Towards welfare-oriented recommendations in activity-travel behavior

Current recommender systems (RS) in activity-travel behavior often fail to adequately account for user welfare, potentially leading to recommendations that leave users worse off than alternative choices. This research introduces a framework to address this gap by focusing on 'net utility' to ensure recommendations actively improve user welfare, particularly relevant where users incur non-recoupable costs like time and energy.

Why it matters

This research highlights a fundamental flaw in current recommendation technologies that can lead to suboptimal user experiences and wasted resources. Adopting welfare-oriented recommendation frameworks is crucial for organizations aiming to build trust, enhance user satisfaction, and improve the efficiency and effectiveness of services that guide user choices involving significant personal investment.

Key insights

• Mainstream recommender systems (RS) generally lack a principled account of user welfare, meaning they may not ensure recommendations leave users better off.
• This issue is particularly pronounced in activity-based travel behavior, where users expend non-recoupable resources such as energy and time.
• Existing systems, relying on popularity or collaborative filtering, might recommend options that are inferior to user-selected or nearby alternatives.
• The research proposes a welfare-oriented framework for activity recommendation that evaluates suggestions based on net utility to overcome these limitations.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2608.16922