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Journal of the Academy of Marketing Science
Published in: Journal of the Academy of Marketing Science 6/2012

01-11-2012 | Original Empirical Research

Understanding the co-creation effect: when does collaborating with customers provide a lift to service recovery?

Authors: Anne L. Roggeveen, Michael Tsiros, Dhruv Grewal

Published in: Journal of the Academy of Marketing Science | Issue 6/2012

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Abstract

Because co-creation allows customers to help shape or personalize the content of their experience, it can affect customer satisfaction with recovery efforts, as well as offer a more cost-effective alternative to compensation. This article identifies specific situations in which co-creation is and is not useful. Study 1 tests the impact of co-creation in comparison with compensation for enhancing satisfaction with the recovery process and demonstrates that co-creation offers a cost-efficient strategy for companies when customers must deal with severe delays. Study 2 extends these results by showing that the impact extends to repurchase intentions. Study 3 details conditions in which co-creation harms evaluations. Finally, Study 4 explores whether it is necessary for the company to meet the customer’s requests when co-creating a recovery, as well as what happens when the company exceeds a customer’s requests. The article concludes with a discussion of the theoretical and managerial implications, limitations, and research directions that emerge from the studies.
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Appendix
Available only for authorised users
Footnotes
1
Although the sample size is relatively small, recent evidence shows that the convergence and accuracy of confirmatory factor analysis solutions are affected by the quality of the latent variable indicators rather than by the sample size or observations per free parameter (Guadagnoli and Velicer 1988; Marsh et al. 1998).
 
2
Recent evidence (Chen et al. 2008) suggests using multiple indicators of model fit and claims that the arbitrary cut-off point of .05 for RMSEA rejects too many valid models with small sample sizes (n = 100); it performs better with larger samples (but accepts too many when n > 800).
 
3
Post-hoc power analysis for interaction justice indicates low power (.35). Thus, the non-significant results are more likely due to the test being underpowered for a small effect at the .10 level (Cohen 1992).
 
4
Mediation tests for the individual justice measures are available via web appendix. We find full mediation for all justice measures.
 
5
Here, ab represents the indirect effects of the independent variable on the dependent variable through the mediator, c represents the direct effect of the independent variable on the dependent variable, and c’ represents the total effect of the independent variable on the dependent variable.
 
6
Post-hoc power analysis for interaction justice indicates low power (.45). Thus, the non-significant results are more likely due to the test being underpowered for a small effect at the .10 level (Cohen 1992).
 
7
Mediation tests for the individual justice measures are available via web appendix. We find full mediation for all justice measures.
 
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Metadata
Title
Understanding the co-creation effect: when does collaborating with customers provide a lift to service recovery?
Authors
Anne L. Roggeveen
Michael Tsiros
Dhruv Grewal
Publication date
01-11-2012
Publisher
Springer US
Published in
Journal of the Academy of Marketing Science / Issue 6/2012
Print ISSN: 0092-0703
Electronic ISSN: 1552-7824
DOI
https://doi.org/10.1007/s11747-011-0274-1

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