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Generalized cross entropy method for analysing the SERVQUAL model

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  • E. Ciavolino
  • A. Calcagnì

Abstract

The aim of this paper is to define a new approach for the analysis of data collected by means of SERVQUAL questionnaires which is based on the generalized cross entropy (GCE) approach. In this respect, we firstly give a short review about the important role that SERVQUAL plays in the analysis of service quality as well as in the assessment of the competitiveness of public and private organizations. Secondly, we provide a formal definition of GCE approach together with a brief discussion about its features and usefulness. Finally, we show the application of GCE for a SERVQUAL model, based on a patients' satisfaction case study and we discuss the results obtained by using the proposed GCE-SERVQUAL methodology.

Suggested Citation

  • E. Ciavolino & A. Calcagnì, 2015. "Generalized cross entropy method for analysing the SERVQUAL model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 520-534, March.
  • Handle: RePEc:taf:japsta:v:42:y:2015:i:3:p:520-534
    DOI: 10.1080/02664763.2014.963526
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    References listed on IDEAS

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    1. Pakdil, Fatma & Aydın, Özlem, 2007. "Expectations and perceptions in airline services: An analysis using weighted SERVQUAL scores," Journal of Air Transport Management, Elsevier, vol. 13(4), pages 229-237.
    2. E. Ciavolino & J. J. Dahlgaard, 2009. "Simultaneous Equation Model based on the generalized maximum entropy for studying the effect of management factors on enterprise performance," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(7), pages 801-815.
    3. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    4. Babakus, Emin & Boller, Gregory W., 1992. "An empirical assessment of the SERVQUAL scale," Journal of Business Research, Elsevier, vol. 24(3), pages 253-268, May.
    5. Golan, Amos, 2002. "Information and Entropy Econometrics--Editor's View," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 1-15, March.
    6. Golan, Amos & Judge, George & Karp, Larry, 1996. "A maximum entropy approach to estimation and inference in dynamic models or Counting fish in the sea using maximum entropy," Journal of Economic Dynamics and Control, Elsevier, vol. 20(4), pages 559-582, April.
    7. Enrico Ciavolino & Amjad Al-Nasser, 2009. "Comparing generalised maximum entropy and partial least squares methods for structural equation models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(8), pages 1017-1036.
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    Cited by:

    1. Jun-Hwa Cheah & Hiram Ting & T. Ramayah & Mumtaz Ali Memon & Tat-Huei Cham & Enrico Ciavolino, 2019. "A comparison of five reflective–formative estimation approaches: reconsideration and recommendations for tourism research," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1421-1458, May.
    2. Sharon Tan & Evan Lau & Hiram Ting & Jun-Hwa Cheah & Biagio Simonetti & Tan Hiok Lip, 2019. "How Do Students Evaluate Instructors’ Performance? Implication of Teaching Abilities, Physical Attractiveness and Psychological Factors," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 61-76, November.
    3. Enrico Ciavolino & Gloria Lagetto & Andrea Montinari & Amjad D. Al-Nasser & Amer I. Al-Omari & Matteo J. Zaterini & Sergio Salvatore, 2020. "Customer satisfaction and service domains: a further development of PROSERV," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(5), pages 1429-1444, December.

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