dr. F. Schuberth (Florian)

I graduated in Economics from the University of Wuerzburg. Subsequently, I did my Ph.D. under the supervision of Prof. Dr. Martin Kukuk (University of Würzburg) and Prof. Dr. Jörg Henseler (University of Twente) at the Chair of Econometrics at the University of Wuerzburg. My main research interests are composite-based methods for structural equation modeling (SEM), and the composite model.

Occasionally, I instruct seminars on PLS path modeling at the PLS School,

Business & Economics

# Information Systems Research
# Modeling
# Monte Carlo Simulation
# Partial Least Squares
# Structural Equation Modeling

Mathematics

# Partial Least Squares
# Structural Equation Modeling

Social Sciences

# Structural Model

Faculty of Engineering Technology (ET), Product–Market Relations (PMR)

Yu, X. (2023). Incorporating Composites in Structural Equation Modeling: Exploiting the Henseler—Ogasawara Specification. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036557214

Schuberth, F. (2023). A new approach for specifying composites in structural equation models: The Henseler–Ogasawara Specification. Abstract from 10th European Congress of Methodology, EAM 2023, Ghent, Belgium.

Schuberth, F., Schamberger, T. , & Henseler, J. (Accepted/In press). More powerful parameter tests? No, rather biased parameter estimates. Some reflections on path analysis with weighted composites. Behavior research methods.

Müller, T. (2023). Studying theoretical concepts in management research: Categorization, operationalization, and validation using partial least squares path modeling. [PhD Thesis - Research external, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036555395

Schuberth, F., Hubona, G., Roemer, E., Zaza, S., Schamberger, T., Chuah, F., Cepeda-Carrión, G. , & Henseler, J. (2023). The choice of structural equation modeling technique matters: A commentary on Dash and Paul (2021). Technological forecasting and social change, 194, [122665]. https://doi.org/10.1016/j.techfore.2023.122665

Schuberth, F., Schamberger, T., Rönkkö, M., Liu, Y. , & Henseler, J. (Accepted/In press). Premature Conclusions about the Signal-to-Noise Ratio in Structural Equation Modeling Research: A Commentary on Yuan and Fang (2023). British journal of mathematical and statistical psychology.

Castillo, A., Ruiz, L., Benitez, J. , Schuberth, F., & Reina, R. (2023). IT impact on open innovation performance: Insights from a large-scale empirical investigation. Decision support systems, [114025]. https://doi.org/10.1016/j.dss.2023.114025

Yu, X. , Schuberth, F. , & Henseler, J. (Accepted/In press). Specifying composites in growth curve analysis. Abstract from Advanced Techniques for Longitudinal Data Analysis in Social Science, ATLASS 2023 , Bielefeld, North Rhine-Westphalia, Germany.

Yu, X. , Schuberth, F. , & Henseler, J. (2023). Specifying composites in structural equation modeling: A refinement of the Henseler-Ogasawara specification. Statistical Analysis and Data Mining, 16(4), 348-357. https://doi.org/10.1002/sam.11608

Schuberth, F., Rosseel, Y., Rönkkö, M., Trinchera, L., Kline, R. B. , & Henseler, J. (2023). Structural parameters under partial least squares and covariance-based structural equation modeling: A comment on Yuan and Deng (2021). Structural equation modeling, 30(3), 339-345. https://doi.org/10.1080/10705511.2022.2134140

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I mainly train students in quantitative research methods.

Bachelor

Creative Technology

Master

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