I am a Postdoctoral researcher in the Department of Organizational Psychology at the University of Groningen. In my main line of research, I am interested in situations nobody likes to be in but which are inevitable in organizations - I study the impact bad news, such as layoffs or denied promotions have on managers, employees, and organizations. Besides my focus on bad news and providing evidence-based guidance on how to navigate these events effectively, I am conducting research on topics such as infodemic and its impact on workplaces (i.e., information overload during uncertain times), how we can leverage large-scale online data to derive insights for employees and organizations, or self-regulation in leadership. I am also involved in projects linked to contextual determinants of resilience and enhancing rigor in quantitative research methods. I am also an external lecturer for Human Resource Management at the Faculty of Law and Business in Klagenfurt, Austria.
Project Title
Adapting to the changing landscape of working in Tech: Navigating societal challenges and behavioral transitions amidst mass layoffs.
Systemic or Behavioral change(s) addressed
I am interested in how organizations within a whole industry and individuals employed within this industry adapt to recent developments. For example, I aim to address the questions as to how organizations strive to maintain their profitability at the expense of laying off thousands of employees via questionable layoff practices (e.g., automated emails, 2-minute Zoom calls), how employees make sense and engage in coping strategies when losing their jobs, how individual reassess and redirect their work-related interests (e.g., job search outside the industry), how the knowledge of the unstable industry and job-characteristics impacts how students evaluate and decide for/against their educational programs or how they redirect their efforts toward careers within more stable industries. Taking these aspects into consideration, I aim to investigate how the disruption of a mass layoffs that also involve existential crises impact not only individuals but also how industries and organizations (e.g., talent-attraction and retention, employee satisfaction), families (e.g., work-family spillover, coping with financial instability), societies (e.g., peer-support and supervision, identity maintenance and restoration) and cultures (e.g., differences in handling these transitions) adapt and transform. Besides the negative consequences, I also aim to address positive experiences, reflecting “silver linings” of these challenges that help individuals, organizations, or societies grow.
Theoretical approach
The projects use a variety of theories, including the appraisal theory of stressful encounters (Folkman et al., 1987; Lazarus, 1991), Frese & Zapf’s (1988) exposure-time model, identity maintenance, restoration, and negotiation (Petriglieri, 2011; Swann, 1987), the predicament of injustice (Bies, 1997), and organizational crisis theories (e.g., Gundel, 2005; Iqbal et al., 2023).
Empirical research strategies
The projects aim to apply mixed-method research strategies, and qualitative and quantitative methods to analyze large-scale datasets. Specifically, I combine sentiment analysis and unsupervised machine learning (i.e., structural topic modeling) with longitudinal modeling and qualitative coding to model changes in individual evaluations and company ratings over time.
First, by drawing on different online employer rating platforms and subsequent organizations within the tech industries, I aim to conduct a natural experiment of employee perceptions of mass layoffs, including several hundred thousand qualitative and quantitative ratings that will be analyzed using sentiment analysis (e.g., work attitudes, affect, moral emotions) and unsupervised machine learning (i.e., structural topic modeling). This allows comparing effects from pre-to post-mass layoff time frames and longitudinal modeling starting as early as 2006. Based on the nature of the data available, the data can reflect current and former employees, thereby allowing assessing how employees who remain within organizations after mass layoffs assess their employer and report on work-related characteristics such as demands, work-life balance, or salary. Further, I also include another employer rating platform to compare these effects with findings from the DACH region. This allows examining differences in employee perceptions of how employers within the same industry but at geographically diverse locations manage and enact mass layoffs. In addition, it is possible to link relevant stock-related performance of organizations to the events of mass layoffs, allowing us also to see how organizations/the industry suffer/s and/or recover/s from market instabilities and transitions. Second, to examine the far-reaching impact on multiple stakeholders and their coping and/or sense-making strategies/processes, I draw on online forums in which employees from the tech sector post their experiences, share advice, ask for help and feedback, or reach out to others to show support or share best-practices to deal with mass layoffs. This allows for a far more profound discussion of the current disruption. In addition, due to the nature of the forums, it is possible to track interactions and reciprocal discussions between individuals in the comments of each posting depicting group coping/supervision processes over time.
Possibilities for inter- and transdisciplinary collaboration
The project offers a broad foundation for interdisciplinary collaborations. For example, while my (and my current collaborators) expertise mainly focuses on the individual level, I would highly appreciate sharpening the sociological and management lens to reflect the macro perspective of the project further. More specifically, the questions on how a whole industry, respective careers, or financial markets adapt, overcome, and potentially excel from this transition would benefit from an interdisciplinary approach to best examine the multiple layers to this challenge. In addition, the data derived from the online forum includes interactions (i.e., discussions) tied to several hundreds of posts. However, modeling the co-dependencies of comments lacks sufficient methodological approaches in the organizational psychology/behavior discipline. Therefore, interdisciplinary input and collaborations would pave the way to analyze and interpret the rich data.
Social transition(s) addressed
My research project aims to address the recent development of change within the tech industry characterized by the current recession leading to mass layoffs. These developments negatively affect organizations, employees, and future talent (e.g., reputation, career uncertainty, negative affect). I focus on the recent mass layoffs in the tech industry that leave thousands of employees unemployed (i.e., layoff victims), employees still employed with the constant fear of “being next” or actively reorienting their careers to avoid being laid off in the future (i.e., layoff survivors), or students (i.e., future talent) deciding against study programs or careers in tech. In addition, I also expand this lens by including advancements in AI that further amplify the already persistent fear and related uncertainties in employees of being made redundant in the foreseeable future.