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An integrated fuzzy MICMAC with a revised IPA approach to explore service quality improvement

Importance-Performance Analysis (IPA) and SERVQUAL are both widely applied in service quality assessment. Even two model integration is also commonly used to eliminate the shortcomings in their respective single application. However, several modified IPA methods for improving traditional IPA has been put forward continuously, the integration model becomes difficult. This research proposes a new revised IPA method which can be integrated with SERVQUAL and preserve the advantages described in previous studies. Meanwhile, we further propose that the integration method for Fuzzy theory and Impact Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) consider the interdependence between attributes. Furthermore, the importance or performance of the respective attributes is to be corrected based on the degree of influence and dependency between the respective attributes. This novel hybrid IPA approach is not only valuable in the exploration of service quality but also identifies a strategy to improve overall satisfaction. The feasibility of this approach was demonstrated through an empirical study of the visitors at the Xiamen International Conference and Exhibition Center.