Résultat de la recherche
Helping Each Other uit Online: Understanding User Engagement and Real Life Outcomes of the r/StopSmoking Digital Smoking Cessation Community
Bringing Computational Thinking to non-STEM Undergraduates through an Integrated Notebook Application
Breadcrumbs: A Rich Mobility Dataset with Point-of-Interest Annotations (short paper)
ResPred: A privacy preserving location prediction system ensuring location-based service utility
Promoting Computational Thinking Skills in Non-Computer-Science Students: Gamifying Computational Notebooks to Increase Student Engagement
A Framework to Predict Consumption Sustainability Levels of Individuals
What Are You Willing to Sacrifice to Protect Your Privacy When Using a Location-Based Service?
From Digital Community Engagement to Smoking Cessation: Insights from the Reddit r/StopSmoking Thread
Supporting Green IS through a Framework Predicting Consumption Sustainability Levels of Individuals
In order to encourage individuals to adopt more sustainable behaviors, it is crucial to know their current levels of consumption in specific domains (e.g., mobility) before exposing them to personalized incentives. Although various theoretical models exist, there is currently no technological solution that automatically estimates individual’s consumption sustainability levels. This short paper aims at addressing this gap and presents the design of a framework that enables to estimate these levels based on multiple features (e.g., demographics). It also presents a preliminary validation of a part of the framework through two empirical comparative studies related to the mobility consumption domain. These studies evaluate the performance of six classifiers using a large-scale survey of approximately 3000 representative individuals living in Switzerland. The results highlight that the gradient boosting trees and the multinomial logistic regression models are promising, and accommodation, habits and demographic variables are the most decisive features to estimate mobility behaviors.