Standard

Two-Factor DEA Modeling and Clustering of Homogeneous Firms. / Bure, V. M.; Parilina, E. M.; Staroverova, K. Yu.

в: Automation and Remote Control, Том 82, № 5, 05.2021, стр. 877-888.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Bure, VM, Parilina, EM & Staroverova, KY 2021, 'Two-Factor DEA Modeling and Clustering of Homogeneous Firms', Automation and Remote Control, Том. 82, № 5, стр. 877-888. https://doi.org/10.1134/s0005117921050118

APA

Bure, V. M., Parilina, E. M., & Staroverova, K. Y. (2021). Two-Factor DEA Modeling and Clustering of Homogeneous Firms. Automation and Remote Control, 82(5), 877-888. https://doi.org/10.1134/s0005117921050118

Vancouver

Bure VM, Parilina EM, Staroverova KY. Two-Factor DEA Modeling and Clustering of Homogeneous Firms. Automation and Remote Control. 2021 Май;82(5):877-888. https://doi.org/10.1134/s0005117921050118

Author

Bure, V. M. ; Parilina, E. M. ; Staroverova, K. Yu. / Two-Factor DEA Modeling and Clustering of Homogeneous Firms. в: Automation and Remote Control. 2021 ; Том 82, № 5. стр. 877-888.

BibTeX

@article{093c5f337fa442fb8bf36a06827423fe,
title = "Two-Factor DEA Modeling and Clustering of Homogeneous Firms",
abstract = "Abstract: The paper presents a model for clustering homogeneous firms according to their operationefficiency over a certain time period. The firm efficiency is studied by the Data EnvelopmentAnalysis (DEA) methodology, which is based on solving optimization problems and permits one tocompare firms taking into account many factors of their operation. At the second step of theanalysis, the time series of firm efficiency estimators obtained by DEA modeling are used tocluster firms and find stable partitions of the set of firms.",
keywords = "DEA modeling, firm efficiency analysis, time series clustering",
author = "Bure, {V. M.} and Parilina, {E. M.} and Staroverova, {K. Yu}",
note = "Publisher Copyright: {\textcopyright} 2021, Pleiades Publishing, Ltd. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",
year = "2021",
month = may,
doi = "10.1134/s0005117921050118",
language = "English",
volume = "82",
pages = "877--888",
journal = "Automation and Remote Control",
issn = "0005-1179",
publisher = "МАИК {"}Наука/Интерпериодика{"}",
number = "5",

}

RIS

TY - JOUR

T1 - Two-Factor DEA Modeling and Clustering of Homogeneous Firms

AU - Bure, V. M.

AU - Parilina, E. M.

AU - Staroverova, K. Yu

N1 - Publisher Copyright: © 2021, Pleiades Publishing, Ltd. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/5

Y1 - 2021/5

N2 - Abstract: The paper presents a model for clustering homogeneous firms according to their operationefficiency over a certain time period. The firm efficiency is studied by the Data EnvelopmentAnalysis (DEA) methodology, which is based on solving optimization problems and permits one tocompare firms taking into account many factors of their operation. At the second step of theanalysis, the time series of firm efficiency estimators obtained by DEA modeling are used tocluster firms and find stable partitions of the set of firms.

AB - Abstract: The paper presents a model for clustering homogeneous firms according to their operationefficiency over a certain time period. The firm efficiency is studied by the Data EnvelopmentAnalysis (DEA) methodology, which is based on solving optimization problems and permits one tocompare firms taking into account many factors of their operation. At the second step of theanalysis, the time series of firm efficiency estimators obtained by DEA modeling are used tocluster firms and find stable partitions of the set of firms.

KW - DEA modeling

KW - firm efficiency analysis

KW - time series clustering

UR - http://www.scopus.com/inward/record.url?scp=85107721012&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/6feef9ff-c16e-39f2-841c-13e7756a3172/

U2 - 10.1134/s0005117921050118

DO - 10.1134/s0005117921050118

M3 - Article

AN - SCOPUS:85107721012

VL - 82

SP - 877

EP - 888

JO - Automation and Remote Control

JF - Automation and Remote Control

SN - 0005-1179

IS - 5

ER -

ID: 77945334