With this chapter, we seek to shed light on the question how headquarters (HQ) can cope with geographic distance and effectively transfer relevant knowledge to their subsidiaries. By constructing a mediating model, we aim at disentangling the effects of geographic distance on the relevance of HQ...

Partial least squares-based path modeling with latent variables is a methodology that allows to estimate complex cause-effect relationships using empirical data. The assumption that the data is collected from a single homogeneous population is often unrealistic. Identification of different...

Hwang and Takane (2004) introduced generalized structured component analysis (GSCA) as an alternative structural equation modeling technique. In a recent JMR article, Hwang et al. (forthcoming) claim to have analyzed the performance of GSCA relative to covariance-based structural equation...

Partial least squares analysis is a multivariate statistical technique that allows comparison between multiple response variables and multiple explanatory variables. Partial least squares is one of a number of covariance-based statistical methods which are often referred to as structural...