Year: 2016
Type: conference-paper
Abstract: Happiness is one of the most important aspects of human lives, yet the literature on emotional well-being indicates that people often fail to correctly anticipate the hedonic consequences of future events. As a result, individuals end up being not as happy as they thought they would be. This phenomenon also applies to the domain of personal finance where people make bad decisions about purchases. In this paper, we identified a new opportunity for the research on recommender systems in personal finance and through analysis demonstrated that intelligent recommenders can help to minimize errors in affective forecasts and enhance happiness of people in the domain of consumption. Furthermore, we reviewed problems associated with design of such recommenders and proposed approaches to overcome them.
Authors: Leonid Ivonin, Mark Perry, Sriram Subramanian
Institutions: Brunel University of London, University of Sussex
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: European Commission
OpenAlex ID: W2575851466