Jenny Baker
/ Categories: 584

SIOP Award Winners: Hogan Award for Personality and Work Performance

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 winners of the Hogan Award for Personality and Work Performance: Filip Lievens and Ronald Bledow from Singapore Management University and Jonas Lang, Filip De Fruyt, Jan Corstjens, and Myrjam Van de Vijver from Ghent University.

L to R: Filip Lievens, Jonas W. B. Lang, Filip De Fruyt, Jan Corstjens, Myrjam Van de Vijver, Ronald Bledow

The title of the paper was “The Predictive Power of People’s Intraindividual Variability Across Situations: Implementing Whole Trait Theory in Assessment” (Journal of Applied Psychology, 2018, vol. 103, pp. 753–771).

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

We are a team of researchers from Singapore Management University (SMU) and Ghent University. We have been working together for some years on various projects.

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

The project lasted about 5 years. We were familiar with the main tenets of whole trait theory in personality psychology. Whole trait theory proposes a broader and more contemporary trait concept. The overarching idea is that although traits provide a useful summary of a person’s general behavioral tendencies (e.g., their level of sociability) across many situations, additional information can be obtained if we know how much variability in trait expressions the person displays across various situations. Therefore, to improve prediction in an assessment context, we reasoned that we should measure both between- and within-person trait variability. However, the implications of this new paradigm that emphasizes both the level and the variability of traits had not found its way into the field of assessment, selection, and prediction. Probably, this was because in an assessment context it is practically difficult to ask candidates to complete a diary on different moments or to come back on several occasions for repeated assessment.

Our studies presented test takers with a large set of written situations (like in a situational judgment test, SJT) followed by response options that varied in terms of trait levels (higher vs. lower). This allowed us to compute people’s mean-level scores as well as their variation across situations and to use these mean-level as well as variability scores for prediction purposes.

In three studies (either in student or employee samples), both test takers’ mean trait scores and the variability of their responses across multiple written job-related situations of an SJT were assessed. Results revealed that people’s intraindividual variability (a) was related to their self-rated adaptability, (b) predicted performance above their mean scores, and (c) predicted their actual personality state variability over 10 days.

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

This is always difficult to say, but the paper has both conceptual and practical appeal: Theoretically, this paper integrates a broader and more contemporary trait conceptualization (whole trait theory) into assessment and prediction. This means that not only between-person differences but also people’s within-person variability across situations is assessed. This expansion adds a more dynamic assessment perspective to the traditional static approaches that have dominated personality selection for years. Whereas within-person variability has been one of the major themes in OB, this study is one of the first to adopt it in an assessment context. At a practical level, this paper presents a different and more comprehensive approach of assessing personality traits. That is, we redesigned situational judgment tests (SJTs) to assess such intraindividual variability across situations. We developed a new SJT but also showed how it could be applied to already existing SJTs.

What do you learn that surprised you? Did you have an “aha” moment? What was it? 

As far as I recall, there were two “aha” moments: First, we established evidence that intraindividual variability in people’s responses to written SJT situations predicted actual intraindividual variability as captured by a diary study 2 years later. We found this remarkable because we are the first to link SJT scores to future diary-study ratings. Second, after the first review, we realized that the associate editor and the reviewers were correct that using the standard deviation to assess within-person variability in SJTs would be a confounded index. It could also reflect varying degrees of difficulty, for instance. Fortunately, we discovered that recent advances in IRT modelling (IRT tree models) led to a more sophisticated approach for disentangling the relevant sources of variance and obtaining an unconfounded index of within-person variability.

What was the “turning point” moment where you started thinking about the problem/work through the other disciplines' lenses?  To what extent would you say this work/research was interdisciplinary? How do you think the work benefitted by having multiple disciplines involved? 

This project required expertise related to within-person variability, SJTs, personality, and IRT modelling. So, it was great that we had a diverse team. The idea for the project stemmed from the SJT field. However, SJT studies often do not pay a lot of attention to what is being measured. Therefore, we enriched the SJT field by drawing on insights from recent developments in the personality domain (whole trait theory).

Are you still doing work/research in the same area where you won the award? If so, what are you currently working on in this space? If not, what are you working on now, and how did you move into this different work/research area? 

Yes, we are expanding this idea to measure within-person variability (adaptability) to other selection procedures. So, we aim to examine other methods for assessing within-person variability as part of the assessment process. A related project deals with multiple speed assessment in which candidates go through many short role-plays in a carousel-like approach. Moreover, we want to examine whether the assessment of people’s within-person variability can also predict other criterion components. In this study, self-reported actual personality state variability across days and performance ratings provided by supervisors served as external variables. In the future, we recommend linking intraindividual variability to adaptive and leadership performance.

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

When the paper is being published, I have the habit of inviting all coauthors for dinner in an excellent restaurant to celebrate our teamwork and the result of it. 

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

Work hard and play hard.


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 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!

1512 Rate this article:
No rating
Comments are only visible to subscribers.


Information on this website, including articles, white papers, and other resources, is provided by SIOP staff and members. We do not include third-party content on our website or in our publications, except in rare exceptions such as paid partnerships.