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SIOP Award Winners: Meet Jonas Lang, Winner of the SIOP Jeanneret Award for Excellence in the Study of Individual or Group Assessment (Along With Paul D. Bliese & Alex de Voogt)

Liberty J. Munson

As part of our ongoing series to provide visibility into what it takes to earn a SIOP award or grant, we highlight a diverse class of award winners in each edition of TIP. We hope that this insight encourages you to consider applying for a SIOP award or grant because you are probably doing something amazing that can and should be recognized by your peers in I-O psychology!

This quarter, we are highlighting the winner of the SIOP Jeanneret Award for Excellence in the Study of Individual or Group Assessment: Jonas Lang, who won this award along with Paul D. Bliese and Alex de Voogt.

Share a little a bit about who you are and what you do.

I am a member of the Department of Human Resource Management and Organizational Psychology at Ghent University in Belgium (close to Brussels) and the Business School of the University of Exeter (UK). I am originally from Aachen, Germany, which is a city in the triborder area between Germany, Belgium, and the Netherlands. I received my psychology degree from the University of Mannheim in 2004 and my PhD from RWTH Aachen University in 2007 (both in Germany). I worked at Maastricht University (Netherlands) before I came to Ghent.

My research mostly focuses on the application of multilevel methods and the measurement and use of individual differences in organizational settings. I have been an associate editor for Organizational Research Methods the past 2 years, and I am a member of Lillian Eby’s incoming team at the Journal of Applied Psychology as an associate editor.

Describe the research/work that you did that resulted in this award. What led to your idea?

The starting point was the observation that many researchers are interested in studying the emergence of climates, or “how do climates form in groups or organizations?” This question seems quite central to organizational research and especially industrial and organizational (I–O) psychology. Researchers had studied these ideas using a variety of approaches like qualitative methods, event analyses, or network analyses. However, these approaches require special types of datasets or research skills and cannot readily be applied to questionnaire data or behavioral data. The arguably most common quantitative method used in our field—multilevel methods—had not been adapted or used to study emergence at the time we conducted this research. The multilevel methods that researchers were using were only suited to study how climates that had already formed affected individuals in organizations or to check whether groups at particular points in time had shared ideas, so there was a clear gap in the literature and a need to allow researchers to study emergence in their longitudinal datasets.

What do you think was key to you winning this award?

The support of my coauthors—Paul D. Bliese (University of South Carolina) and Alex de Voogt (Drew University)—who won the award with me. I think it was a true team effort. The paper also went through several iterations because some of these ideas seemed unfamiliar to reviewers, especially when we first started to talk about it at conferences, so I think it was key that we hung in there.

What did you learn that was surprising to you? Did you have an “aha” moment? What was it?

I was quite surprised by the fact that changes in the intraclass correlation type 1 do not really provide much information about how teams change in consensus over time. The ICC1 is a quite common measure of “sharedness” and is reported in most articles. Intuitively, most people assume that the ICC1 can straightforwardly be estimated at each point in time. When we originally started with this research, we already had a sense that the ICC1 would be an imperfect measure for longitudinal datasets. However, what was surprising was the fact that there are circumstances that quite regularly occur in organizational research in which the ICC1 can be misleading. Trends in the ICC1 may even run counter to the true underlying trend in consensus emergence.

What do you see as the lasting/unique contribution of this work to our discipline? How can it be used to drive changes in organizations, the employee experience, and so on?

It is always hard to determine what element of a paper—if anything—will have a lasting impact. I think one important take-away message is that the emergence of a common climate and sense of meaning in an organization/group/team is at least as interesting and important to study as the impact that an organizational/group/team climate has on individuals. Another important take-away message is that emergence processes are a dynamic, complex phenomenon that we do not yet fully understand and have rarely studied. The goal of the article is to provide researchers with a tool to study this phenomenon. I think both messages directly translate to driving changes in organizations. In practice, we talk about change processes, and I think many practitioners have a good sense of how these processes work. There is a reason for that; for instance, Kurt Lewin’s classic work on unfreezing-change-refreezing is very popular (even though there is some debate whether he ever came up with this model in this form). However, statistically there is not an evidence-based equivalent to these types of processes in organizations and units. I think an important goal could be to develop this knowledge base by conducting more research in this area.

Who would you say was the biggest advocate of your research/work that resulted in the award? How did that person become aware of your work?

Probably my coauthor Paul (Bliese). When I do have an idea, I frequently ask him to do a solid reality/ usefulness/no-nonsense check, and this time he thought there was something in there, so we proceeded with the work.

To what extent would you say this work/research was interdisciplinary? 

Our research question certainly goes beyond I-O and is certainly theoretically relevant for other areas like social psychology, sociology, management, or clinical psychology (e.g., group therapy). Another interdisciplinary element was the fact that a group of archeologists agreed to take part in a data collection for one of the coauthors of the paper—Alex de Voogt—who has, himself, a background in archeology and anthropology. We used these data in the article, and there was huge interest from the archeology community about our research questions as they quite regularly face situations in which teams of people who do not know each other well before a mission all of a sudden need to work together closely.

What was the “turning point” moment where you started thinking about the problem/work through the other disciplines’ lenses? 

We realized that the problem may be more general than I-O psychology when we came across the link to Muzafer Sherif’s work. Sherif conducted studies of group norms in the 1930s, and many psychologists may remember his work from their social psychology introduction courses. We reanalyzed the data he published in his book chapters using the methods described in the article. This analysis is included in a recent book chapter that we published (Lang, J. W. B., & Bliese, P. D. [2018]. A temporal perspective on emergence: Using three-level mixed-effects models to track consensus emergence in groups. In S. E. Humphrey & J. M. LeBreton [Eds.], The handbook for multilevel theory, measurement, and analysis [pp. 519–540]. Washington, DC: APA.)

What, if any, were the challenges you faced doing this work across disciplines (e.g., different jargon)?

A general challenge in this area and across disciplines may be that terms are frequently mostly verbal descriptions, and it is not always clear how the theoretical ideas can be translated into actual research designs and statistical analyses. So, it is unclear to what degree terms converge across fields. We believe that the methodological approach we described in the paper provides some needed clarity in this area. We have also recently followed up with a more general paper on group processes in a journal for the broader psychology audience (Lang, J. W. B., Bliese, P. D., & Adler, A. B. [in press]. Opening the black box: A multilevel framework for studying group processes. Advances in Methods and Practices in Psychological Science. https://doi.org/10.1177/2515245918823722). We believe that the work can also be useful for research in many areas beyond I-O like fundamental work on group processes or in applications of psychology to jury decision making in criminal and civil cases.

What’s a fun fact about yourself (something that people may not know)?

In my free time, I play a lot of badminton—preferably doubles. I love traveling to the US because I really like blueberry pancakes for breakfast, and we do not really have them in Europe.

What piece of advice would you give to someone new to I-O psychology? (If you knew then what you know now…)

When I was an undergraduate student back at the University of Mannheim, one of our professors told us to “Learn research methods and measurement. When you want to become a clinical psychologist, there are a lot of things that the physicians can do better than you so the competition will be stiff. When you want to become an industrial and organizational psychologist, there is a lot that the business administration people can do better than you. They can present themselves and do a lot of internships [Germany at the time]. Two things you can do and where you can beat them are research methods and measurement so learn them and you will see that you are very valuable on the labor market.” At the time, I thought it was just some empty sales pitch so that people would come to lectures. I admit that it took me some time to realize that he was right. Of course, this was all before big data, analytics, and so on. So, when you ask, my advice would be to learn as much as possible about research methods and measurement. These skills are clearly the most important competencies for an I-O psychologist. From learning multilevel methods, you also learn multilevel theory and thinking, and this is something that one can easily use to actually help organizations. I would also recommend that people learn R (or possibly Python).

Another piece of advice I learned mostly by observing other successful researchers is to always be open. I think in research it is always very hard to have very strict rules on how to do things. You should develop concepts, rules, and guidelines on how to do things but then should also be open to being proved wrong. I always come across new work/articles and then need to admit, “I never thought about doing this and this this way.”

 

About the author:

Liberty Munson is currently the principal psychometrician of the Microsoft Technical Certification and Employability programs in the Worldwide Learning organization. She is responsible for ensuring the validity and reliability of Microsoft’s certification and professional programs. Her passion is for finding innovative solutions to business challenges that balance the science of assessment design and development with the realities of budget, time, and schedule constraints. Most recently, she has been presenting on the future of testing and how technology can change the way we assess skills.

Liberty loves to bake, hike, backpack, and camp with her husband, Scott, and miniature schnauzer, Apex. If she’s not at work, you’ll find her enjoying the great outdoors, or she’s in her kitchen tweaking some recipe just to see what happens.

Her advice to someone new to I-O psychology?

  • Statistics, statistics, statistics—knowing data analytic techniques will open A LOT of doors in this field and beyond!

 

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