Chapter 11 Design of PLS-Based Satisfaction Studies

In this chapter we focus on design of PLS structural equation model- ing with respect to satisfaction studies in general. Previous studies have found the PLS technique to be affected by things as the skewness of manifest variables, mul- ticollinearity between latent variables, misspecification, question order, sample size as well as the size of the path coefficients (Cassel et al. 1999; Auh et al. 2003; Eskildsen and Kristensen 2005; Kristensen and Eskildsen 2005a,b). In this chapter we expand on these contributions in order to provide the reader with recommenda- tions on all aspects included in designing PLS-based satisfaction studies. The recommendations are based on an empirical PLS project conducted at the Aarhus School of Business, Center for Corporate Performance. Within this project five different studies have been conducted that cover a variety of aspects of design- ing PLS-based satisfaction studies. The data used in subsequent sections comes from a variety of sources. In relation to the empirical PLS project at the Aarhus School off Business the following five different studies have been conducted: � Scale study � Empirical experiment � Simulation study - data collection � Simulation study - missing values � Empirical study of model specification for a customer satisfaction model