PlumX Metrics
Embed PlumX Metrics

Integration of SERVQUAL, Analytical Kano, and QFD using fuzzy approaches to support improvement decisions in an entrepreneurial education service

Applied Soft Computing, ISSN: 1568-4946, Vol: 112, Page: 107786
2021
  • 42
    Citations
  • 0
    Usage
  • 185
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    42
    • Citation Indexes
      42
  • Captures
    185

Article Description

Quality tools such as Kano’s model, SERVQUAL, and Quality Function Deployment (QFD) have been used to design and improve services. Although these tools can be used separately, their integration can provide a deep analysis of the service quality, generating opportunities for its improvement. However, the effective integration of these tools requires the proper handling of their variables, which contains imprecision and uncertainties since they are based on customer’s perceptions. Fuzzy approaches are feasible alternatives to overcome these limitations and integrate these tools. Nevertheless, sophisticated fuzzy methods can deal better with these limitations. This article proposes an integrative framework involving SERVQUAL, Analytical Kano (A-Kano), and QFD using fuzzy approaches (Fuzzy Inference System and 2-tuple fuzzy linguistic representation). The framework comprises four main phases concerning (i) the identification of quality attributes and service processes using the A-Kano and SERVQUAL; (ii) the integration of these two quality tools using the Fuzzy Inference System (FIS); (iii) the integration between A-Kano and SERVQUAL output and QFD matrix using 2-tuple fuzzy linguistic representation; and (iv) the identification of improvement projects to address the opportunities identified in the previous phases. The proposed integrative framework was tested and validated in an entrepreneurial education company that provides experiential services. It contributes to providing a new method to assess the service quality perceptions, categorizing these perceptions according to their effects on customer satisfaction, prioritizing improvements, and identifying technical requirements. Mainly, this study presents a new proposal for integrating the SERVQUAL, A-Kano, and QFD using advanced fuzzy techniques, which contributes to overcoming the limitations found in the extant literature.

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know