Публікація: Assessment of logistics service quality based on the application of fuzzy methods modeling
Завантаження...
Дата
2022
Назва журналу
ISSN журналу
Назва тома
Видавництво
Problems and Perspectives in Management
Анотація
Improving the logistics service quality (LSQ) requires its assessment to identify appropriate reserves, which actualizes the scientific task of improving the appropriate methodological support for LSQ assessment. The purpose of this paper is to develop a model for assessing the quality of logistics services based on a specified list of criteria, their grouping, and the application of the mathematical apparatus of the fuzzy sets theory.
The study substantiates the expediency of using the fuzzy set method to assess the quality of logistics service and builds an LSQ assessment model that includes 12 criteria grouped into four groups: company reputation, product availability/quality, reliability/flexibility, and consumer service.
As a result of assessing the quality of logistics service, an integral indicator was obtained, which made it possible to determine the evaluations of its components: product availability/quality is rated high; reliability/flexibility – average; consumer service – good; and company reputation – poor. The obtained results indicate that such an aspect of logistics service quality assessment as company reputation needs particular attention, which confirms the modern trend of prioritizing the perception of the quality of logistics service, personal service/contact, and empathy by customers. Therefore, customers' perception of the quality of logistics service becomes a decisive factor in the competitive struggle in the logistics services market. Moreover, it is a bottleneck in the process of increasing LSQ, which requires further research to develop appropriate management mechanisms.
Опис
Ключові слова
logistics, service, quality, logistics company, logistics services, customs logistics, fuzzy set method
Бібліографічний опис
Assessment of logistics service quality based on the application of fuzzy methods modeling / T. Kolodizieva, Е. Zhelezniakova, K. Melnykova, V. Pysmak, O. Kolodiziev // Problems and Perspectives in Management. – 2022. – №20(3), P. 552-576. – Режим доступу: http://dx.doi.org/10.21511/ppm.20(3).2022.44