Repository logo
Research Data
Publications
Projects
Persons
Organizations
English
Français
Log In(current)
  1. Home
  2. Publications
  3. Contribution à un congrès (conference paper)
  4. Supporting Green IS through a Framework Predicting Consumption Sustainability Levels of Individuals

Supporting Green IS through a Framework Predicting Consumption Sustainability Levels of Individuals

Author(s)
Moro, Arielle  
Faculté des sciences économiques  
Holzer, Adrian  
Chaire de management des systèmes d'information  
Date issued
December 17, 2019
Abstract
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.
Notes
, 2019
Event name
International Conference of Information Systems (ICIS)
Location
Munich, Germany
Later version
https://aisel.aisnet.org/icis2019/sustainable_is/sustainable_is/7/
Publication type
conference paper
Identifiers
https://libra.unine.ch/handle/20.500.14713/21495
-
https://libra.unine.ch/handle/123456789/27898
File(s)
Loading...
Thumbnail Image
Download
Name

2020-02-11_2827_9213.pdf

Type

Main Article

Size

715.38 KB

Format

Adobe PDF

Checksum

(MD5):7a3195e2b9c8293722a40eda81e89bd3

Université de Neuchâtel logo

Service information scientifique & bibliothèques

Rue Emile-Argand 11

2000 Neuchâtel

contact.libra@unine.ch

Service informatique et télématique

Rue Emile-Argand 11

Bâtiment B, rez-de-chaussée

Powered by DSpace-CRIS

v2.0.0

© 2025 Université de Neuchâtel

Portal overviewUser guideOpen Access strategyOpen Access directive Research at UniNE Open Access ORCIDWhat's new