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Quantitative Models in Marketing Research by Philip Hans Franses,Richard Paap Pdf
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.
Quantitative Modelling in Marketing and Management by Luiz Moutinho,Kun-Huang Huarng Pdf
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 and Marketing Management by Adamantios Diamantopoulos,Wolfgang Fritz,Lutz Hildebrandt Pdf
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.
Quantitative Methods in Marketing by Graham J. Hooley,Michael K. Hussey Pdf
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.
Econometric Models in Marketing by P.H. Franses,A.L. Montgomery Pdf
In the 16th Edition of "Advances in Econometrics", we present twelve papers discussing the current interface between Marketing and Econometrics. The authors are leading scholars in the fields and introduce the latest models for analysing marketing data. The papers are representative of the types of problems and methods that are used within the field of marketing. Marketing focuses on the interaction between the firm and the consumer. Economics encompasses this interaction as well as many others. Economics, along with psychology and sociology, provides a theoretical foundation for marketing. Given the applied nature of marketing research, measurement and quantitative issues arise frequently. Quantitative marketing tends to rely heavily upon statistics and econometrics. However, quantitative marketing can place a different emphasis upon the problem than econometrics, even when using the same techniques. A basic difference between quantitative marketing research and econometrics tends to be the pragmatism that is found in many marketing studies. Another important motivating factor in marketing research is the type of data that is available. Applied econometrics tends to rely heavily on data collected by governmental organizations. In contrast, marketing often uses data collected by private firms or marketing research firms. Observational and survey data are quite similar to those used in econometrics. However, the remaining types of data, panel and transactional, can look quite different from what may be familiar to econometricians. The automation and computerization of much of the sales transaction process leaves an audit trail that results in huge quantities of data. A popular area of study is the use of scanner data collected at the checkout stand using bar code readers. Methods that work for small data sets may not work well in these larger data sets. In addition, new sources of data, such as clickstream data from a web site, will offer new challenges. This volume addresses these and related issues.
Marketing Research and Modeling: Progress and Prospects by Yoram Wind,Paul E. Green Pdf
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.
R for Marketing Research and Analytics by Chris Chapman,Elea McDonnell Feit Pdf
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.
Python for Marketing Research and Analytics by Jason S. Schwarz,Chris Chapman,Elea McDonnell Feit Pdf
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.
The Handbook of Marketing Research by Rajiv Grover,Marco Vriens Pdf
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.
Market Response Models by Dominique M. Hanssens,Leonard J. Parsons,Randall L. Schultz Pdf
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.
Len Tiu Wright,Luiz Moutinho,Merlin Stone,Richard P. Bagozzi
Author : Len Tiu Wright,Luiz Moutinho,Merlin Stone,Richard P. Bagozzi Publisher : Taylor & Francis Page : 633 pages File Size : 53,5 Mb Release : 2021-06-27 Category : Business & Economics ISBN : 9781134826797
The Routledge Companion to Marketing Research by Len Tiu Wright,Luiz Moutinho,Merlin Stone,Richard P. Bagozzi Pdf
This single-volume reference provides an alternative to traditional marketing research methods handbooks, focusing entirely on the new and innovative methods and technologies that are transforming marketing research and practice. Including original contributions and case studies from leading global specialists, this handbook covers many pioneering methods, such as: Methods for the analysis of user- and customer-generated data, including opinion mining and sentiment analysis Big data Neuroscientific techniques and physiological measures Voice prints Human–computer interaction Emerging approaches such as shadowing, netnographies and ethnographies Transcending the old divisions between qualitative and quantitative research methods, this book is an essential tool for market researchers in academia and practice.
As the importance of marketing to business grows, and as new concepts and applications of marketing emerge and evolve, so too does the need for up-to-date market intelligence. This book recognizes that the contribution which qualitative research can make to market understanding and insight is immense, and that statistical information flows are never enough but need to be compounded by market intelligence gained through qualitative methods. Qualitative Marketing Research clearly explains the use and importance of qualitative methods, clarifying the theories behind the methodology and providing concrete examples and exercises which illustrate its application to Management Studies and Marketing. This book is intended for all students of marketing who are required to complete their studies with a dissertation or research project.
Statistics for Marketing and Consumer Research by Mario Mazzocchi Pdf
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
Market Research by Erik Mooi,Marko Sarstedt,Irma Mooi-Reci Pdf
This book is an easily accessible and comprehensive guide which helps make sound statistical decisions, perform analyses, and interpret the results quickly using Stata. It includes advanced coverage of ANOVA, factor, and cluster analyses in Stata, as well as essential regression and descriptive statistics. It is aimed at those wishing to know more about the process, data management, and most commonly used methods in market research using Stata. The book offers readers an overview of the entire market research process from asking market research questions to collecting and analyzing data by means of quantitative methods. It is engaging, hands-on, and includes many practical examples, tips, and suggestions that help readers apply and interpret quantitative methods, such as regression, factor, and cluster analysis. These methods help researchers provide companies with useful insights.
Building Models for Marketing Decisions by Peter S.H. Leeflang,Dick R. Wittink,Michel Wedel,Philippe A. Naert Pdf
This book is about marketing models and the process of model building. Our primary focus is on models that can be used by managers to support marketing decisions. It has long been known that simple models usually outperform judgments in predicting outcomes in a wide variety of contexts. For example, models of judgments tend to provide better forecasts of the outcomes than the judgments themselves (because the model eliminates the noise in judgments). And since judgments never fully reflect the complexities of the many forces that influence outcomes, it is easy to see why models of actual outcomes should be very attractive to (marketing) decision makers. Thus, appropriately constructed models can provide insights about structural relations between marketing variables. Since models explicate the relations, both the process of model building and the model that ultimately results can improve the quality of marketing decisions. Managers often use rules of thumb for decisions. For example, a brand manager will have defined a specific set of alternative brands as the competitive set within a product category. Usually this set is based on perceived similarities in brand characteristics, advertising messages, etc. If a new marketing initiative occurs for one of the other brands, the brand manager will have a strong inclination to react. The reaction is partly based on the manager's desire to maintain some competitive parity in the mar keting variables.