Abstract
This Handbook on Partial Least Squares (PLS) represents a comprehensive presentation of the current, original and most advanced research in the domain of PLS methods with specific reference to their use in Marketing-related areas and with a discussion of the forthcoming and most challenging directions of research and perspectives. The Handbook covers the broad area of PLS Methods from Regression to Structural Equation Modeling, from methods to applications, from software to interpretation of results. This work features papers on the use and the analysis of latent variables and indicators by means of the PLS Path Modeling approach from the design of the causal network to the model assessment and improvement.Moreover, within the PLS framework, the Handbook addresses, among others, special and advanced topics such as the analysis of multi-block, multi-group and multistructured data, the use of categorical indicators, the study of interaction effects, the integration of classification issues, the validation aspects and the comparison between the PLS approach and the covariance-based Structural Equation Modeling. Most chapters comprise a thorough discussion of applications to problems from Marketing and related areas. Furthermore, a few tutorials focus on some key aspects of PLS analysis with a didactic approach. This Handbook serves as both an introduction for those without prior knowledge of PLS but also as a comprehensive reference for researchers and practitioners interested in the most recent advances in PLS methodology.
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Acknowledgements
The PLS Handbook Editors are very grateful to Rosaria Romano and Laura Trinchera from the University of Naples Federico II (Italy) for their endeavor and enthusiasm as editorial assistants and to the more than 50 referees for their highly professional contribution to the three rounds of the peer reviewing process. A special thank goes also to the owners and the staff of the Hotel San Michele in Anacapri (Island of Capri, Italy) for offering a very peaceful and inspiring summer environment during the completion of the editorial work.
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Vinzi, V.E., Chin, W.W., Henseler, J., Wang, H. (2010). Editorial: Perspectives on Partial Least Squares. In: Esposito Vinzi, V., Chin, W., Henseler, J., Wang, H. (eds) Handbook of Partial Least Squares. Springer Handbooks of Computational Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_1
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DOI: https://doi.org/10.1007/978-3-540-32827-8_1
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