Water saving tips, peer pressure, and gamification: long-term behavior
change and rebound effects from a long experimental trial
Abstract
Demand-side management strategies based on customized feedback have
proved their worth in supporting water conservation efforts and behavior
change programs. Several studies in both the water and energy sectors
report of observed short-term savings deriving from feedback-based
programs and awareness campaigns, often based on smart metered data and
high levels of customization in presenting information on resource usage
to users in the form of past consumption, real-time information, peer
comparison, analogies, and resource saving tips. Yet, feedback-based
programs are often run as part of experimental trials with a limited
duration, and their effectiveness is therefore only evaluated for a
short time span, potentially overlooking rebound effects. Assessing the
long-term effect of feedback information on behavior change is still an
open research question. In this work, we analyze the long-term impacts
of a smart-meter fed gamified ICT platform providing customized feedback
to water users, which was deployed starting in 2014 in a long experiment
trial with over 200 users of the Global Omnium utility in Valencia
(Spain). The platform core is a data-driven demand management pipeline
that enables water utilities to foster consumer engagement and promote
water conservation via customized feedbacks. It includes customized
water saving tips, peer-comparison of water usage, and a reward program
based on gamification tools and mechanisms. After three years of
development and testing from 2014 to 2017, the platform has proven to be
very effective in the short-term, when a user is engaged. A 5.7%
volumetric water use reduction among Global Omnium users was achieved
after the first year of full implementation, along with a 20%
approximate water consumption difference with respect to non-platform
users. Here, we analyze the smart meter data of the platform users,
respectively after one and two years from the end of the funded platform
trial period, to assess long-term behavior changes and rebound effects
on different groups of platform adopters.