Marko Sarstedt Which Metrics Perform Best in PLS Model Comparisons?
© Otto von Guericke Universität Magdeburg
Otto-von-Guericke University Magdeburg (Otto-von-Guericke-Universität Magdeburg)Magdeburg, Germany
Founded in 1993, the Otto von Guericke University Magdeburg is one of the youngest universities in Germany. As a catalyst and driver of innovation, both in the region and well beyond, the Otto von Guericke University Magdeburg pursues innovative strategies for reinforcing the transfer of technology and knowledge in regional and international enterprises. The university’s main focus of expertise is in the traditional areas of engineering, the natural sciences and medicine. It also views economics and management and the social sciences and humanities as essential disciplines for a modern university in the information age. The key areas of research transfer are automotive, digital engineering, medical technology, and renewable energies. (more)
Consumer Research Group
The Consumer Research group (CoRe) at the Otto von Guericke University Magdeburg seeks to generate insights about different consumer groups, their preferences, and the mechanisms that trigger certain behaviors. Numerous examples from management practice such as Apple, Google, and Uber show that consumer-centric management is the key to company success. However, successfully managing consumer relationships requires developing a thorough understanding of their varying needs and wants. Specifically, marketers now recognize that consumer behavior is a dynamic process, which goes well beyond what happens at the point-of-sale. The analysis of consumer behavior covers the entire consumption process and requires a holistic multi-method approach. Following this concept, researchers at CoRe conduct and disseminate rigorous research in the fields of choice anomalies, the physiology of consumer behavior, and research methodology. Regular publications in internationally renowned scientific journals are proof of the outstanding research work conducted at CoRe. Several of these publications are among the most frequently cited articles in the social sciences. (more)
Social science researchers need to use modeling to understand complex real-life phenomena. But how does a researcher decide which of the available models is most appropriate? In this video, MARCO SARSTEDT analyzes the metrics employed by researchers in assessing PLS (Partial Least Squares) models, outlining how such assessments can be optimized. Running a Monte Carlo simulation study, Sarstedt explains the inadequacies (for PLS researchers) of commonly used metrics like R² and the Goodness of Fit index by comparison with information criteria like BIC and GM. Offering suggestions as to how these metrics should ideally be implemented, Sarstedt notes that further work is required to assess whether their advantages extend to studies which employ more complex modeling.
LT Video Publication DOI: https://doi.org/10.21036/LTPUB10696
PLS-Based Model Selection: The Role of Alternative Explanations in Information Systems Research
- P. N. Sharma, M. Sarstedt, G. Shmueli, K. H. Kim and K. O. Thiele
- Journal of the Association for Information Systems
- Published in 2019