Analyzing factorial experimental data using PLS: an alternative approach and application in an online complaining context.

Abstract

Structural equation modeling (SEM) can be employed to emulate more traditional analysis techniques, such as MANOVA, discriminant analysis, and canonical correlation analysis. Recently, it has been realized that this emulation is not restricted to covariance-based SEM, but can easily be extended to components-based SEM, or partials least squares (PLS) path analysis (Guinot et al. 2001; Tenenhaus et al. 2005; Wetzels et al. 2005). In this paper we will apply PLS path analysis to a fixed-effects, between-subjects factorial design in a online complaint handling context. The results of our empirical study reveal that satisfaction with online recovery is determined by both the level of procedural and distributive justice. Furthermore, customers’ satisfaction with the way their complaints are handled has a positive influence on the customers’ intentions to repurchase and to spread positive word of mouth. Taking into account the entire chain of effects, we find the influence of justice perceptions on behavioral intentions is almost fully mediated by satisfaction. From a managerial perspective, the results of our study provide insight in how to design effective complaint handling strategies in order to maintain a satisfied and loyal customer base.