A Design Methodology for a Green and Healthy Food Choice Decision Support System Based on Multi-Dimensional Information Fusion and Behavioral Interventions

Abstract

Consumers’ food choices are constrained by information asymmetry across multiple attributes (nutrition/health, environmental impacts, and corporate social responsibility). This paper presents GreenChoice-DSS, a mobile decision support system that integrates multi-source food information and delivers behavior-change interventions (nudge and gamification) to support green and healthy choices in everyday settings. The system comprises (i) a multi-dimensional assessment model that produces standardized scores for health and sustainability attributes, (ii) a recommendation and intervention engine that adapts interventions to user context and historical behavior, and (iii) an end-to-end logging pipeline for behavioral analytics. We evaluated the system via an 8-week randomized controlled trial (N=120 completers) with three arms (control, nudge, gamification+nudge), collecting repeated-measures questionnaires and in-app behavioral logs. Results indicate that intervention arms improved users’ green/healthy choice patterns and engagement relative to control, with the combined gamification+nudge configuration showing the most consistent effects on sustained use. To facilitate reproducibility, we describe the scoring pipeline, data sources, and evaluation protocol in detail, and provide a structured description of logging fields and analysis procedures in the supplementary materials (with anonymized data/code available upon reasonable request, subject to licensing constraints for third-party datasets).