Predicting of citizens’ well-being in large cities

Urošević, Vladimir and Jovanović, Predrag and Ostojić, Ivana (2020) Predicting of citizens’ well-being in large cities. In: Business and Artificial Intelligence : Symposium proceedings. Faculty of organizational sciences, Belgrade, pp. 114-122. ISBN 978-86-7680-385-9

[img] Text
VUrosevic_PJovanović_IOstojicSYMORG_2020.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (2MB)

Abstract

The well-being of citizens in large cities is an important issue due to potential gaps between needs and capacities for providing health care. That became particularly visible during the Covid pandemic. Thus identifying factors of citizens’ well-being in large cities and based on that developing a model of its improvement is of high significance. In the paper six relevant sub-domains of well-being were identified: Evaluative, Emotional, Functional, Vitality, Community, and Supportive. Three of them: Emotional well-being, Evaluative well-being, and Functioning appeared to be highly correlated with each other. The three of the most predictive features of well-being proved to be the presence of anxiety or depression feelings (Anxiety/depression), the presence of pain or discomfort (Pain/discomfort), and the general self-evaluation of health status in the day the participants respond (Health scale). The results of this research may serve local self-governments to get insights into citizens’ well-being and to predict changes in the future.

Item Type: Book Section
Additional Information: XVII International Symposium Business and Artificial Intelligence, SYMORG Belgrade, September 7-9, 2020
Uncontrolled Keywords: well-being, wearable trackers data, prediction, physical activity, health
Institutional centre: Centre for economic research
Depositing User: Vesna Jovanović
Date Deposited: 29 Nov 2020 22:07
Last Modified: 29 Nov 2020 22:07
URI: http://iriss.idn.org.rs/id/eprint/411

Actions (login required)

View Item View Item