ABSTRACT The Circular Food Economy is a recent concept referred to co-creative food ecosystems where stakeholders from different echelons work together to improve the chain by using circular economy solutions for managing food loss and waste while increasing stakeholders’ income and reducing the environmental affectation. There is a lack of quantitative information on what should be prioritized when designing circular options considering the actors’ preferences. This study presents an application of the FITradeoff method within the Agri-Food Supply Chain in a multicriteria decision problem of ranking circular economy initiatives using six criteria (CO2 generation, blue-water usage, land usage efficiency, social impact, income, and implementation) and nine hypothetical alternatives artificially created from available data. It explores information regarding preferable alternatives for householders. The results are considered a quantitative starting point for collecting consumers’ preferences as a basis for further research to refine such circular initiatives into more beneficial and attractive ones. cocreative co creative affectation actors AgriFood Agri CO2 CO (CO generation bluewater blue water efficiency impact implementation data householders consumers ones

ABSTRACT The Flexible and Interactive Tradeoff (FITradeoff) method is a multicriteria decision making/aiding (MCDM/A) method that uses partial information about the decision maker’s (DM’s) preferences in order to build a recommendation. This method preserves the strong axiomatic structure of the traditional tradeoff procedure, with an interactive and flexible process that demands less cognitive effort from the DM. Although FITradeoff has already been applied for aiding several practical decision situations, there is no previous study that tests the performance of this method with respect to expected theoretical benefits such as time and effort reduction. In this context, this paper presents the results of a simulation experiment that aims to analyze the behavior of FITradeoff in a wide range of scenarios. Computational constraints were identified in the simulation process, such as the number of simulations for each iteration. Despite the memory limitation of the software used, the number of total simulations performed was greater than what is commonly found in literature. We investigate how the performance of FITradeoff can be affected by changes in number of criteria, number of alternatives and weight pattern, and therefore it is possible to have a deeper understanding of the method and its main features. Therefore, this work focuses on studying, through simulations, the behavior of the multicriteria method FITradeoff, developed by De Almeida et al. (2016), filling a lack in the literature by analyzing said method in a wide array of scenarios by a simulation process in order to bring a better understanding of the method, as well as to validate it in a simulation study.