Scott Tonidandel

Dr. Scott Tonidandel is a professor of management in the Belk College of Business and the director of the Organizational Science doctoral program at UNC Charlotte.

Scott’s research interests include issues related to leadership effectiveness, the impact of diversity in organizations and research methods and statistics. His recent work focuses on people analytics and the interface of big data and the organizational sciences. He co-edited the SIOP Frontiers series volume titled Big Data at Work: The Data Science Revolution and Organizational Psychology and recently completed work on a NSF funded project that uses sensors to understand team interactions and the impact of diversity.

Scott serves as an associate editor for the Journal of Business and Psychology, is a former associate editor for Organizational Research Methods, and is a fellow of the Association for Psychological Science, the American Psychological Association and the Society for Industrial and Organizational Psychology.

Education

Ph.D., 2001
Industrial/Organizational Psychology
Rice University

Master of Arts, 1999
Psychology
Rice University

Bachelor of Arts, 1996,
Psychology with Honors, cum laude
Davidson College

Summer Program, 1994
London School of Economics

Research Interests

• Using AI to score open-ended assessments
• Using machine learning to examine the challenges faced by leaders
• Assessing leaders using natural language processing
• Leveraging machine learning for personnel selection and assessment
• What makes someone an ethical leader?
• How to be a transformational leader

Publications

Thompson, I., Koenig, N., Mracek, D., & Tonidandel, S. (2023). Deep learning in employee selection: Evaluation of algorithms to automate the scoring of open-ended assessments. Journal of Business and Psychology, 38, 509–527. https://doi.org/10.1007/s10869-023-09874-y  

Tonidandel, S., & Albritton, B. H. (2023). Transforming Leadership Assessment using Natural Language Processing. In T. Kantrowitz, D. H. Reynolds, & J. Scott (Eds.), Talent assessment: Embracing innovation and mitigating risk in the digital age. Essay, Oxford University Press. https://doi.org/10.1093/oso/9780197611050.001.0001

Koenig, N., Tonidandel, S., Thompson, I., Albritton, B., Koohifar, F., Yankov, G., Speer, A., Hardy, J. H., Gibson, C., Frost, C., Liu, M., McNeney, D., Capman, J., Lowery, S., Kitching, M., Nimbkar, A., Boyce, A., Sun, T., Guo, F., … Newton, C. (2023). Improving measurement and prediction in personnel selection through the application of machine learning. Personnel Psychology, 00, 1–63. Advance online publication. https://doi.org/10.1111/peps.12608

Tonidandel, S., Summerville, K.M., Gentry, W.A., Young, S. (2022). Using structural topic modeling to gain insight into challenges faced by leaders. The Leadership Quarterly, 33(5). https://doi.org/10.1016/j.leaqua.2021.101576

Banks, G. C., Ross, R., Toth, A. A., Tonidandel, S., Goloujeh, A. M., Duo, W. W., & Wesslyn, R. (2022). The triangulation of ethical leader signals using qualitative, experimental, and data science methods. The Leadership Quarterly, https://doi.org/10.1016/j.leaqua.2022.101658

Stock, G., Banks, G. C., Voss, E. N., Tonidandel, S., & Woznyj, H. (2022). Putting leader (follower) behavior back into transformational leadership: A theoretical and empirical course correction. The Leadership Quarterly. https://doi.org/10.1016/j.leaqua.2022.101632.