Start Date
16-8-2018 12:00 AM
Description
The right information can foster behavior change towards energy conservation – given that the receiving individuals pay attention to the feedback provided and integrate the information in their decision making. As human information processing capabilities are limited, intervention designers need to choose content carefully to avoid information overload. Based on energy consumption and survey data collected in field trial, this article investigates the attention paid to different elements of the user interface (N=426) and establishes a relationship to actual energy conservation. We find that self-reported attention paid to content explains only very little of the measured behavior change (explanatory power of approx. 3%). The article is a first step towards better understanding the black box of feedback interventions in the energy sector. The results highlight the importance of collecting real-world data on behavior – rather than relying on self-reported user perceptions – in the resource consumption context and beyond.
Recommended Citation
Ableitner, Liliane; Tiefenbeck, Verena; Fleisch, Elgar; and Staake, Thorsten, "Eco-Feedback Interventions: Selective Attention and Actual Behavior Change" (2018). AMCIS 2018 Proceedings. 11.
https://aisel.aisnet.org/amcis2018/HCI/Presentations/11
Eco-Feedback Interventions: Selective Attention and Actual Behavior Change
The right information can foster behavior change towards energy conservation – given that the receiving individuals pay attention to the feedback provided and integrate the information in their decision making. As human information processing capabilities are limited, intervention designers need to choose content carefully to avoid information overload. Based on energy consumption and survey data collected in field trial, this article investigates the attention paid to different elements of the user interface (N=426) and establishes a relationship to actual energy conservation. We find that self-reported attention paid to content explains only very little of the measured behavior change (explanatory power of approx. 3%). The article is a first step towards better understanding the black box of feedback interventions in the energy sector. The results highlight the importance of collecting real-world data on behavior – rather than relying on self-reported user perceptions – in the resource consumption context and beyond.