Aktuelles / News
Die Klausureinsicht für die Veranstaltungen Marketing, Marketing Performance Management und Marketing Management findet am 19.04.2018 von 8 bis 9 Uhr im Raum G22A-362 statt.
The exam inspection for the courses Marketing, Marketing Performance Management, and Marketing Management will be held on April 19, 2018 between 8 and 9 a.m. in room G22A-362.
Optimiertes Babymanagement live! Im Rahmen einer Buchpräsentation am Sonntag, dem 18. März 2018, von 10:30 bis 11:00 Uhr auf der Leipziger Buchmesse geht Professor Sarstedt elementaren Fragen des Elterndaseins nach und illustriert die Schönheit betriebswirtschaftlicher Optimierungsmethoden. Mehr Informationen zur Veranstaltung finden sich in der Pressemitteilung des Springer-Verlags.
The article titled "Heuristics versus statistics in discriminant validity testing: A comparison of four procedures,“ authored by George Franke (University of Alabama) and Marko Sarstedt has been accepted for publication in Internet Research, a leading journal in the management information systems field (impact factor: 2.93). This study reviews and extends recent simulation studies on discriminant validity measures, contrasting the use of cutoff values (i.e., heuristics) with inferential tests. Based on a simulation study, which considers different construct correlations, sample sizes, numbers of indicators, and loading patterns, the study assesses each criterion’s sensitivity to type I and type II errors. The findings provide further evidence for the robustness of the heterotrait-monotrait ratio of correlations (HTMT) criterion as an estimator of disattenuated (perfectly reliable) correlations between constructs, whose performance parallels that of the standard constrained Phi approach. Furthermore, the study dentify situations in which both methods fail and suggest an alternative criterion.
Franke, George and Sarstedt, Marko (2018). "Heuristics versus statistics in discriminant validity testing: A comparison of four procedures,“ Internet Research, forthcoming.
Two papers on the use of partial least squares structural equation modeling (PLS-SEM) in hospitality management and human resource management have recently been accepted for publication. In both papers, the authors critically review the use of the PLS-SEM in the corresponding fields, derive guidelines for the method’s use in future studies, and offer recommendations for future research on the method. The first paper will appear in International Journal of Contemporary Hospitality Management, which is the leading journal in the field with an Impact Factor of 3,196. The second paper will be published in International Journal of Human Resource Management, a premier journal in the field with an Impact Factor of 1,65.
Ali, Faizan, S. Mostafa Rasoolimanesh, Marko Sarstedt, Christian M. Ringle, and Kisang Ryu (2018). “An Assessment of the Use of Partial Least Squares Structural Equation Modeling (PLS-SEM) in Hospitality Research,” International Journal of Contemporary Hospitality Management, forthcoming.
Ringle, Christian M., Marko Sarstedt, Rebecca Mitchell, and Siegfried P. Gudergan (2018). “Partial Least Squares Structural Equation Modeling in Human Resource Management Research,” International Journal of Human Resource Management, forthcoming.
We’re happy to announce the publication of our latest book, “Market Research. The Process, Data, and Methods Using Stata.” Authored by Erik Mooi (University of Melbourne), Marko Sarstedt, and Irma Mooi-Reci (University of Melbourne) the book is an easily accessible and comprehensive guide for researchers and students who wish to know more about the process, data management, and most commonly used methods in market research using Stata. The book is engaging, hands-on and includes many practical examples, tips and suggestions that make it easy for the readers to apply and interpret quantitative methods such as regression, factor and cluster analysis.
The website https://www.guide-market-research.com/stata/ contains further details on the book, instructor resources, and a sample chapter on principal component and factor analysis.