Identifying probabilistic and necessary conditions for sustainable food purchasing behaviors: insights from surplus food platforms

Purpose This study examines the determinants of sustainable food purchasing behaviors (SPB) within the context of surplus food mobile applications (SFMA). It integrates the Elaboration Likelihood Model (ELM) and Norm Activation Model (NAM) to identify necessary and probabilistically sufficient conditions for SPB. Design/methodology/approach A dual-method approach was employed, combining Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA). Central-route variables (e.g. argument quality, information relevance) and peripheral-route cues (e.g. source attractiveness) were evaluated, alongside NAM constructs such as awareness of consequences, ascription of responsibility, and personal norms. Additionally, the novel approach, that is Combined Importance Performance Map Analysis (cIPMA), was used to identify critical performance gaps. Findings The results demonstrate that both central-route and peripheral-route variables significantly influence SPB. NAM constructs emerged as both necessary and probabilistically sufficient conditions, underscoring their foundational role in fostering sustainable food purchasing. cIPMA revealed underperforming areas, such as limited user awareness and weak engagement with sustainability messaging, offering actionable insights for platform refinement. Originality/value This study contributes to the literature by integrating ELM and NAM in the SFMA context and adopting an innovative dual-method approach (PLS-SEM and NCA) to uncover both necessary and sufficient conditions for SPB. The findings provide theoretical and practical insights for advancing sustainable consumption in the digital economy.