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Mechanisms of Patients' Satisfaction and Loyalty Formation

Student: Ekaterina Oreshkova

Supervisor: Efim Galitsky

Faculty: Graduate School of Business

Educational Programme: Marketing (Master)

Final Grade: 9

Year of Graduation: 2018

This study is motivated by a managerial problem which clinics encounter on Russian medical services market with highly competitive environment: the problem of patients' experience improving. Due to intensive and extensive development of market’s competitors and increasing awareness of medical services’ consumers it is extremely important for a certain medical organization to comprehend what factors contribute more to the patients’ satisfaction and loyalty growth. The article examines the mechanisms of patients’ satisfaction and loyalty formation due to the latent constructs illustrating the aspects of patients’ experience in the medical commercial organization. Following method was employed: questionnaire based on SERVQUAL approach filled by 1904 patients on the media source Health@mail.ru to grasp how they estimate their experience of clinic visiting and how much they feel satisfied and loyal to that clinic. Structural Equation Modeling was applied to analyze the quantitative data. The findings illustrate that the satisfaction and loyalty are indirectly positively influenced by latent constructs «Interaction with a medical workers» and «Flexibility of a service» through «Benefits Evaluation» and «Choice Correctness» constructs whereas the construct «Physical Attributes» has a negative impact on these marketing indicators. Theoretical contributions and practical implications are discussed. Recommendations for marketing managers of clinics are to pay more attention to development of medical and administrative personnel, to conduct training on medical ethics and deontology; to conduct internal research of employees, to expand the range of communication channels with patients; to form a set of service attributes with caution, for example, using the Kano model; to conduct regular Express monitoring of patients ' experience according to the questionnaire proposed in the work, developed using the method of classification trees.

Full text (added May 20, 2018)

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