Using regulatory fit in cost reduction announcements

Purpose: The purpose of this paper is to examine whether and how the usage of regulatory fit in cost reduction announcements affects employees’ willingness to engage in the cost reduction program (CRP). Design/methodology/approach: Based on the regulatory fit theory, a scenario-based experiment was conducted (n= 517) to investigate the effect of promotion- or prevention-oriented framing of the CRP on the acceptance and the motivation to actively contribute to the CRP using multiple ANOVAs. Findings: The study results point out that the framing of the cost announcement messages should use feelings or emotions and ensure gains for promotion-focused employees to decrease the negative effects of regulatory nonfit. However, in the case of prevention-focused employees, facts and reasons should be used in combination with an assertion of nonlosses in the announcement message to prevent regulatory nonfit. Research limitations/implications: This research deepens the understanding on the decision-influencing role of managerial cost announcements on employee motivation and the impact of different regulatory orientations. By this, the authors enhance the current understanding of how employees can effectively be integrated into CRPs and expand previous research on how regulatory fit theory can be used by organizations dealing with negative events. Practical implications: The study findings offer several opportunities and implications for managers engaged in corporate communication. More specifically, the study findings provide helpful guidelines for organizations to align their cost reduction announcement with the regulatory focus of their employees to reach regulatory fit and thus enhance employee willingness to participate in the CRP. Originality/value: Despite the increasing attention of regulatory focus and regulatory fit theory and to the best of the authors’ knowledge, this is the first attempt to search for combined effects of emotions and facts versus potential gains and ensuring nonlosses, which both were shown to influence outcomes predicted by regulatory fit.