Service quality gaps analysis based on Fuzzy linguistic SERVQUAL with a case study in hospital out‐patient services

Abstract

PurposeThis study seeks to propose a conceptual approach to assess the perceived service quality properly using Fuzzy logic. First, it aims to verify whether it is a better solution than the Likert scale. Second, it seeks to evaluate patients' feedback towards hospital service quality using Fuzzy linguistic analysis.Design/methodology/approachThe SERVQUAL questionnaire was developed according to the characteristics of each hospital's out‐patient service. Three regional hospitals in Hsin‐Chu, Taiwan were evaluated. After being completed and collected, first, the effectiveness of the Fuzzy linguistic scale and the Likert scale was compared. Second, gap values of each element were evaluated to find the core service quality attributes for continuous improvement. Finally, analysis of variance (ANOVA) was conducted to segment markets using certain service quality attributes and different demographic variables.FindingsThe result indicated that the Fuzzy linguistic scale is higher than the Likert scale in terms of reliability in the measurement. Moreover, through gap analysis and ANOVA, a better focus was achieved on the 8th, 10th, 14th, 21st and 3rd service quality attributes from the SERVQUAL measurement on which management should concentrate and which they should endeavor to work out. The 1st, 2nd, 14th and 16th items from the SERVQUAL measurement can be market segment factors, respectively.Originality/valueThe study successfully introduced Fuzzy linguistic analysis into the Gap theory and SERVQUAL measurements, and provided more internal consistency and stability than the Likert scale. After discussing the findings of the gap analysis and ANOVA, the organization could find the critical service quality attributes and create a value for improving or enhancing them.