Companies are continuously trying to understand consumer perceptions of products in order to design better future products to meet emerging technical, environmental and societal challenges. The techniques traditionally employed by firms include focus groups, surveys, and observation of customers during product use. However, various challenges exist in using these approaches. For example, focus groups often yield emotional assessments that can be influenced by other participants. Surveys (and focus groups) are typically conducted while the customer is far removed from actual product usage, limiting their relevance. Observations rely on interpretations by observers. In all of these approaches, information is qualitative and open to subjective interpretation. This award supports fundamental research to build a foundation for techniques that provide a quantitative understanding of consumer perceptions and how these perceptions link with product features. This will lead to objective interpretations for designers to act on when developing the next generation of goods and services.
The framework for cyber-empathic design in this research will focus on integration of sensors and information technologies with existing products that allow products to "observe themselves" and takes advantage of new cyber-infrastructure technologies to report back to designers. Such a paradigm takes advantage of the ever-improving cyber-infrastructure and decreasing size and cost in sensing technologies to provide not otherwise obtainable product usage data. The specific objectives of the research plan include: (i) validation of a generalized analytical framework based on structural equation modeling (SEM) that can be used to couple multi-modal data streams of a qualitative (e.g., surveys) and quantitative (e.g., sensors) nature, (ii) application of the framework for causal modeling which maps consumer perceptions to specific product features, and (iii) demonstration of direct confirmatory design inference through application of cyber-empathic data. These objectives will be facilitated through human subject experiments in both laboratory and field settings. In an economy increasingly reliant on knowledge, the cyber-empathic framework will provide designers a novel, quantitative and more efficient way to learn about their products and systems after they are put in the hands of end-users. Such understanding has the ability to transform product engineering by improving the ability to identify opportunities for innovation, leading to products and systems that better meet the needs of heterogeneous end-users.
