Do you really know your consumers? : analyzing the impact of consumer knowledge on use and failure evaluation of consumer electronics

Abstract

The field of Consumer Electronics (CE) can be characterized by continuous technological innovation, fierce global competition, strong pressure on time-to-market, fast adoption cycles and increasingly complex business processes. In this context it is increasingly challenging for product designers and developers to provide products with unique features and excellent price / performance characteristics, as well as having to provide products that meet all the consumer’s expectations. From a business perspective, research has shown that the number of complaints and even product returns is increasing for complex CE (Den Ouden, 2006). Further research on the causes of these complaints showed that almost half of the complaints were due to non-technical reasons. Therefore, more insight is needed into product quality and reliability from a point of view. A literature review showed that quality and reliability methods that are currently used in product development insufficiently prevent the large variety of complaints: the number of complaints is rising while at the same time the root cause of these complaints is more difficult to retrace. Product failures need to be measured and analyzed from a consumer’s point of view since the traditional fault-complaint propagation model fails to capture all potential sources of complaints. More insight is needed into the relation between the diversity of consumers and the propagation of product development faults to these Consumer-Perceived Failures (CPFs).A conceptual framework was developed to model the underlying factors related to the propagation of product development faults to complaints from a point of view. This framework is based on insights from human-computer interaction and behavior literature and the results of an explorative experiment. Furthermore, the most commonly used selection criteria for tests based on demographics and/or product adoption related characteristics do not sufficiently cover differences in CPFs. The characteristic consumer is hypothesized to have a strong impact on differences in the underlying variables of this framework. A review of relevant models and characteristics used in human-computer interaction and behavior research shows that this construct relates to cognitive structures consumers have about a product’s functioning as well as cognitive processes needed to use a complex CE product. This dissertation therefore aimed to investigate the hypothesized effect of knowledge on two important variables of the conceptual framework: product usage behavior and failure attribution. By using multiple surveys, two laboratory experiments and a web-based experiment, the following aspects of the conceptual framework were investigated in this dissertation: • How and to what extent consumers can be differentiated on knowledge of complex CE • The effect of knowledge on differences in product usage behavior • The effect of knowledge on differences in attribution of product failures The results of the surveys to differentiate consumers on knowledge (both core and supplemental domains) of innovative LCD televisions demonstrated the successful development and validation of measurements of both subjective and objective measurements of expertise and familiarity. It was concluded that the selection of knowledge constructs as criterion for differentiating consumers for a test depends on the target group for a product (e.g. a very narrow homogeneous group versus mass markets), the type of product (e.g. passive versus active interaction) and the goal of the test. The laboratory experiment which investigated the effect of subjective expertise and objective familiarity on product usage behavior showed that higher levels of subjective expertise on both the television and computer domain result in significantly better effectiveness and efficiency and less interaction problems when performing complex product related tasks. Next, the results also showed that differences in subjective expertise stronger relate to differences in product usage behavior than those in objective familiarity. The findings of this study help product developers and designers to better understand differences in product usage behavior when consumers encounter interaction problems and can therefore help the product designers and developers to take better design decisions.The results of both failure attribution experiments with simulated failure scenarios of picture quality failures in an LCD television showed that only objective expertise differences affect differences in perception of product failures. However, although the failure attribution of consumers with higher levels of objective expertise has more dimensions and is more refined, higher levels of objective expertise on a product do not automatically result in attributions that are more in accordance with the real physical cause of the failure. This has important implications because currently used test methods often differentiate consumers only on previous experience (i.e. familiarity) with a product. The results of both studies also demonstrated that both failure cause and failure impact do not significantly affect how consumers attribute the failures. In total it can be concluded that, when evaluating the effect of diversity on fault-complaint propagation, knowledge can be used to differentiate product use and failure attribution for complex CE. However, it should be noted that especially for failure attribution this effect is not consistent across different types of failures. In addition, compared to objective and subjective familiarity and subjective expertise, objective expertise has the strongest impact. In the context of fast evolving complex CE, objective expertise measurements are becoming increasingly important because familiarity or subjective expertise measurements on the (technical) functioning of currently available products can quickly become incorrect or incomplete for the next generation of products. These insights can support product designers and developers to make the right design decisions to enhance satisfaction.