Browsing by Subject "Scenario analysis"

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Open Access
A new lens to the understanding and reduction of household food waste: A fuzzy cognitive map approach
(Elsevier BV, 2022-07-15) Genç, Tuğce Özgen; Ekici, Ahmet
Food waste generated at the household level is known to be the main contributor to total food waste, particularly in developed regions. Reducing household food waste (HFW), however, is an extremely compelling task as there are many complex and interacting factors behind the HFW behavior. This study aims to address the factors behind the complexity by applying the Fuzzy Cognitive Map (FCM) method. FCM represents a new approach that enables the use of multiple resources, consideration of outnumbered factors, handling of linguistic ambiguities, and scenario analysis. Through FCM, this study aims to develop a more complete model of the complex HFW drivers' system and identify the most influential HFW drivers addressing which is key while designing HFW-reducing interventions. The current study employs a three-stage methodology that utilizes content analysis of scholarly published academic articles and exploits expert opinion to construct an FCM. In the final stage, through scenario analysis, the study tests and reports the effects of each HFW driver and evaluates them based on their potential to reduce HFW. The findings of this research reveal that system concepts A12 (fail to consume what is in the fridge), A2 (excessive purchasing), and A9 (cooking and serving too much) are the most influential practices concerning HFW. While the study suggests innovative approaches that would enable people not to give up their normality to cope with A12, tackling A9 requires challenging the normality, and addressing A2 requires changing food store-related infrastructural elements. Moreover, the study draws attention to the concept C2 (food safety and health concerns) due to its potential to be a disincentive to FW reduction efforts as well as to the concept G1 (lack of knowledge/skill/awareness) which requires special attention to maximize its potential. Finally, the paper offers specific recommendations to practitioners and policymakers and provides future research directions.
Open Access
Untangling the complex nature of household food waste drivers through fuzzy cognitive mapping
(2021-08) Özgen Genç, Tuğçe
Since reducing household food waste (HFW) has serious environmental, social, and economic implications, researchers across disciplines have investigated this phenomenon from multiple angles and identified a substantial number of drivers that account for HFW. Despite these efforts, empirical investigation of the complex web of HFW drivers is still in its infancy. The methodologies that have been used to investigate the phenomenon have been generally insufficient in capturing the complexity surrounding consumers’ food waste behavior. Therefore, the main objective of this thesis is to provide a more complete representation of this complexity. To this end, a distinctive method, fuzzy cognitive mapping (FCM) was used to demonstrate the system of HFW drivers. Through an iterative process between the content analysis of previous studies and expert opinion, the most prevalent HFW drivers as system concepts and their causal relationships were synthesized and consolidated in the first stage. Then in the second stage, this well-refined framework was transformed into an FCM that provides a consistent base to conduct simulations and to compare the HFW-reducing intervention alternatives. In the third stage, the most influential drivers were revealed, and the ambiguities due to conflicting findings reported in the literature were resolved. Then, through scenario analysis, intervention alternatives were compared based on their impact on HFW. In the final section, findings of each stage were integrated and discussed with their theoretical, methodological, and practical implications.