Graduate Degree Type
School of Engineering
Accelerated and advanced development of the electronics industry in the 21st century is creating the rapid obsolescence of electrical and electronic equipment. This causes one of the largest and unstoppable waste streams called electronic waste (e-waste). There have been obstacles in e-waste recycling, including the existence of the informal sector such as peddlers (a larger issue in developing countries) and insufficient consumer awareness. The ideal e-waste recycling system would be able to overcome these obstacles. To establish an effective e-waste recycling system, the first important step is to implement an e-waste collection system. To implement an e-waste collection system, many organizations such as companies, universities, and neighborhoods have found it difficult to determine the consumers’ willingness to participate in e-waste collection and to estimate the amount of e-waste that would be collected. This thesis introduces a model that can be used to determine consumers’ willingness to participate in e-waste recycling and estimate the amount of electronic waste that could be collected. After that, the next step to improve an e-waste collection system can be planned based on the factors that affect the consumers’ willingness to participate in e-waste recycling and the estimated amount of e-waste that would be collected. The methods that were used in the existing studies including the formulations for estimating the amount of e-waste were modified to fit correctly into the proposed model. The purpose of the thesis is applying the model to improve e-waste collection in an educational institution community by identifying the willingness of students, faculty, and university staff members to participate in ewaste recycling in this community, estimating the collected amount of e-waste, and recommending the next step based on the consumers’ willingness and estimated amount of e-waste.
Nguyen, Quang Tran Nhat, "Modeling and Improvement of Electronic Waste Collection System: Case Study at Grand Valley State University" (2019). Masters Theses. 960.