This repository contains the RStudio code employed for the analysis of Structural Equation Modelling using Partial Least Squares, applied to a Theory of Planned behaviour survey. The code has been developed specifically for this study and allows for the replication of the results published at (Springer Nature?). The main R library is "plspm".
Hair, J., Sarstedt, M., Pieper, T., Ringle, C. (2012). The use of partial least squares structural equation modelling in strategic management research: a review of past practices and recommendations for future applications. Long Range Planning, 45 (5-6), 320—340, https://doi.org/10.1016/j.lrp.2012.09.008
Hair, J.F., Black, W., Babin, B., Anderson, R. (2010). Multivariate data analysis. 7th edition. Pearson.
Hair, J.F., Ringle, C.M., Sarstedt, M. (2011). Pls-sem: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19 (2), 139–152, https://doi.org/10.2753/MTP1069-6679190202
Hair, J.F., Ringle, C.M., Sarstedt, M. (2012). Partial least squares: The better approach to structural equation modeling? Long Range Planning, 45 (5-6), 312—319, https://doi.org/10.1016/J.LRP.2012.09.011
Hair, J.F., Risher, M., J. J.and Sarstedt, Ringle, C.M. (2019). hen to use and how to report the results of pls-sem. European Business Review , 31 (1), 2–24, https://doi.org/10.1108/EBR-11-2018-0203/FULL/XML
Tenenhaus M., Esposito Vinzi V., Chatelin Y.M., and Lauro C. (2005) PLS path modeling. Computational Statistics & Data Analysis, 48, pp. 159-205.
If you use this code in your research or software, you must cite the following article: Morales, B. and Ovando, P. (2025) Organisational Attitudes and Preferences Toward Forest Carbon Offsets in Spain’s Carbon Footprint Registry
BibTeX citation:
@article{MoralesOvando2025,
author = {Morales, Brenda and Ovando, Paola},
title = {Organisational Attitudes and Preferences Toward Forest Carbon Offsets in Spain’s Carbon Footprint Registry},
journal = {Journal Name},
year = {2025},
volume = {XX},
pages = {XX-XX},
doi = {DOI link}
}