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 [...]

Especially in industrial countries the portion of elderly people is growing in many societies. Their needs are more intensified than the demands of younger people in many aspects. Companies need the right tools (e.g. market research methods for elderly people) to detect these needs, preferences, and demands of elderly people. Samah Abu-Assab verifies two existing research methods and suggests a new one for determining the preferences of elderly people. The new method seems to be promising and adequate for the elderly target group.

It is a great privilege and pleasure to write a foreword for a book honor ing Wolfgang Gaul on the occasion of his sixtieth birthday. Wolfgang Gaul is currently Professor of Business Administration and Management Science and the Head of the Institute of Decision Theory and Management Science, Faculty of Economics, University of Karlsruhe (TH), Germany. He is, by any measure, one of the most distinguished and eminent scholars in the world today. Wolfgang Gaul has been instrumental in numerous leading research initia tives and has achieved an unprecedented level of success in facilitating com munication among researchers in diverse disciplines from around the world. A particularly remarkable and unique aspect of his work is that he has been a leading scholar in such diverse areas of research as graph theory and net work models, reliability theory, stochastic optimization, operations research, probability theory, sampling theory, cluster analysis, scaling and multivariate data analysis. His activities have been directed not only at these and other theoretical topics, but also at applications of statistical and mathematical tools to a multitude of important problems in computer science (e.g., w- mining), business research (e.g., market segmentation), management science (e.g., decision support systems) and behavioral sciences (e.g., preference mea surement and data mining). All of his endeavors have been accomplished at the highest level of professional excellence.

Most organizations recognize the impact that both customer and employee satisfaction have on overall financial performance. Actually acting on that information is the hard part. That is the focus of Linking Customer and Employee Satisfaction to the Bottom Line, which focuses on the relationship between customer satisfaction and tangible business outcomes like market share, revenue, and profitability. Intended for advanced service quality managers and marketing researchers with more than a modest exposure to statistical data analysis, this book provides a comprehensive overview of how these data may be related to critical business outcomes. Perhaps more importantly, researchers with mature customer satisfaction systems may use the techniques described in this book to maximize the value of their existing programs. While no technique or methodology can guarantee a strong link between customer satisfaction and key business outcomes, this book can ensure that appropriate scales, variables, and assumptions are used.

Especially in industrial countries the portion of elderly people is growing in many societies. Their needs are more intensified than the demands of younger people in many aspects. Companies need the right tools (e.g. market research methods for elderly people) to detect these needs, preferences, and demands of elderly people. Samah Abu-Assab verifies two existing research methods and suggests a new one for determining the preferences of elderly people. The new method seems to be promising and adequate for the elderly target group.

7. 1. 1 Background Uncertainty can be considered as the lack of adequate information to make a decision. It is important to quantify uncertainties in mathematical models used for design and optimization of nondeterministic engineering systems. In general, - certainty can be broadly classi?ed into three types (Bae et al. 2004; Ha-Rok 2004; Klir and Wierman 1998; Oberkampf and Helton 2002; Sentz 2002). The ?rst one is aleatory uncertainty (also referred to as stochastic uncertainty or inherent - certainty) – it results from the fact that a system can behave in random ways. For example, the failure of an engine can be modeled as an aleatory uncertaintybecause the failure can occur at a random time. One cannot predict exactly when the engine will fail even if a large quantity of failure data is gathered (available). The second one is epistemic uncertainty (also known as subjective uncertainty or reducible - certainty) – it is the uncertainty of the outcome of some random event due to lack of knowledge or information in any phase or activity of the modeling process. By gaining information about the system or environmental factors, one can reduce the epistemic uncertainty. For example, a lack of experimental data to characterize new materials and processes leads to epistemic uncertainty.

New ideas for new products are not enough for creating successful markets: Product Innovation means to manage the whole chain from invention to new and best selling products in market. This innovation roadmap has to be carefully and systematically planned and procured. There are a lot of methods for creativity, market analysis, evaluation, technology forecast, and decision gates available within this book. These methods and tools are brought together and their scopes of application as well as their limitations are shown. The whole tool kit of methods and decision models like market studies, value engineering, TRIZ or portfolio analysis and others are linked together to the overall Aachen Innovation Model (AIM). This handbook is to be used as an innovation management guide as well as an information source for nearly all methods and tools in the field of innovation for technical products. The complete Innovation Road Map is supported by an interactive, multiple user software tool "EDEN" on an ontology basis. Thus the user has not only access to the collected know how of the past, but can also contribute to growth of expertise within his or her enterprise.