Evaluating the effectiveness of household food waste interventions through scenario-based fuzzy cognitive map methodology: A new tool and guide to food policy-research

Abstract

Reducing household food waste (HHFW), one of the major contributors to total food waste, is a critical responsibility shared by food researchers and policymakers. To date, researchers have examined the drivers of HHFW and proposed various recommendations to mitigate it. Although the growing body of literature on HHFW interventions has generated valuable insights, several limitations—such as methodological inconsistencies, narrow scope, missing variables, concerns over reliability, and limited research designs—complicate meaningful comparisons and hinder the aggregation of findings across studies. Moreover, while numerous intervention strategies have been proposed and implemented, their effectiveness often remains underexplored or is assessed within the constraints of these limitations. The Fuzzy Cognitive Map (FCM) methodology presents a unique opportunity for food policy researchers to investigate the effectiveness of food waste prevention activities and interventions. We argue that FCM holds this potential because it offers a consistent analytical foundation, supported by theoretical frameworks and prior findings, through which diverse intervention alternatives can be tested and compared. Accordingly, following the construction of a fuzzy cognitive map of HHFW—based on a comprehensive review of the literature and expert assessment—this paper aims to utilize the FCM to determine and compare the HHFW-reduction capacity of various real-world intervention alternatives. Our findings highlight the strong potential of specific emerging retail formats (e.g., zero-packaging grocery stores) and manufacturing technologies (e.g., intelligent fridges) to reduce HHFW, although both require careful implementation to achieve their intended impact. Commonly employed interventions, such as informational campaigns, may prove ineffective when used in isolation and should therefore be complemented by other types of interventions. Online shopping—an increasingly prevalent food purchasing behavior—can substantially contribute to HHFW, underscoring the need for practitioners to consider the potential negative consequences of algorithm-driven purchasing systems. We provide an in-depth discussion of these findings, examine the study’s limitations, and elaborate on their implications for consumers, producers, distributors, and policymakers.