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Improvement of the Service Quality Management System in Automobile Dealerships Using Dynamic Fuzzy Numbers Tools. / Kostikova, A. V.; Skiter, N. N.; Simonov, A. B.; Egorova, I. E.; Tarasova, I. A.

2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9271448 (2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаяРецензирование

Harvard

Kostikova, AV, Skiter, NN, Simonov, AB, Egorova, IE & Tarasova, IA 2020, Improvement of the Service Quality Management System in Automobile Dealerships Using Dynamic Fuzzy Numbers Tools. в 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020., 9271448, 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020, Institute of Electrical and Electronics Engineers Inc., 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020, Vladivostok, Российская Федерация, 6/10/20. https://doi.org/10.1109/FarEastCon50210.2020.9271448

APA

Kostikova, A. V., Skiter, N. N., Simonov, A. B., Egorova, I. E., & Tarasova, I. A. (2020). Improvement of the Service Quality Management System in Automobile Dealerships Using Dynamic Fuzzy Numbers Tools. в 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020 [9271448] (2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FarEastCon50210.2020.9271448

Vancouver

Kostikova AV, Skiter NN, Simonov AB, Egorova IE, Tarasova IA. Improvement of the Service Quality Management System in Automobile Dealerships Using Dynamic Fuzzy Numbers Tools. в 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9271448. (2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020). https://doi.org/10.1109/FarEastCon50210.2020.9271448

Author

Kostikova, A. V. ; Skiter, N. N. ; Simonov, A. B. ; Egorova, I. E. ; Tarasova, I. A. / Improvement of the Service Quality Management System in Automobile Dealerships Using Dynamic Fuzzy Numbers Tools. 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020. Institute of Electrical and Electronics Engineers Inc., 2020. (2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020).

BibTeX

@inproceedings{f1a04e971b5e40a2bfffb6d556970016,
title = "Improvement of the Service Quality Management System in Automobile Dealerships Using Dynamic Fuzzy Numbers Tools",
abstract = "The problem of providing high-quality service and a high level of service is relevant for enterprises in all fields of activity with an extensive customer base and a large number of competitors. The purpose of this article is to adapt the dynamic fuzzy modeling tool to solve the problem of evaluating and managing the quality of service in an automobile dealership. Based on the analysis of time changes in the values of various socio-economic factors we propose the concept of dynamic fuzzy sets and define an algorithm for constructing a dynamic membership function. Further, by forming five-level linguistic variables, we present a comprehensive methodology for evaluating service quality management. The article defines 23 rules for the desired service quality indicator formed on the basis of a combination of values of subjective and objective criteria. Finally, we demonstrate experimental work on calculating a comprehensive indicator of the quality of service of an automobile dealership to verify and justify the chosen approach.",
keywords = "dynamic fuzzy models, fuzzy inference system, linguistic variables, quality of service, rule base",
author = "Kostikova, {A. V.} and Skiter, {N. N.} and Simonov, {A. B.} and Egorova, {I. E.} and Tarasova, {I. A.}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020 ; Conference date: 06-10-2020 Through 09-10-2020",
year = "2020",
month = oct,
day = "6",
doi = "10.1109/FarEastCon50210.2020.9271448",
language = "English",
series = "2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020",
address = "United States",

}

RIS

TY - GEN

T1 - Improvement of the Service Quality Management System in Automobile Dealerships Using Dynamic Fuzzy Numbers Tools

AU - Kostikova, A. V.

AU - Skiter, N. N.

AU - Simonov, A. B.

AU - Egorova, I. E.

AU - Tarasova, I. A.

N1 - Publisher Copyright: © 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/10/6

Y1 - 2020/10/6

N2 - The problem of providing high-quality service and a high level of service is relevant for enterprises in all fields of activity with an extensive customer base and a large number of competitors. The purpose of this article is to adapt the dynamic fuzzy modeling tool to solve the problem of evaluating and managing the quality of service in an automobile dealership. Based on the analysis of time changes in the values of various socio-economic factors we propose the concept of dynamic fuzzy sets and define an algorithm for constructing a dynamic membership function. Further, by forming five-level linguistic variables, we present a comprehensive methodology for evaluating service quality management. The article defines 23 rules for the desired service quality indicator formed on the basis of a combination of values of subjective and objective criteria. Finally, we demonstrate experimental work on calculating a comprehensive indicator of the quality of service of an automobile dealership to verify and justify the chosen approach.

AB - The problem of providing high-quality service and a high level of service is relevant for enterprises in all fields of activity with an extensive customer base and a large number of competitors. The purpose of this article is to adapt the dynamic fuzzy modeling tool to solve the problem of evaluating and managing the quality of service in an automobile dealership. Based on the analysis of time changes in the values of various socio-economic factors we propose the concept of dynamic fuzzy sets and define an algorithm for constructing a dynamic membership function. Further, by forming five-level linguistic variables, we present a comprehensive methodology for evaluating service quality management. The article defines 23 rules for the desired service quality indicator formed on the basis of a combination of values of subjective and objective criteria. Finally, we demonstrate experimental work on calculating a comprehensive indicator of the quality of service of an automobile dealership to verify and justify the chosen approach.

KW - dynamic fuzzy models

KW - fuzzy inference system

KW - linguistic variables

KW - quality of service

KW - rule base

UR - http://www.scopus.com/inward/record.url?scp=85098917837&partnerID=8YFLogxK

U2 - 10.1109/FarEastCon50210.2020.9271448

DO - 10.1109/FarEastCon50210.2020.9271448

M3 - Conference contribution

AN - SCOPUS:85098917837

T3 - 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020

BT - 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020

Y2 - 6 October 2020 through 9 October 2020

ER -

ID: 73301237