Randall L. Schultz – författare

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.

As in the first edition, "Market Response Models": integrates technical material with discussions of its relevance to management; provides continuity to a decades-long research stream; illustrates how marketing generalizations are the basis of marketing theory and knowledge; shows how research can be applied to marketing planning and forecasting; and presents original research in marketing. This second edition of "Market Response Models": places much more emphasis on the basic building blocks of market response modelling - markets, data, and sales drivers, through a separate chapter; splits the design of response models into separate chapters on static and dynamic models; discusses techniques and findings spawned by the marketing information revolution such as scanner data; emphasizes new insights available on marketing sales drivers, especially improved understanding of sales promotion; demonstrates methodological developments to assess long-term impacts, where present, of current marketing efforts; includes a new chapter on sales forecasting; adds mini-case histories in the form of boxed inserts entitled "Industry Perspectives", which are primarily written by business executives.

This book presents a structural model of information system implementation and tests using data from several independent system implementation efforts. The model is based on the results of 15 years of implementation research and integrates the two primary streams of that research: factor studies and process studies. Testing the model involved three studies in diverse implementation contexts. The tests provide strong support for some aspects of the model and identify areas where the model is in need of further development and testing. The book includes a detailed review of past implementation research, a thorough explanation of the basis for the structural model's mathematical properties, descriptions of two field tests of the model including details about the research instruments employed, and a discussion of the utility of these studies for implementation research and practice.

A guide to the use of market response models for planning and forecasting. The text can serve as a text for graduate students in marketing, as a guide for marketing scientists and as a handbook for marketing professionals. In each case the purpose has been the same: to capture the essence of a technique so advanced it has changed the style of marketing mix decision making. Now, in its second edition, the book covers everything from advances in technology and science to the recognition of database and Internet-age marketing.It places much more emphasis on the basic building blocks of market response modelling - markets, data, and sales drivers - through a separate chapter; splits the design of response models into separate chapters on static and dynamic models; discusses techniques and findings spawned by the marketing information revolution; emphasizes insights available on marketing sales drivers, especially improved understanding of sales promotion; demonstrates methodological developments to assess long-term impacts, where present, of current marketing efforts in the 21st century; includes a chapter on sales forecasting; and adds mini-case histories in the form of boxed inserts entitled "Industry Perspectives", which are primarily written by business executives.

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. Some of its contributions to marketing are the following: 1. It integrates state-of-the art technical material with discussions of its relevance to management. 2. It provides continuity to a research stream over 20 years old. 3. It illustrates how marketing generalizations are the basis of marketing theory and marketing knowledge. 4. It shows how the research can be applied to marketing planning and forecasting. 5. It presents original research in marketing. The book addresses both marketing researchers and marketing managers. This can be done because empirical decision models are helpful in practice and are also based on theories of response. Econometric and time series analysis (ETS) is one of the few areas in marketing where there is little, if any, conflict between the academic sphere and the world of professional practice. Market Response Models is a sequel to Marketing Models and Econometric Research, published in 1976. It is rare for a research-oriented book in market­ ing to be updated or to have a sequel. Unlike many other methodologies, ETS research in marketing has stood the test of time. It remains the main method for discovering relations among marketing variables.