Using the elements from a fuzzy sets theory in the process of diagnosing the loyalty of consumers of motor transport services

Authors

DOI:

https://doi.org/10.15587/1729-4061.2019.169079

Keywords:

fuzzy sets, linguistic variable, membership function, perceptual (attitudinal) loyalty, behavioral loyalty

Abstract

We developed an approach to diagnosing the complex loyalty of consumer of motor transport services based on the perceptual and behavioral characteristics with application of the theory of fuzzy sets. Diagnosing the level of consumer loyalty is the basis of a cyclical process of managing the loyalty of consumers of a motor transport company (MTC) in the field of freight transportation. Formation of loyalty depends on subjective perception by a consumer; therefore, the usual quantitative methods of analysis are not effective under conditions of fuzzy (incomplete) information. Application of the results of the theory of fuzzy sets to the analysis and evaluation of the consumer loyalty makes it possible to obtain fundamentally new models and methods of analysis.

The method of data aggregation based on the fuzzy classifier makes it possible to proceed from quantitative and qualitative values of individual indicators of perception and behavior of a consumer to complex indicators of loyalty. We obtained the empirical data used in the present study by questioning consumers. The study is based on actual data on the transportation of goods for each customer of a company. We performed quantitative assessment of integral factors of perceptual (attitudinal), behavioral and complex customer loyalty according to the standard matrix assessment scheme. A three-level classification has been applied with "Low level, Middle level, High level" subset-terms of "Loyalty level" linguistic variable to recognize the level of these factors. It was found that most consumers have an average and high level of loyalty to MTC in the assessment based on results of estimating the level of customer loyalty of the motor transport company.

The use of fuzzy sets makes it possible to identify the mutual influence of perceptual and behavioral factors on formation of the complex consumer loyalty comprehensively, as well as to simulate different situations depending on the predicted indicators of interaction with a consumer. It is a prerequisite for the development of loyalty of consumers of motor transport services through the development of loyalty programs and individual strategies for interaction.

Author Biographies

Iryna Fedotova, Kharkiv National Automobile and Highway University Yaroslava Mudroho str., 25, Kharkiv, Ukraine, 61002

PhD, Associate Professor

Department of Management and Administration

Oksana Kryvoruchko, Kharkiv National Automobile and Highway University Yaroslava Mudroho str., 25, Kharkiv, Ukraine, 61002

Doctor of Economic Sciences, Professor

Department of Management and Administration

Volodymyr Shynkarenko, Kharkiv National Automobile and Highway University Yaroslava Mudroho str., 25, Kharkiv, Ukraine, 61002

Doctor of Economic Sciences, Professor

Department of Management and Administration

Nadiia Bocharova, Kharkiv National Automobile and Highway University Yaroslava Mudroho str., 25, Kharkiv, Ukraine, 61002

PhD

Department of Management and Administration

Liudmyla Sotnychenko, National University "Odessa Maritime Academy" Didrikhson str., 8, Odessa, Ukraine, 65029

Doctor of Economic Sciences, Associate Professor

Department of Management and Economy

Svetlana Dimitrakieva, Technical University of Varna Studentska str., 1, Varna, Bulgaria, 9010

Doctor of Economics and Management, Professor

Department of Industrial Management

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Published

2019-05-29

How to Cite

Fedotova, I., Kryvoruchko, O., Shynkarenko, V., Bocharova, N., Sotnychenko, L., & Dimitrakieva, S. (2019). Using the elements from a fuzzy sets theory in the process of diagnosing the loyalty of consumers of motor transport services. Eastern-European Journal of Enterprise Technologies, 3(3 (99), 39–49. https://doi.org/10.15587/1729-4061.2019.169079

Issue

Vol. 3 No. 3 (99) (2019): Control processes

Section

Control processes

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Copyright (c) 2019 Iryna Fedotova, Oksana Kryvoruchko, Volodymyr Shynkarenko, Nadiia Bocharova, Liudmyla Sotnychenko, Svetlana Dimitrakieva

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