Economic Analysis: Theory and Practice
 

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Analyzing and modeling the assessment of consumer preferences of medical and preventive treatment facility services

Vol. 18, Iss. 8, AUGUST 2019

Received: 28 March 2019

Received in revised form: 19 April 2019

Accepted: 29 May 2019

Available online: 30 August 2019

Subject Heading: MATHEMATICAL METHODS AND MODELS

JEL Classification: C8, M31

Pages: 1581–1592

https://doi.org/10.24891/ea.18.8.1581

Ivanova I.A. National Research Ogarev Mordovia State University (MRSU), Saransk, Republic of Mordovia, Russian Federation
ivia16@mail.ru

https://orcid.org/0000-0003-1113-0858

Antipenkov A.G. National Research Ogarev Mordovia State University (MRSU), Saransk, Republic of Mordovia, Russian Federation
anton.antipenkov@gmail.com

ORCID id: not available

Subject The article investigates management practices of customer loyalty in medical and preventive treatment facilities.
Objectives The aim is to provide a rationale for applying the concept of relationship marketing, develop a methodology for evaluating the management systems of organization's customer relationship, analyze the structure of consumers of health care services, using the data mining, and develop a methodology and a model to identify their preferences.
Methods In assessing the organization's customer relationship management system, we employ methods for creating databases that characterize potential clients of medical and preventive treatment facilities and their preferences, data mining and correlation analysis techniques, etc.
Results We analyzed the consumer demand and supply for medical and preventive treatment facilities services, offered an algorithm for assessing the consumer loyalty management based on identified approaches. We also developed a system to reveal customer preferences given the feedback between the market players and the application of data mining results, depending on client characteristics for providing the most rational services. The paper presents a methodology to identify customer preferences. It is implemented, using a multiple linear regression model with a variable structure, including quantitative and qualitative exogenous variables. We organized service consumption profiles based on their clustering and classification, using the ABC-XYZ analysis.
Conclusions The findings may be used as a practical tool to improve the economic efficiency of the organization on the basis of customer loyalty formation, considering the customer preferences and automation of medical and preventive service formation process.

Keywords: management, customer relationship, data mining

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