Examination of the Predictive Power of Service Quality Dimensions on Customer Satisfaction with Health Services in Rwanda
DOI:
https://doi.org/10.47941/jbsm.2803Keywords:
Service Quality, Customer Satisfaction, Health Services, Predictive Power, Service Quality MeasurementAbstract
Purpose: The study examined whether the five service quality dimensions predict the satisfaction with health services in Rwanda and their predictive abilities.
Methodology: The quantitative research approach was employed to collect data for this study. The population of the study was 17,842,187 individuals who sought services from different health facilities from which a sample of 487 was chosen using a probability sampling method. Data were merged and cleaned to ensure quality before the actual analysis. The analysis of data was done using Statistical Package for Social Sciences (SPSS) and exported to Microsoft Excel for categorization of responses and easy manipulation of the data. Multiple linear regression analysis was employed to test how the service quality dimensions are associated with customer satisfaction with health services and the predictive power of each dimension.
Findings: Hypotheses tests were carried out and results showed that, all the five service quality dimensions are predictors of customer satisfaction with health services. As a result, the null hypotheses were rejected and alternative hypotheses were accepted. If the service quality dimensions are arranged in order of their predictive power beginning with the highest predictor; they can be ordered as Empathy, Assurances, Reliability, Tangibles and Responsiveness.
Contribution to Theory, Policy, and Practice: The research showed significant relationship between the five service quality dimensions and customer satisfaction with health services which has not been measured before. It also showed the predictive power of each of the dimensions which highlights where more efforts should be invested to improve satisfaction with health services in Rwanda. More efforts should be invested in those dimensions that predict satisfaction of customers more than others in case resources to improve all are not sufficient in a particular period of time.
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