At this point in time, there is no generally accepted methodology for explaining and predicting human behavior given a product choice situation. This is true despite the critical importance of such meth odology to marketing, transportation and urban planning. While the social sciences provide numerous theories to be tested and the mathe matical and statistical procedures exist in general to do so, at this point, no single unified theory has emerged. It is generally accepted that to explain product choice behav ior,products must be described in terms of attributes. Using anyone of a number of procedures, it is possible to obtain measurements on the attributes of the products under consideration. However, there is no generally accepted methodology. Given the attribute profiles of two products, in order to explain and predict preference, it is necessary to determine the relative importance of each of the product attributes. Once again, there is no generally accepted methodology. There are two basic approaches: The first, called the attitudinal approach, obtains importance measure ments directly from respondents using one of many scaling techniques; the second, termed the inferential method endeavors to infer impor tances from product preference and attribute data. Since it is gen erally felt that respondents are unwilling and/or unable to provide meaningful importance measurements, the inferential method is most widely accepted.

EBOOK: Principles and Practice of Marketing

Conjoint analysis is probably the most significant development in marketing research in the past few decades. It can be described as a set of techniques ideally suited to studying customers’ decision-making processes and determining tradeoffs. Though this book is oriented towards methods and applications of conjoint analysis in marketing, conjoint methods are also applicable for other business and social sciences. After an introduction to the basic ideas of conjoint analysis the book describes the steps involved in designing a ratings-based conjoint study, it covers various methods for estimating partworth functions from preference ratings data, and dedicates a chapter on methods of design and analysis of conjoint-based choice experiments, where choice is measured directly. Chapter 5 describes several methods for handling a large number of attributes. Chapters 6 through 8 discuss the use of conjoint analysis for specific applications like product and service design or product line decisions, product positioning and market segmentation decisions, and pricing decisions. Chapter 9 collates miscellaneous applications of marketing mix including marketing resource allocation or store location decisions. Finally, Chapter 10 reviews more recent developments in experimental design and data analysis and presents an assessment of future developments.

​This volume includes the full proceedings from the 1999 Academy of Marketing Science (AMS) Annual Conference held in Coral Gables, Florida. The research and presentations contained in this volume cover many aspects of marketing science including marketing strategy, consumer behaviour, international marketing, advertising, marketing education, among others. Founded in 1971, the Academy of Marketing Science is an international organization dedicated to promoting timely explorations of phenomena related to the science of marketing in theory, research, and practice. Among its services to members and the community at large, the Academy offers conferences, congresses and symposia that attract delegates from around the world. Presentations from these events are published in this Proceedings series, which offers a comprehensive archive of volumes reflecting the evolution of the field. Volumes deliver cutting-edge research and insights, complimenting the Academy’s flagship journals, the Journal of the Academy of Marketing Science (JAMS) and AMS Review. Volumes are edited by leading scholars and practitioners across a wide range of subject areas in marketing science.​

Helping tech-savvy marketers and data analysts solve real-world business problems with Excel Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today's busy offices, marketers and analysts need simple, low-cost ways to process and make the most of all that data. This expert book offers the perfect solution. Written by data analysis expert Wayne L. Winston, this practical resource shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques—and achieve optimum results. Practical exercises in each chapter help you apply and reinforce techniques as you learn. Shows you how to perform sophisticated business analyses using the cost-effective and widely available Microsoft Excel instead of expensive, proprietary analytical tools Reveals how to target and retain profitable customers and avoid high-risk customers Helps you forecast sales and improve response rates for marketing campaigns Explores how to optimize price points for products and services, optimize store layouts, and improve online advertising Covers social media, viral marketing, and how to exploit both effectively Improve your marketing results with Microsoft Excel and the invaluable techniques and ideas in Marketing Analytics: Data-Driven Techniques with Microsoft Excel.

This monograph is intended as a contribution to applied work in production theory by treating: a) The measurement problems involved whenever several outputs are jointly produced, and b) The (possible) econometric framework for estimating production function parameters whenever (relative) prices vary sufficiently over the observations. Thus, the "pure" theory of production, and the theory of non-linear regression is not treated in sufficient detail: for these topics we refer to the available literature~ for a comprehensive list of references we refer to Uebe (1975). Some years ago, papers by L. J. Lau and W. E. Diewert initiated my interest in duality within production theory, and then I started to appreciate R. W. Shephard's fundamental contribution to this topic. This monograph is a (minor) revision of a Ph. D. dissertation submitted to the Department of Economics, The University of Wisconsin, Madison, in August 1973. The Graduate School and the Social Systems Research Institute provided funds for the reported computer work, Lawrence R. Klein and Laurits R. Christensen provided data, and as a Graduate Student I received financial support in form of an University Fellowship~ all this is very much appreciated. With some nostalgia I think back to the enjoyable period of learning during the preparation of my diFosertation~ I appreciate the spirit within the department, and the guidance of my committee Arthur S. Goldberger, Dennis J. Aigner, and Laurits R. Christensen.

As the residential buildings sector accounts for around 30 percent of the final energy demand in Germany, this sector is increasingly becoming the focus of public attention with regard to climate change. In this book, decisions on energy consumption by private households are examined. The analyses are based on several empirical methods. The results show that the road to more sustainable energy consumption in residential buildings is not hampered by a lack of will on behalf of the consumers. However one should be realistic that there are many instances where improving thermal institution involves additional economic costs for individual households.