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Handbook of Partial Least Squares: Concepts, Methods and Applications

Handbook of Partial Least Squares: Concepts, Methods and Applications (Hardcover, 2010)

Vincenzo Esposito Vinzi, Wynne W. Chin, Joerg Henseler, Huiwen Wang (엮은이)
Springer Verlag
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Handbook of Partial Least Squares: Concepts, Methods and Applications
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책 정보

· 제목 : Handbook of Partial Least Squares: Concepts, Methods and Applications (Hardcover, 2010) 
· 분류 : 외국도서 > 과학/수학/생태 > 수학 > 확률과 통계 > 일반
· ISBN : 9783540328254
· 쪽수 : 798쪽
· 출판일 : 2010-02-26

목차

I . Methods: PLS Path Modeling: Concepts, Model Estimation and Assessment: Latent Variables and Indicators: Herman Wold's Basic Design and Partial Least Squares.- PLS Path Modeling: Recent Developments and Open Issues for Model Assessment and Improvement.- Bootstrap Cross-Validation Indices for PLS Path Model Assessment. PLS Path Modeling: Extensions: How to use PLS Path modeling for analyzing multi-block data sets.- How to use ULS-SEM and PLS-SEM to measure interaction effect in a regression model relating two blocks of binary variables.- A new Multiblock PLS based method to estimate causal models. Application to the post-consumption behaviour in tourism.- A Permutation Based Procedure for Multi-Group PLS Analysis: Results of Tests of Differences on Simulated Data and a Cross of Information System Services between Germany and the USA.- Looking at the Antecedents of Perceived Switching Costs - A PLS Path Modeling Approach with Categorical Indicators. PLS Path Modeling with Classification Issues: The Finite Mixture Partial Least Squares Approach - Methodology and Application.- Prediction-oriented classification in PLS Path Modelling.- Conjoint use of variables clustering and PLS structural equations modelling. PLS Path Modeling for Customer Satisfaction Studies: Design of PLS-based Satisfaction Studies.- Applying Bootstrap and Structural Equation Models to a Customer Satisfaction Model on Mobile Telecommunications Sector.- Comparison of Likelihood and PLS estimators for Structural Equation Modeling. A Simulation with Customer Satisfaction Data.- Modeling Customer Satisfaction: A Comparative Performance Evaluation of Covariance Structure Analysis versus Partial Least Squares. PLS Regression: PLS and Data Mining.- Three-block data modeling by endo- and exo-LPLS Regression.-Regression Modeling Analysis on Compositional Data.- A Modification of the PLSR Method. II. Applications to Marketing and Related Areas: PLS and Success Factor Studies in Marketing.- Applying Maximum Likelihood and PLS on Different Sample Sizes: Studies on Servqual Model and Emloyee Behaviour Model.- A PLS Model to Study Brand Preference: An Application to a Product Class.- An Application of PLS in Multi-Group Analysis: The need for differentiated corporate-level marketing in the mobile communications industry.- Modelling the Impact of Corporate Reputation on Customer Satisfaction and Loyalty Using PLS.- Reframing Customer Value in a Service-based Paradigm: An Evaluation of a Formative Measure in a Multi-Industry, Cross-Cultural Context.- Analyzing factorial data using PLS: Application in an online complaining context.- Content Strategies in the Internet. - Use of Partial Least Squares (PLS) in TQM Research: TQM Practices and Business Performance in SMEs.- Using PLS to Investigate Interaction Effects Between Higher Order Branding Constructs. III. Tutorials with Didactic Approach: How to Write Up and Report PLS analyses.- On the Operalization of Constructs in Multiple Groups.- Evaluation of Structural Equation Models using the Partial Least Squares (PLS-) Approach.- PLS and Confirmatory Tetrad Testing for Formative Measurement Scales in Marketing.- Testing Moderating Effects in PLS Path Models: An Illustration of Available Procedures.- A Comparison of Current PLS Path Modeling Software - Features, Ease-of-Use, and Performance.- PLS Regression Modeling with Qualitative Variables and Its Application to Beijing Sand Storm Prevention.- Interpretation of the preferences of automotive customers applied to air conditioning supports by combining GPA and PLS regression.

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Wynne W. Chin (엮은이)    정보 더보기
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Joerg Henseler (엮은이)    정보 더보기
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