DAIAD components allow users to gather, visualize, and analyse data on their water and energy consumption at high granularity. We suppose that individuals have a beforehand interest for collecting and analyzing quantified information about their private lives. They like to quantify themselves. This aspect is especially relevant to DAIAD in the context of technology adoption. With a favorable attitude towards such self-tracking devices and applications (in our case the DAIAD@feel, DAIAD@home and DAIAD@know components), technology adoption is positively affected. When we are able to identify such attitudes in an earlier phase we can better predict adoption of the DAIAD components. In order to assess these attitudes in a survey-environment, we develop a specific attitude towards self-tracking measurement scale.
Our research-in-progress paper stating the exact steps of our research proposal and first results from in-depth interviews has been accepted at one of the most relevant conference in Information Systems: the European Conference on Information Systems 2016 in Istanbul, Turkey. We are looking forward to present our ideas and receive valuable feedback from the IS community.