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Book ChapterDOI

Use of ULS-SEM and PLS-SEM to Measure a Group Effect in a Regression Model Relating Two Blocks of Binary Variables

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TLDR
In this article, the use of unweighted least squares (ULS) structural equation modeling (SEM) and partial least squares path modeling in a regression model relating two blocks of binary variables, when a group effect can influence the relationship.
Abstract
The objective of this paper is to describe the use of unweighted least squares (ULS) structural equation modeling (SEM) and partial least squares (PLS) path modeling in a regression model relating two blocks of binary variables, when a group effect can influence the relationship. Two sets of binary variables are available. The first set is defined by one block X of predictors and the second set by one block Y of responses. PLS regression could be used to relate the responses Y to the predictors X, taking into account the block structure. However, for multigroup data, this model cannot be used because the path coefficients can be different from one group to another. The relationship between Y and X is studied in the context of structural equation modeling. A group effect A can affect the measurement model (relating the manifest variables (MVs) to their latent variables (LVs)) and the structural equation model (relating the Y -LV to the X-LV). In this paper, we wish to study the impact of the group effect on the structural model only, supposing that there is no group effect on the measurement model. This approach has the main advantage of allowing a description of the group effect (main and interaction effects) at the LV level instead of the MV level. Then, an application of this methodology on the data of a questionnaire investigating sun exposure behavior is presented.

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Book ChapterDOI

Testing Moderating Effects in PLS Path Models: An Illustration of Available Procedures

TL;DR: In this paper, the identification and quantification of moderating effects in complex causal structures by means of Partial Least Squares Path Modeling is discussed. But the authors do not consider the effect of group comparisons.
Book ChapterDOI

PLS Path Modeling: From Foundations to Recent Developments and Open Issues for Model Assessment and Improvement

TL;DR: The authors introduce the development of new estimation modes and schemes for multidimen- sional (formative) constructs, i.e. the use of PLS Regression for formative indicators, and the uses of path analysis on latent variable scores to estimate path coefficients.
Journal ArticleDOI

Assessing between-group differences in information systems research: a comparison of covariance-and component-based SEM

TL;DR: This paper compares the conditions under which covariance-based multigroup analysis is more appropriate as well as those under which there either is no difference or the component-based approach is preferable, and finds that when data are normally distributed, with a small sample size and correlated exogenous variables, the component's approach is more likely to detect differences between-group than is the covariance's approach.
Journal ArticleDOI

Knowledge driven preferences in informal inbound open innovation modes. An explorative view on small to medium enterprises

TL;DR: The empirical research was conducted on 175 small to medium enterprises in the United Kingdom, suggesting that the knowledge-driven approach is the strongest determinant, leading to a preference for informal inbound OI modes.
Journal ArticleDOI

The effect of social networking sites and absorptive capacity on SMES’ innovation performance

TL;DR: In this article, the role of social networking sites in relation to innovation and knowledge in small-to medium enterprises has been investigated, and recommendations are proffered as to what small-medium enterprises should do in order to enhance their innovativeness.
References
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Journal ArticleDOI

A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study

TL;DR: A new latent variable modeling approach is provided that can give more accurate estimates of interaction effects by accounting for the measurement error that attenuates the estimated relationships.
Journal ArticleDOI

PLS path modeling

TL;DR: PLS path modeling can be used for analyzing multiple tables so as to be related to more classical data analysis methods used in this field and some new improvements are proposed.
Journal ArticleDOI

The American Customer Satisfaction Index: Nature, Purpose, and Findings

TL;DR: The American Customer Satisfaction Index (ACSI) as discussed by the authors is a new market-based performance measure for firms, industries, economic sectors, and national economies that measures the satisfaction of customers.
Journal ArticleDOI

The SU.VI.MAX Study: a randomized, placebo-controlled trial of the health effects of antioxidant vitamins and minerals.

TL;DR: After 7.5 years, low-dose antioxidant supplementation lowered total cancer incidence and all-cause mortality in men but not in women, suggesting that supplementation may be effective in men only because of their lower baseline status of certain antioxidants, especially of beta carotene.
Journal ArticleDOI

A Parsimonious Estimating Technique for Interaction and Quadratic Latent Variables

TL;DR: In this article, an alternative estimation technique for quadratic and interaction latent variables in structural equation models using LISREL, EQS, and CALIS is proposed, which specifies these vari...