International Series in Quantitative Marketing – serie

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.

In the corporate world, there is an increased emphasis on making different functional areas work together seamlessly. This book provides state-of-the-art summary as well as new thoughts in managing business interfaces. Through eleven invited chapters, it brings together the latest developments in leading-edge research related to new product development, supply chain management, e-business operations, and field studies. (Also available in hardcover - 1-4020-7614-2.)

Database marketing is at the crossroads of technology, business strategy, and customer relationship management. Enabled by sophisticated information and communication systems, today’s organizations have the capacity to analyze customer data to inform and enhance every facet of the enterprise—from branding and promotion campaigns to supply chain management to employee training to new product development. Based on decades of collective research, teaching, and application in the field, the authors present the most comprehensive treatment to date of database marketing, integrating theory and practice. Presenting rigorous models, methodologies, and techniques (including data collection, field testing, and predictive modeling), and illustrating them through dozens of examples, the authors cover the full spectrum of principles and topics related to database marketing."This is an excellent in-depth overview of both well-known and very recent topics in customer management models. It is an absolute must for marketers who want to enrich their knowledge on customer analytics." (Peter C. Verhoef, Professor of Marketing, Faculty of Economics and Business, University of Groningen)"A marvelous combination of relevance and sophisticated yet understandable analytical material. It should be a standard reference in the area for many years." (Don Lehmann, George E. Warren Professor of Business, Columbia Business School)"The title tells a lot about the book's approach—though the cover reads, "database," the content is mostly about customers and that's where the real-world action is. Most enjoyable is the comprehensive story – in case after case – which clearly explains what the analysis and concepts really mean. This is an essential read for those interested in database marketing, customer relationship management and customer optimization." (Richard Hochhauser, President and CEO, Harte-Hanks, Inc.)"In this tour de force of carefulscholarship, the authors canvass the ever expanding literature on database marketing. This book will become an invaluable reference or text for anyone practicing, researching, teaching or studying the subject." (Edward C. Malthouse, Theodore R. and Annie Laurie Sills Associate Professor of Integrated Marketing Communications, Northwestern University)

Product sales, especially for new products, are influenced by many factors. These factors are both internal and external to the selling organization, and are both controllable and uncontrollable. Due to the enormous complexity of such factors, it is not surprising that product failure rates are relatively high. Indeed, new product failure rates have variously been reported as between 40 and 90 percent. Despite this multitude of factors, marketing researchers have not been deterred from developing and designing techniques to predict or explain the levels of new product sales over time. The proliferation of the internet, the necessity or developing a road map to plan the launch and exit times of various generations of a product, and the shortening of product life cycles are challenging firms to investigate market penetration, or innovation diffusion, models. These models not only provide information on new product sales over time but also provide insight on the speed with which a new product is being accepted by various buying groups, such as those identified as innovators, early adopters, early majority, late majority, and laggards. New Product Diffusion Models aims to distill, synthesize, and integrate the best thinking that is currently available on the theory and practice of new product diffusion models. This state-of-the-art assessment includes contributions by individuals who have been at the forefront of developing and applying these models in industry. The book's twelve chapters are written by a combined total of thirty-two experts who together represent twenty-five different universities and other organizations in Australia, Europe, Hong Kong, Israel, and the United States. The book will be useful for researchers and students in marketing and technological forecasting, as well as those in other allied disciplines who study relevant aspects of innovation diffusion. Practitioners in high-tech and consumer durable industries should also gain newinsights from New Product Diffusion Models. The book is divided into five parts: I. Overview; II. Strategic, Global, and Digital Environments for Diffusion Analysis; III. Diffusion Models; IV. Estimation and V. Applications and Software. The final section includes a PC-based software program developed by Gary L. Lilien and Arvind Rangaswamy (1998) to implement the Bass diffusion model. A case on high-definition television is included to illustrate the various features of the software. A free, 15-day trial access period for the updated software can be downloaded from http://www.mktgeng.com/diffusionbook. Among the book's many highlights are chapters addressing the implications posed by the internet, globalization, and production policies upon diffusion of new products and technologies in the population.

The market environment is changing rapidly. Prior to scanner data, ACNielsen, the major supplier of information on brand performances, said its business was to provide the score but not to explain or predict it. Now, model-based insights are not only demanded by managers, but can also be meaningfully provided. It is common for managers in many countries to receive market feedback frequently, quickly and in great detail due to the use of scanners and computers. With advances in information technology and expertise in modeling, IRI introduced model-based services in the US that explain and predict essential parts of the marketplace. ACNielsen followed, and marketing researchers have been developing increasingly valid, useful and relevant models of marketplace behavior ever since. Models that provide information about the sensitivity of market behavior to marketing activities such as advertising, pricing, promotions and distribution are now routinely used by managers for the identification of changes in marketing programs that can improve brand performances.Building Models for Marketing Decisions describes marketing models that managers can use as an aid in decision making. It has long been known that even simple models outperform judgments in predicting outcomes in a wide variety of contexts. More complex models potentially provide insights about structural relations not available from casual observations. Although marketing models are now widely accepted, the quality of the marketing decisions is critically dependent upon the quality of the models on which those decisions are based. In this book, which is a revision and expansion of Naert and Leeflang's Building Implementable Marketing Models (1978), the authors discuss in detail the model-building process. They distinguish four parts in this process: specification, estimation, validation and use of models. Throughout the book, the authors provide examples and illustrations. This book will be of interest to researchers, analysts, managers and students who want to understand, develop or use models of marketing phenomena.

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.

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.

Marketing management support systems are designed to make marketing managers more effective decision makers in this electronic era. Developments in information technology have caused a marketing data explosion, but have also provided a powerful set of tools that can transform this data into applicable marketing knowledge. Consequently, companies are making major investments in such marketing decision aids. This book is the first comprehensive, systematic textbook on marketing management support systems. The basic issue is the question of how to determine the most effective type of support for a given marketing decision maker in a particular decision situation. The book takes a demand-oriented approach. Decision aids for marketing managers can only be effective if they match with the thinking and reasoning process of the decision makers who use them. Consequently, the important questions addressed in this book are: how do marketing managers make decisions; how can marketing management support systems help to overcome several (cognitive) limitations of human decision makers; and what is the most appropriate type of management support system for assisting the problem-solving methods employed by a marketing decision-maker?

Modern marketing techniques in industrialized countries cannot be implemented without segmentation of the potential market. Goods are no longer produced and sold without a significant consideration of customer needs combined with a recognition that these needs are heterogeneous. Since first emerging in the late 1950s, the concept of segmentation has been one of the most researched topics in the marketing literature. Segmentation has become a central topic to both the theory and practice of marketing, particularly in the recent development of finite mixture models to better identify market segments. This second edition of Market Segmentation updates and extends the integrated examination of segmentation theory and methodology begun in the first edition. A chapter on mixture model analysis of paired comparison data has been added, together with a new chapter on the pros and cons of the mixture model. The book starts with a framework for considering the various bases and methods available for conducting segmentation studies. The second section contains a more detailed discussion of the methodology for market segmentation, from traditional clustering algorithms to more recent developments in finite mixtures and latent class models. Three types of finite mixture models are discussed in this second section: simple mixtures, mixtures of regressions and mixtures of unfolding models. The third main section is devoted to special topics in market segmentation such as joint segmentation, segmentation using tailored interviewing and segmentation with structural equation models. The fourth part covers four major approaches to applied market segmentation: geo-demographic, lifestyle, response-based, and conjoint analysis. The final concluding section discusses directions for further research.

This book is about the role of expert systems in marketing, particularly in the consumer goods industry. Section I describes the changing nature of consumer marketing and presents the rationale and need for expert systems. The remainder of the book combines a tutorial on expert systems with a series of expert system prototypes. The tutorial material is presented in three places. First, section II is devoted to introducing expert systems in general. Chapter 3 provides a general introduction to the topic, which is continued in chapter 4 where a small expert system (the Promotion Advisor) is used to illustrate the important features of a backward-chaining, rule-based system. The promotion theme is extended in chapter 5 where a larger system is presented. The material in all three of these chapters was designed as an introduction and tutorial on the most common technology for building applied expert systems: the backward-chaining, rule-based inference engine. Tutorial material is also contained in the body of the chapters that describe the prototypes. This material is usually in the form of sample rules and a description of the process for applying the rules. The third location of the expert system material is in chapters that follow discussions of the prototypes. Chapter 7 is a technical chapter on the coupling of expert systems to traditional systems.

For years, I have been impressed by how dynamic markets are. Marketing strategies are rarely successful without adjustments over time, and marketing managers need constantly to monitor, and anticipate when possible, important changes in the marketing environment, so that they can adapt their marketing strategies to changing market conditions. It strikes me as important that the dynamic elements of marketing be modeled and studied, and a significant part of my research activity has been dedicated to exploring the nature and implications of dynamic marketing strategies. The marketing field has used various models and methodologies in the attempt to understand dynamic markets. I must thank my dissertation advisor, Dave Montgomery at Stanford, for originally turning my attention toward time-varying parameter models some 14 years ago. From that plat­ form, I have proceeded to search for models that capture the essence of dynamic marketing, as well as for methodological tools, empirical as well as analytical, that allow insightful study of such models.

Divergence: A Source of Creative Thinking The outstanding job accomplished by Bernard, Gary, and Gilles is really praiseworthy: not only did they succeed in completing within a remark­ ably short span of time the editing of the contributions to the conference that marked the 20th Anniversary of the European Institute for Ad­ vanced Studies in Management; they have also managed to elicit numerous insightful comments from a host of dashing young scholars as well as from the fortunate few established authorities whose findings have long be­ come leading articles in the best academic journals, who now chair those journals' editorial boards, and after whom great scientific awards have been named. In so doing, our dedicated triumvirate has blended together pieces of diverse research traditions-some of them quite puzzling-and mixed significantly differentiated styles of expression. The controversial display of self-confidence by some distinguished colleagues, the amazingly emo­ tional "good old" memories revived by their peers, the scapegoat-finding and moralizing confessions produced by some of their disciples together with the detached systematic rigidity of some others all combine to pro­ duce a multivarious patchwork that may well prove the existence of a marketing scholar lifecycle. This cartoon-like four-class typology might even make it worth the reader's while to indulge in some guesswork to discover the sequence of the four stages as an exercise and then partition the author population accordingly.

Remarkable advance in quantitative marketing research in the last two decades, incorporating applied microeconomic theories, operations research and management applications, has brought the field of marketing alongside with finance, accounting and productionto within an executive'sreach for a sophisticatedtoolbox for decision­ making in an increasingly competitive and complex business environment. A quick look at Marketing, a recently published book edited by Eliashberg and Lilien would indicate even to the casual reader the extent of such methodological progress made by marketing scholars. Even in such an impressive and nearly exhaustive collection oftopics, with the notable exception pointed out by the editors of applicationsofthe scanner data, and in spite of the reference to it, an important omission is related to the issues ofmarketing decisions under conditions ofuncertainty. It is fairly obvious to the marketing executive and academician alike to recognize the important role uncertaintyplays in marketingdecisions such as pricing, promotion, advertising, sales force management, and others. The major purpose of this study is to address certain major marketing decision variables within the general context of an uncertain environment. While there have been significant progresses in analyzing marketing behaviors in a stochastic environment,the sourcesscatteramong differentmanagementandmarketingjoumals; and to the extent that these issues are addressed at all, they have aimed mainly at each separate, specifictopic at a time. Thus, our effort to bring these studies together in the same framework should facilitate our in-depth analysis of these important phenomena.

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. At the heart of their analysis is a single-manufacturer/multiple-retailer meta-model that embraces any degree of inter-retailer competition and any distribution of market shares. In Chapters 1 and 2 the authors provide an introduction to the current, analytical literature on distribution channels, and they present an intuitively appealing prologue to the Channel Myths that are developed rigorously in later Chapters. In Chapters 3, 4, and 10 they extend the literature by ascertaining the relationship between the manufacturer-optimal wholesale-price strategy and channel breadth. Specific analyses include multiple, non-competing retailers, multiple states-of-nature, and multiple, competing retailers. In Chapters 5-7 the authors determine the profitability of various wholesale-price strategies; this analysis culminates in Chapters 8 and 9 with the determination of the (very limited) conditions under which channel coordination can be optimal for the manufacturer. In Chapter 11 they prove that existing methods of measuring the effect of a change in the degree of inter-retailer substitutability are totally misleading. They then develop an original, theoretical basis for measuring the impact of a change in the degree of inter-retailer substitutability that yields insightful, intuitively appealing results. In Chapter 12 the authors set forth an agenda for future research based on a meta-model that embraces all existing models in the literature. They also issue an appeal for creation of a "Unifying Theory of Distribution Channels" that will enable researchers to work independently and yet to contribute toward the common goal of deepening the marketing science professions’ understanding of distribution channels.

The dynamic modelling and analysis of advertising competition continues to be a topic of importance to scholars and practitioners. The second edition of this text reviews empirical and analytical research on the topic and extends the research through analytical and numerical investigation. Three types of model frameworks - Lanchester, Vidale-Wolfe, and diffusion - are combined with two different approaches to developing competitive advertising strategies - perfect equilibria and dynamic conjectural variations - in the analysis of duopoly and triopoly competition. Advertising strategies developed with the different approaches are compared and contrasted to open-loop strategies.

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.

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.

Game theory has proven useful to represent and conceptualize problems of conflict and cooperation in a formal way, and to predict the outcome of such situations. Differential games are dynamic games that are particularly designed to study systems where observations and decisions are made in real time. The book conveys to the reader the state of the art of research in marketing applications of differential game theory. This research started about 25 years ago and the literature has now reached an extent and a maturity that makes it natural to take stock. The book deals with differential games in advertising, pricing, and marketing channels, as well as with marketing-production and pricing-advertising interfaces. It provides also a tutorial on main concepts in differential games.

Integration is an important and practical matter in today's globalized commerce. This has led companies and organizations to place increasing emphasis on creating a seamless workflow environment from one business function to another. The academic research community recognizes the importance of providing problem-solving direction to the different, and sometimes conflicting, functional perspectives of marketing, engineering, logistics, and manufacturing. The research streams that characterize these issues are in the domain of business interfaces. These include the benefits of coordination, new product development, product portfolio management, supply chain coordination, and partnerships and collaboration in the internet space.Managing Business Interfaces: Marketing, Engineering, and Manufacturing Perspectives provides state-of-the-art summary as well as new thoughts in managing business interfaces. Through eleven invited chapters, it brings together the latest developments in leading edge research related to new product development, supply chain management, e-business operations, and field studies.

Database marketing is at the crossroads of technology, business strategy, and customer relationship management. Enabled by sophisticated information and communication systems, today’s organizations have the capacity to analyze customer data to inform and enhance every facet of the enterprise—from branding and promotion campaigns to supply chain management to employee training to new product development. Based on decades of collective research, teaching, and application in the field, the authors present the most comprehensive treatment to date of database marketing, integrating theory and practice. Presenting rigorous models, methodologies, and techniques (including data collection, field testing, and predictive modeling), and illustrating them through dozens of examples, the authors cover the full spectrum of principles and topics related to database marketing."This is an excellent in-depth overview of both well-known and very recent topics in customer management models. It is an absolute must for marketers who want to enrich their knowledge on customer analytics." (Peter C. Verhoef, Professor of Marketing, Faculty of Economics and Business, University of Groningen)"A marvelous combination of relevance and sophisticated yet understandable analytical material. It should be a standard reference in the area for many years." (Don Lehmann, George E. Warren Professor of Business, Columbia Business School)"The title tells a lot about the book's approach—though the cover reads, "database," the content is mostly about customers and that's where the real-world action is. Most enjoyable is the comprehensive story – in case after case – which clearly explains what the analysis and concepts really mean. This is an essential read for those interested in database marketing, customer relationship management and customer optimization." (Richard Hochhauser, President and CEO, Harte-Hanks, Inc.)"In this tour de force of carefulscholarship, the authors canvass the ever expanding literature on database marketing. This book will become an invaluable reference or text for anyone practicing, researching, teaching or studying the subject." (Edward C. Malthouse, Theodore R. and Annie Laurie Sills Associate Professor of Integrated Marketing Communications, Northwestern University)

Product sales, especially for new products, are influenced by many factors. These factors are both internal and external to the selling organization, and are both controllable and uncontrollable. Due to the enormous complexity of such factors, it is not surprising that product failure rates are relatively high. Indeed, new product failure rates have variously been reported as between 40 and 90 percent. Despite this multitude of factors, marketing researchers have not been deterred from developing and designing techniques to predict or explain the levels of new product sales over time. The proliferation of the internet, the necessity or developing a road map to plan the launch and exit times of various generations of a product, and the shortening of product life cycles are challenging firms to investigate market penetration, or innovation diffusion, models. These models not only provide information on new product sales over time but also provide insight on the speed with which a new product is being accepted by various buying groups, such as those identified as innovators, early adopters, early majority, late majority, and laggards. New Product Diffusion Models aims to distill, synthesize, and integrate the best thinking that is currently available on the theory and practice of new product diffusion models. This state-of-the-art assessment includes contributions by individuals who have been at the forefront of developing and applying these models in industry. The book's twelve chapters are written by a combined total of thirty-two experts who together represent twenty-five different universities and other organizations in Australia, Europe, Hong Kong, Israel, and the United States. The book will be useful for researchers and students in marketing and technological forecasting, as well as those in other allied disciplines who study relevant aspects of innovation diffusion. Practitioners in high-tech and consumer durable industries should also gain newinsights from New Product Diffusion Models. The book is divided into five parts: I. Overview; II. Strategic, Global, and Digital Environments for Diffusion Analysis; III. Diffusion Models; IV. Estimation and V. Applications and Software. The final section includes a PC-based software program developed by Gary L. Lilien and Arvind Rangaswamy (1998) to implement the Bass diffusion model. A case on high-definition television is included to illustrate the various features of the software. A free, 15-day trial access period for the updated software can be downloaded from http://www.mktgeng.com/diffusionbook. Among the book's many highlights are chapters addressing the implications posed by the internet, globalization, and production policies upon diffusion of new products and technologies in the population.

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. At the heart of their analysis is a single-manufacturer/multiple-retailer meta-model that embraces any degree of inter-retailer competition and any distribution of market shares. In Chapters 1 and 2 the authors provide an introduction to the current, analytical literature on distribution channels, and they present an intuitively appealing prologue to the Channel Myths that are developed rigorously in later Chapters. In Chapters 3, 4, and 10 they extend the literature by ascertaining the relationship between the manufacturer-optimal wholesale-price strategy and channel breadth. Specific analyses include multiple, non-competing retailers, multiple states-of-nature, and multiple, competing retailers. In Chapters 5-7 the authors determine the profitability of various wholesale-price strategies; this analysis culminates in Chapters 8 and 9 with the determination of the (very limited) conditions under which channel coordination can be optimal for the manufacturer. In Chapter 11 they prove that existing methods of measuring the effect of a change in the degree of inter-retailer substitutability are totally misleading. They then develop an original, theoretical basis for measuring the impact of a change in the degree of inter-retailer substitutability that yields insightful, intuitively appealing results. In Chapter 12 the authors set forth an agenda for future research based on a meta-model that embraces all existing models in the literature. They also issue an appeal for creation of a "Unifying Theory of Distribution Channels" that will enable researchers to work independently and yet to contribute toward the common goal of deepening the marketing science professions’ understanding of distribution channels.

Game theory has proven useful to represent and conceptualize problems of conflict and cooperation in a formal way, and to predict the outcome of such situations. Differential games are dynamic games that are particularly designed to study systems where observations and decisions are made in real time. The book conveys to the reader the state of the art of research in marketing applications of differential game theory. This research started about 25 years ago and the literature has now reached an extent and a maturity that makes it natural to take stock. The book deals with differential games in advertising, pricing, and marketing channels, as well as with marketing-production and pricing-advertising interfaces. It provides also a tutorial on main concepts in differential games.

I am gratified that there is sufficient interest in the subject matter so as to support the offering of a second edition of this monograph. The of differential games dynamic interpretation and game theoretic foundation form a powerful and vital methodology for helping us study and understand marketing competition. This second edition offers a blend of what proved to be successful with the first edition and new material. The first two chapters, reviewing empirical and modeling research, have been updated to include contributions in the last decade that have advanced the area. I have not changed the essential content in the duopoly analyses in chapters 3, 4, and 5. A notable addition to the present edition are the new chapters, 6, 7, and 8, which offer analysis of three triopoly models. In the final chapter, I offer my summary view of the area and hope for continued contributions. I want to express my appreciation for the support of Josh Eliashberg, editor of the International Series in Quantitative Marketing, as well as Zachary Rolnik, Director, and David Cella, Publishing Editor, of Kluwer. Their encouragement has provided crucial motivation in this endeavor.

Marketing management support systems are designed to make marketing managers more effective decision makers in this electronic era. Developments in information technology have caused a marketing data explosion, but have also provided a powerful set of tools that can transform this data into applicable marketing knowledge. Consequently, companies are making major investments in such marketing decision aids. This book is the first comprehensive, systematic textbook on marketing management support systems. The basic issue is the question of how to determine the most effective type of support for a given marketing decision maker in a particular decision situation. The book takes a demand-oriented approach. Decision aids for marketing managers can only be effective if they match with the thinking and reasoning process of the decision makers who use them. Consequently, the important questions addressed in this book are: how do marketing managers make decisions; how can marketing management support systems help to overcome several (cognitive) limitations of human decision makers; and what is the most appropriate type of management support system for assisting the problem-solving methods employed by a marketing decision-maker?

Modern marketing techniques in industrialized countries cannot be implemented without segmentation of the potential market. Goods are no longer produced and sold without a significant consideration of customer needs combined with a recognition that these needs are heterogeneous. Since first emerging in the late 1950s, the concept of segmentation has been one of the most researched topics in the marketing literature. Segmentation has become a central topic to both the theory and practice of marketing, particularly in the recent development of finite mixture models to better identify market segments. This second edition of Market Segmentation updates and extends the integrated examination of segmentation theory and methodology begun in the first edition. A chapter on mixture model analysis of paired comparison data has been added, together with a new chapter on the pros and cons of the mixture model. The book starts with a framework for considering the various bases and methods available for conducting segmentation studies. The second section contains a more detailed discussion of the methodology for market segmentation, from traditional clustering algorithms to more recent developments in finite mixtures and latent class models. Three types of finite mixture models are discussed in this second section: simple mixtures, mixtures of regressions and mixtures of unfolding models. The third main section is devoted to special topics in market segmentation such as joint segmentation, segmentation using tailored interviewing and segmentation with structural equation models. The fourth part covers four major approaches to applied market segmentation: geo-demographic, lifestyle, response-based, and conjoint analysis. The final concluding section discusses directions for further research.

Remarkable advance in quantitative marketing research in the last two decades, incorporating applied microeconomic theories, operations research and management applications, has brought the field of marketing alongside with finance, accounting and productionto within an executive'sreach for a sophisticatedtoolbox for decision­ making in an increasingly competitive and complex business environment. A quick look at Marketing, a recently published book edited by Eliashberg and Lilien would indicate even to the casual reader the extent of such methodological progress made by marketing scholars. Even in such an impressive and nearly exhaustive collection oftopics, with the notable exception pointed out by the editors of applicationsofthe scanner data, and in spite of the reference to it, an important omission is related to the issues ofmarketing decisions under conditions ofuncertainty. It is fairly obvious to the marketing executive and academician alike to recognize the important role uncertaintyplays in marketingdecisions such as pricing, promotion, advertising, sales force management, and others. The major purpose of this study is to address certain major marketing decision variables within the general context of an uncertain environment. While there have been significant progresses in analyzing marketing behaviors in a stochastic environment,the sourcesscatteramong differentmanagementandmarketingjoumals; and to the extent that these issues are addressed at all, they have aimed mainly at each separate, specifictopic at a time. Thus, our effort to bring these studies together in the same framework should facilitate our in-depth analysis of these important phenomena.

The pharmaceutical industry is one of today’s most dynamic and complex industries, involving commercialization of cutting-edge scientific research, a huge web of stakeholders (from investors to doctors), multi-stage supply chains, fierce competition in the race to market, and a challenging regulatory environment.  The stakes are high, with each new product raising the prospect of spectacular success—or failure.  Worldwide revenues are approaching $1 trillion; in the U.S. alone, marketing for pharmaceutical products is, itself, a multi-billion dollar industry.  In this volume, the editors showcase contributions from experts around the world to capture the state of the art in research, analysis, and practice, and covering the full spectrum of topics relating to innovation and marketing, including R&D, promotion, pricing, branding, competitive strategy, and portfolio management.  Chapters include such features as:·         An extensive  literature review, including coverage of research from fields other than marketing·         an overview of how practitioners have addressed the topic·         introduction of relevant analytical tools, such as statistics and ethnographic studies·         suggestions for further research by scholars and students The result is a comprehensive, state-of-the-art resource that will be of interest to researchers, policymakers, and practitioners, alike.

This book is about how models can be developed to represent demand and supply on markets, where the emphasis is on demand models. Its primary focus is on models that can be used by managers to support marketing decisions.Modeling Markets presents a comprehensive overview of the tools and methodologies that managers can use in decision making. It has long been known that even simple models outperform judgments in predicting outcomes in a wide variety of contexts. More complex models potentially provide insights about structural relations not available from casual observations. In this book, the authors present a wealth of insights developed at the forefront of the field, covering all key aspects of specification, estimation, validation and use of models. The most current insights and innovations in quantitative marketing are presented, including in-depth discussion of Bayesian estimation methods. Throughout the book, the authors provide examples and illustrations. This book will be of interest to researchers, analysts, managers and students who want to understand, develop or use models of marketing phenomena.