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Joseph Hair, Abdullah Alamer
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1998
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2022
Unresolved referenced work
2019
Unresolved referenced work
2013
Unresolved referenced work
2022
Unresolved referenced work
2022
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10.1007/s11747-017-0517-x · 2017
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10.2753/mtp1069-6679190202 · 2011
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10.1007/s40685-018-0072-4 · 2018
When to use and how to report the results of PLS-SEM
10.1108/ebr-11-2018-0203 · 2019
Rethinking some of the rethinking of partial least squares
10.1108/ejm-10-2018-0665 · 2019
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10.1177/8756972819882132 · 2021
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10.1177/8756972819882132 · 2020
10.1177/8756972821999945
10.1177/8756972821999945
Next generation prediction metrics for composite-based PLS-SEM
10.1108/imds-08-2020-0505 · 2021
Unresolved referenced work
2016
Minimum sample size estimation in PLS-SEM: The inverse square root and gamma–exponential methods
10.1111/isj.12131 · 2018
Unresolved referenced work
2015
Unresolved referenced work
2017
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10.1016/j.jeap.2020.100884 · 2020
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2020
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10.1080/2331186x.2020.1746105 · 2020
Assessing students' metacognitive awareness of reading strategies
10.1037/0022-0663.94.2.249 · 2002
Learning Japanese; learning English: Promoting motivation through autonomy, competence and relatedness
2013
Why are you learning a second language? Motivational orientations and self-determination theory
10.1111/0023-8333.00111 · 2000
Motivating young language learners: A longitudinal model of self-determined motivation in elementary school foreign language classes
10.1016/j.cedpsych.2017.01.010 · 2017
Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict
10.1108/ejm-02-2019-0189 · doi-reference
The elephant in the room: Predictive performance of PLS models
10.1016/j.jbusres.2016.03.049 · doi-reference
How accurate is your correlation? Different methods derive different results and different interpretations
10.3389/fpsyg.2022.901412 · doi-reference
Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers
10.1016/j.jfbs.2014.01.002 · doi-reference
Beyond a tandem analysis of SEM and PROCESS: Use PLS-SEM for mediation analyses!
10.1177/1470785320915686 · doi-reference
How to specify, estimate, and validate higher-order constructs in PLS-SEM
10.1016/j.ausmj.2019.05.003 · doi-reference
On the adoption of partial least squares in psychological research: Caveat emptor
10.1016/j.paid.2015.07.019 · doi-reference
rethinking partial least squares path modeling: in praise of simple methods
10.1016/j.lrp.2012.09.010 · doi-reference