Mathematical Models in Marketing

Mathematical Models in Marketing PDF

Author: Ursula H. Funke

Publisher: Springer Science & Business Media

Published: 2013-04-17

Total Pages: 534

ISBN-13: 3642515657

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Mathematical models can be classified in a number of ways, e.g., static and dynamic; deterministic and stochastic; linear and nonlinear; individual and aggregate; descriptive, predictive, and normative; according to the mathematical technique applied or according to the problem area in which they are used. In marketing, the level of sophistication of the mathe matical models varies considerably, so that a nurnber of models will be meaningful to a marketing specialist without an extensive mathematical background. To make it easier for the nontechnical user we have chosen to classify the models included in this collection according to the major marketing problem areas in which they are applied. Since the emphasis lies on mathematical models, we shall not as a rule present statistical models, flow chart models, computer models, or the empirical testing aspects of these theories. We have also excluded competitive bidding, inventory and transportation models since these areas do not form the core of ·the marketing field.

Mathematical Models of Distribution Channels

Mathematical Models of Distribution Channels PDF

Author: Charles A. Ingene

Publisher: Springer Science & Business Media

Published: 2006-01-27

Total Pages: 590

ISBN-13: 0387227903

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Mathematical Models of Distribution Channels identifies eight "Channel Myths" that characterize almost all analytical research on distribution channels. The authors prove that models that incorporate one or more Channel Myths generate distorted conclusions; they also develop a methodology that will enable researchers to avoid falling under the influence of any Channel Myth.

Quantitative Modelling in Marketing and Management

Quantitative Modelling in Marketing and Management PDF

Author: Luiz Moutinho

Publisher: World Scientific

Published: 2015-11-06

Total Pages: 568

ISBN-13: 9814696366

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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

Introduction to Mathematical Models in Market and Opinion Research

Introduction to Mathematical Models in Market and Opinion Research PDF

Author: T. Harder

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 203

ISBN-13: 940103396X

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In the introduction to his book Dr. Harder has very clearly described its purpose and organization. I only want to add for the English-speaking reader a few words on the place the present text is likely to have in the cur rent literature. At first Dr. Harder's undertaking might come as a surprise. Only a few years ago, Zeisel's Say it with Figures gave the market research practi tioner some ideas of how simple figures and tables could be successfully employed; Langhoff's publication for the American Marketing Associa tion presented some pertinent mathematical models in the most elemen tary form; why should a German author believe he can already introduce us to serious mathematical procedures for use in product management and advertising? After reading the book, incredulity turns into pleasure because of the skill with which the author has pursued his task. As a matter of fact, the book can serve two audiences who at first glance might appear to have quite opposing interests. For the mathematically trained market re searcher, the book has the marked advantage of combining a variety of ap proaches not ordinarily mixed in one volume. If the market researcher be gan as an economist he is already familiar with difference equations and time series analysis; if he moved in from psychology, he is already ac quainted with factor analysis. But as he reads this book, he finds the two worlds well integrated.

Mathematical Modelling of Contemporary Electricity Markets

Mathematical Modelling of Contemporary Electricity Markets PDF

Author: Athanasios Dagoumas

Publisher: Academic Press

Published: 2021-01-30

Total Pages: 444

ISBN-13: 0128218398

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Mathematical Modelling of Contemporary Electricity Markets reviews major methodologies and tools to accurately analyze and forecast contemporary electricity markets in a ways that is ideal for practitioner and academic audiences. Approaches include optimization, neural networks, genetic algorithms, co-optimization, econometrics, E3 models and energy system models. The work examines how new challenges affect power market modeling, including discussions of stochastic renewables, price volatility, dynamic participation of demand, integration of storage and electric vehicles, interdependence with other commodity markets and the evolution of policy developments (market coupling processes, security of supply). Coverage addresses all major forms of electricity markets: day-ahead, forward, intraday, balancing, and capacity. Provides a diverse body of established techniques suitable for modeling any major aspect of electricity markets Familiarizes energy experts with the quantitative skills needed in competitive electricity markets Reviews market risk for energy investment decisions by stressing the multi-dimensionality of electricity markets

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