Integration of Preference Analysis Methods into Quality Function Deployment

We are living in a technological era where many of the products are complex and have a large number of characteristics.¹ For companies, it represents a big challenge to conceive the consumer requirements concerning the characteristics especially of technological products at a time when adapting to the customers’ needs and wishes constitutes a main success factor for the survival of the company on the market. After all, the marketing process begins, continues, and ends through the decisions of consumers.

The common word used for elderly people is “seniors”. It originates from Latin and designates elderly people (e.g. Artho 1996, pp. 25-26). However, in this work, the term “seniors” will not be used because, according to the face-to-face interview and written questionnaire results conducted in the current work, it showed that most of the elderly people in the sample were not pleased with the term “seniors”. Therefore, the author will be using the term “elderly people” instead throughout this work.

The compositional self-explicated (SE) method is one of the three main approaches used in marketing to measure the preference structures of respondents (Green and Srinivasan 1990, p. 9). Its main underlying idea is that it asks respondents directly about their preferences of a product and is based on an additive model (Hensel-Börner 2000, p. 15). The SE method is considered an alternative to the decompositional conjoint analysis method. In this section, an overview of the SE method is presented.

QFD was developed in Japan in 1966 as a result of extensive efforts to reach product development based on originality and not imitation. The method was introduced as part of the total quality control (TQC) concept, as a method for new product development (Akao and Mazur 2003, p. 20). Nevertheless, the real starting point of QFD was in 1972 with the publication of an article by Mitsubishi Heavy Industry and Akao’s first publication in the monthly magazine Standardization and Quality Control (1972). However, it was not until the first book about QFD edited by Mizuno and Akao (1978) was published that the application of QFD increased in Japan (see Table 9 for the main milestones in QFD’s history). In 1975, the Japanese Society for Quality Control (JSQC) created the Computer Research Committee.²⁹ This group dedicated the next 13 years to research on the method of QFD. Their final report in 1987 analysed the status of QFD applications in 80 companies in Japan (Akao and Mazur 2003, p. 22).

In the work of Pullman, Moore, and Wardell, they compared the QFD and conjoint analysis methods on the example of a new all purpose climbing harness for the beginning/ intermediate ability climbers. They view the two methods QFD and conjoint analysis “as complementary approaches that should be conducted simultaneously,” in which each method’s result supports the other. They concluded that QFD and conjoint analysis provide two “different lenses” that combine the product developers and the marketers in producing new or improved product (Pullman et al. 2002, p. 354).

Study 1 consists of the Pullman’s and Baier’s conjointQFD approaches to be tested on the example of mobile phones for elderly people. The goal of the study is to investigate the two approaches exclusively on the target group of elderly people and to compare the direct results and convergent validities of the two conjointQFD approaches for elderly people. This study is a pre-test before presenting the new approach for elderly people and introducing the adaptations measures in study 2 in Chapter 7.

Study 2 consists of the Pullman’s and Baier’s conjointQFD approaches and the CCSEQFD new approach. These approaches are tested on the example of the “smart home” for elderly people. The goal of study 2 is to further investigate these approaches adapted to elderly people and to compare their results directly and indirectly. This study is an extended empirical investigation for study 1 (Chapter 6) with adaptations measures to elderly people as explained in Section 5.3 and Section 5.5. In study 2 conversely to study 1, two levels of adaptations are taken into consideration: by the introduction of a new approach for elderly people and by adaptation measures taken within each approach. Additionally, the examples selected for the study “smart home” is also focused on the elderly and the features are relevant to them.

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.