Marko Sarstedt Which Metrics Perform Best in PLS Model Comparisons?
Marko Sarstedt is Chaired Professor of Marketing at Ludwig-Maximilians-University München and won the 2018 Research Award. He is also an Adjunct Professor at Babeș-Bolyai University, Cluj. Sarstedt has previously worked at the University of Newcastle (Australia) and Ludwig Maximilian University of Munich. His research focuses on consumer behavior and on the improvement of marketing decision making. The winner of five Emerald Citations of Excellence and two AMS William R. Darden awards, in 2020, Sarstedt was judged the second most influential business researcher in Germany, Austria and Switzerland (F.A.Z.-Ökonomenranking).
Area of Research
Marketing, Structural Equation Modeling, Partial Least Squares, Context Effects
since 2018
Adjunct Professor
Babeș-Bolyai-University Cluj
2012-2021
Professor of Marketing
Otto-von-Guericke University Magdeburg (Otto-von-Guericke-Universität Magdeburg) (more details)
Fakultät für Wirtschaftswissenschaft
2011-2018
Conjoint Professor
University of Newcastle
2010-2012
Associate Professor for Quantitative Methods in Marketing & Management
Ludwig Maximilian University Munich (Ludwig-Maximilians-Universität München)
Department of Economics
2009-2009
Visiting Professor
University of Technology Sydney
2008-2008
Visiting Professor
Villanova University
Villanova School of Business
2008-2010
Assistant Professor
Ludwig Maximilian University Munich (Ludwig-Maximilians-Universität München)
Institute for Market-based Management
since 2021
Chaired Professor of Marketing
Ludwig Maximilian University Munich (Ludwig-Maximilians-Universität München)
Department of Economics
2006-2007
Master of Business Research
Ludwig Maximilian University Munich (Ludwig-Maximilians-Universität München)
2003-2005
Diploma
Ludwig Maximilian University Munich (Ludwig-Maximilians-Universität München)
Prizes
- Best textbook award, Verband der Hochschullehrer für Betriebswirtschaft for Advanced Issues in Partial Least Squares Structural Equation Modeling (2019)
- Emerald Citations of Excellence Award 2017 for the Article “Partial Least Squares Structural Equation Modeling (PLS-SEM): An Emerging Tool in Business Research,” Published in European Business Review
- Emerald Citations of Excellence Award 2017 for the Article “A New Criterion for Assessing Discriminant Validity in Variance-based Structural Equation Modeling” Published in Journal of the Academy of Marketing Science
- Emerald Citations of Excellence Award 2017 for the Article “Common Beliefs and Reality About PLS: Comments on Rönkkö and Evermann (2013),” Published in Organizational Research Methods
- Taylor & Francis Citation Award for the Article “PLS-SEM. Indeed a Silver Bullet,” Published in Journal of Marketing Theory & Practice
- Outstanding Paper Award 2014 for the Article “Partial Least Squares Structural Equation Modeling (PLS-SEM): An Emerging Tool in Business Research,” Published in European Business Review
- Best Paper Award in the Advancing Research Methods Track at the 2010 Global Marketing Conference, Tokyo, Japan
- William R. Darden Award at the 2009 Annual Conference of the Academy of Marketing Science, Baltimore, USA
- Dissertation Award of the Munich School of Management
- Best Paper Award in the Integrated Marketing Communications Track at the 2008 Global Marketing Conference, Shanghai, China
- Acquisition of Industry Funds through the Corporate Reputation Monitor, a Corporate Branding Instrument Used by Several Major DAX Companies (e.g., Allianz, BMW Group, Deutsche Telekom)
- Cooperation with YouGov Panel Germany for Database Access
- Grant from the German Academic Exhange Service for a Research Say at the University of Technology Sydney, Australia
- Grant from the German Academic Exhange Service for Presenting a Special Session at the 2011 Annual Conference of the Academy of Marketing, Coral Gables, USA
- Three-Year Research Project with Volkswagen AG
- Research Co-operations with Local SMEs (SWM, MDWI)
© Otto von Guericke Universität Magdeburg
Otto-von-Guericke University Magdeburg (Otto-von-Guericke-Universität Magdeburg)
Magdeburg, GermanyFounded 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)
Research Group
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)
Map
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
