What we do
Technology is changing faster than ever. Our research focus is the human perspective on innovation: how users want to and are able to interact with the technology of our future. We take this human-centered research approach to the analysis of new technologies and innovations of all kinds, from new transport solutions, such as air taxis, to new applications of artificial intelligence, such as digital assistants.
Why we are doing it
Our goal is to help make the technology of our future more humane – incorporating human needs and desires from the earliest point possible into the technological development and commercialization plan of innovations. We believe that any new idea and technology should ultimately serve us – the humans. Therefore, our primary research focus is to develop an understanding of the conscious and unconscious reasons potential user have for accepting or rejecting a new technology.
What is Innovation Acceptance Research?
The psychological view
Human behavior plays an important, if not the most important, role in the innovation process. Consumers are not always rational, objective and utility-maximizing. Instead, they tend to base their decisions on other, more subjective, beliefs about a new technology. Reasonable innovations fail or take longer than expected to reach wide-spread acceptance, despite their proven usefulness. This paradox is generally explained by consumer resistance to change learned behavior. By using some products repeatedly over a long period of time, consumers form habits and routines. In general, they aim to preserve these habits and strive for consistency and status quo rather than to continuously search for and embrace new behaviors. If a new idea is not compatible with existing behavior, the perceived relative advantage of the new idea must be large enough to offset the perceived complexity of adopting to a new behavior. This insight forms the basis of the Technology Acceptance Model and its successors.
The sociological view
Sociology zooms out on this question to understand how an innovation diffuses through a group, or a society as a whole. According to Rogers Diffusion Paradigm the adoption decision of a society follows a bell-shaped curve over time, with view early adopters and a steep increase of acceptance, once the early majority of users is reached. The most critical point in this process is the transition from early adopters to the early majority (Geoffrey A. Moore wrote a whole book about this point called Chrossing the Chasm). The overall aim is thus to understand if those users will happily accept or reject a new idea, before the underlying technology is actually widely available to them. This brings along all sorts of challenges, since the valid assessment of user acceptance at this point of time will depend on how realistic the situation can be presented and on how much external factors, such as social influence, can be integrated in the research design.
Generally, Innovation Acceptance Research focuses on new ideas, which need a change in consumer behavior to become adopted. Thus, the scope of Innovation Acceptance Research can be defined as:
- Innovations and new technologies which aim at changing the life of a significant majority of the population
- Innovations and new technologies which aim for widespread adoption in the population and at the same time require a change in habits and routines of users
- Technologies, which are not yet market-ready or only exist as prototypes as well as technologies, which are market ready but not yet adopted by a larger part of the population.
This definition allows for a wide range of applications, from autonomous driving cars to digital Assistents. The clear distinction, however, is towards gradual or evolutionary improvements of already existing innovations. These research areas are typically covered by User Experience Research (UX) or User Interface (UI) Research.
As technologies mature, the scope of research usually shifts towards a more detailed view. As example, consider autonomous cars: User Acceptance Research has its focus on whether or not people want to use self-driving cars and which determinants influence their decision. UX Research will focus on the overall experience of self-driving cars, e.g. whether users would expect to have entertainment options ready, as they do no longer have to steer their vehicle. UI research, finally would dig deeper into how the screen layout and the overall interaction concept with the vehicle should be designed, e.g. would you talk to the car and if so will it be a male or female voice etc.. Generally, acceptance research thus predates UX research, which in turn predates UI research.