An Optimization-Based System Dynamics Simulation for Sustainable Policy Design in WEEE Management Systems

Llerena-Riascos, Camilo; Jaén, Sebastián; Montoya‐Torres, Jairo R.; Villegas, Juan G.

doi:10.3390/su132011377

Cited by 7 publications

(20 citation statements)

References 63 publications

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“…If significant measures are not taken, this number is expected to rise to 120 Mt by 2050. Unfortunately, only 20% of this tremendous amount of e-waste was recycled in some useful sense [7][8][9]. The remaining 80% were usually disposed of at the landfill, thus causing harm to the environment [9].…”

Section: Introductionmentioning

confidence: 99%

The Determinants of Consumers’ E-Waste Recycling Behavior through the Lens of Extended Theory of Planned Behavior

2022

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Cutting-edge technological advancements have turned many electronic devices into waste within a short time of usage. Electronic waste (e-waste) has become a global problem. Due to the adverse impact of e-waste on the environment and human health, a regulatory system for effective collection and treatment of e-waste disposed of by the community and business sectors is in dire need. In an attempt to address the setbacks and cope with e-waste issues, this study determined factors that influence e-waste recycling intentions (ERIs) and e-waste recycling behavior (ERB) among consumers in Malaysia through the lens of an extended theory of planned behavior (TPB) model. Via an online survey, 159 questionnaires were collected from targeted respondents in Malaysia aged 18 years and above identified using the purposive sampling method. The structural equation modeling (SEM) approach was deployed for data analysis. As a result, moral obligation (MO) emerged as the most significant factor toward ERI, followed by perceived convenience (PC). Next, ERI displayed a significant effect on ERB. The multi-group analysis (MGA) outcomes revealed significant group differences in education variables, signifying that the lower/middle education group was more easily influenced to perform ERB than the higher education group. Essentially, this study contributes to many aspects especially in enhancing the awareness of e-waste issues and emphasizing the broad knowledge about e-waste recycling. This study provides practical implications for the government, the policymakers and all stakeholders, including consumers, non-government agencies, collectors, retailers, and recycling facilities. The study outcomes may be considered when formulating laws and regulations to enhance e-waste recycling efforts that guarantee a sustainable ecosystem in the future.

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Section: Introductionmentioning

confidence: 99%

The Determinants of Consumers’ E-Waste Recycling Behavior through the Lens of Extended Theory of Planned Behavior

2022

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“…The results emphasized the failure of formal collection and the growth of the informal sector. Llerena-Riascos et al (2021) discussed sustainable WEEE management system policies. The authors used a system dynamics model and a mixed-integer nonlinear programming model.…”

Section: Literature Reviewmentioning

confidence: 99%

The Influence of Eco-Investment on E-Waste Recycling-Evidence From EU Countries

Platon

Surugiu

Frone

et al. 2022

Front. Environ. Sci.

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Waste electrical and electronic equipment is the fastest growing waste stream internationally. Due to its physical characteristics, e-waste is a suitable subject for the development of recovery, repair, and recycling policies, prolonging products’ life cycle for as long as possible, and is an objective pursued by the specific mechanisms of the circular economy. From the point of view of economic development models, e-waste management is one of the areas with significant potential for the implementation of the circular economy. The circular economy is analyzed through a set of 10 indicators that can be found in the Eurostat database. In this paper, we focus on the relationship between two main indicators with significance for this topic (e-waste recycling and eco-investment) and their evolution in European countries. An econometric model regarding the influence of eco-investment on e-waste recycling in EU member states will highlight the impact of circular economy indicators and the importance of promoting the reduce-reuse-recycle paradigm, especially for e-waste. A panel analysis was performed on data from European Union (EU) countries for the period (2008–2018). The analysis uses e-waste recycled per inhabitant as the determined variable and eco-investment per inhabitant as independent variable. The results of the econometric analysis performed show that, although all EU member states benefit from eco-investment, there is a group of countries that have already achieved a high capacity of e-waste recycling, while others should increase eco-investment further.

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“…Thus, it is considered relevant to incorporate the principles of the circular economy in the reverse logistics operations associated with WEEE [4], namely to consider the players in the reverse chains [5] and to establish the circularity of WEEE through remanufacturing, repair, reuse, recycling, and/or sale to the secondary market. This is to be performed [3] in compliance with the regulation of the local policies that are aimed at eliminating the disposal of WEEE in landfill, thus allowing for a reduction in CO 2 in addition to improving the recovery rate, as well as the capacity of the facilities in relation to the total expected profit [6].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, Lv and Du used the Kriging method [29], whereas Moslehi et al [30] used a multi-objective stochastic model and a bi-objective mixed-integer programming model under certain uncertainties. An approach using system dynamics and a mixed-integer nonlinear programming model was utilized by Llerena-Riascos et al [4], and a convolutional neural network-based quality prediction and closed-loop control method was used by Zhang et al [31]. Lastly, agent-based modeling, system dynamics, and discrete event simulation were implemented by Guo and Zhong [5].…”

Section: Introductionmentioning

confidence: 99%

“…In this regard, the studies that presented an environmental assessment-listed in Table 1-only offered a quantification in percentage using data extracted from the computer simulation. These studies generally emphasized the reduction of WEEE disposal in landfills and the reduction of CO 2 , such as in Gamberini et al [24]; Achilles et al [21]; Achilles et al [22]; Assavapokee and Wongthatsanekorn [20]; Shokohyar and Mansour [25]; Yu and Solvang [23]; Bal and Satoglu [15]; Elia et al [16]; Duman et al [28]; Tosarkani et al 2020 [6]; Llerena-Riascos et al 2021 [4]; Lv and Du [29]; Moslehi et al [30]; and Guo and Zhong [5]. From this, the second gap identified was that no research evaluated the reduction of environmental impacts in the abiotic, biotic, and water dimensions using the Material Intensity Factor (MIF), which is a relevant tool for global assessment of the minimization of environmental impacts, not just using percentage data.…”

Section: Introductionmentioning

confidence: 99%

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Simulation of Electronic Waste Reverse Chains for the Sao Paulo Circular Economy: An Artificial Intelligence-Based Approach for Economic and Environmental Optimizations

Oliveira Neto,

de Araujo,

Gomes

et al. 2023

Sensors

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The objective of this study was to apply simulation and genetic algorithms for the economic and environmental optimization of the reverse network (manufacturers, waste managers, and recyclers in Sao Paulo, Brazil) of waste from electrical and electronic equipment (WEEE) to promote the circular economy. For the economic evaluation, the reduction in fuel, drivers, insurance, depreciation, maintenance, and charges was considered. For the environmental evaluation, the impact of abiotic, biotic, water, land, air, and greenhouse gases was measured. It was concluded that the optimized structure of the WEEE reverse chains for Sao Paulo, Brazil provided a reduction in the number of collections, thus making the most of cubage. It also generated economic and environmental gains, contributing to the strategic actions of the circular economy. Therefore, the proposed approach is replicable in organizational practice, which is mainly required to meet the 2030 agenda of reducing the carbon footprint generated by transport in large cities. Thus, this study can guide companies in structuring the reverse WEEE chains in Sao Paulo, Brazil, and other states and countries for economic and environmental optimization, which is an aspect of great relevance considering the exponential generation of WEEE.

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An Optimization-Based System Dynamics Simulation for Sustainable Policy Design in WEEE Management Systems

Cited by 7 publications

References 63 publications

The Determinants of Consumers’ E-Waste Recycling Behavior through the Lens of Extended Theory of Planned Behavior

The Determinants of Consumers’ E-Waste Recycling Behavior through the Lens of Extended Theory of Planned Behavior

The Influence of Eco-Investment on E-Waste Recycling-Evidence From EU Countries

Simulation of Electronic Waste Reverse Chains for the Sao Paulo Circular Economy: An Artificial Intelligence-Based Approach for Economic and Environmental Optimizations

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