Aspects of Information and Analytical Support for the Supply Chain Management of Healthcare Customers’ Loyalty

Abstract

Abstract- The practice of managing customer loyalty to the organization’s services based on the concept of Customer Relationship Management (CRM) is becoming increasingly relevant in the supply chain strategies. It is necessary to study potential consumers, identify their requirements and develop a competent marketing strategy for building mutually beneficial relations of the organization with customers. The development of a mechanism for assessing consumer loyalty to the healthcare facility services, its automation with the help of customer relationship management tools should be methodologically justified. Purpose. The research is aimed at developing a methodological approach to healthcare customer loyalty assessment, including identification of target and profitable segments, regulation of business processes, analysis of the customer database and business environment of an organization to increase the effectiveness of its marketing activities. Systemic research of customer relationships includes the following methods and tools: Data Mining methods with instrumental support of Statistica software, including factor analysis and formation of databases of endogenous and exogenous variables; specification of a mathematical model; correlation analysis; variable multiple linear regression analysis based on the generalized least squares method; model verification using R²-statistics and Fisher (F-test) and Student (t-test) criteria; ABC- and XYZ analysis of revealing customer consumption profiles; the analytic hierarchy process (AHP) based on expert assessments of the multicriteria problem solution while evaluating the support tools for managing consumer loyalty with a hierarchical structure. The practical and theoretical significance of the results. A methodological approach has been developed to identify healthcare facility (HCF) customer preferences, implemented using a variable multiple linear regression model, including both quantitative (age, number of bed days, etc.) and qualitative (social status, gender, marital status, parental status, education, medical service type) exogenous variables. Consumption profiles of HCF services have been constructed on the basis of their clustering and classification using ABC- and XYZ analyzes. An algorithm for evaluating the support tools of the consumer loyalty analysis has been proposed. The analysis of consumer demand for the organization’s services enables to develop an algorithm for assessing consumer loyalty management information systems, to form a system of indicators characterizing potential customers and their preferences in the medical services market; the most rational and customer-oriented services that reflect the customer’s consumption profile. The results can be used as practical tools for improving the economic efficiency of the organization depending on the cluster dynamics of consumption and changes in personal customer characteristics and CRM-based marketing performance support tools.