The HAT Living Labs (HALL) is an experimental environment or ‘sandbox’ within the HAT live ecosystem environment where individuals volunteer their data to participate for the wider purpose of research; to exchange data and co-create innovations as well as test out business and economic models of data exchanges.*
Funded through a £1.2m research grant from the Engineering and Physical Sciences Research Council (EPSRC) to the Universities of Warwick, Cambridge, Surrey and West of England, HALL is all about Business Model Innovation within the HAT ecosystem.
Innovation in business models is a challenge, as its proof has to be in a live environment with real users and real transactions; it cannot be tested within a traditional ‘lab’ or a research space setting. A Living Lab approach ensures that experiments can occur within a live environment, but also that research is applied under controlled conditions to draw insights, create new knowledge and generate the innovations.
The rationale behind the HALL’s principles is to support the involvement of real users in real‐life environments, where these users, together with researchers, developers, and companies work together in the development of new solutions, goods, services and business models. By using the business and innovation Living Lab principles, the HALL will support an open innovation process for all involved stakeholders, especially end users, with their needs as a driving force for innovation.
The HALL will focus on HAT data exchanges within the retail industry through the HALL’s partners including Tesco, Hollywood Elite Music, Sky, Hearst, and Methods. Technological support will be provided by HATDEX, the operational arm of the HAT Foundation, and IBM.
*The HALL research project has no access to any personal data outside of the HALL-specific sandbox and volunteers to the HALL project offer their data through the normal data debit system on their HATs.
Invitation to Research
The HALL is inviting proposals for research on its empirical platform for the understanding of service systems, markets, innovation and economic/business models. Types of data available for analysis include:
- Trading of personal data by popularity (data points and combinations)
- Average price of trades against popular data points combinations
- Characteristics of trading among demographic groups
- Trading patterns according to various industries or even companies
- Data on ecosystem stakeholders, strategies, decisions pertaining to the innovation, management, support and roll out of the platform through emails, discussions, interviews, minutes and notes.