Although ethical scandals are a common phenomenon in the service industry, there is little research on the service-specific aspects of crisis management. In this research, we argue that frontline employees are of crucial importance after a scandal and examine how firms can secure the support of frontline employees following different kinds of scandals. Specifically, we demonstrate that corrective responses that address the internal causes of a scandal and ceremonial responses that guide attention to positive aspects unrelated to the scandal moderate the impact of different scandals on frontline employee support. Three experiments showed that frontline employee support was greater after scandals that involved a great rather than a small number of wrongdoers and after scandals that had been caused by high-ranking managers rather than low-ranking employees when a corrective response was implemented. In contrast, support was greater following scandals that had been committed by a few low-ranking employees rather than high-ranking managers when a ceremonial response was employed. These results have important implications by illustrating how companies can effectively restore frontline employee support following a scandal.

Although applicant-employee fit has emerged as an important topic in recruitment research, little is known about how job seekers' perceived similarity with the employees working for an organization affects employer attraction. In this research, we introduce temporal construal as a crucial moderating variable and study how the temporal decision context affects the weighting of applicant-employee fit. In particular, we argue that applicant-employee fit is construed in abstract, high-level terms, and exerts a stronger influence when prospective applicants hold a distant time perspective. In contrast, instrumental attributes such as pay level represent low-level construals and gain greater relevance when prospective applicants hold a near time perspective. Two experiments involving a student sample and a sample of unemployed job seekers supported these predictions.

RÉSUMÉ

There is little research on how consumers decide whether they want to use algorithmic advice or not. In this research, we show that consumers’ lay beliefs about artificial intelligence (AI) serve as a heuristic cue to evaluate accuracy of algorithmic advice in different professional service domains. Three studies provide robust evidence that consumers who believe that AI is higher than human intelligence are more likely to adopt algorithmic advice. We also demonstrate that lay beliefs about AI only influence adoption of algorithmic advice when a decision task is perceived to be complex.