Author Description

The 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 computational techniques. This book focuses on the description and applications of many quantitative modelling approaches applied to marketing and management. The structure encompasses statistical, computer and mathematical as well as other models. The topics range from fuzzy logic and logical discriminant models to growth models and k-clique models. It also covers current research being conducted in the field. Errata(s) Errata (16 KB) Contents: Statistical Modelling: A Review of the Major Multidimensional Scaling Models for the Analysis of Preference/Dominance Data in Marketing (Wayne S DeSarbo and Sunghoon Kim) Role of Structural Equation Modelling in Theory Testing and Development (Parikshat S Manhas, Ajay K Manrai, Lalita A Manrai and Ramjit) Partial Least Squares Path Modelling in Marketing and Management Research: An Annotated Application (Joaquín Aldás-Manzano) DEA — Data Envelopment Analysis: Models, Methods and Applications (Dr Alex Manzoni and Professor Sardar M N Islam) Statistical Model Selection (Graeme D Hutcheson) Computer Modelling: Artificial Neural Networks and Structural Equation Modelling: An Empirical Comparison to Evaluate Business Customer Loyalty (Arnaldo Coelho, Luiz Moutinho, Graeme D Hutc