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Articles

Applying flexible fuzzy numbers for evaluating service features in healthcare – patients and employees in the focus

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Abstract

Purpose: The main purpose of this paper is to introduce a flexible fuzzy number based methodology in order to enhance the reliability of traditional Likert scale based evaluations related to the measurement and evaluation of service quality, particularly in the healthcare context. Methodology: Due to the problems arising with the application of traditional Likert scales and to the methodological issues when interpreting the results, the concept of fuzzy scales is increasingly applied in service quality context by adding properties to Likert scales to model human judgement and thinking more precisely and reliably. The proposed fuzzy rating scale based methodology is built on the novelty of presenting multiform fuzzy numbers and by that means the inherent uncertainty, subjectivity and vagueness characterising healthcare stakeholders’ perceptions related to service features could be reflected in various ways. Relevance/findings: The main benefit of the methodology is the ability to model the imprecision and the uncertainty inherent in human evaluations as well as the representation of performance variation in case of specific service features. By being able to express overall evaluations as well, the proposed methodology can be applied to contrast different stakeholders’ perceptions compared to mainly patient-centred adaptations. A demonstrative healthcare example is also included to highlight these methodological benefits. Research implications: The application of the presented methodology may arise in any kind of service quality evaluations where Likert-type scales are applied traditionally. Originality/Value: By providing a fuzzy Likert scale to evaluate specific healthcare service attributes, patients and employees can express their uncertainty, contrasting perceptions and the variability of service features in a quantitative way and they also become comparable in certain aspects. On the other hand, fuzzy evaluation based results support healthcare decision-makers to facilitate effective, efficient and well-grounded strategies related to service quality improvements.