Research methods

A major goal of marketing research is to analyze and understand consumer perception and behavior. However, the investigation of corresponding effects places high demands on research methods. Against this background, we are concerned with evaluating existing and developing new techniques for modeling relationships between phenomena that are not directly observable, such as customer satisfaction or corporate reputation. The research interest is directed toward structural equation modeling, particularly Partial Least Squares Structural Equation Modeling (PLS-SEM).

Recent publications
Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2024). Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd Edition). Thousand Oaks: Sage
Adler, S. J., Sharma, P. N., & Radomir, L. (2023). Toward open science in PLS-SEM: Assessing the state of the art and future perspectives. Journal of Business Research, 169, 114291.
Cho, G., Hwang, H., Sarstedt, M., & Ringle, C. M. (2022). A Prediction-Oriented Specification Search Algorithm for Generalized Structured Component Analysis. Structural Equation Modeling: A Multidisciplinary Journal, 29(4), 611-619.
Cho, G., Sarstedt, M., & Hwang, H. (2022). A comparative evaluation of factor- and component-based structural equation modelling approaches under (in)correct construct representations. British Journal of Mathematical and Statistical Psychology, 75(2), 220-251.
Franke, G., Sarstedt, M., & Danks, N. (2021). Assessing measure congruence in nomological networks. Journal of Business Research, 130, 318-334.
Sarstedt, M. & Danks, N. P. (2022). Prediction in HRM research − A gap between rhetoric and reality. Human Resource Management Journal, 32(2), 485-513. Video abstract.
Sarstedt, M., Hair, J. F., Pick, M., Liengaard, B. D., Radomir, L., & Ringle, C. M. (2022). Progress in partial least squares structural equation modeling use in marketing in the last decade. Psychology & Marketing, 39(5), 1035-1064.
Sarstedt, M., Radomir, L., Moisescu, O. I., & Ringle, C. M. (2022). Latent class analysis in PLS-SEM: A review and recommendations for future applications. Journal of Business Research, 138, 398-407.