LEADER 05501nam 2200661Ia 450 001 9910464801003321 005 20200520144314.0 010 $a1-283-85086-9 010 $a981-4407-72-0 035 $a(CKB)3400000000087234 035 $a(EBL)1080984 035 $a(OCoLC)817609708 035 $a(SSID)ssj0000754876 035 $a(PQKBManifestationID)12294405 035 $a(PQKBTitleCode)TC0000754876 035 $a(PQKBWorkID)10730107 035 $a(PQKB)11228667 035 $a(MiAaPQ)EBC1080984 035 $a(WSP)00002815 035 $a(Au-PeEL)EBL1080984 035 $a(CaPaEBR)ebr10627518 035 $a(CaONFJC)MIL416336 035 $a(EXLCZ)993400000000087234 100 $a20120824d2013 uy 0 101 0 $aeng 135 $aurbuu|||uu||| 181 $ctxt 182 $cc 183 $acr 200 10$aQuantitative modelling in marketing and management$b[electronic resource] /$fby Luiz Moutinho, Kun-Huang Huarng 210 $aSingapore ;$aHackensack, N.J. $cWorld Scientific$dc2013 215 $a1 online resource (530 p.) 300 $aDescription based upon print version of record. 311 $a981-4407-71-2 320 $aIncludes bibliographical references and index. 327 $aCONTENTS; Preface; Introduction; Part 1. Statistical Modelling; Part 2. Computer Modelling; Part 3. Mathematical and Other Models; References; Part 1. Statistical Modelling; Chapter 1. A Review of the Major Multidimensional Scaling Models for the Analysis of Preference/Dominance Data in Marketing Wayne S. DeSarbo and Sunghoon Kim; 1. Introduction; 2. The Vector MDS Model; 2.1. The individual level vector MDS model; 2.2. The segment level or clusterwise vector MDS model; 3. The Unfolding MDS Model; 3.1. The individual level simple unfolding model 327 $a3.2. The segment level or clusterwise multidimensional unfolding model 4. A Marketing Application; 4.1. The vector model results; 4.2. The simple unfolding model results; 5. Discussion; References; Chapter 2. Role of Structural Equation Modelling in Theory Testing and Development Parikshat S. Manhas, Ajay K. Manrai, Lalita A. Manrai and Ramjit; 1. Introduction; 1.1. Structural equation modelling; 1.2. Terminology, rules, and conventions; 2. Structural Equation Modeling - Example; 2.1. Model identification; Model specification; 2.2. Goodness-of-fit 327 $a2.3. Model fit summary for the current example 3. Model Estimation, Modification and Interpretation; References; APPENDIX; Steps To Launch Amos Graphics; Chapter 3. Partial Least Squares Path Modelling in Marketing and Management Research: An Annotated Application Joaqui?n Alda?s-Manzano; 1. Introduction; 2. The PLSPM Algorithm; 3. PLSPM Properties: Strengths and Weaknesses; 4. Applied Example: The Role of Trust on Consumers Adoption of Online Banking; 4.1. The model; 4.2. Method; 4.3. Estimating a PLSPM. Step 1. Dealing with second order factors 327 $a4.4. Estimating a PLSPM. Step 2. Validating the measurement (outer) model 4.4.1. Reliability; 4.4.2. Convergent validity; 4.4.3. Discriminant validity; 4.5. Estimating a PLSPM. Step 3. Assessing the structural (inner) model; 4.5.1. R2 of dependent LV; 4.5.2. Predictive relevance; 4.6. Estimating a PLSPM. Step 4. Hypotheses testing; 5. Conclusion; References; Chapter 4. DEA- Data Envelopment Analysis: Models, Methods and Applications Dr. Alex Manzoni and Professor Sardar M.N Islam; 1. Introduction; 2. Basic DEA Model; 3. Slack and Returns to Scale; 4. Assumptions, Strengths and Limitations 327 $a5. Applications, Examples and Computation Programs 6. Conclusion; Acknowledgement; References; Chapter 5. Statistical Model Selection Graeme D Hutcheson; 1. Introduction; 2. Some Example Analyses; 2.1. Tourism in Portugal; 2.2. Union membership; 3. Problem 1: Including Non-Important Variables in the Model; 3.1. Simulating data; 3.2. Models derived from simulated data; 4. Problem 2: Not Including Important Variables in the Model; 4.1. Modelling fuel consumption; 5. Conclusion; References; Part 2. Computer Modelling 327 $aChapter 6. Artificial Neural Networks and Structural Equation Modelling: An Empirical Comparison to Evaluate Business Customer Loyalty Arnaldo Coelho, Luiz Moutinho, Graeme D Hutcheson and Maria Manuela Santos Silva 330 $aThe field of marketing and management has undergone immense changes over the past decade. These dynamic changes are driving an increasing need for data analysis using quantitative modelling.Problem solving using the quantitative approach and other models has always been a hot topic in the fields of marketing and management. Quantitative modelling seems admirably suited to help managers in their strategic decision making on operations management issues. In social sciences, quantitative research refers to the systematic empirical investigation of social phenomena via statistical, mathematical or 606 $aManagement$xMathematical models 606 $aMarketing$xMathematical models 608 $aElectronic books. 615 0$aManagement$xMathematical models. 615 0$aMarketing$xMathematical models. 676 $a658.8001 676 $a658.80011 700 $aMoutinho$b Luiz$0116945 701 $aHuarng$b Kun-Huang$0913925 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910464801003321 996 $aQuantitative modelling in marketing and management$92223816 997 $aUNINA