Bøger i International Series in Quantitative Marketing serien

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.

This book is about how models can be developed to represent demand and supply on markets, where the emphasis is on demand models. 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.

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. A notable addition to the present edition are the new chapters, 6, 7, and 8, which offer analysis of three triopoly models.

Based on decades of research, teaching and application, this book presents a comprehensive treatment of database marketing. Integrating theory and practice, it offers rigorous models, methodologies and techniques illustrated through numerous examples.

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;

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.

This volume presents advanced techniques to modeling markets, with a wide spectrum of topics, including advanced individual demand models, time series analysis, state space models, spatial models, structural models, mediation, models that specify competition and diffusion models.

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.

This volume presents advanced techniques to modeling markets, with a wide spectrum of topics, including advanced individual demand models, time series analysis, state space models, spatial models, structural models, mediation, models that specify competition and diffusion models.

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.

This book reports over a decade's worth of research on the development of empirical response models that have important uses for generating marketing knowledge and improving marketing decisions. It illustrates how marketing generalizations are the basis of marketing theory and marketing knowledge.

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.

This book is about the role of expert systems in marketing, particularly in the consumer goods industry. 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 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.

Marketing management support systems are designed to make marketing managers more effective decision makers in this electronic era. 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.

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.

Amiya Chakravarty is a big name in production manufacturing and Josh Eliashberg is a huge name in marketing. This is one of the first books that examines the interface of Marketing and Production, with the chapters written by well-known people in the field. Hardcover version published in December 2003.

Amiya Chakravarty is a big name in production manufacturing and Josh Eliashberg is a huge name in marketing. This is one of the first books that examines the interface of Marketing and Production, with the chapters written by well-known people in the field. Hardcover version published in December 2003.

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 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.

Marketing management support systems are designed to make marketing managers more effective decision makers in this electronic era. 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.

Addresses marketing decisions under stochastic conditions in a unified framework within which potential interactions among the firm's marketing efforts may take place. This book begins with static, stochastic formulations of individual marketing decisions for single-product, competitive firms and formal results are presented and analyzed.

This book is about marketing models and the process of model building. Since models explicate the relations, both the process of model building and the model that ultimately results can improve the quality of marketing decisions.

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.

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.

Reviews the research in marketing by considering the different research streams together to understand, evaluate and criticize those various streams and to explore potential overlaps and divergence likely to emerge in the future. This book is organized into quantitative and qualitative parts.

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.

This book is about the role of expert systems in marketing, particularly in the consumer goods industry. 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.