Quantitative Modelling In Marketing And Management

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 Hutcheson and Maria Manuela Santos Silva) The Application of NN to Management Problems (Arnaldo Coelho, Luiz Moutinho and Maria Manuela Santos Silva) Logical Discriminant Models (Margarida G M S Cardoso) Meta-heuristics in Marketing (Stephen Hurley and Luiz Moutinho) Hold a Mirror Up to Nature: A New Approach on Correlation Evaluation with Fuzzy Data and Its Applications in Econometrics (Chih Ching Yang, Yu-Ting Cheng, Berlin Wu and Songsak Sriboonchitta) Non-parametric Test with Fuzzy Data and Its Applications in the Performance Evaluation of Customer Capital (Yu-Lan Lee, Ming-leih Wu and Chunti Su) Too Much ADO About Nothing? Fuzzy Measurement of Job Stress for School Leaders (Berlin Wu and Mei Fen Liu) Fuzzy Composite Score and Situational Judgement Test: An Integrated Operation Perspective of Scoring (Hawjeng Chiou and Tsung-Lin Ou) Mathematical and Other Models: Cluster Analysis: An Example Analysis on Personality and Dysfunctional Customer Behaviour (Malcolm J Beynon and Kate L Daunt) Assessing the Perception of Superstitious Numbers and Its Effect on Purchasing Intentions (Dina-Fu Chang and Yi-Sheng Jiang) Qualitative Comparison Analysis: An Example Analysis of Clinical Directorates and Resource Management (Malcolm J Beynon, Aoife McDermott and Mary A Keating) Data Mining Process Models: A Roadmap for Knowledge Discovery (Armando B Mendes, Luís Cavique and Jorge M A Santos) Growth Models (Mladen Sokele) PROMETHEE: Technical Details and Developments, and Its Role in Performance Management (Malcolm J Beynon and Harry Barton) Clique Communities in Social Networks (Luís Cavique, Armando B Mendes and Jorge M A Santos) Conclusion Readership: Undergraduates and postgraduates of management and business administration, academic researchers marketing professionals, financial professionals and business consultants.