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|Title:||Integration of Preference Analysis Methods into Quality Function Deployment|
|Keywords:||Quality function deployment|
|Abstract:||The point of departure of the present work is elderly people. In the last decade, the proportion of elderly people in the overall population has remarkably increased in all industrialised countries including Germany (the present country focus). Thus the importance of the group that elderly people form is continuously increasing, especially on the economic level, as they shape a present and future purchasing power. The companies are thus compelled to adjust to the changing needs and requirements of elderly consumers if they want to survive and have chances in present and future markets. Market research methods are a substantial tool for companies to listen to their consumers and produce products that consumers want and need. Accordingly, those methods need to be adapted to elderly consumers to enhance their effectiveness in collecting the required data and hence produce products that elderly people need and want to buy.Consequently, this work investigates the question of adapting research methods to elderlypeople by proposing a new combination of conjunctive-compensatory selfexplicatedmethod and the QFD method. It investigates two combinations of conjointanalysis and QFD methods within the example of two complex technological products. To achieve the abovementioned goals, a theoretical description of the methods and the target group is carried out, to be followed by a description of the main approaches used in this work, namely Pullman’s conjointQFD, Baier’s conjointQFD, and the CC-SEQFD new approach. Finally, two empirical studies are explained and analysed. After offering an introduction to the problem and an overview of the work in Chapter 1, the target group of elderly people in Germany is analysed in Chapter 2. The main emphasis lays on the demographical development until 2060 and the socio-economic situation of elderly people in Germany.In Chapter 3, the preference analysis methods are analysed. The main focus lays on the two main methods, namely on self-explicated and conjoint analysis. More specifically,descriptions of the procedures of the conjunctive-compensatory self-explicated method and the adaptive conjoint analysis are presented. Finally, a comparison of advantages and disadvantages based on empirical studies and an assessment of the methods takes place.The second method used in this work, QFD is analysed in Chapter 4. The basics of QFD including its history, main definitions, and main matrix, the “house of quality”, are presented. Special attention is given to the advantages and disadvantages of the method and solutions to some of the QFD problems are presented. At the end of the chapter, an overview of the solutions considering the integration of preference analysis into QFD is given, based on an in-depth review of researchers who used those combinations. As the attention is given to the integration of preference analysis methods into QFD, three approaches, namely Pullman’s conjointQFD approach, Baier’s conjointQFD approach, and the CC-SEQFD new approach, are described in Chapter 5. To achieve an empirical comparison, Pullman’s and Baier’s approaches for elderly people were applied to the case study example of mobile phones (study 1). The results are analysed in Chapter 6 on three levels of comparison: (1) direct comparison between the results of the two approaches, (2) comparison “within” the approach using the convergent validity, and (3) comparison “between” the approaches using the convergent validity. The second empirical study, conducted on the example of “smart home” for elderly people (study 2), is described in Chapter 7. In this chapter, the CC-SEQFD new approach is compared to Pullman’s and Baier’s approaches in which adjustment measures on the conjoint analysis and conjunctive-compensatory self-explicated methods for the elderly people were considered. Finally, direct and indirect comparisons took place. The direct comparisons are similar to the comparisons made in the previous chapter, where (1) the results of the three approaches were directly compared; (2) validity comparisons between the three approaches were conducted. Additionally, (3) and indirect comparison were made including a time analysis comparison and the contingent indirect factors comparison.|
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