2023 - Research.com Social Sciences and Humanities in Netherlands Leader Award
His primary areas of investigation include Partial least squares regression, Partial least squares path modeling, Structural equation modeling, Covariance and Econometrics. His Partial least squares regression research is multidisciplinary, incorporating perspectives in Omnibus test, Empirical research, Information retrieval and Rendering. His studies deal with areas such as LISREL, Path, Latent variable and Operations research as well as Partial least squares path modeling.
Jörg Henseler has included themes like Variance, Categorical variable and Artificial intelligence in his Structural equation modeling study. The Covariance study combines topics in areas such as Monte Carlo method and Consistency. As a member of one scientific family, Jörg Henseler mostly works in the field of Econometrics, focusing on Statistical power and, on occasion, Sample size determination.
His primary scientific interests are in Marketing, Structural equation modeling, Partial least squares regression, Partial least squares path modeling and Path. He works mostly in the field of Marketing, limiting it down to concerns involving Advertising and, occasionally, Co-creation. His Structural equation modeling research focuses on Covariance and how it connects with Consistency.
His Partial least squares regression research includes themes of Empirical research, Econometrics, Factor analysis and Statistical power. The Partial least squares path modeling study which covers Strengths and weaknesses that intersects with Point. His research in Path intersects with topics in Algorithm, Data science and Artificial intelligence.
Jörg Henseler mainly investigates Marketing, Structural equation modeling, Partial least squares path modeling, Partial least squares regression and Field. His Marketing study combines topics from a wide range of disciplines, such as Creativity and Pragmatism. Jörg Henseler combines subjects such as Composite number, Monte Carlo method, Applied mathematics and Empirical research with his study of Structural equation modeling.
Jörg Henseler conducts interdisciplinary study in the fields of Partial least squares path modeling and Context through his works. His Partial least squares regression study integrates concerns from other disciplines, such as Specification and Business value. His study in Business value is interdisciplinary in nature, drawing from both Test, Latent variable, Causal information, Econometrics and Estimator.
Partial least squares path modeling, Partial least squares regression, Structural equation modeling, Monte Carlo method and Business value are his primary areas of study. The concepts of his Structural equation modeling study are interwoven with issues in Specification, Empirical research and Management information systems. His work carried out in the field of Empirical research brings together such families of science as Covariance, Machine learning, Artificial intelligence and Identification.
The Monte Carlo method study combines topics in areas such as Algorithm, Sample size determination, Outlier and Distortion. His Business value research is multidisciplinary, relying on both Test, Latent variable, Causal information, Econometrics and Estimator.
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The use of partial least squares path modeling in international marketing
Jörg Henseler;Christian M. Ringle;Rudolf R. Sinkovics.
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Joerg Henseler;Christian M. Ringle;Marko Sarstedt;Marko Sarstedt.
Journal of the Academy of Marketing Science (2015)
An empirical comparison of the efficacy of covariance-based and variance-based SEM
Werner Reinartz;Werner Reinartz;Michael Haenlein;Jörg Henseler.
Using PLS path modeling in new technology research: updated guidelines
Jörg Henseler;Geoffrey S. Hubona;Pauline Ash Ray.
Industrial Management and Data Systems (2016)
Common Beliefs and Reality About PLS: Comments on Rönkkö and Evermann (2013)
Joerg Henseler;Joerg Henseler;Theo K. Dijkstra;Marko Sarstedt;Marko Sarstedt;Christian M. Ringle;Christian M. Ringle.
Handbook of Partial Least Squares
Vincenzo Esposito Vinzi;Wynne W Chin;Jörg Henseler;Huiwen Wang.
Testing Moderating Effects in PLS Path Models: An Illustration of Available Procedures
Jörg Henseler;Georg Fassott;Vincenzo Esposito Vinzi;Wynne W. Chin.
Esposito Vinzi, V.; Chin, W.W.; Henseler, J.; Wang, H. [et al.] (eds.), Handbook of partial least squares : concepts, methods and applications in marketing and related fields (2010)
Goodness-of-fit indices for partial least squares path modeling
Jörg Henseler;Marko Sarstedt.
Computational Statistics (2013)
Multigroup Analysis in Partial Least Squares (PLS) Path Modeling: Alternative Methods and Empirical Results
Marko Sarstedt;Jörg Henseler;Christian M. Ringle.
Advances in International Marketing (2011)
A Comparison of Approaches for the Analysis of Interaction Effects Between Latent Variables Using Partial Least Squares Path Modeling
Jörg Henseler;Wynne W. Chin.
Structural Equation Modeling (2010)
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