Survey Research Methods

Abstract and Learning Objectives

Despite the availability of vast amounts of secondary data, there is little doubt that survey research continues to play an important role in economic research. Carefully conducted surveys allow researchers to gain an understanding of the nature of and relationships among unobserved conceptual variables and provide insights into consumer perceptions, attitudes, and intentions. While it may seem easy to create a questionnaire (just ask what you want to know, right?), there are many problems that can turn good intentions into bad results. Developing questionnaires to measure unobserved conceptual variables also requires a solid understanding of measurement theory and the steps required to operationalize constructs. The first part of this course is designed to familiarize participants with the key design decisions for good surveys and the principles of measurement theory.

Complementing these topics, the second part of the course introduces participants to partial least squares structural equation modeling (PLS-SEM), a method that has recently gained massive dissemination in a variety of business research fields. More precisely, the course offers an introduction to PLS-SEM by familiarizing participants with the principles of model estimation and evaluation. In addition to these foundations, the course also covers advanced topics from the field of PLS-SEM (e.g., higher-order modeling, confirmatory tetrad analysis, measurement invariance). Practical applications and the use of the software application SmartPLS 4 (http://www.smartpls.com) are an integral part of this course.

Date of Event:

September 12-15, 2023


Ludwig-Maximilians-Universität München
Institut für Marketing
Raum 329
Ludwigstr. 28 RG/III
80539 München

Prof. Dr. Sascha Raithel, Freie Universität (FU) Berlin

Prof. Dr. Christian M. Ringle, Technische Universität Hamburg (TUHH)

Prof. Dr. Marko Sarstedt, Ludwig-Maximilians-Universität (LMU) München


Click for information on fees, payment and registration,

or email us: prodok@vhbonline.org.


Registration Deadline: August 13, 2023