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Advances in data collection and data storage techniques have enabled marketing researchers to study the individual characteristics of a large range of transactions and purchases, in particular the effects of household-specific characteristics. This 2001 book presents important and practically relevant quantitative models for marketing research. Each model is presented in detail with a self-contained discussion, which includes: a demonstration of the mechanics of the model, empirical analysis, real world examples, and interpretation of results and findings. The reader of the book will learn how to apply the techniques, as well as understand the methodological developments in the academic literature. Pathways are offered in the book for students and practitioners with differing numerical skill levels; a basic knowledge of elementary numerical techniques is assumed.
Book Synopsis Quantitative Models in Marketing Research by : Philip Hans Franses
Download or read book Quantitative Models in Marketing Research written by Philip Hans Franses and published by Cambridge University Press. This book was released on 2001-08-09 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in data collection and data storage techniques have enabled marketing researchers to study the individual characteristics of a large range of transactions and purchases, in particular the effects of household-specific characteristics. This 2001 book presents important and practically relevant quantitative models for marketing research. Each model is presented in detail with a self-contained discussion, which includes: a demonstration of the mechanics of the model, empirical analysis, real world examples, and interpretation of results and findings. The reader of the book will learn how to apply the techniques, as well as understand the methodological developments in the academic literature. Pathways are offered in the book for students and practitioners with differing numerical skill levels; a basic knowledge of elementary numerical techniques is assumed.
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. The first edition of "Quantitative Modelling in Marketing and Management" focused on the description and applications of many quantitative modelling approaches applied to marketing and management. The topics ranged from fuzzy logic and logical discriminant models to growth models and k-clique models. The second edition follows the thread of the first one by covering a myriad of techniques and applications in the areas of statistical, computer, mathematical as well as other novel nomothetic methods. It greatly reinforces the areas of computer, mathematical and other modeling tools that are designed to bring a level of awareness and knowledge among academics and researchers in marketing and management, so that there is an increase in the application of these new approaches that will be embedded in future scholarly output. 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)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, Graeme D Hutcheson and Maria Manuela Santos Silva)Meta-heuristics in Marketing (Stephen Hurley and Luiz Moutinho)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)Interactive Virtual Platform for Shopping Furniture Based on Unity 3D (Yingwan Wu, Simon Fong, Suash Deb and Thomas Hanne)Mathematical and Other Models:Qualitative Comparison Analysis: An Example Analysis of Clinical Directorates and Resource Management (Malcolm J Beynon, Aoife McDermott and Mary A Keating)Growth Models (Mladen Sokele)Bayesian Prediction with Linear Dynamic Model: Principle and Application (Yun Li, Luiz Moutinho, Kwaku K Opong and Yang Pang)PROMETHEE: Technical Details and Developments, and its Role in Performance Management (Malcolm J Beynon and Harry Barton)Data Mining Process Models: A Roadmap for Knowledge Discovery (Armando B Mendes, Luís Cavique and Jorge M A Santos)Metaheuristics in Logistics (Thomas Hanne, Suash Deb and Simon Fong)A Model for Optimizing Earned Attention in Social Media Based on a Memetic Algorithm (Pedro Godinho, Luiz Moutinho and Manuela Silva)Stream-based Classification for Social Network Recommendation Systems (Yan Zhuang and Hang Yang)Clique Communities in Social Networks (Luís Cavique, Armando B Mendes and Jorge M A Santos)Measuring the Effects of Marketing Actions: The Role of Matching Methodologies (Iola Pinto and Margarida GMS Cardoso)Mathematical Programming Applied to Benchmarking in Economics and Management (Jorge Santos, Armando B Mendes, Luís Cavique and Magdalena Kapelko)Conclusion Readership: Undergraduates and postgraduates of management and business administration, academic researchers marketing professionals, financial professionals and business consultants. Key Features:Contains statistical (more commonly known), computer, mathematical, and other modelling approaches that provide a framework to analyse the issues, tools and examples associated with each techniqueDemonstrates the applicability of quantitative methods and highlights the potential utilisation of each methodology by using the research (quantitative) modelling approachKeywords:Quantitative Analysis;Modeling;Marketing Management;Statistical Modelling;Computer Modelling;Memetic Algorithm;Structural Equation Modelling;Artificial Neural Networks
Book Synopsis Quantitative Modelling in Marketing and Management by : Luiz Moutinho
Download or read book Quantitative Modelling in Marketing and Management written by Luiz Moutinho and published by World Scientific. This book was released on 2015-11-06 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. The first edition of "Quantitative Modelling in Marketing and Management" focused on the description and applications of many quantitative modelling approaches applied to marketing and management. The topics ranged from fuzzy logic and logical discriminant models to growth models and k-clique models. The second edition follows the thread of the first one by covering a myriad of techniques and applications in the areas of statistical, computer, mathematical as well as other novel nomothetic methods. It greatly reinforces the areas of computer, mathematical and other modeling tools that are designed to bring a level of awareness and knowledge among academics and researchers in marketing and management, so that there is an increase in the application of these new approaches that will be embedded in future scholarly output. 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)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, Graeme D Hutcheson and Maria Manuela Santos Silva)Meta-heuristics in Marketing (Stephen Hurley and Luiz Moutinho)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)Interactive Virtual Platform for Shopping Furniture Based on Unity 3D (Yingwan Wu, Simon Fong, Suash Deb and Thomas Hanne)Mathematical and Other Models:Qualitative Comparison Analysis: An Example Analysis of Clinical Directorates and Resource Management (Malcolm J Beynon, Aoife McDermott and Mary A Keating)Growth Models (Mladen Sokele)Bayesian Prediction with Linear Dynamic Model: Principle and Application (Yun Li, Luiz Moutinho, Kwaku K Opong and Yang Pang)PROMETHEE: Technical Details and Developments, and its Role in Performance Management (Malcolm J Beynon and Harry Barton)Data Mining Process Models: A Roadmap for Knowledge Discovery (Armando B Mendes, Luís Cavique and Jorge M A Santos)Metaheuristics in Logistics (Thomas Hanne, Suash Deb and Simon Fong)A Model for Optimizing Earned Attention in Social Media Based on a Memetic Algorithm (Pedro Godinho, Luiz Moutinho and Manuela Silva)Stream-based Classification for Social Network Recommendation Systems (Yan Zhuang and Hang Yang)Clique Communities in Social Networks (Luís Cavique, Armando B Mendes and Jorge M A Santos)Measuring the Effects of Marketing Actions: The Role of Matching Methodologies (Iola Pinto and Margarida GMS Cardoso)Mathematical Programming Applied to Benchmarking in Economics and Management (Jorge Santos, Armando B Mendes, Luís Cavique and Magdalena Kapelko)Conclusion Readership: Undergraduates and postgraduates of management and business administration, academic researchers marketing professionals, financial professionals and business consultants. Key Features:Contains statistical (more commonly known), computer, mathematical, and other modelling approaches that provide a framework to analyse the issues, tools and examples associated with each techniqueDemonstrates the applicability of quantitative methods and highlights the potential utilisation of each methodology by using the research (quantitative) modelling approachKeywords:Quantitative Analysis;Modeling;Marketing Management;Statistical Modelling;Computer Modelling;Memetic Algorithm;Structural Equation Modelling;Artificial Neural Networks
Quantitative marketing has been gaining importance during the last decade. This is indicated by the growing number of model- and method-oriented studies published in leading journals as well as by the many successful applications of quantitative approaches in pricing, advertising, new product planning, and market segmentation decisions. In addition, market research has clearly benefitted from applying advanced quantitative models and methods in practice. Some 60 researchers – among them worldwide leading scholars – offer a broad overview of quantitative approaches in marketing. They not only highlight diverse mathematical and methodological perspectives, but also demonstrate the relevance and practical consequences of applying quantitative approaches to marketing problems.
Book Synopsis Quantitative Marketing and Marketing Management by : Adamantios Diamantopoulos
Download or read book Quantitative Marketing and Marketing Management written by Adamantios Diamantopoulos and published by Springer Science & Business Media. This book was released on 2013-01-31 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative marketing has been gaining importance during the last decade. This is indicated by the growing number of model- and method-oriented studies published in leading journals as well as by the many successful applications of quantitative approaches in pricing, advertising, new product planning, and market segmentation decisions. In addition, market research has clearly benefitted from applying advanced quantitative models and methods in practice. Some 60 researchers – among them worldwide leading scholars – offer a broad overview of quantitative approaches in marketing. They not only highlight diverse mathematical and methodological perspectives, but also demonstrate the relevance and practical consequences of applying quantitative approaches to marketing problems.
Marketing is second only to the physical sciences in its use of quantitative techniques. Quantitative Methods in Marketing provides a survey of the latest techniques used by marketers and market research organisations.
Book Synopsis Quantitative Methods in Marketing by : Graham J. Hooley
Download or read book Quantitative Methods in Marketing written by Graham J. Hooley and published by Cengage Learning EMEA. This book was released on 1999 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Marketing is second only to the physical sciences in its use of quantitative techniques. Quantitative Methods in Marketing provides a survey of the latest techniques used by marketers and market research organisations.
From 1976 to the beginning of the millennium—covering the quarter-century life span of this book and its predecessor—something remarkable has happened to market response research: it has become practice. Academics who teach in professional fields, like we do, dream of such things. Imagine the satisfaction of knowing that your work has been incorporated into the decision-making routine of brand managers, that category management relies on techniques you developed, that marketing management believes in something you struggled to establish in their minds. It’s not just us that we are talking about. This pride must be shared by all of the researchers who pioneered the simple concept that the determinants of sales could be found if someone just looked for them. Of course, economists had always studied demand. But the project of extending demand analysis would fall to marketing researchers, now called marketing scientists for good reason, who saw that in reality the marketing mix was more than price; it was advertising, sales force effort, distribution, promotion, and every other decision variable that potentially affected sales. The bibliography of this book supports the notion that the academic research in marketing led the way. The journey was difficult, sometimes halting, but ultimately market response research advanced and then insinuated itself into the fabric of modern management.
Book Synopsis Market Response Models by : Dominique M. Hanssens
Download or read book Market Response Models written by Dominique M. Hanssens and published by Springer Science & Business Media. This book was released on 2005-12-19 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: From 1976 to the beginning of the millennium—covering the quarter-century life span of this book and its predecessor—something remarkable has happened to market response research: it has become practice. Academics who teach in professional fields, like we do, dream of such things. Imagine the satisfaction of knowing that your work has been incorporated into the decision-making routine of brand managers, that category management relies on techniques you developed, that marketing management believes in something you struggled to establish in their minds. It’s not just us that we are talking about. This pride must be shared by all of the researchers who pioneered the simple concept that the determinants of sales could be found if someone just looked for them. Of course, economists had always studied demand. But the project of extending demand analysis would fall to marketing researchers, now called marketing scientists for good reason, who saw that in reality the marketing mix was more than price; it was advertising, sales force effort, distribution, promotion, and every other decision variable that potentially affected sales. The bibliography of this book supports the notion that the academic research in marketing led the way. The journey was difficult, sometimes halting, but ultimately market response research advanced and then insinuated itself into the fabric of modern management.
This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.
Book Synopsis R for Marketing Research and Analytics by : Chris Chapman
Download or read book R for Marketing Research and Analytics written by Chris Chapman and published by Springer. This book was released on 2015-03-25 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.
Marketing Research and Modeling addresses state of the art developments including new techniques and methodologies by leading experts in marketing and marketing research. This work emphasizes new developments in Bayesian Decision Analysis, Multivariate Analysis, Multidimensional Scaling, Conjoint Analysis, Applications of Conjoint and MDS technique, Data Mining, Cluster Analysis, and Neural Networks.
Book Synopsis Marketing Research and Modeling: Progress and Prospects by : Yoram Wind
Download or read book Marketing Research and Modeling: Progress and Prospects written by Yoram Wind and published by Springer Science & Business Media. This book was released on 2013-06-05 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: Marketing Research and Modeling addresses state of the art developments including new techniques and methodologies by leading experts in marketing and marketing research. This work emphasizes new developments in Bayesian Decision Analysis, Multivariate Analysis, Multidimensional Scaling, Conjoint Analysis, Applications of Conjoint and MDS technique, Data Mining, Cluster Analysis, and Neural Networks.
The Handbook of Marketing Research: Uses, Misuses, and Future Advances comprehensively explores the approaches for delivering market insights for fact-based decision making in a market-oriented firm. Divided into four parts, the Handbook addresses (1) the different nuances of delivering insights; (2) quantitative, qualitative, and online data gathering techniques; (3) basic and advanced data analysis methods; and (4) the substantial marketing issues that clients are interested in resolving through marketing research.
Book Synopsis The Handbook of Marketing Research by : Rajiv Grover
Download or read book The Handbook of Marketing Research written by Rajiv Grover and published by SAGE Publications. This book was released on 2006-06-23 with total page 721 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Marketing Research: Uses, Misuses, and Future Advances comprehensively explores the approaches for delivering market insights for fact-based decision making in a market-oriented firm. Divided into four parts, the Handbook addresses (1) the different nuances of delivering insights; (2) quantitative, qualitative, and online data gathering techniques; (3) basic and advanced data analysis methods; and (4) the substantial marketing issues that clients are interested in resolving through marketing research.
This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas. Following the Python scientific computing movement toward reproducible research, the book presents all analyses in Colab notebooks, which integrate code, figures, tables, and annotation in a single file. The code notebooks for each chapter may be copied, adapted, and reused in one's own analyses. The book also introduces the usage of machine learning predictive models using the Python sklearn package in the context of marketing research. This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS; analysts or students who already program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics.
Book Synopsis Python for Marketing Research and Analytics by : Jason S. Schwarz
Download or read book Python for Marketing Research and Analytics written by Jason S. Schwarz and published by Springer Nature. This book was released on 2020-11-03 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas. Following the Python scientific computing movement toward reproducible research, the book presents all analyses in Colab notebooks, which integrate code, figures, tables, and annotation in a single file. The code notebooks for each chapter may be copied, adapted, and reused in one's own analyses. The book also introduces the usage of machine learning predictive models using the Python sklearn package in the context of marketing research. This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS; analysts or students who already program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics.
Balancing simplicity with technical rigour, this practical guide to the statistical techniques essential to research in marketing and related fields, describes each method as well as showing how they are applied. The book is accompanied by two real data sets to replicate examples and with exercises to solve, as well as detailed guidance on the use of appropriate software including: - 750 powerpoint slides with lecture notes and step-by-step guides to run analyses in SPSS (also includes screenshots) - 136 multiple choice questions for tests This is augmented by in-depth discussion of topics including: - Sampling - Data management and statistical packages - Hypothesis testing - Cluster analysis - Structural equation modelling
Book Synopsis Statistics for Marketing and Consumer Research by : Mario Mazzocchi
Download or read book Statistics for Marketing and Consumer Research written by Mario Mazzocchi and published by SAGE. This book was released on 2008-05-22 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Balancing simplicity with technical rigour, this practical guide to the statistical techniques essential to research in marketing and related fields, describes each method as well as showing how they are applied. The book is accompanied by two real data sets to replicate examples and with exercises to solve, as well as detailed guidance on the use of appropriate software including: - 750 powerpoint slides with lecture notes and step-by-step guides to run analyses in SPSS (also includes screenshots) - 136 multiple choice questions for tests This is augmented by in-depth discussion of topics including: - Sampling - Data management and statistical packages - Hypothesis testing - Cluster analysis - Structural equation modelling
