She explains that the thesis develops new statistical methods to help researchers better capture how teams evolve.
“They are not static entities: trust can build or erode, members can leave or join, and events can strengthen or disrupt collaboration. Understanding these dynamics is crucial but studying them is challenging”, says Yvette Baurne.
The first part of the thesis focuses on how shared team states, such as team trust or team cohesion, are formed. Researchers often assume that individuals in a team gradually converge toward a common perspective, but current statistical measures can give misleading results about whether this is happening or not.
“We propose a new way of defining and estimating these processes, which avoids several common pitfalls,” Yvette explains.
She continues with the second part which addresses how team dynamics unfold over time. Using advanced tools from machine learning, the research develops methods that allow for nonlinear patterns such as rapid increases followed by plateaus, which traditional models cannot capture. These methods also make it possible to study how variability itself changes, for example, whether team members are becoming more similar or more different over time.
In the third part Yvette Baurne investigates what happens once a shared state has formed. She has studied trust in entrepreneurial teams, showing how significant events can disrupt or strengthen trust, and how trust influences whether members stay or leave.
“To do this, we combine models for changes over time with models for discrete events, while also accounting for the fact that survey responses are often missing in ways that are not random,” says Yvette.
She concludes by saying that the thesis shows how more flexible and precise statistical methods can provide deeper insights into how teams function, adapt, and sometimes fall apart.
Congratulations Yvette, could you tell us a little about your academic background?
“I started out in social psychology, but along the way I realized I was more interested in how we can measure and model people’s behavior rather than in the behavior itself. That curiosity eventually led me to statistics.”
What has it been like to be a PhD student at LUSEM — how would you describe your experience here?
“It’s been intense at times, but also very rewarding. I’ve had the chance to dig into questions that really interest me, and I’ve grown a lot along the way. Overall, it’s been a good mix of challenge, learning, and development.”
What are your plans after the dissertation, and do you have any advice for those just starting their PhD journey?
“After the defence I’ll begin a postdoc at Jyväskylä University School of Business and Economics, where I’ll study how statistical methods are applied in organizational research and what happens when analytical mistakes sneak in. For those just starting a PhD, my advice is to pay attention not only to the research but also to how you work. The journey can be stressful, and finding strategies that suit you makes all the difference. I really recommend the “Finish on time” course at Lund University. It offers practical tools for both stress management and working more efficiently.”