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A meta-analysis of satisfaction with complaint handling in services

Abstract

Academics as well as managers have long been interested in the role of satisfaction with complaint handling (SATCOM) in shaping customers’ attitudes and repurchasing decisions. This interest has generated a widespread belief that SATCOM is driven by the perception that the complaint handling process is just. To test how SATCOM is modulated by distributive, interactional, or procedural justice, we performed a meta-analysis of 60 independent studies of the antecedents and consequences of SATCOM. Results indicate that SATCOM is affected most by distributive justice, then by interactional justice, and only weakly by procedural justice. We also find that SATCOM mediates the effects of justice dimensions on word-of-mouth. However, contrary to common belief, SATCOM does not mediate the effects of justice dimensions on overall satisfaction and return intent. We draw on our results to suggest several avenues for further research.

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Notes

  1. 1.

    Correlation coefficients were adjusted with an attenuation factor calculated as the product of the square root of (1) the reliability of the independent variable, (2) the reliability of the dependent variable, and (3) the sample size (Hunter and Schmidt 2004). Cronbach’s alpha values of each study were used as an indicator of the reliability of dependent and independent variables. However, not all studies reported Cronbach’s alpha. When they were unavailable we used imputation procedures (Becker 1992), and we imputed reliably from studies that were as similar as possible to those with missing data. However, the great majority of the studies reported Cronbach’s alpha, only 3% presented missing values. The average Cronbach’s alpha coefficients are: 0.87 for SATCOM, 0.91 for distributive justice, 0.89 for interactional justice, 0.87 for procedural justice, 0.89 for return intent, 0.90 for WOM, and 0.88 for overall satisfaction.

  2. 2.

    We asked authors for the correlation matrix whenever this information was not reported in the studies. In case of non-response, we imputed correlations from similar studies (Becker 1992). Three studies (Chung 2006, Lapidus and Pinkerton 1995, and Brown et al. 1996) were dropped because of lack of correlation coefficients and unavailability of enough information to perform a meaningful imputation.

  3. 3.

    One was built using all available adjusted correlation coefficients, the other using only the effect sizes coming from a reduced set of homogeneous studies, i.e., only those studies that contained jointly all the constructs included in the causal model. The aim of this analysis is to test whether the two matrices are homogeneous and can be pooled (see Brown and Peterson 1993, Appendix, for a similar approach). We tested the equivalence between the two matrices through a two-group confirmatory factor analysis. Since the test indicated that the complete adjusted average correlations were equivalent (χ2 = 28.18, p = 0.14, CFI = 1.00, TLI = 0.99, RMSEA = 0.031, RMSR = 0.02), in the second step we used the complete adjusted average correlation matrix.

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Acknowledgement

The authors would like to thank the editor, David W. Stewart, and the four anonymous JAMS reviewers for their insightful critiques of this manuscript. In addition the authors thank Gian Luca Marzocchi for his suggestions on previous versions of this article.

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Correspondence to Chiara Orsingher.

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The complete list of studies included in the meta-analysis is available from the authors.

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Orsingher, C., Valentini, S. & de Angelis, M. A meta-analysis of satisfaction with complaint handling in services. J. of the Acad. Mark. Sci. 38, 169–186 (2010). https://doi.org/10.1007/s11747-009-0155-z

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Keywords

  • Satisfaction with complaint handling
  • Meta-analysis
  • Service recovery
  • Service failure
  • Justice theory