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Export Reference (APA) 
Aguiar, T. R., Tomprou, Maria & Costa, S. (2025). Managing the Bad News Matters! Layoff Announcements and their Impact on Victims and Observers. 22nd European Association of Work and Organizational Psychology (EAWOP 2025).
Export Reference (IEEE) 
T. M. Aguiar et al.,  "Managing the Bad News Matters! Layoff Announcements and their Impact on Victims and Observers", in 22nd European Association of Work and Organizational Psychology (EAWOP 2025), Praga, 2025
Export BibTeX 
@misc{aguiar2025_1765575058597,
	author = "Aguiar, T. R. and Tomprou, Maria and Costa, S.",
	title = "Managing the Bad News Matters! Layoff Announcements and their Impact on Victims and Observers",
	year = "2025",
	url = "https://eawop2025.com/"
}
Export RIS 
TY  - CPAPER
TI  - Managing the Bad News Matters! Layoff Announcements and their Impact on Victims and Observers
T2  - 22nd European Association of Work and Organizational Psychology (EAWOP 2025)
AU  - Aguiar, T. R.
AU  - Tomprou, Maria
AU  - Costa, S.
PY  - 2025
CY  - Praga
UR  - https://eawop2025.com/
AB  - Traditional downsizing practices often disregard employees’ emotional and professional investment, leading to increased feelings of betrayal by both laid-off workers and remaining staff with implications for mental well-being. However, there is a significant lack of evidence of how different methods of communicating layoffs (e.g., email versus personalized meetings) and varying levels of transparency affect recipients’ emotionality and their perception of organizational justice and fairness. To explore this, we propose and test a model examining the relationship between layoff communication methods, perceived procedural justice, and experienced emotionality. We suggest that layoffs perceived as transparent and respectful, such as those involving one-on-one communication and proactive job placement support, may mitigate negative emotional responses and perceptions of unfairness. Conversely, impersonal, abrupt methods such as mass emails can exacerbate emotional responses and victims’ reactions. Implications of this model are significant for organizational policy and human resources practices. We seek to test these propositions by using data from social media to test how different modes of layoff announcements within organizations influence victims' and observers' reactions and analyze them using Linguistic Inquiry and Word Count (LIWC). Our findings will provide recommendations and evidence about the efficiency of these strategies and practices when layoffs cannot be avoided.
ER  -