova2020
ER  -