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Using WarpPLS in e-Collaboration Studies: Descriptive Statistics, Settings, and Key Analysis Results

Using WarpPLS in e-Collaboration Studies: Descriptive Statistics, Settings, and Key Analysis Results

Ned Kock
Copyright: © 2011 |Volume: 7 |Issue: 2 |Pages: 18
ISSN: 1548-3673|EISSN: 1548-3681|EISBN13: 9781613506745|DOI: 10.4018/jec.2011040101
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MLA

Kock, Ned. "Using WarpPLS in e-Collaboration Studies: Descriptive Statistics, Settings, and Key Analysis Results." IJEC vol.7, no.2 2011: pp.1-18. http://doi.org/10.4018/jec.2011040101

APA

Kock, N. (2011). Using WarpPLS in e-Collaboration Studies: Descriptive Statistics, Settings, and Key Analysis Results. International Journal of e-Collaboration (IJeC), 7(2), 1-18. http://doi.org/10.4018/jec.2011040101

Chicago

Kock, Ned. "Using WarpPLS in e-Collaboration Studies: Descriptive Statistics, Settings, and Key Analysis Results," International Journal of e-Collaboration (IJeC) 7, no.2: 1-18. http://doi.org/10.4018/jec.2011040101

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Abstract

This is a follow-up on a previous article (Kock, 2010b) discussing the five main steps through which a nonlinear structural equation modeling analysis could be conducted with the software WarpPLS (warppls.com). Both this and the previous article use data from the same e-collaboration study as a basis for the discussion of important WarpPLS features. The focus of this article is on specific features related to saving and analyzing grouped descriptive statistics, viewing and changing analysis algorithm and resampling settings, and viewing and saving the various minor and major results of the analysis. Even though its focus is on an e-collaboration study, this article contributes to the broad literature on multivariate analysis methods, in addition to the more specific research literature on e-collaboration. The vast majority of relationships between variables, in investigations of both natural and behavioral phenomena, are nonlinear; usually taking the form of U and S curves. Structural equation modeling software tools, whether variance- or covariance-based, typically do not estimate coefficients of association based on nonlinear analysis algorithms. WarpPLS is an exception in this respect. Without taking nonlinearity into consideration, the results can be misleading; especially in complex and multi-factorial situations such as those stemming from e-collaboration in virtual teams.

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