Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Principles of Marketing Engineering, 2nd Edition
The 21st century business environment demands more analysis and rigor in marketing decision making. Increasingly, marketing decision making resembles design engineering-putting together concepts, data, analyses, and simulations to learn about the marketplace and to design effective marketing plans. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems). Marketing Engineering is the systematic approach to harness data and knowledge to drive effective marketing decision making and implementation through a technology-enabled and model-supported decision proces...
Marketing Engineering
Several forces are transforming the structure and content of the marketing profession. Marketers are seeing increasingly faster changes in the marketplace and are barraged with an ever increasing amount of information. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering. This textbook, combined with a comprehensive collection of 26 leading-edge software models provides the student with the know-how and tools to collect the right information and perform analysis to make better marketing plans, better product designs, and better decisions. Our purpose in writing this book is to help educate and train a new generation of marketing managers. We aim to train marketing engineers to translate concepts into context-specific operational decisions and actions using analytical, quantitative, and computer modeling techniques. We link theory to practice and practice to theory.
Marketing Models
The view of this book is that there are essentially three purposes for modeling in marketing: measuring marketing actions and outcomes, developing operational support for marketing decisions, and explaining marketing observations or phenomena.
Handbook of Business-to-Business Marketing
This path-breaking Handbook is targeted primarily at marketing academics and graduate students who want a comprehensive overview of the academic state of the business-to-business marketing domain. It will also prove an invaluable resource for forward-thinking business-to-business practitioners who want to be aware of the current state of knowledge in their domains.
New Product and Brand Management
Learning good table manners has never been this much fun! "Chocolate mousse!" says greedy Goose. "Don't just grab it," says angry Rabbit. Good manners are not on the menu at this meal. Duck won't eat his carrots. Moth's eating the cloth, and Sheep would rather sleep than wash the dishes. Thank goodness some of the animals know how to behave. Children's favorite foods and animals are combined in delicious rhyming phrases, making this story of the funniest dinner party ever perfect to read aloud.
The History Of Marketing Science
The field of marketing science has a rich history of modeling marketing phenomena using the disciplines of economics, statistics, operations research, and other related fields. Since it is roughly 50 years from its origins, The History of Marketing Science is a timely review of the accomplishments of marketing scientists in a number of research areas.Different research areas of marketing science, such as Pricing, Internet Marketing, Diffusion Models, and Advertising, are treated to a highly readable and easy-to-digest historical analysis by the contributing authors. Each chapter provides a chronological timeline of key historical developments in the area of marketing science covered. Readers of other disciplinary backgrounds outside of economics, statistics, and operations research will be more than able to appreciate the development of marketing science as a field of research and its pioneers through the book.
Marketing Engineering
Accompanying CD-ROM contains ... "26 software programs, help files and tutorials."--Page 4 of cover.
Marketing
Hardbound. Leading marketing scientists, with an MS/OR orientation, present in this book a state-of-the-art review of their area of expertise. The wide range of material spans the marketing discipline and represents excellent coverage of both what is known and what problem-areas present themselves as ripe for further development.The articles are written with a technically sophisticated reader in mind, but not necessarily an expert in marketing. The authors provide a discussion of the motivation - the behavioral foundations or key assumptions - leading to the development of the important models or methods in each area.While not primarily a text, the book provides an excellent foundation for advanced students in marketing. MS/OR professionals, both academic and practitioner alike, will appreciate the impact that the MS/OR approach has had in the marketing area. Finally, the book provides must reading for marketing scientists, academics and practitio
Handbook of Marketing Decision Models
Marketing models is a core component of the marketing discipline. The recent developments in marketing models have been incredibly fast with information technology (e.g., the Internet), online marketing (e-commerce) and customer relationship management (CRM) creating radical changes in the way companies interact with their customers. This has created completely new breeds of marketing models, but major progress has also taken place in existing types of marketing models. Handbook of Marketing Decision Models presents the state of the art in marketing decision models. The book deals with new modeling areas, such as customer relationship management, customer value and online marketing, as well as recent developments in other advertising, sales promotions, sales management, and competition are dealt with. New developments are in consumer decision models, models for return on marketing, marketing management support systems, and in special techniques such as time series and neural nets.
