Purpose – Partial least squares (PLS) path modeling is a variance-based structural equation modeling (SEM) technique that is widely applied in business and social sciences. Its ability to model composites and factors makes it a formidable statistical tool for new technology research. Recent reviews, discussions, and developments have led to substantial changes in the understanding and use of PLS. The paper aims to discuss these issues. Design/methodology/approach – This paper aggregates new insights and offers a fresh look at PLS path modeling. It presents new developments, such as consistent PLS, confirmatory composite analysis, and the heterotrait-monotrait ratio of correlations. Findings – PLS path modeling is the method of choice if a SEM contains both factors and composites. Novel tests of exact fit make a confirmatory use of PLS path modeling possible. Originality/value – This paper provides updated guidelines of how to use PLS and how to report and interpret its results.

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More powerful contemporary computer hardware has enabled the development and exploration of a wide variety of techniques to depict spatial characteristics of computer-generated objects in three-dimensional (3D) space. Particularly, the role of stereoscopic viewing and the use of object motion to reflect the position and size of objects in 3D space have been extensively studied. However, the effective use of computer-rendered object shadows to provide spatial information about the relative position and size of objects in virtual space has not. Subjects perform two tasks with 3D geometric patterns of objects presented on a computer screen: (1) positioning the object to complete a symmetrical geometric figure and (2) resizing the object to match the size of other objects. Performance accuracy and speed are recorded under the following conditions: (1) objects casting shadows on and off, (2) shadows from one or two light sources (nested within the shadows-on condition), (3) stereoscopic and monoscopic viewing, and (4) different scene backgrounds: flat plane (i.e., floor), "stair-step" floor with no walls, and floor with walls (i.e., room). The use of object shadows as depth cues enhances the accuracy (but not the speed) of object positioning, but does not enhance either the accuracy or the speed of object resizing. Moreover, the object shadows are not as effective as stereoscopic viewing in facilitating both positioning-task and resizing-task performances. Furthermore, task performances degrade with the stair-step scene background and when the number of shadowing light sources increases from one to two.