Strategies in e-waste reverse logistics: collection, disassembly, and recycled materials sourcing

Abstract

The global economic paradigm is shifting away from the traditional linear "take-make dispose" model of production and consumption towards a more resilient and responsible framework grounded in sustainability and the principles of a circular economy. Electrical and electronic equipment waste (WEEE or e-waste) refers to all types of electrical and electronic equipment and their parts that the owner has discarded as waste without the intention of reuse. On the one hand, if e-waste is not disposed of properly, it can endanger human health and the environment by contaminating air, water, and soil. On the other hand, extracting valuable materials from e-waste and redirecting them into the production cycle could reduce the mining of natural resources, protecting the environment and benefiting human society. The purpose of e-waste reverse logistics is to collect, disassemble, remanufacture, recycle, and dispose of e-waste to mitigate environmental damage and promote economic value extraction.

However, challenges such as competition from uncertified collection channels, which have led to a decline in the recycling rate; selective disassembly planning that focuses on high-value components, leaving residues as waste again; and sophisticated competition between virgin material suppliers and recycled materials suppliers affect the effectiveness and efficiency of e-waste reverse logistics deployment. Hence, the thesis addresses these challenges and research gaps in the literature, proposing strategic frameworks and operational decision-making models through a multi methodological approach. Real cases or numerical experiments are presented to illustrate the framework and the validity of the models; in addition, insights and implications are discussed for various stakeholders in the e-waste reverse logistics network.

In improving the official collection and recycling rate of the certified e-waste collection network, the thesis develops a robust bi-objective mixed-integer linear programming model to help certified network decision-makers establish community collection and treatment centers that address the ‘last mile’ deficiency, aiming to provide accessible services to communities competing with uncertified channels while maintaining economic viability. The robust bi-objective mixed-integer linear programming model considers maximizing the collection rate and the profit of the three-echelon reverse logistics network. A piecewise function is proposed to simulate competition among community collection centers, treatment centers, and uncertified channels, based on prior literature. Two realistic uncertainty parameters—the lower boundary of the entire collection and the reuse rate—are incorporated into the model, which deliberately addresses the dynamics of collection and processing complexity. A real-world case is presented to validate the model's effectiveness in supporting location decision-making for community collection and treatment centers. The Gurobi optimizer is used to solve the robust model, and the resulting optimal solutions are presented on the Pareto front. ArcGIS software illustrates the eight selected community collection and treatment centers on the map, which achieved a 61.6% collection rate and a profit of 0.15 million RMB.

To enhance holistic disassembly planning for e-waste recovery, this thesis constructs a bi-objective integer linear programming model to maximize the WEEE recovery rate and minimize recovery costs, guiding disassembly planning for circular plants using a disassembly bill-of-materials approach that recovers the entire product, including both high- and low-value items. The optimal solutions provide optimal recovery or disposal options for each item across all product hierarchies—products, sub-assemblies, and components comprehensively. A sum utility function is proposed to convert the bi objective problem into a single-objective problem, which is then solved. A real-life case study of disassembly planning for multi-functional copiers is presented, validating the effectiveness of a bi-objective hierarchical decision model. The results show that reuse is the economic and environmental anchor of the circular economy for WEEE recovery. Circular plant operators can navigate trade-offs between the two conflicting objectives under different regulatory regimes; for example, in Europe, the optimal recovery and disposal decision may yield an 86.2% recovery rate at 1.81 million.

To simulate competition between the virgin material supplier and the recycled materials supplier, the thesis develops a three-echelon, two-stage Stackelberg game model that integrates asymmetric competition and dual drivers from regulation (known as ‘Pull’ force) and market (known as ‘Push’ force) to examine a manufacturer's strategic sourcing decision between a virgin supplier and a local recycler. By deriving the Stackelberg equilibrium in three regimes (Unconstrained Regime, Capacity-Constrained Regime, and Emission-Constrained Regime), counterintuitive conclusions are made through four lemmas and two corollaries. Managerial implications are discussed for the manufacturer, virgin supplier, recycler, and policymaker.

The thesis aims to provide a comprehensive overview and present strategic frameworks and operational decision models to various stakeholders in the e-waste reverse logistics network to address the realistic challenges encountered in the e-waste collection, disassembly, and final sourcing of recycled materials in the forward production cycle, thereby contributing to enriching e-waste reverse logistics research literature and offering practical guidance to various e-waste reverse logistics network operators.

Date of Award	15 Jun 2026
Original language	English
Awarding Institution	University of Nottingham
Supervisor	Hing Kai Chan (Supervisor) & Zhen Tan (Supervisor)