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Service crisis recovery and firm performance: insights from information breach announcements

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Abstract

The extant literature has studied the effects of a firm’s service recovery efforts on the reactions of customers and employees following an individual service failure. However, the impact of recovery efforts on a firm’s performance after a public and large service failure—such as a large-scale information breach—has received scant attention. To address this gap, this current research develops a framework and finds support for the impact of service crisis recoveries on a firm’s performance, as measured by firm-idiosyncratic risk. Using a unique dataset of service crisis recoveries, the authors find that firms offering compensation (i.e., tangible redresses) or process improvement (i.e., improvements in organizational processes) show more stable performance (less idiosyncratic risk), from two quarters to two calendar years after the announcement of their recovery plan. In line with the documented dual effect of apologies, firms that offer apology-based recoveries display more volatile performance (higher idiosyncratic risk). Of note, this volatility increases with the number of affected individuals, and it remains unaffected even when the apology is expressed with high intensity.

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Notes

  1. We highlight that compensation does not only have an effect on distributive justice; this recovery effort also influences the other justice dimensions (i.e., procedural and interactional), but to a lesser extent. Gelbrich and Roschk (2011) in their meta-analysis found the greatest effect size between compensation and distributive justice. Consistently, researchers generally assume that compensation operates mainly through its effects on distributive justice (Gelbrich et al. 2015).

  2. Similar to the effects of compensation, process improvement efforts influence the two other justice dimensions (i.e., distributive and interactional), but to a lesser extent (Gelbrich and Roschk 2011).

  3. Gelbrich and Roschk’s (2011) meta-analysis incorporates tangible compensation and an apology in the same broad category called “compensation.” We contacted the authors about the specific effects of an apology. Their results confirmed that an apology typically had a positive effect on satisfaction and the other variables of their model.

  4. Privacy Rights Clearinghouse. Chronology of Data Breaches. Retrieved January 10, 2014 from https://www.privacyrights.org/data-breach.

  5. Ir = {[(F/N) – (1/k)][k/(k–1)]}0.5, for F/N > 1/k; where F is the frequency of agreement between coders, N is the total number of judgments and k is the number of categories.

  6. The fact that 57 observations did not offer any recovery action shows that our sample is not biased by the inclusion of only firms that offered recoveries. In the current context, we minimize the potential bias that would result from selecting only firms that made a recovery decision—this bias would be based on the assumption that these firms would have different characteristics compared to firms that did not provide any recovery action (Certo et al. 2016).

  7. When independent variables are not discrete new actions of firms, but changes in existing strategies of firms (e.g., changes in the marketing alliance strategy), changes models (first-differenced regression) are especially appropriate to test the hypotheses. Changes models examine the impact of changes in independent variables on changes in a dependent variable. The rationale for changes models is that an event announcement may carry relevant information from the past, and this “prior” information can affect the reaction of investors to the announcement of a target event. By using changes models through time series datasets, researchers can ensure that they focus only on the impact of new information. Since announcements of recovery strategies are discrete decisions that carry little prior information, our analyses rely on levels models rather than changes models.

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  1. Department of Marketing, HEC Montreal, 3000, Chemin de la Côte-Sainte-Catherine, Montréal, Québec, H3T 2A7, Canada

    Shahin Rasoulian, Yany Grégoire & Renaud Legoux

  2. Department of Marketing, HEC Montreal, 5540, Avenue Louis-Colin, Montréal, Québec, H3T 1T7, Canada

    Sylvain Sénécal

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Rasoulian, S., Grégoire, Y., Legoux, R. et al. Service crisis recovery and firm performance: insights from information breach announcements. J. of the Acad. Mark. Sci. 45, 789–806 (2017). https://doi.org/10.1007/s11747-017-0543-8

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