Agent-Based Model for End-of-Life Product Flow Analysis

Abstract

This paper presents an agent-based simulation model for end-of-life product flow analysis in recuperation and recycling supply networks that focuses on individual consumer behaviors. The simulation model is applied to a deposit-return program on wine bottles that could be developed in the province of Quebec. Canadian data was used to calibrate and validate the model. A series of experiments was then conducted with three artificial populations to analyse how they would react to several implementation scenarios of this end-of-life product flow strategy. The results suggest that the distance to the nearest depot is an important decision factor, but less predominant than the ownership of a private vehicle and the deposit value. The results also indicate that the use of agent-based modeling combined with the theory of planned behavior (TPB) can produce modular behavior models, that are intuitive and simple, to better understand consumer-behavior-driven supply chains. Such models can be used to give insights to decision-makers and policy-makers about the potential performance of end-of-life product flows strategies and further facilitate efficient resource management.

Integrating sociotechnical factors to assess efficacy of PV recycling and reuse interventions

“…We run 30 simulations for each scenario from 2020 to 2050 and present means in the paper's main body; we selected the number of simulations based on a stability analysis reported in Supplementary Figure 2. The ABM differs from similar waste-management models by including decisions related to the demand and supply sides of reuse, accounting for technical factors such as the recycling learning effect, and extending reported metrics [21][22][23][24] . Our approach also differs from current literature on PV EOL management in that behavioral aspects are captured to better characterize the CE transition.…”

“…In the equation, is the intention to perform the behavior, and , , and are the weights of each factor in the overall decision. The TPB is often used in ABMs of socio-technical systems because it explains the process of individual decision making straightforwardly 21,24,57 and has been applied in many waste-management ABMs 21,22,24 . The theory explains consumers' decisions 58,59 as well as decisions within companies 13,[60][61][62] .…”

“…Although this distribution of agents is rather simple when compared to the literature 21 , it is deemed sufficient for this exploratory analysis. Because the parameters of the truncated normal distribution were unknown, they were calibrated.…”

“…An ABM is well suited for studying the CE transition because it considers temporal aspects, adopts a systemic view, and accounts for human decisions and interactions between actors 16 , exploiting recent advances in behavioral economics and psychology 16,[18][19][20] . ABMs have been used to study CE scenarios in relation to waste management [21][22][23][24] , but no previous model has included secondary market dynamics underlying the reuse CE strategy. Many ABM studies have addressed PV adoption 19 , but the method has never been used to investigate renewable technologies through EOL.…”

Erratum: Labelle, A., et al. Agent-Based Model for End-of-Life Product Flow Analysis, Resources 2018, 7, 42

“…The authors wish to make the following corrections to this paper [1]: On page 11, there are six "(%)" in the table headers that should be deleted.…”