Book ChapterDOI
How to Write Up and Report PLS Analyses
Wynne W. Chin
- pp 655-690
Reads0
Chats0
TLDR
A discussion of key differences and rationale that researchers can use to support their use of PLS is provided, followed by two examples from the discipline of Information Systems.Abstract:
The objective of this paper is to provide a basic framework for researchers interested in reporting the results of their PLS analyses. Since the dominant paradigm in reporting Structural Equation Modeling results is covariance based, this paper begins by providing a discussion of key differences and rationale that researchers can use to support their use of PLS. This is followed by two examples from the discipline of Information Systems. The first consists of constructs with reflective indicators (mode A). This is followed up with a model that includes a construct with formative indicators (mode B).read more
Citations
More filters
Journal ArticleDOI
The effects of vulnerability mitigation strategies on supply chain effectiveness: risk culture as moderator
TL;DR: In this article, the relationship between vulnerability mitigation strategies and supply chain effectiveness with security culture as a moderator was explored with data gathered via a survey of 209 Indonesian manufacturing firms, and the data were analyzed using partial least squares technique.
Journal ArticleDOI
Perceived information transparency in B2C e-commerce: An empirical investigation
TL;DR: It is found that product transparency, vendor transparency, and transaction transparency significantly influence perceived information transparency; perceived information Transparency significantly increases consumers’ online purchase intention; and perceived risk partially mediates the effects of perceived informationparency on purchase intention.
Journal ArticleDOI
Does big data enhance firm innovation competency? The mediating role of data-driven insights
Maryam Ghasemaghaei,Goran Calic +1 more
TL;DR: In this paper, the authors collected data from 280 middle and top-level managers to investigate the impact of each big data characteristic (i.e., data volume, data velocity, data variety, and data veracity) on firm innovation competency mediated through data-driven insight generation.
Journal ArticleDOI
How organizational pride and emotional exhaustion explain turnover intentions in call centers
TL;DR: In this paper, the authors examined how emotional exhaustion and organizational pride affect turnover intentions in call center agents and investigated the moderating effects of gender and organizational tenure on the job demands-resources model.
Journal ArticleDOI
Age and gender differences in online travel reviews and user-generated-content (UGC) adoption: extending the technology acceptance model (TAM) with credibility theory
TL;DR: In this paper, the effects of trustworthiness, expertize, perceived usefulness (PU), and perceived ease of use (PEOU) on usage intention toward user-generated content (UGC) and online reviews were examined.
References
More filters
Book
Statistical Power Analysis for the Behavioral Sciences
TL;DR: The concepts of power analysis are discussed in this paper, where Chi-square Tests for Goodness of Fit and Contingency Tables, t-Test for Means, and Sign Test are used.
Journal ArticleDOI
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Claes Fornell,David F. Larcker +1 more
TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
Journal ArticleDOI
Cross-Validatory Choice and Assessment of Statistical Predictions
TL;DR: In this article, a generalized form of the cross-validation criterion is applied to the choice and assessment of prediction using the data-analytic concept of a prescription, and examples used to illustrate the application are drawn from the problem areas of univariate estimation, linear regression and analysis of variance.
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.
Related Papers (5)
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Claes Fornell,David F. Larcker +1 more