Data: LancelotMiltgenetal2016
A data frame containing 10 variables with 1090 observations.
LancelotMiltgenetal2016
An object of class data.frame with 1090 rows and 11 columns.
The data was analysed by Lancelot-Miltgen et al. (2016) to study young consumers’ adoption intentions of a location tracker technology in the light of privacy concerns. It is also used in Henseler (2020) for demonstration purposes, see the corresponding tutorial.
This data has been collected through a cooperation with the European Commission Joint Research Center Institute for Prospective Technological Studies, contract “Young People and Emerging Digital Services: An Exploratory Survey on Motivations, Perceptions, and Acceptance of Risk” (EC JRC Contract IPTS No: 150876-2007 F1ED-FR).
Henseler J (2020).
Composite-Based Structural Equation Modeling: An Introduction to Partial Least Squares & Co. Using ADANCO.
Guilford Press.
Lancelot-Miltgen C, Henseler J, Gelhard C, Popovic A (2016).
“Introducing new products that affect consumer privacy: A mediation model.”
Journal of Business Research, 69(10), 4659–4666.
doi: 10.1016/j.jbusres.2016.04.015, https://doi.org/10.1016/j.jbusres.2016.04.015.
#============================================================================
# Example is taken from Henseler (2020)
#============================================================================
model_Med <- "
# Reflective measurement model
Trust =~ trust1 + trust2
PrCon =~ privcon1 + privcon2 + privcon3 + privcon4
Risk =~ risk1 + risk2 + risk3
Int =~ intent1 + intent2
# Structural model
Int ~ Trust + PrCon + Risk
Risk ~ Trust + PrCon
Trust ~ PrCon
"
out <- csem(.data = LancelotMiltgenetal2016, .model = model_Med,
.PLS_weight_scheme_inner = 'factorial',
.tolerance = 1e-06
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