Federico Magni

My current main lines of research include:

⦾ How people react to the utilisation of AI in organisational settings, including creative production by AI and the employment of AI in recruitment processes.

⦾ How are creativity and performance at work are impacted by factors such as power, errors, network position, and work-life interfaces.

⦾ How people appraise and react to diversity and uncertainty in the workplace, and how these appraisals affect relevant work outcomes

In some of my research work, I take a learning lens, for instance studying how learning motivation (e.g. goal orientation) impacts and is impacted by performance. In relation to this, with some collaborators we are also studying how the Covid19 pandemic has impacted education professionals, who have to both learn how to cope with the new situation, and facilitate others' learning.  Our work on Covid19 was included in the AOM OB Rapid Research Plenary on Covid19 at the 2020 AOM (Virtual) Annual Meeting.

I am also interested in the interplay between arts and management, and I am actively pursuing research opportunities that would allow me to understand how artistic and economic logics can co-exist and thrive in organisations.

I am also interested in the current developments of statistical methods for organisational research, and have been analysing data research projects using techniques such as SEM (Structural Equation Modelling), Growth Modelling, Multi-level analysis, Monte-Carlo estimations of Confidence Intervals (with Bootstrap) to test mediation, Dynamic Mediation, Effect Size analysis (of direct effects and mediation indices), and Reciprocal Relationship tests using softwares such as R, MPlus, Stata, and SPSS (Process). I am familiar in handling both correlational (e.g. field studies) and experimental research designs, as well as with qualitative data (thematic and content analysis).