Conjoint Measurement

This fascinating book covers all the recent developments in conjoint analysis. Leading scientists present different aspects of the theory and applications of this technique. A wide variety of models, techniques, and applications are discussed, including normative models that maximize return, extension of choice-based conjoint simulations, latent class, hierarchical Bayes modeling, new choice simulators, and normative models for representing competitive actions and reactions (based on game theory).

by Paul E. Green I am honored and pleased to respond to authors request to write a Fore word for this excellent collection of essays on conjoint analysis and related topics. While a number of survey articles and sporadic book chapters have appeared on the subject, to the best of my knowledge this book represents the first volume of contributed essays on conjoint analysis. The book re flects not only the geographical diversity of its contributors but also the variety and depth of their topics. The development of conjoint analysis and its application to marketing and business research is noteworthy, both in its eclectic roots (psychometrics, statistics, operations research, economics) and the fact that its development reflects the efforts of a large variety of professionals -academics, market ing research consultants, industry practitioners, and software developers. Reasons for the early success and diffusion of conjoint analysis are not hard to find. First, by the early sixties, precursory psychometric techniques (e.g., multidimensional scaling and correspondence analysis, cluster analy sis, and general multivariate techniques) had already shown their value in practical business research and application. Second, conjoint analysis pro vided a new and powerful array of methods for tackling the important problem of representing and predicting buyer preference judgments and choice behavior-clearly a major problem area in marketing.

Covers all recent developments in Conjoint Analysis. Leading scientists present theory and applications of this technique. In short, the following models, techniques, and applications are discussed: normative models that maximize return, extension of choice-based conjoint simulations, latent class, hierarchical Bayes modelling, new choice simulators, normative models for representing competitive actions and reactions (based on game theory), applications in diverse areas, computation of monetary equivalents of part worth, share/return optimisation (including Pareto frontier analysis), coupling of conjoint analysis with the perceptual and preference mapping of choice simulator results.

Inhaltsangabe:Zusammenfassung: Die vorliegende Arbeit (in Englisch) beschäftigt sich mit der Integration der Methodik Conjointanalyse (CA) in den Quality Function Deployment Prozeß, um den QFD-Prozeß in Entscheidungs- und Bewertungssituationen zu unterstützen. Im Mittelpunkt steht dabei die Untersuchung der gängigen Conjointmethoden auf Anwendbarkeit und Eignung für groß angelegte Studien, wie z. B. QFD-Anwendungen. Detailliert wird dabei auf eine Erweiterung oder Unterstützung der Conjointanalyse eingegangen, um eine Vielzahl an Merkmalen und Merkmalsausprägungen (Kundenanforderungen) berücksichtigen zu können. Die kommerzielle Anwendung der einzelnen Methodiken, eine Fragebogenauswertung sowie ein Vergleich von 21 CA- und 3 der bekanntesten QFD Software-tools runden diese Arbeit ab. Abstract: This paper is structured into 5 chapters: Chapter 1 contains an introduction into the problem area and the aim of the thesis. Moreover, it gives a survey of the procedure to reach the target of extending and supporting several Conjoint Analysis methodologies to be able for an integration into the Quality Function Deployment approach with its huge amount of customer requirements (attributes and levels). Chapter 2 shows the integration of Conjoint Analysis and Quality Function Deployment into the Total Quality Management concept as quality improving, customer orientated (key word mass customization), and cost reducing tools. The importance to support Quality Function Deployment by Conjoint Analysis is pointed out to lead over to the main chapter of the paper. Chapter 3 is dedicated to several Conjoint Analysis models and the way in which to extend and support these methods, so that an integration into a large industrial study such as a Quality Function Deployment application can take place without any problems. To this purpose several conjoint techniques are described in detail, are extended by further techniques, and are compared to each other concerning their validity so that, finally, explicit recommendations can be given. The commercial use of Conjoint Analysis and the method transfer into several software-tools round off this chapter. Chapter 4 describes the Quality Function Deployment methodology in relation to the aim of this paper. The central subject is the House of Quality and its places where the Conjoint Analysis technique(s) can be applied. Results about the commercial use of several software-tools finish this chapter. Chapter 5 sums up [...]

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.

Paul Kline reveals that the scientific basis of psychological testing is weak. He argues that truly scientific forms of measurement could be developed using measurement theory, to create a new psychometrics.

The goal of Norman H. Anderson's new book is to help students develop skills of scientific inference. To accomplish this he organized the book around the "Experimental Pyramid"--six levels that represent a hierarchy of considerations in empirical investigation--conceptual framework, phenomena, behavior, measurement, design, and statistical inference. To facilitate conceptual and empirical understanding, Anderson de-emphasizes computational formulas and null hypothesis testing. Other features include: *emphasis on visual inspection as a basic skill in experimental analysis to help students develop an intuitive appreciation of data patterns; *exercises that emphasize development of conceptual and empirical application of methods of design and analysis and de-emphasize formulas and calculations; and *heavier emphasis on confidence intervals than significance tests. The book is intended for use in graduate-level experimental design/research methods or statistics courses in psychology, education, and other applied social sciences, as well as a professional resource for active researchers. The first 12 chapters present the core concepts graduate students must understand. The next nine chapters serve as a reference handbook by focusing on specialized topics with a minimum of technicalities.