The current COVID-19 crisis has seen governments worldwide mobilising to develop and implement contact-tracing apps as an integral part of their lockdown exit strategies. The challenge facing policy makers is that tracing can only be effective if the majority of the population uses the one app developed; its specifications must therefore be carefully considered. We theorise on tracing apps and mass acceptance and conduct a full-factorial experiment to investigate how app installation intention is influenced by different app specifications based on three benefit appeals, two privacy designs, and two convenience designs. By applying quantile regression, we not only estimate the general effect of these app specifications but also uncover how their influence differs among citizens with different propensities for acceptance (i.e. critics, undecided, advocates)-a crucial insight for succeeding with mass acceptance. This study contributes to research in three ways: we theorise how mass acceptance differs from established app acceptance, we provide a fine-grained approach to investigating the app specifications salient for mass acceptance, and we reveal contextualised insights specific to tracing apps with multi-layered benefit structures. Our findings can guide policy makers by providing specification recommendations for facilitating mass acceptance of tracing apps during pandemics or other societal crises.
With the increasing number of companies actively collecting data, the number of data breaches has exploded. It can be observed that affected often discontinue their relationship with the company. In order to avoid this kind of response, companies should develop and deploy their own recovery strategies. In our paper, we examined the effectiveness of different recovery strategies geared towards retaining customer satisfaction immediately after a data breach. We examine a data breach of a fitness tracker that varies in severity and tests the recovery actions compensation and remorse. The results found that customer satisfaction depends on the severity of the data breach, while combining compensation and remorse together demonstrates itself as the best strategy for increasing customer satisfaction in almost all cases. However, it was also discovered that in case of a severe data breach, customer satisfaction is difficult to restore and in the end remorse has virtually no effect.
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