SEM techniques that attempt to minimize the differences between the observed and predicted covariance matrices.
Published in Chapter:
Using Partial Least Squares in Digital Government Research
J. Ramon Gil-Garcia (Centro de Investigación y Docencia Económicas, Mexico)
Copyright: © 2008
|Pages: 15
DOI: 10.4018/978-1-59904-857-4.ch023
Abstract
Digital government is a complex socio-technical phenomenon, which is affected by technical, managerial, institutional, and environmental factors (Dawes & Pardo, 2002; Fountain, 2001; Gant, 2003; Garson, 2000; Heeks, 2005; Kraemer, King, Dunkle et al., 1989; Landsbergen & Wolken, 2001; Laudon, 1985; Rocheleau, 2003). Recent studies have greatly contributed to developing the necessary knowledge about e-government benefits and success factors (Barrett & Greene, 2000; Dawes, 1996; Gil-García & Pardo, 2005; Heeks, 2003; Holmes, 2001; O’Looney, 2002; Rocheleau, 1999; West, 2005; Zhang et al., 2002). However, an important portion of this research has used a single measure of e-government and relatively simple assumptions about the relationships between information technologies and organizational, institutional, and contextual factors (Gil-García, 2005b).