Mastering Partial Least Squares Structural Equation Modeling (Pls-Sem) with Smartpls in 38 HoursiUniverse, 22 Feb 2019 - 184 halaman Partial least squares is a new approach in structural equation modeling that can pay dividends when theory is scarce, correct model specifications are uncertain, and predictive accuracy is paramount. Marketers can use PLS to build models that measure latent variables such as socioeconomic status, perceived quality, satisfaction, brand attitude, buying intention, and customer loyalty. When applied correctly, PLS can be a great alternative to existing covariance-based SEM approaches. Dr. Ken Kwong-Kay Wong wrote this reference guide with graduate students and marketing practitioners in mind. Coupled with business examples and downloadable datasets for practice, the guide includes step-by-step guidelines for advanced PLS-SEM procedures in SmartPLS, including: CTA-PLS, FIMIX-PLS, GoF (SRMR, dULS, and dG), HCM, HTMT, IPMA, MICOM, PLS-MGA, PLS-POS, PLSc, and QEM. Filled with useful illustrations to facilitate understanding, you’ll find this guide a go-to tool when conducting marketing research. “This book provides all the essentials in comprehending, assimilating, applying and explicitly presenting sophisticated structured models in the most simplistic manner for a plethora of Business and Non-Business disciplines.” — Professor Siva Muthaly, Dean of Faculty of Business and Management at APU. |
Isi
| 3 | |
Evaluating PLSSEM Results in SmartPLS | 15 |
Evaluating Model with Formative Measurement | 25 |
Handling NonLinear Relationship Using Quadratic | 33 |
Analysing Segments Using Heterogeneity Modeling | 42 |
Estimating Complex Models Using Higher Order | 74 |
Mediation Analysis | 92 |
New Techniques in PLSSEM | 101 |
Recommended PLSSEM Resources | 111 |
Conclusion | 117 |
Epilogue | 118 |
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Mastering Partial Least Squares Structural Equation Modeling (Pls-Sem) with ... Ken Kwong-Kay Wong Pratinjau tidak tersedia - 2019 |
Istilah dan frasa umum
Analysis IPMA arrows assess Bootstrapping café patrons Calculate Chapter coefficient of determination Collinearity composite reliability Consistent PLS Algorithm convergent validity Crosstab CTA-PLS customer loyalty LOYAL Customer satisfaction SATIS CXSAT dataset Dijkstra discriminant validity endogenous latent variable exogenous f2 Effect Figure FIMIX-PLS Henseler Heterotrait-Monotrait Ratio hyperlink hypothesis Indicator Data indicator reliability Inner Model internal consistency reliability Least Squares Structural linear marketing research measurement invariance menu and select MICOM missing values non-member Non-student number of segments Nyenrode Business Universiteit outer loadings Outer Model outer weights p-Values parameters Partial Least Squares path coefficients performed Permutation PLS path modeling PLS-SEM Predictive Relevance PRICE procedure Prof Quadratic Effect Quality Criteria reflective measurement model regression relationship restaurant example Results Ringle Ryerson University sample Sarstedt Seneca College significantly influences customer SmartPLS SPSS Squares Structural Equation statistical Structural Equation Modeling structural model Structural Path Total Effect unobserved heterogeneity variance window Wong
