Modeling and Improvement of Electronic Waste Collection System C.pdf

Grand Valley State University
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ScholarWorks@GVSU
Masters Theses Graduate Research and Creative Practice
12-2019
Modeling and Improvement of Electronic Waste Collection
Modeling and Improvement of Electronic Waste Collection
System: Case Study at Grand Valley State University
System: Case Study at Grand Valley State University
Quang Tran Nhat Nguyen
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Nguyen, Quang Tran Nhat, "Modeling and Improvement of Electronic Waste Collection System: Case
Study at Grand Valley State University" (2019). Masters Theses. 960.
https://scholarworks.gvsu.edu/theses/960
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Modeling and Improvement of Electronic Waste Collection System
Case Study at Grand Valley State University
Quang Tran Nhat Nguyen
A Thesis Submitted to the Graduate Faculty of
GRAND VALLEY STATE UNIVERSITY
In
Partial Fulfillment of the Requirements
For the Degree of
Master of Science in Mechanical Engineering
School of Engineering
December 2019

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Dedication
For my family, my friends, and everyone who has supported me throughout this journey.

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Acknowledgements
I would like to thank Dr. Sharbbir Choudhuri for recruiting me into the graduate mechanical
engineering program at Grand Valley State University. I would like to thank Dr. Huihui Qi, Dr.
Arjumand Ali, Dr. Shirley Fleischmann and Dr. Sung-Hwan Joo for pushing my limits and setting
such high standards for my work. I would like to thank Mr. Brad Kamp and Mr. Jason Stair from
Padnos for helping in collection information. I would also like to thank all of my friends and family
who have supported me throughout this journey. I truly could not have done it without their support
and encouragement.

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Abstract
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 e-
waste 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.

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Table of contents
Dedication...................................................................................................................................... 3
Acknowledgements ....................................................................................................................... 4
Abstract.......................................................................................................................................... 5
Table of contents ........................................................................................................................... 6
List of Tables ............................................................................................................................... 10
List of Figures.............................................................................................................................. 16
1. Chapter 1: Introduction...................................................................................................... 18
2. Chapter 2: Background ...................................................................................................... 22
2.1. E-waste and its impact................................................................................................ 22
2.2. E-waste Management around the world................................................................... 24
2.3. Regulatory Environment in the United States and State of Michigan................... 25
2.4. Alternate path for end of use e-product to avoid landfill........................................ 30
3. Chapter 3: Literature Review ............................................................................................ 32
3.1. Consumers’ Willingness toward e-waste recycling.................................................. 35
3.2. E-waste Amount Estimation ...................................................................................... 40

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4. Chapter 4: Proposed model to design the e-waste collection system for a given population
44
4.1. Framework of the proposed model ........................................................................... 44
4.2. Determine the consumers’ willingness to participate in e-waste recycling ........... 45
4.3. Estimate the amount of e-waste that would be collected......................................... 52
5. Chapter 5: Case Study: E-waste Collection at Grand Valley State University ............. 57
5.1. Current e-waste management in Grand Rapids and Grand Valley State University
community................................................................................................................................ 57
5.2. Methodology................................................................................................................ 63
5.2.2. Questionnaire Design and Data Collection ............................................................. 63
5.2.2. Modeling willingness to participate in e-waste recycling using chi-square test of
independence........................................................................................................................ 65
5.2.3. Estimate the amount of e-waste would be collected from Grand Valley State
University students, faculty members, and staff members in 2019................................. 66
5.3. Result and Discussion ................................................................................................. 67
5.3.1. Significant factors that affect the consumers’ willingness to participate in e-
waste recycling based on chi-square test of independence and Fisher exact test .......... 67

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5.3.2. Estimating the amount of e-waste that would be collected from students,
faculty members, and staff members at Grand Valley State University........................ 70
5.3.2.1. PC/Laptop.................................................................................................... 70
5.3.2.2. Summary............................................................................................................. 74
5.3.3. Recommended next step to improve the e-waste collection system at Grand
Valley State University........................................................................................................ 76
5.3.4. Buy-back price and economic feasibility of a buy-back program: cell/mobile
phones case........................................................................................................................... 81
5.3.4.1. Human Resources ....................................................................................... 83
5.3.4.2. Infrastructure.............................................................................................. 84
5.3.4.3. Equipment ................................................................................................... 85
5.3.4.4. Maintenance, repair, and cleaning cost .................................................... 86
5.3.4.5. Electricity..................................................................................................... 87
5.3.4.6. Administration ............................................................................................ 88
5.3.4.7. Depreciation................................................................................................. 88
5.3.4.8. Revenue........................................................................................................ 89
5.3.4.9. Profit and buy-back price calculation....................................................... 91

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5.3.5. Buy-back price and economic feasibility of buy-back program: My own
experience with Laptops ..................................................................................................... 94
a. Dell PR09S model.................................................................................................... 95
b. MacBook Pro model A1502 ..................................................................................... 103
c. Revenue calculation .................................................................................................. 109
d. Profit and buy-back price calculation .................................................................... 111
e. Insight on my own experience with the dismantling process............................ 114
5.4. Conclusion on case study.......................................................................................... 116
6. Conclusion.......................................................................................................................... 118
7. References.............................................................................................................................. 119
Appendix A: Survey questionnaire ......................................................................................... 130
Appendix B: Percentiles of the Chi-square Distribution....................................................... 141
Appendix C: SAS Programming ............................................................................................. 142
Appendix D: Contingency Table ............................................................................................. 143
Appendix E: Chi-square and Fisher Exact Test example..................................................... 157
Appendix F: Table to calculate Np(t) and Lr(t) in section 5.3.2............................................ 161

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List of Tables
Table 1: Common Toxic Substances in e-waste [2] ..................................................................... 23
Table 2: CESQG, SQG, and LQG definition................................................................................ 29
Table 3:Example of Contingency Table [50]................................................................................ 49
Table 4: Contingency Table of Fisher Exact Test ........................................................................ 51
Table 5: Average weight per piece of different electronic product types [48] ............................. 54
Table 6: Data analysis result......................................................................................................... 68
Table 7: Frequency of the number of PCs/Laptops that the respondent currently owned............ 72
Table 8: Frequency table of average duration from the time when the consumers bought a
PC/Laptop to when they brought it to recycle without money back............................................. 73
Table 9: Summary of results......................................................................................................... 75
Table 10: Contingency table between age range and consumers’ willingness to participate in e-
waste recycling.............................................................................................................................. 77
Table 11: Contingency table between education level and consumers’ willingness to participate in
e-waste recycling .......................................................................................................................... 79
Table 12: Contingency table between economic benefits and consumers’ willingness to participate
in e-waste recycling ...................................................................................................................... 80

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Table 13: Human resources and staff cost for dismantling facility [64][65]................................ 83
Table 14: Space for the dismantling facility whose e-waste input was 2500 tons per year ......... 85
Table 15: Equipment for facility whose e-waste input was 2500 tons per years [64].................. 86
Table 16: Administration cost [64]............................................................................................... 88
Table 17: Depreciation cost .......................................................................................................... 89
Table 18: Material composition and Revenue per year [64], [71]................................................ 91
Table 19: Profit without buy-back cost: Cell/mobile phone case................................................. 93
Table 20: Buyback price and profit margin.................................................................................. 93
Table 21: Dell PR09S material composition ................................................................................ 96
Table 22: MacBook Pro model A1502 material composition .................................................... 104
Table 23: Average material composition.................................................................................... 110
Table 24: Material composition and revenue per year [64], [71] ............................................... 111
Table 25: Cost for e-waste dismantling facility to process 2500 tons of e-waste....................... 113
Table 26: Profit without buy-back cost: PCs/Laptops case ........................................................ 114
Table 27: Buy-back price and profit margin............................................................................... 114
Table 28: Estimate weight amount of e-waste that would be collected in 2019......................... 117

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Table 29: Percentiles of the Chi-square Distribution [50].......................................................... 141
Table 30: Age Range versus Consumers' Willingness to participate in e-waste recycling ........ 143
Table 31: Income Level Versus Consumer's willingness to participate in e-waste recycling.... 144
Table 32: Education Level Versus willingness to participate in e-waste recycling .................. 145
Table 33: Vehicle availability Versus willingness to participate in e-waste recycling .............. 146
Table 34: Residential Condition Versus willingness to participate in e-waste recycling........... 146
Table 35: Awareness on the materials used in e-waste and their toxic effect on natural habitat
Consumer's willingness to participate in e-waste recycling ....................................................... 147
Table 36: Awareness on the materials used in e-waste and their toxic effect on human health
Table 37: Awareness on State Law about e-waste recycling versus Consumer's willingness to
participate in e-waste recycling .................................................................................................. 148
Table 38: Recycling Habit versus Consumer's willingness to participate in e-waste recycling. 149
Table 39:Convenience to Recycling Service versus Consumer's willingness to participate in e-
waste recycling............................................................................................................................ 150
Table 40 Economic Benefits versus willingness to participate in e-waste recycling ................. 150

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Table 41: Willingness to bring end of use Cell/Mobile phones to collection location versus
Table 42: Willingness to bring end of use TVs/Monitors to collection location versus Consumer's
willingness to participate in e-waste recycling........................................................................... 152
Table 43: Willingness to bring end of use PCs/Laptops to collection location versus Consumer's
willingness to participate in e-waste recycling........................................................................... 153
Table 44: Willingness to bring end of use large home appliances to collection location versus
Table 45 Willingness to bring end of use medium home appliances to collection location versus
Table 46: Willingness to bring end of use small electrical equipment to collection location versus
Table 47: Willingness to bring end of use other small electrical equipment to collection location
versus Consumer's willingness to participate in e-waste recycling ............................................ 156
Table 48: Age Range versus Consumers' Willingness to participate in e-waste recycling ........ 157
Table 49: Vehicle availability Versus willingness to participate in e-waste recycling .............. 160
Table 50: Frequency of the number of phones that the respondent currently owned................. 161

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cell/mobile phone to when they brought it to recycle without money back............................... 161
Table 52: Frequency of the number of TVs/Monitors that the respondent currently owned ..... 163
TV/Monitor to when they brought it to recycle without money back ........................................ 163
Table 54: Frequency of the large home appliances that the respondent currently owned.......... 165
Table 55: Frequency table of average duration from the time when the consumers bought a large
home appliance to when they brought it to recycle without money back................................... 165
Table 56: Frequency of the number of medium home appliances that the respondent currently
owned.......................................................................................................................................... 167
Table 57: Frequency table of average duration from the time when the consumers bought a medium
home appliance to when they brought it to recycle without money back................................... 167
Table 58: Frequency of the number of small electronic equipment that the respondent currently
owned.......................................................................................................................................... 169
Table 59: Frequency table of average duration from the time when the consumers bought a small
electronic equipment to when they brought it to recycle without money back .......................... 170
Table 60: Frequency of the number of other small electronic equipment that the respondent
currently owned .......................................................................................................................... 171

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Table 61: Frequency table of average duration from the time when the consumers bought another
small electronic equipment to when they brought it to recycle without money back................. 172

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List of Figures
Figure 1: General framework of proposed e-waste collection model........................................... 44
Figure 2: Statistical Analysis Model............................................................................................. 52
Figure 3: Dell PR09S.................................................................................................................... 95
Figure 4: MacBook Pro model A1502.......................................................................................... 95
Figure 5: Copper from Dell PR09S Laptop.................................................................................. 96
Figure 6: Aluminum from Dell PR09S......................................................................................... 97
Figure 7: Steel from PR09S Laptop.............................................................................................. 97
Figure 8: Plastic from Dell PR09S Laptop ................................................................................... 98
Figure 9: Magnesium alloy cover of the PR09S laptop................................................................ 98
Figure 10: Glass content from PR09S laptop ............................................................................... 99
Figure 11: Battery of Dell PR09S Laptop..................................................................................... 99
Figure 12: Wire from Dell PR09S Laptop.................................................................................. 100
Figure 13: IC, Flatpacks, MLCC, and BGA chips [72,73,74,75]............................................... 101
Figure 14: Low-grade PCBs from Dell PR09S Laptop .............................................................. 102
Figure 15: Medium-grade PCBs from Dell PR09S laptops........................................................ 102

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Figure 16: High-grade PCBs from Dell PR09S Laptop.............................................................. 103
Figure 17: Aluminum from MacBook Pro model A1502........................................................... 105
Figure 18: Steel from MacBook Pro model A1502.................................................................... 105
Figure 19: Cable from MacBook Pro model A1502................................................................... 106
Figure 20: Plastic from MacBook Pro model A1502 ................................................................. 106
Figure 21: Glass from MacBook Pro model A1502................................................................... 107
Figure 22: Battery from MacBook Pro model A1502 ................................................................ 107
Figure 23: Medium-grade PCBs from MacBook Pro model A1502.......................................... 108
Figure 24: High-grade PCBs from MacBook Pro model A1502................................................ 109
Figure 25: SAS programming..................................................................................................... 142
Figure 26: Chi-square table example.......................................................................................... 160

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1. Chapter 1: Introduction
I was born and grew up in Vietnam, a beautiful country in Southeast Asia. Vietnam is
famous for its ancient history, friendly and hospitable people, and fascinating natural landscapes.
However, Vietnam is also the country where a lot of e-waste has been transferred to for processing
due to cheap labor and lack of government regulation. In Vietnam, a worker who works in a craft
village that processes e-waste is paid only about $150 per month. Additionally, the environmental
protection law of Vietnam does not mention e-waste in hazardous waste category. Although in
circular 12/2011/TT-BTNMT of Vietnam requires that e-waste must be subjected to law as
hazardous waste, the Vietnamese government is easy to be bribed. Therefore, many companies,
by bribing government officials, can import e-waste into Vietnam illegally without any notices. In
Vietnam, there are many villages that have treated e-waste in improper ways. They do not have
proper dismantling and recycling processes or safety procedures. Therefore, during the time I was
in Vietnam, I saw that many workers who worked in e-waste processing workshops had health
issues. They had to be exposed to improper e-waste processes every day without proper safety
labor equipment. They inhaled the polluted air contained hazardous substances from improper
cutting and grinding e-waste, drank polluted water, and consumed meat and plants that grew on
polluted soil. Not only were the workers at e-waste processing sites affected by e-waste, but also
people who lived near the e-waste processing site were threatened. Moreover, their family and
their next generation were affected by substances from the e-waste processing site.
Therefore, I was inspired to study the e-waste recycling system in order to reduce the
amount of e-waste that can be released into the environment. Fortunately, during the time I was in
the undergraduate program at Grand Valley State University, I was offered a great opportunity to

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enroll in the combined program, in which I can complete both undergraduate and graduate degrees
in a shorter time. Hence, I had a chance to do a thesis, in which I could start learning more about
e-waste and applying my knowledge to improve the e-waste recycling system.
The rapid growth of the electronics industry in the 21st
century is creating the fast obsolesce
of electrical and electronic equipment. Generally recognized as electronic waste, waste electrical
and electronic equipment (WEEE), or end-of-life (EoL) electronics, e-waste refers to electronic
and electronic equipment, including all components, items, and consumables with printed circuit
board, deemed obsolete or unwanted by a user [1]. E-waste consists of components that can
adversely affect the environment and human health. For example, there are many substances
associated with e-waste including metals and persistent organic pollutants (POPs) [2]. These
substances can significantly contaminate the air when burned, or leach into soil and water sources
when buried in landfills. When e-waste leaches into ground, it can bring toxic substances into soil
and groundwater, while e-waste combustion emits toxic vapors into the atmosphere. Inappropriate
e-waste disposal poses significant harm not only to the environment, but also to human health. E-
waste disposals can directly impact and indirectly impact human health. The indirect way is the
impact on the food web that transfers to humans. Contamination by toxic substances from disposal
and primitive recycling processes results in by-products entering the food chain thus transferring
to humans. For example, blood, serum, hair, human milk and urine from people who live in the
areas where e-wastes are being recycled exhibit significant concentrations of toxic substances [2].
The direct way is the impact on workers whose jobs require them to be exposed to e-waste. Human
exposure to heavy metals and POPs released from e-waste treatment processes pose significant
health risks to workers and local inhabitants especially pregnant women and children [2].

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Therefore, e-waste management is a critical issue in both developed and developing
countries. Many countries and regions, such as the European Union, Japan, South Korea, and
Taiwan are currently working to improve e-waste management and recycling systems. There have
been difficulties in e-waste management including the presence of the informal sectors, which are
the same as craft villages in Vietnam, and the lack of consumer awareness. Informal sectors handle
e-waste improperly without following any environment and safety standards. Moreover, because
informal sectors are small communities and organizations that operate illegally without any
registration with the authorities, they do not have any formal report on their business. This causes
difficulties in managing the e-waste flow and controlling the proper e-waste recycling operation.
Moreover, the lack of consumer awareness on the harmful effects of e-waste on environment and
human health causes improper e-waste recycling. The consumers may dispose e-waste with normal
waste, possibly allowing the informal sector to recycle their e-waste, and release more and more
e-waste into the environment. This makes e-waste management very challenging.
An effective e-waste recycling system would be able to reduce the amount of e-waste
released into the environment by reducing the presence of informal sectors, and allowing
consumers to recycle e-waste more frequently. Creating an effective e-waste collection system
plays an important role in improving the e-waste recycling system. An effective collection system
can accurately anticipate the amount of e-waste generated by consumers. It is also able to collect
the amount of generated e-waste in a proper and effective way. Moreover, an effective e-waste
collection system can increase the consumers’ willingness to participate in e-waste recycling. This
thesis introduces a multi-stage model to improve e-waste collection system. The model can
identify the consumers’ willingness to participate in e-waste recycling, estimate the amount of e-

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waste that would be collected based on their willingness, and plan the next step based on the factors
that affect the consumers’ willingness to participate in e-waste recycling and the amount of e-
waste that would be collected. The existing methods for determining the consumers’ willingness
to participate in e-waste recycling and estimating the amount of e-waste that would be collected
were applied to two populations available at the university: (1) faculty, staff, and students as
private citizens and (2) the university as an institution.

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2. Chapter 2: Background
2.1. E-waste and its impact
E-waste contains many hazardous materials including metals and persistent organic
pollutants (POPs) [2]. E-waste is a mixture of metals including lead, cadmium, mercury, PCBs
and PVC. These substances contaminate the air when they are burned, or leach into soil and poison
water sources when they are buried in landfill. E-waste leaches into grounds from e-waste
dumpsites, and it can bring metals into soil and underground water sources. Toxins from e-waste
that leach into soil can degrade soil quality and transfer to plants as well as livestock and animals
nearby the dumpsite, entering the food chains that transfer to humans [3]. Moreover, toxins from
e-waste that enter water sources can increase the concentration of metals and contaminants in
aquatic ecosystem, which seriously harms plants and living creatures in water [3]. On the other
hand, combustion from burning e-waste can emit harmful vapors into the atmosphere, which will
be absorbed by humans, animals, livestock and plants. Inappropriate e-waste disposal poses
significant threats not only to the environment, but also to human health. The list of negative
impacts of e-waste on human health are specified in Table 1. It directly impacts laborers working
on e-waste sites and people living near e-waste dumpsites. The contaminants of e-waste can spread
into the atmosphere and pollute the surrounding air, which indirectly impacts human ingestion and
inhalation system [3]. For example, B. H. Robinson [3] found workers at e-waste processing plants
had high concentrations of PBDEs in their blood, a flame retardant in e-waste which causes
hormone disorders. Children who lived near e-waste processing plants and dumpsites had elevated
levels of lead and cadmium in their blood [3]. Furthermore, breastfeeding mothers have high levels

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of Polychlorinated biphenyl in their breast milk which can directly transfer to their children [3].
Polychlorinated biphenyl is a substance in e-waste that reduces the function of human organs.
Table 1 shows common toxic substances that are associated with e-waste and their negative
impacts on human health.
Table 1: Common Toxic Substances in e-waste [2]
Substance Applied in e-waste Impact on human health
Sb: Antimony A softening agent in glass and
computer housing.
Leads to abdomen pain, vomiting,
diarrhea and stomach ulcers through
high Sb intake levels over a long period.
As: Arsenic Gallium arsenide appears in
light emitting diodes.
Produces damaged nerve signaling, lung
cancer, and skin disease.
Ba: Barium Used in Sparkplugs, Cathode-
Ray Tube (CRT), and
fluorescent lamps.
Weakens muscle, makes brain disease,
and damages the organs though
exposure.
Be: Beryllium Used in motherboards, power
supply boxes, relays and finger
clips.
Causes berylliosis, increase chance of
lung cancer and skin defect.
Cd: Cadmium Used in rechargeable batteries,
semiconductor chips, infrared
detectors, printer inks and
toners.
Cause serious risk to the kidneys.
BFRs:
Brominated flame
retardants
Used in printed circuit boards,
plastic cases and insulation to
reduce flammability
Leads to hormonal disorders if burned

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Pb: Lead Used in soldering, CRT,
batteries, cabling, printed
circuit boards and fluorescent
tubes.
Infect the blood. Harm the brain,
nervous system, kidney and
reproductive scheme in human.
Hg: Mercury Used in flat panel displays,
batteries, backlight product,
thermostats and switches.
Causes disease to kidneys, brain, and
fetuses.
Ni: Nickel Used in computer casing,
batteries, CRT and printed
circuit boards.
Leads to lung dysfunction, allergic
reaction, and bronchitis.
PCBs:
Polychlorinated
biphenyls
Used in fluids in heat transfer
application, condensers, and
transformers.
Defects human’s liver and leads to
cancer in animal.
PVC: Polyvinyl
chloride
Used in making keyboard,
housing, monitors, and
cabling.
Leads to respiratory defects when it was
burned
2.2. E-waste Management around the world
Extensive research is currently underway into e-waste management in order to mitigate
problems at both national and international levels [4]. On March 22, 1989, the Basel Convention
was adopted. The Convention considers e-waste as toxic substances and its export could be
allowed under special conditions. Currently, there are 183 countries and the European Union that

25
are parties to the Basel Convention. There are several approaches that have been developed and
applied to e-waste management, including: Life Cycle Assessment (LCA), Extended Producer
Responsibility (EPR), Multi Criteria Analysis (MCA), and Material Flow Analysis (MFA). With
the laws in different countries, these e-waste control tools have helped reduce the disposal of
electronic waste in the world. For example, in Europe, many legislative documents have been
drafted and implemented requiring manufacturers and other stakeholders to adopt an
environmental approach to design and assess the environmental impact of their products
throughout their lifecycle [4]. One such example of managing waste electrical and electronic
equipment is the Restriction of the Use of Certain Hazardous Substance (RoHS) Directives [4].
Moreover, China has adopted legislation to manage the pollution caused by electronic products,
and Japan has introduced and adopted the Home Appliance Recycling Law (HARL) to decrease
the environmental impact of waste electrical and electronic equipment. Several countries in
Latin/South America, such as Brazil, Chile, and Peru have taken part in policy formulation related
to waste electrical and electronic equipment. In the United States and Canada, although there is no
national legislation specifically concerning e-waste, several regions already have their own
legislation [4]. Currently, the approach to solve e-waste problems is focusing on properly
collecting, safely recycling, and appropriately disposing of e-waste, as well as raising awareness
about the negative impact e-waste has on the environment and human health.
2.3. Regulatory Environment in the United States and State of Michigan
There are laws and regulations that manage e-waste in the United States. Currently, 25
states in the United States have passed e-waste laws including: California, Connecticut, Hawaii,

26
Illinois, Indiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Jersey,
New York, North Carolina, Oklahoma, Oregon, Pennsylvania, South Carolina, Texas, Utah,
Vermont, Virginia, Washington, West Virginia, and Wisconsin [5]. The remaining 25 states
haven’t passed any e-waste law, but in my opinion, this fact does not indicate the lack of federal’s
efforts. The federal government Interagency Task Force on Electronics Stewardship (ITFES)
issued a National Strategy for Electronics Stewardship (NSES) which has four main goals: (1)
Promoting greener design for electronic devices, (2) assuring federal government leads by
example, (3) ensuring safety and efficient management in processing e-waste, (4) decreasing harm
from exporting e-waste to developing countries [5]. Moreover, electronics recyclers in the United
States are encouraged by the Environment Protection Agency (EPA) to be certified under an
accredited standard such as Responsible Recycling (R2) Standards or e-Stewards Standards for
Responsible Recycling and Reuse of Electronic Equipment (e-Stewards) [6]. R2 and e-Stewards
are worldwide-recognized standards for e-waste recycling industry which are specific to a facility.
Both standards ensure the correct management operation, and improve safety, worker health,
security practice, and sustainability in an electronics recycling facility [6]. In addition, R2 and e-
Stewards promote reusing and recycling, reduce exposure of human and environment to e-waste,
assure proper material management, and require data security in an electronics recycling facility
[6]. Because the government encourages electronics recyclers to be certified under these two
standards, certified electronics recyclers will become preferable to do business with. This creates
the competitive environment in which electronics recyclers work their best to enhance their
operation to meet the requirements of these standards. Therefore, e-waste recycling system will be
more effective, sustainable, and safe. The EPA has its own regulations for recycling toxic

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substances in e-waste including cathode ray tubes (CRTs) and Polychlorinated Biphenyls (PCBs).
According to the EPA, CRTs are classified as hazardous waste due to the existence of lead, and it
is recommended to be reused and repaired before recycled [7]. This helps reduce the rate that CRTs
are disposed into the environment. Moreover, companies that transport CRTs overseas must notify
the EPA and be allowed by the EPA before the shipment; these companies are also required to
submit yearly reports to the EPA [7]. This regulation limits CRTs export to developing countries
for improper recycling, which can seriously harm the environment and human health in these
countries. PCBs are groups of artificial organic chemicals that are used in many electronics
applications including transformers, capacitors, voltage regulators, switches, re-closers, bushings,
electromagnets, fluorescent light ballast, cable insulation, and old electrical devices and appliances
[8]. According to the Toxic Substances Control Act of 1976, the EPA has the authority to control
the use of PCBs [8]. The details on PCBs regulations on manufacturing, processing, distribution,
and prohibitions are attached in Title 40 of the Code of Federal Regulation (CFR) in part 761.
These regulations on PCBs helps decrease the number of PCBs that are released into the
environment and promotes proper PCBs recycling. The EPA also published a PCBs question and
answer manual that covers all the EPAs’ regulations on handling, processing, and disposal of PCBs
[8].
In Michigan, according to State of Michigan Department of Environmental Quality (DEQ),
the e-waste laws are specified in the Natural Resources and Environment Protection Act (NREPA)
act 451 of 1994, part 173, electronics. In general, manufacturers of electronics products must
register with the DEQ and must have takeback programs, whose information must be available
online for consumers and businesses [5]. Also, retailers in Michigan are only allowed to sell new

28
computers and televisions from registered manufacturers [5]. Moreover, electronics recyclers are
required to register every year with the DEQ and to keep records of the environment, health, and
safety management system for being audited. Moreover, recyclers are required to maintain the
records of the total amount of e-waste recycled and the records of all companies who buy the
materials for further processing [5]. This act not only allows the DEQ to control the flow of e-
products, but also encourages consumers and businesses to give back their e-waste for recycling.
Specifically, dismantling facilities that recycle household and CESQG e-waste in Michigan, must
be permitted and licensed under Part 115, Solid Waste Management, of the NREPA act 451 of
1994 [9]. Moreover, the facilities that recycle SQG and LQG e-waste as universal waste must meet
the requirements under Part 111, Hazardous Waste Management, of the NREPA act 451 of 1994
[9]. Table 2 shows the differences among CESQG, SQG, and LQG. Moreover, these facilities must
be known as universal waste facilities that can accept hazardous waste and must meet the
exemption requirements from hazardous waste permitting and licensing if they process cathode
ray tubes (CRT) and printed circuit boards [9]. If the facilities recycle SQG and LQG e-waste as a
hazardous waste, the e-waste must be transported under the requirement of the NREPA act 138 on
licensed and registered hazardous carrier [9]. All these requirements ensure that e-waste will be
managed effectively and treated in proper way that promotes environment sustainability and
protects human health.

29
Table 2: CESQG, SQG, and LQG definition
CESQG (Conditionally
exempt small quantity
generator)
Release less than 100 kilograms of non-acute hazardous waste each
month, less than one kilogram of acute hazardous waste per month,
and never have more than 1000 kilograms at any moment
SQG (Small quantity
generator)
Release from 100 to 1000 kilograms of non-acute hazardous waste
each month, less than one kilogram of acute hazardous waste per
month, and never have more than 6000 kilograms at any moment
LQG (Large quantity
generator)
Release more than 1000 kilograms of non-acute hazardous waste or
one kilogram of acute hazardous waste each month
Beside laws and regulations on e-waste recycling, there also are standards for quality,
environment, health, and safety management system that recyclers should follow such as e-
Stewards, RIOS, and R2. For example, Padnos Recycling and Scrap Management has operated
their e-waste processing facility under the RIOS:2016 and R2:2013 standards. RIOS stands for the
recycling industry operating standard, which was created for recyclers by recyclers. RIOS assures
compliance and safety across the facility, improves the products’ quality, and promotes
environment sustainability in all operations [10]. R2:2013 assures the quality, transparency, and
environment and social responsibility inside an e-waste recycling facility [11]. These standards
promote the development of e-waste recycling industry. They ensure safety, quality, and
environment sustainability of e-waste recycling system. They also create the competitive

30
environment for e-waste recyclers to grow, in which e-waste recyclers work their best every day
to achieve these standards.
2.4. Alternate path for end of use e-product to avoid landfill
Currently, there are many alternative options for consumers to get rid of their end of use e-
products instead of disposing them in landfill. First, consumers can look for the certified e-waste
recyclers. In the United States, e-waste recyclers which are certified with accredited standards such
R2:2103 and e-Stewards must follow proper e-waste recycling procedures that ensure workplace
safety, worker health, material quality, and environment sustainability. By bringing their e-waste
to these certified recyclers, consumers will be ensured that their e-waste will be handled properly
without being disposed in landfills or being transported to other developing countries. Some types
of e-waste such as CRT TVs and CRT monitors require fees for recycling, but some other types
such as phones, laptops, and personal computers are recycled for free. Consumers can find the list
of R2 and e-Stewards certified recyclers on the official website of R2 and e-Stewards, which are
shown here: (1) https://sustainableelectronics.org/recyclers, and (2) http://e-stewards.org/find-a-
recycler/. Second, consumers can look for electronics retailers such as Best Buy and Staples. These
retailers have their own e-waste take back policy, in which their customers can bring end of use
and unwanted consumer e-products, which were not necessary purchased at these retailers, for
recycling. Staples is a retailer which is e-Stewards certified. Although Best Buy is not certified
with R2 or e-Stewards standards, they commit to work with certified recyclers to handle e-waste
properly [12]. They also ensure that their e-waste will not be transported to another country for
processing [12]. Third, consumers can bring their e-waste to local government recycle sectors if

31
they offer e-waste recycling. Moreover, they can check if local civic institutions such as a
university, high school, or secondary school have any e-waste recycling programs. Another option
for consumers who want to get rid of their end of use and unwanted e-products is donating. Reusing
always stands before recycling in the recycling hierarchy. There are many organizations such as
Goodwill and Salvation Army that accept old and unwanted electronics from consumers. They use
profit from reselling, refurbishing, and recycling these products to create jobs and educate other
people who need help [12]. Moreover, Goodwill has been an active partner with Dell Technology
in a program called Reconnect, which strictly does not allow e-waste exporting to other countries
[12].

32
3. Chapter 3: Literature Review
There has been research on obstacles in e-waste management systems. There are many
obstacles to manage e-waste efficiently in both developed and developing countries.
The first obstacle is the illegal import of e-waste from developed countries to developing
countries because the rules in developed countries limit the amount of e-waste in landfills.
According to Babu, Parande, and Basha [13], in developed countries the attempt to divert waste
electrical and electronic equipment (WEEE) from landfills and incinerators resulted in unsafe
dismantling, shredding, burning, exporting, and other precarious or irresponsible disposal
approaches. Developed countries utilized the word ‘recycling’ to rationalize the free exchange of
harmful waste to the developing countries in Asia, which has cheap labor and negligent restriction
of human health and environment [13]. Moreover, according to Tanskanen [14], in Europe, up to
two-thirds of e-waste was either dumped into landfills or traded with developing countries where
there were not any certified recycling and disposal facilities. Nnorom and Osibanjo [15] found that
developing countries had difficulties in the management of e-waste which was either internally
generated or imported unlawfully.
The second obstacle is the lack of government regulation in developing countries.
According to Nnorom and Osibanjo [15], developing nations lacked both sufficient infrastructure
and government-driven and formal private industry-driven programs for effective e-waste
management. Not only do the developing countries lack formal government-driven forces, but also
the developed countries. Kahhat et al. [16], indicated that some countries were initiating e-waste
regulations.

33
The third obstacle in e-waste management is the existence of informal sectors that illegally
collect and process e-waste. Davis and Garb [17] revealed that the informal sectors were easily
seen in the electronic waste industry, and their amounts and influences have expanded rapidly over
recent decades. Additionally, while the worrisome aspects of informal e-waste sectors have been
broadly examined, less consideration has been placed on their potential benefits and on their
collaborations with formal e-waste sectors and policies [17]. He also outlined the strategies that
are essential for obtaining effective and life-changing partnerships between the informal and
formal e-waste industries including: (1) understanding both sectors, (2) accepting collaboration as
an incremental and continuous process, (3) employing relevant stakeholders, and design
managements co-operatively, (4) concentrating on reducing key risks and improving key strengths
of the informal sector, (5) making alterations by incentivizing rather than punishing the informal
sector, and (6) integrating bottom-up and top-down management approaches [17]. Tran and
Salhofer [18], in their study of the Vietnamese informal sector’s processing of computer waste,
mentioned that in developing nations, the main difficulties were the fact that the informal sector
did not methodically evaluate and audit the process, so it was challenging to comprehend the
problem and figure out solutions.
The fourth major obstacle in e-waste management is the lack of consumer recognition for
recycling of e-waste and its benefits to the environment, and the foundation of a sustainability-
minded society [14]. Moreover, due to lack of education, the general public still did not realize,
nor were they fully alerted to the hazardous substances in their old electronics [19].
The fifth obstacle in e-waste management is the life span of electronic products, which is
an aspect that affects the process of e-waste recycling. In the analysis of e-waste stream, Kwak et

34
al. [20], noted that secondhand products, components, or materials that have a second life through
reuse could decrease the volume of electronic waste that must be landfilled and bring about
economic and social advantages. Kwak et al. [20], also showed that the reusability of secondhand
goods is dependent more on their technological end-of-life rather than their reliability. For
example, people are less likely to want to buy the old model of a product when the new model
comes out. In addition, the obsolescence of electronic products makes reusing e-waste impractical
and unprofitable [20]. Similarly, people tend to keep their old electronic devices for a long time
after they no longer utilize them, which makes the device outdated, less valuable, and difficult to
extract the valuable components that could be resold or refurbished [19]. Tanskanen [14] pointed
out that the fast improvement in information and communication devices, both the increasing
adaptability of most electronic technologies together with more affordable costs has led to an
extremely reduced lifespan for most electronic equipment. Bhuie, Ogunseitan, Saphores, and
Shapiro [1] indicated that cell phones and computers have relatively short life expectancy, and
they are often held for a long time in garages, closets or storage spaces before being delivered to a
landfill or recycling center.
To overcome the obstacles in the e-waste recycling system, it is necessary to implement an
efficient e-waste collection system. An efficient e-waste collection system will reduce the amount
of e-waste released into the environment, support e-waste management, reduce the presence of
informal sectors, increase consumers’ awareness of benefits of e-waste recycling, and allow
consumers to recycle e-waste more frequently.

35
3.1. Consumers’ Willingness toward e-waste recycling
To create an effective e-waste collection system, the first important task is to understand
the consumers’ willingness to participate in e-waste collection. A lot of research was conducted to
investigate the behavior and willingness of customers around the world in recycling e-waste.
Borthakura and Govind [21] did research on the emerging tendency in consumers’ e-waste disposal
behavior and awareness in many countries over the world including China, Japan, Korea, Thailand,
Vietnam, India, Switzerland, Spain, Germany, the United Kingdom, Nigeria, Ghana, the United
States, Canada, Brazil, Mexico, and Australia. This research showed that universal knowledge and
experience with consumers’ e-waste disposal behavior will provide a significant support for many
countries in creating the effective strategies to solve their current e-waste problem.
According to the Ciocoiu, Cicea, and Tofana’s [22] analysis on the volume and consumer
disposal behavior for e-waste in Romania, consumers still have not achieved the e-waste disposal
awareness. Moreover, in Romania, the consumers’ disposal willingness is significantly different
between rural areas and urban areas [22]. Ciocoiu, Cicea, and Tofana [22] revealed that only
approximately 60% of metropolitan citizens separated e-waste to recycle later, but the other 40%
didn’t separate e-waste from other wastes because (1) they did not know that they were taken
separately afterwards, (2) they could not find an e-waste site, (3) they lacked knowledge, and (4)
they lacked time. Perez-Belis, Bovea, and Simó [23] conducted a study on consumer behavior and
environmental education in the field of waste electrical and electronic toys in Spain, which
indicated that other than the consumers who gave away the unused toys to some social
organizations, two-thirds of the consumers threw them in the trash bin with other types of waste,
while the remaining one-third brought their toys to the recycling centers. The study also pointed

36
out that the disposal and recycling habits were significantly dependent on the family size, in which
the one-child families discarded toys because they were not used anymore, whereas the larger
families which had three or more children discarded toys because they were broken and unusable
[23]. Moreover, the time that toys were kept rose with the increase of family size, which was the
increase in the number of children [23]. Lozano, Esparza1, Adenso-Díaz, and García [24],
clustered the answers from the survey of consumers’ habits and behaviors towards replacing and
discarding of electronic appliances in Spain, which pointed out that the consumers’ behaviors were
dependent on the types of appliances. The responses from the survey also indicated that there was
a need to better the consumers’ awareness in regard to e-waste disposal and to improve the
accessibility of public green points [24].
The survey that Song, Wang, and Li [25] conducted to determine Macau citizens’
behaviors, attitudes, and willingness to pay for recycling e-waste showed that despite the lack of
knowledge in e-waste problems, most citizens were still willing to bring the e-waste to formal
collection centers. Moreover, the positive responses to the “willing to pay” question elevated as
the education level and income level increased, while these responses dropped as the respondent’s
ages decreased [25]. In the study on willingness and behavior towards e-waste recycling for
residents in Beijing city, China, Wang, Zhang, Yin, and Zhang [26] mentioned that the primary
portion of Beijing’s civilians were reluctant to take part in e-waste recycling, as nearly two-thirds
of the population still sold electronic scrap to peddlers instead of the formal e-waste recyclers. A
list of recommendations was brought up including developing infrastructure, constructing
effective monitoring programs, increasing the penalty for illegal disposal, introducing incentive
programs, and implementing e-waste recycling in the education system [26]. Li et al., did research

37
on the behavior of urban residents in e-waste recycling in Baoding, China. According to Li et al.
[27], in Baoding, e-waste disposal system was malfunctioning because the peddler route was the
primary channel through which e-waste was sold [27]. The high-income households bought more
electronic products, while the college community was the majority that were willing to be charged
for e-waste disposal [27]. By analyzing the stream of various e-wastes types, this research revealed
the reasons to dispose electronics, and the consumers’ response to the cost of recycling revealed
that the most accurate indicator in the e-waste management system was the separation of
consumption patterns in using household appliances, and the purchase price of the electronic
products was the most critical factor in choosing recycling methods [27]. Chi, Wang, and Reuter
[28] also conducted a study about e-waste collection channels and household recycling behavior
in Taizhou, China. The study also revealed the fact that informal collections, such as peddlers were
the main disposal channel of urban household e-waste, whereas the e-waste stream to the formal
sector remained insignificant [28]. According to the study, although most consumers understood
the importance of e-waste recycling, the informal sectors were chosen due to their scope of
collecting, and their convenient, flexible and accessibility services as well as the insufficient
compensation from formal e-waste sectors [28]. Manomaivibool and Vassanadumrongdee [29]
assessed the e-waste disposal behavior and future interest of consumers in Thailand. According to
them, the primary e-waste collection sector in Thailand was the waste dealer because of their pick-
up service. Also, the large portion of households supported the government’s public recycle
program without caring too much about financial incentives [29]. This assessment recommended
that to achieve the public support, developing convenience in recycling e-waste played crucial
roles [29]. This convenience could be obtained by partially utilizing buy-back money at the local-

38
government drop-off center to arrange a scheduled pick-up service and by requiring retailers and
convenience stores to buy back the e-waste from their customers [29]. Kwatra, Pandey, and
Sharma [30] conducted another study on urban citizens’ knowledge and awareness of e-waste in
Delhi, India. This research showed that a large portion of middle-class residents had a little
awareness of problems in e-waste recycling [30]. For the residents who understood the problem,
their main information sources were the internet and newspaper [30]. Additionally, these people
had no perception about the proper way to recycle and manage e-waste. One-third of respondents
in Dehli changed their electronic goods and appliances within their useful life, which advocated
the generation of e-waste [30].
Saphores, Ogunseitan, and Shapiro [31] studied the United States households’ willingness
to engage in a pro-environment behavior, which was recycling e-waste at drop-off centers.
According to the study, the households’ willingness to engage in e-waste management was
impacted by many internal variables including the convenience of recycle processes, consumers’
awareness about e-waste issues, previous experience in e-waste recycling, gender, and marital
status [31]. Interestingly, other factors such as education, age, and ethnicity had insignificant
effects; on the other hand, awareness of e-waste legislation, accessibility of recycling centers, and
consumers’ salary were not statistically considerable [31]. Furthermore, Saphores, Nixon,
Ogunseitan, and Shapiro [32] published a case study on household willingness to recycle e-waste
in California, United States. The case study revealed that education, environmental beliefs and
convenience were the important factors that impacted the intentions to discard e-waste at recycling
centers [32]. It also recommended opening e-waste recycling centers in the communities that had
a curbside collection program, getting contracts with retailers to collect e-waste, introducing e-

39
waste education programs for high school students, and creating e-waste recycling events for the
young adults [32].
Nduneseokwu, Qu, and Appolloni [33] worked on a fundamental platform to determine the
effects of the behavior, the attitude, and the awareness on the consumers’ intention to take part in
the formal e-waste management activities in Nigeria. Their work explained that the behavior, the
attitude, and the awareness significantly impacted the consumer’s engagement in the formal e-
waste management activities [33]. Sabbaghia, Behdadb, and Zhuanga [34] modeled a game
theories formulation between consumers and electronics producers to study consumer interests and
behavior in attending the electronics take-back program. The research obtained the results that
convenience of services, consumers’ tendency to overvalue the obsolete products, the usage time
of electronics, consumers’ perceptions of products’ obsolescence, and the re-marketability of
refurbished products affected the consumers’ decisions about when to return the end of used
electronic equipment [34]. Mishima and Nishimura [35] published a survey that investigated
consumers’ behavior in recycling small-sized e-waste, which led to the fact that consumers usually
did not want to recycle small e-waste because these types of e-waste held many private and
personal information. The survey also indicated that instead of compensation and reward money,
information security, data transfer, and appropriate education about e-waste were the most
significant factors affecting e-waste recycling practice [35]. Zhong and Huang [36] introduced a
research questionnaire to investigate the effect of point reward incentive systems on consumers’
behavior in taking part in formal e-waste management sectors, which showed that there was a close
relationship between the willing behavior and the length of participation, subjective attitudes,
unique consumers’ features, and objective conditions. This also concluded that a proposed point

40
reward system could efficiently change consumers’ attitude towards e-waste recycling and develop
China’s e-waste management system [36]. Sabbaghi et al. [37], set up a statistical study of the
dynamic character of e-waste to investigate consumers’ e-waste storage and utilization behavior.
In this research, by investigating the impact of design features, brand name, and consumer
classification of e-waste lifespan and e-waste’s time in storage from the database of 10063 hard
disk drives of used computers, Sabbaghi et al. [37], revealed that, without regard to brand name
and storage space, the household consumers had stored computers less than commercial consumers
had [37].
3.2. E-waste Amount Estimation
The accurate estimation of current and future e-waste quantities is important information
in order to design an optimal e-waste collection and treatment system. Many existing researchers
put their great efforts into studying and developing the e-waste estimations method. Breivik,
Armitage, Wania, and Jones [38] applied the mass balance method in tracking the global
generation and exports of e-waste. According to the mass balance method, the net generated
amount of e-waste was equal to the sum of e-waste amount that domestically generated and e-
waste amount that was imported minus the amount of e-waste that was exported [38]. The mass
balance method used in this research had a disadvantage; it lacked data in the illicit flow of e-
waste, so the amount of e-waste was underestimated [38]. For example, in many countries such as
China and Ghana, e-waste was imported illegally into the countries for processing because e-waste
processing cost in these countries were cheap. E-waste can enter and exit these countries illegally

41
without any notices because the government was easy to be bribed. Therefore, it was impossible
to obtain the data about this illicit e-waste flow.
Araujo, Magrini, Mahler, and Bilitewski [39] developed a model for estimation of a
potential generation of electronic products in Brazil, in which the consumption and use method
was used to estimate the e-waste in a saturated market. The market is saturated when the sales of
the products or services reach a point when the customers’ demands are met. Some examples for
a saturated market are the television market, personal computer, washing machine market, and so
on. Basically, according to consumption and use method, the amount of generated e-waste per year
was equal to the fraction between stock in use and average life span [39]. The time-step method
was applied in the dynamic market which is the market in which the products have short design
cycles including computers and cell phones. According to the time-step method, the amount of
generated e-waste was equal the number of product sale in current year minus the differences
between number of stocks in use in current year and previous year [39]. Ikhlayel [40], in his
research, showed the comparison among different methods that estimated the generation of e-waste
in developing countries including consumption and use method, time step method, simple delay
method, mass balance method and approximation method. According to the simple delay method,
the amount of e-waste generated in year t is equal to the sales of e-products in year (t-L), where L
is the life span of the e-products [40]. In the approximation method, the amount of e-waste
generated is approximated based on the sales data of the current year, which means that the amount
of e-waste generated in year t is equal the sale amount in this year [40]. He also indicated the type
of market that could be applied these methods. The consumption and use method was also modified
so it could be applied in the case of both dynamic and saturated markets [40]. However, this

42
modified method could only estimate the amount of e-waste generated, but not the amount of e-
waste that would be recycled. Consumers possibly could generate the e-wastes and store them
without bringing them to recycle. Moreover, Liu, Tanaka, and Matsui [41] applied the market
supply method to predict the e-waste amount generated in Beijing, China. This market supply
method could estimate the amount of e-waste based on the annual sale data and the obsolete ratio
of the electronic products [41]. Specifically, the obsolete weight amount of e-products (in year t)
was equal to the product between sales amount in (t-i) years and the obsolete ratio of a product in
the i-th year [41]. According to this research, the obsolete ratio of the electronics product could be
obtained by conducting a survey [41]. It is, however, difficult to collect the data on sale amount of
the electronic products in a specific region of the research scope because the sales data for each
type of electronic product is sensitive information of the organizations. Saidan and Tarawneh [42]
estimated the generation of e-waste including cell phones, personal computers, televisions,
refrigerators, and washing machines (16, 874 tons) in Jordan in 2015 based on the sales data and
the estimation of the average life span of electronic items. The estimation also indicated that the
average amount of E-waste produced per capita would grow from 2.38 kg/capita in 2012 to 2.48
kg/capita in 2015 [42].
Some studies investigated the estimation of specific types of e-waste. Li, Yang, Lu, and
Song [43], compared three estimation methods including market supply method, the consumption
and use method, and the sale and new method; the researchers applied them to estimate the amount
of retired mobile phones in China. The study showed that the sale and new method was the most
suitable for estimation of the retired mobile phone [43]. Moreover, it showed that there were
739.98 million retired mobile phones in China in 2012 [43]. Petridis, Stiakakis, Petridis, and Dey

43
[44], by collecting the sales data of computers, presented the e-waste generation model applied to
computers in Western and Eastern Europe, Asia/Pacific, Japan/Australia/ New Zealand, and North
and South America.
Other studies focused on the prediction of the e-waste generation in the future. Once the
policy makers and manufacturers become aware of the expected generation of e-waste, they can
prepare the proper infrastructure to manage and recycle this amount. S. Chang, Assumaning, and
Abdelwahab [45] performed the material flow analysis to predict the weight of e-waste that
generated in the United States in the future. The analysis indicated that in 2025, over one billion
units would come to the end of their useful life, in which cell phone devices accounted for about
66.0% of units of the total amount [45]. Petridis, Stiakakis, Petridis, and Dey [44] provided the
prediction of computer waste quantities using seven forecasting models. The results revealed a
significant increase in the United States and United Kingdom because of the lower computer
lifespan and higher sales [44]. Yu, Williams, Yu, and Yang [46], applied the logistic model and
material flow analysis with the historical penetration rate and sales to predicting the amount of
computer waste generated until 2030, which was estimated as 400 - 700 million units in developing
regions and 200 - 300 million units in developed regions. Other than that, the authors
recommended that policymakers should firstly address the domestic situation in developing
countries in order to ease the negative effect of informal recycling of e-waste [46]. Similarly, Yang
and Williams [47] employed the logistic model to forecast the sales and generation of obsolete
computers in the United States by 2020. According to them, the minimum and maximum
generation of obsolete computers in the United States, by 2020, would be 92 and 107 million
computers [47].

44
4. Chapter 4: Proposed model to design the e-waste collection system for a given
population
4.1. Framework of the proposed model
The general framework of the proposed e-waste collection model is shown in Figure 1.
Basically, the model includes four steps. First, the consumers’ willingness to participate in e-waste
collection and recycling is determined using the data from survey questionnaires that are designed
carefully and distributed to the consumers in the region of the research scope. Simultaneously, the
amount of e-waste that would be collected in this region is estimated based on the consumption
and use method that was presented in the existing literature. After that, the recommended next step
to improve an e-waste collection system is proposed based on the consumers’ willingness to
participate in e-waste recycling and estimated amount of e-waste that would be collected.
Figure 1: General framework of proposed e-waste collection model

45
4.2. Determine the consumers’ willingness to participate in e-waste recycling
The consumers’ willingness to participate in e-waste recycling in the region of the research
scope was determined first by the data from survey questionnaires that were spread out to
consumers in this population in group. These questionnaires focus on some essential points,
including (1) demographic information, (2) residential conditions, (3) consumers’ awareness, (4)
previous recycling habits, (5) convenience of recycling services, (6) economic benefits, (7) type
of e-waste and (8) consumers’ willingness and behavior. These points help evaluate the
consumers’ awareness and behavior to engage in e-waste collection and recycling. In the beginning
of the questionnaire survey, the overall description of the study was introduced, and the purpose
of the study was clearly stated. In addition, the importance of the authenticity of the answers is
emphasized to minimize the uncertainty of the study. There was also a note to assure that the
personal information of respondents was protected and confidential. The scope of e-products was
also specified in the introduction of the survey. The scope of the e-product was determined based
on their weights which is mentioned in detail in the United Nations e-waste statistics [48]. Seven
types of electronic products are listed in Table 5 with their average weight in section 4.3. The
questionnaire includes eight parts mentioned above. In the first part, the information collected
includes the respondents’ age range, income, vehicles availability, and the highest level of
education. The residential condition part asks questions to determine if the respondents rent houses
for temporary living, rent houses for living long-term, own a house, or own many houses. The
consumers’ awareness part identifies the knowledge of consumers in the state law about e-waste
recycling, and in the negative effect of material in e-waste on human health and the environment.
Additionally, the recycling habit shows the questions that identify the respondent’s experiences

46
with recycling in the past. Specifically, this part finds out if the respondents have participated in
e-waste recycling before. The convenience of the recycling service part discovers how the
accessibility of the collection service affects consumers’ decisions to bring their old e-products to
the drop-off locations or the recycling centers. Moreover, this part explores the reasons that prevent
consumers from bringing e-waste to the drop-off locations or the recycling center. The economic
benefits part finds out the influence of economic gain on the consumers’ decisions to recycle e-
waste. The type of e-waste part explores the effects of different types of e-waste on consumers’
willingness to engage in the e-waste collection. The last part, consumers’ willingness and behavior,
determines the willingness of the consumers to participate in the e-waste collection and recycling,
and explores the way that the consumers treat their obsolete e-product. Moreover, the questionnaire
survey has another part that determined the following two variables: (1) the number of different
types of electronic product owned by each consumer and (2) the average duration from the time
consumers bought an electronic product until they would be ready to bring it to a collection point
for recycling or dispose of it. These two variables help compute the estimated amount of the e-
waste that would be collected in the region of the research scope. The survey questionnaire is
attached in the Appendix A.
To draw a random sample of the population in the region of the research scope, the sample
size is determined using equation 4.1 and equation 4.2, which was mentioned in the study of
Nduneseokwu, Qu, and Appoloni [49]:
𝑆𝑆 = (𝑍𝑠𝑐𝑜𝑟𝑒)+
× 𝑝 ×
1 − 𝑝
(𝑚𝑎𝑟𝑔𝑖𝑛 𝑜𝑓 𝑒𝑟𝑟𝑜𝑟)+
(4.1)

47
𝑆𝑆𝑎𝑑𝑗𝑢𝑠𝑡𝑒𝑑 =
𝑆𝑆
1 + [
𝑆𝑆 − 1
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛]
(4.2)
Where SS is the sample size, Z-score is the reliability coefficient which relates to the
confidence level, p is the standard deviation which is usually 0.5 to ensure a large sample, and the
margin of error relates to the confidence interval [49].
The data obtained from the questionnaire helps determine the relationship between 12
independent variables and the dependent variable, which is the willingness of the consumers to
engage in e-waste collection. The independent variables include: Age Range (X1), Income (X2),
Education Level (X3), Vehicle Availability (X4), Type of E-Waste(X5), Residential Condition
(X6), Awareness about Effect on Natural Habitat (X7), Awareness about Effect on Human Health
(X8), Awareness about Law & Regulation (X9), Recycling Habit (X10), Convenience of
Recycling Service (X11), and Economic Benefits (X12). There are many ways to determine the
association between the dependent variable and independent variables. The first method that can
be used is correlation analysis. The correlation analysis can find out which independent variables
strongly affect the consumers’ willingness to participate in e-waste collection. The correlation
analysis determines the significance of the relationship among variables [50]. In the correlation
analysis, the sample correlation coefficient is computed using equation 4.3 [50]:
𝑟 = B
𝛽D
+
E∑ 𝑥H
+
−
(∑ 𝑥H)+
𝑛 I
∑ 𝑦H
+
−
(∑ 𝑦H)+
𝑛
(4.3)

48
Where r is sample correlation coefficient which describes the linear relationship between
the sample observations on two variables, x is random independent variable, y is random dependent
variable, 𝛽D is the slope of the population regression line for x and y, and n is the sample size [50].
The sample correlation coefficient has values between -1 and +1 and indicates the sign and
significance of the linear relationship between two variables [50]. The correlation between two
variables can be positive or negative [51]. The direction of the relationship is indicated by the sign
of the correlation coefficient, while the strength of the relationship is shown by the magnitude of
the coefficient [50]. For instance, a correlation of r = 0.91 indicates a strong and positive
relationship between two variables, whereas a correlation of r = -0.06 indicates a fragile, negative
relationship [51]. A correlation close to zero suggests no linear relationship between two variables
[51].
The second way to determine the relationship between 12 independent variables and the
willingness of the consumers to participate in e-waste recycling is using regression model. The
objectives of the regression model are to evaluate the relationship between independent variables
and dependent variables, and to forecast the value of one variable corresponding to a given value
of other variables [50]. The important factor that evaluates the relationship is the p-value. P-value
is defined as the lowest significance level that would cause the rejection of the null hypothesis
[52]. Therefore, a p-value conveys the information about the weight of evidence against the null
hypothesis, which helps the decision maker draw a conclusion on the level of significance [52]. In
the case of the thesis, small p-value indicates the statistically significant relationship between each
independent variable and the consumers’ willingness to participate in e-waste recycling.

49
In addition, in the analysis of categorical data, the chi-square test of independence is
recommended to assess whether a variable depends on another variable. The chi-square
distribution is the most frequently employed statistical technique for the analysis of frequency data
[50]. The chi-square test of independence verifies the null hypothesis that the two variables are
independent, so if the null hypothesis is rejected, it can be concluded that these two variables are
not independent [50]. The test statistic for the chi-square is calculated using equation 4.4:
𝜒+
= M N
(𝑂H − 𝐸H)+
𝐸H
Q (4.4)
Where 𝑂H is the observed frequency for the 𝑖RS
category of the variable of interest, and 𝐸H
is the expected frequency for the 𝑖RS
category [50].
The contingency table will provide better illustration of the chi-square test of
independence. The r rows represent the various levels of one criterion of classification and the c
columns represent the various levels of the second criterion [50].
Table 3:Example of Contingency Table [50].
Second Criterion
Level
First Criterion Level
1 2 3 … c Total
1 𝑛DD 𝑛D+ 𝑛DT … 𝑛DU 𝑛D.
2 𝑛+D 𝑛++ 𝑛+T … 𝑛+U 𝑛+.

50
3 𝑛TD 𝑛T+ 𝑛TT … 𝑛TU 𝑛T.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
r 𝑛VD 𝑛V+ 𝑛VT … 𝑛VU 𝑛V.
Total 𝑛.D 𝑛.+ 𝑛.T … 𝑛.U 𝑛
For example, the expected frequency 𝐸H in Cell 11 is calculated using equation 4.5 [50]:
(𝑛D.)(𝑛.D)
𝑛
(4.5)
In general, to obtain the expected frequency for a given cell, the total of the row in which
the cell is located is multiplied by the total of the column in which the cell is located and divide
the product by the grand total [50]. The expected frequencies and observed frequencies are
compared based on equation (4): If the discrepancy is sufficiently small, the null hypothesis is
tenable; if the discrepancy is sufficiently large, the null hypothesis is rejected, and it can be
concluded that the two criteria of classification are not independent [50]. After the chi-square is
found, the p-value can be found using the Table 29 in Appendix B with the chi-square value and
degree of freedom. The degree of freedom is calculated using equation 4.6:
𝑑𝑓 = (𝑟 − 1)(𝑐 − 1) (4.6)

51
When samples are small, the distributions of 𝜒+
(and other large-sample based statistics)
are not appropriately calculated by the chi-squared distribution; thus, the p-values for the
hypothesis tests are not to be trusted [53]. Also, if the expected frequency of any cell in
contingency table is smaller than five, the Fisher Exact Test is adopted [50]. Fisher Exact Test is
the test that is designed for the small data set. Table 4 presents the contingency table of the Fisher
Exact Test.
Equation 4.7 computes the p-value of the Fisher Exact Test:
𝑝 − 𝑣𝑎𝑙𝑢𝑒 =
(𝑎 + 𝑏)! (𝑐 + 𝑑)! (𝑎 + 𝑐)! (𝑏 + 𝑑)!
(𝑎 + 𝑏 + 𝑐 + 𝑑)! 𝑎! 𝑏! 𝑐! 𝑑!
(4.7)
The statistical analysis model for the data obtained from the survey to determine the factor
that affect the consumers’ willingness to participate in e-waste recycling is presented in Figure 2.
Table 4: Contingency Table of Fisher Exact Test
Second Criterion
Level
First Criterion Level
1 2
1 𝑎 𝑏 a+b
2 𝑐 𝑑 c+d
a+c b+d a+b+c+d

52
Figure 2: Statistical Analysis Model
4.3. Estimate the amount of e-waste that would be collected
The accurate estimation of current and future e-waste quantities is important information
necessary in order to design an e-waste collection system. The method to estimate the collected
amount of each type of e-waste is developed based on the consumption and use method that was
presented in the Ikhlayel’s [40] research, which is showed in equation 4.8:
𝑊𝐸𝐸𝐸(𝑡) =
𝑃(𝑡)𝑁𝑝(𝑡)𝑊
𝐿
(4.8)
Where WEEE(t) is the generated amount of e-waste per year, P(t) is the population at the
year t, Np(t) is the number of electronic products (e-product) owned by a person in the year t, W is

53
the average weight of each type of e-product, and L is the average lifespan (in years) of each type
of the e-product [40]. This method can be applied in both dynamic and saturated markets, and it
does not require the sale data as other estimation methods do such as the market supply method.
The only disadvantage of the consumption and use method developed by Ikhlayel [40] is
that it can only estimate the amount of e-waste “generated”, but it cannot estimate the amount of
e-waste that “would be collected.” “Would be collected” amount is the actual e-waste amount that
is brought to drop-off points/containers for collecting. “Generated” amount refers to the bigger
scope. “Generated” amount of e-waste can be e-waste that would be collected, e-waste that is left
in the storage, or e-waste that is thrown away as normal waste. The estimation of the e-waste
amount that would be collected can assist the recyclers to accurately determine the amount of
incoming e-waste stream. Therefore, the modified consumption and use method is remodified to
address its drawbacks. The variable L, the average life span of the e-products, is replaced with the
variable Lr(t), the average duration from the time when the electronic product was bought until it
would be collected. The new method is called the remodified consumption and use method. The
remodified consumption and use method is represented by equation 4.9:
𝑊𝐸𝐸𝐸(𝑡) =
𝑃(𝑡)𝑁𝑝(𝑡)𝑊
𝐿𝑟(𝑡)
(4.9)
Where WEEE(t) is the weight amount of each type of e-waste collected per year, P(t) is
the population at the year t, Np(t) is the number of electronic product (e-product) owned by a
person at the year t, W is the average weight of each type of e-product, and Lr(t) is the average
duration (in years) from the time when the electronic product was bought until it would be
collected. The current information of population, P(t), can be obtained from the Community

54
Research Institute statistics, and the average weight, W, of each type of electronic product are
recorded in Table 5.
Table 5: Average weight per piece of different electronic product types [48]
Electronic product types Average
Weight
(kg/piece)
[48]
PC/Laptop 5.015
Cell/mobile phone 0.09
TV/monitor 17.725
Large home appliances (Dish washer, kitchen equipment (oven, cooking equipment),
fridge, freezers, washing machine, dryer, large heating and cooling equipment)
48.01
Medium home appliances (microwave, household heating and ventilation equipment,
A/C)
20.58

55
Small electronic equipment (Radio, music instrument, audio set, video recorder,
speakers, household tools, vacuum cleaner, printer, leisure equipment, food
preparation equipment)
4.51
Other small electronic equipment (Cameras, portable audio and video devices, lamp,
household monitoring and control equipment, telecommunication, small IT equipment
(router, mice, keyboard, driver), small consumer electronic (headphone, remote
control), small household equipment (small ventilator, irons, clocks, adapter), personal
care equipment (hair dryer, razors), household medical equipment, toys, game
console)
0.36
Moreover, the number of e-products owned by a person, Np(t), and average duration from
the time when the electronic product was bought until it would be collected, Lr(t), can be obtained
from the survey questionnaires. Furthermore, the range of value for number of e-products owned
by a person, average duration from the time when the electronic product was bought until it would
be collected, and the estimated amount of e-waste can be calculated applying the confidence
interval for a population proportion. The confidence interval is basically obtained by the general
formula: estimator±(reliablity coefficient)×(standard error of the estimator) [50]. The intervals
for these values are computed using the equation 4.10:
𝑐𝑜𝑛𝑓𝑖𝑑𝑒𝑛𝑐𝑒 𝑖𝑛𝑡𝑒𝑟𝑣𝑎𝑙 𝑜𝑓 𝑝𝑟𝑜𝑝𝑜𝑡𝑖𝑜𝑛 = 𝑝 ± 𝑧e𝑝(1 − 𝑝)/𝑛 (4.10)

56
Where p is the estimated value of the variable, z is reliability coefficient which is equal to
1.96 on 95% confidence interval, and n is the sample size [50].
After that, the next step to improve the e-waste collection system is suggested based on the
factors that consumers’ willingness to participate in e-waste recycling and the estimated amount
of e-waste that would be collected.

57
5. Chapter 5: Case Study: E-waste Collection at Grand Valley State University
This thesis applies the proposed model in chapter 4 in the current situation at Grand Valley
State University by determining college personnel’s willingness to participate in e-waste recycling,
estimating the amount of e-waste that would be collected from this population, and suggesting the
next steps based on the consumers’ willingness and the estimated e-waste amount.
5.1. Current e-waste management in Grand Rapids and Grand Valley State University
community
In Grand Rapids, there are many companies and organizations that have been collecting
and processing e-waste from household and residential drop-offs. These companies and
organizations accept televisions, monitors, mobile phones, computers, laptops, home appliances,
and many other electronic devices which are specified in their websites. Below is an incomplete
list of options that people in Grand Rapids as well as Grand Valley State University community
can bring their e-waste to recycle [54]. Although this list does not contain the complete available
options, it still provides substantial amount of options for Grand Rapids and Grand Valley State
University community. List of options that people can bring their e-waste to:
a. Recyclers: They collect e-waste from consumers. After that, they dismantle e-waste, resell the
valuable parts, and smelt, refine, and recover materials to gain profit.
• Padnos Recycling and Scrap Management
o Address: 2125 Turner Ave. NW, Grand Rapids, MI 49544
o 719 Burton St SW, Grand Rapids, MI 49503

58
o 500 44th
St. SW Grand Rapids, MI 49548
o Phone number: 800-442-3509
o E-wastes that are accepted: Computers, circuit boards, phones, hard drive,
computers hardware, printers, tablets, audio and video equipment, consumer
electronics, cartridges, batteries, gaming system [60].
o Link that includes the detailed list of what is or is not accepted at Padnos Recycling
and Scrap Management: https://padnos.com/sell-your-scrap/sell-electronics/
• Kent County Recycling and Education Center
o Address: 977 Wealthy St SW, Grand Rapids, MI 49504
o E-wastes that are accepted: consumers electronics except Cathode Ray Tube
monitors and televisions [54].
• Valley City Electronic Recycling
o Address: 2929 32nd
St SE, Kentwood, MI 49512 Dock 5-8
o E-waste that are accepted: Computer systems/Accessories, medical equipment,
telecom equipment, audio/video equipment, phones, handheld devices, and office
equipment [62].
o Links that includes the detailed list of what is or is not accepted at Valley City
Electronic Recycling: http://www.valleycityer.com/equipment-accepted

59
b. Donation Centers: They accept old and unwanted electronics from consumers. They use profit
from reselling, refurbishing, and recycling these products to create jobs and educate other
people who need help [12].
• Cascade Engineering
o Address: 5175 36th
St SE, Grand Rapids, MI 49512
o E-wastes that are accepted: cell phones, printer cartridges, sport equipment [54].
• Goodwill Retail and Donation Centers
o Address: 1655 4 Mile Rd NE, Grand Rapids, MI 49525
o 2345 E Beltline Ave NE, Grand Rapids, MI 49525
o 956 Michigan St NE, Grand Rapids, MI 49503
o 4696 Lake Michigan Dr NW, Grand Rapids, MI 49534
o E-wastes that are accepted: computers, laptops, cameras, televisions, monitors,
cameras, small appliances, audio devices, video devices [57]
o Link that includes the detailed list of what is or is not accepted at Goodwill:
https://www.goodwillgr.org/accepted-items-2/
• In the Image
o Address:1823 S. Division Ave, Grand Rapids, MI 49507
o E-wastes that are accepted: large appliances, small appliances, televisions [58].

60
o Link that includes the detailed list of what is or is not accepted at In the Image:
https://www.intheimage.org/items-we-accept
c. Retailers: They have their own e-waste take back policy, in which their customers can bring
end of use and unwanted consumer e-products, which were not necessary purchased at these
retailers, for recycling.
• Best Buy Grand Rapids
o Address: 3410 Alpine Ave NW, Grand Rapids, MI 49544
o E-wastes that are accepted: TV and video, computers and tablets, cell phone and
radios, appliance, ink and toner, audio devices, video devices, video games and
gadgets, cameras and camcorders, and car devices [55].
o Link that includes the detailed list of what is or is not accepted at Best Buy:
https://www.bestbuy.com/site/services/recycling/pcmcat149900050025.c?id=pcm
cat149900050025
• Office Depot OfficeMax
o Address: 675 Center Dr, Walker, MI 49544
o 962 28th
St SW, Wyoming, MI 49509
o E-wastes that are accepted: cell phones, tablets, ipods, desktops, and laptops [59]
o Link that will determine the trade-in price for your e-waste:
https://techtradeup.officedepot.com/
• Staples

61
o Address: 5110 28th
St SE, Grand Rapids, MI 49512
o E-waste that are accepted: rechargeable batteries, ink cartridges, office and
consumer electronics such as: Adapters, computers, calculators, audio and video
equipment, phones, flash drives, gaming devices, monitors, tablets, printers,
telecom equipment [61].
o Links that includes the detailed list of what is or is not accepted at Staples:
https://www.staples.com/sbd/cre/marketing/sustainability-center/recycling-
services/?icid=SustProducts:topnav:3:RECYCLE:
d. Non-profit e-waste recyclers:
• Comprenew
o Address: 629 Ionia Ave SW, Grand Rapids, MI 49503
o E-wastes that are accepted: home appliances, computers, laptop, satellite,
televisions, monitors, telecom equipment, tablets, cameras, servers, printers [56].
o Link that includes the detailed list of what is accepted and recycling fee at
Comprenew: https://comprenew.org/wp-content/uploads/2016/01/electronics-
recycling-handout-rev-2.pdf
Padnos, one of the largest recycling companies in Michigan, provided me a great
opportunity to discuss about the current household e-waste collection situation and the flow of e-
waste after collection. According to Padnos, the company has a network of recycling centers from
Traverse City to Lansing, and further down to Dowagiac, Michigan. The company has many

62
locations where the general public can bring in their scrap materials for recycling. However, the
number of people who brought e-waste to Padnos for recycling was not significant. According to
the company, one possible reason is the fact that many consumers do not have much awareness on
the harmful effect of improperly processed e-waste on the environment and human health. Another
reason is that the consumers do not know where they can bring their e-waste to recycle, so they
store their end-of-life electronic products. The company has taken back e-waste from individual
consumers who bring e-waste to the company’s recycling center. Some items are bought back
directly by weight, but some items are taken back at no money value. In addition, Padnos also
holds some events throughout the year in churches and schools to collect e-waste. The collected
e-waste is then sorted at Padnos’s facility. Some of them which have resale value are refurbished
and then re-sold to consumers through a variety of outlets. On the other hand, the remaining items
are disassembled into base components. These parts/components are commoditized by their
values. For the parts/components that cannot be commoditized, they are sent to Padnos’s shredding
facility for additional separation until they cannot be processed any further.
As noticed earlier, there are two populations that can be studied at Grand Valley State
University. The university as an institution generates e-waste and Facility Service is in charge of
dealing with the e-waste that comes primarily from IT department. The Facilities Service collects
e-waste from the Information Technology (IT) department at different times throughout the year.
According to the IT department, they collect e-waste from faculty members’ and staff members’
offices and not their homes. They also collect old computers, TVs, and equipment from the
computer labs and other locations that the IT department is replacing.

63
Institutionally, in the IT department, if old e-products can be reused or refurbished, they
are resold at Grand Valley State University Surplus Store. The Surplus Store which was used to
locate in Grand Valley State University’s downtown campus, now located at 429 Standale Plaza
NW, Walker, Michigan 49534. On the other hand, e-waste that cannot be resold is stored in a large
cardboard container which is given to the IT department by Facilities Service. When the cardboard
container is full, people at the IT department call Padnos Recycling and Scrap Management to pick
up this container to the company’s processing facility. According to the IT department, the e-waste
that needs to be shredded is picked up and processed by Rapid Shred LLC, which is located at
2972 Sangra Ave SW, Grandvile, Michigan 49418. Some examples of e-wastes that need to be
shredded include hard drives which aren’t wiped, and Grand Valley State University issued cell
phones that cannot be reused.
5.2. Methodology
5.2.2. Questionnaire Design and Data Collection
The consumers’ willingness to take part in e-waste recycling was determined by the data
from survey questionnaires that were spread out to students, faculty members, and staff members.
The survey questionnaire is attached in Appendix A. In the beginning of the questionnaire survey,
the consent form was attached. In the consent form, the title of the study, study purpose,
procedures, and potential risks and benefits were clearly stated. In addition, the importance of the
authenticity of the answers and the voluntary participation to the survey were emphasized to
minimize the uncertainty of the study. There was also a note to assure that the personal information

64
of respondents was protected and confidential. The agreement to participate was also included as
well as the contact information of the researchers.
As specified in section 4.2, the survey included eight parts: (1) Demographic information,
(2) residential condition, (3) consumers’ awareness, (4) recycling habits, (5) convenience of
recycling service, (6) economic benefit, (7) type of e-waste, and (8) consumers’ willingness and
behavior to engage in e-waste collection and recycling. Moreover, the questionnaire also asked for
the number of each type of e-products that the respondent currently owned and the average
duration from the time when the respondents bought an e-product to when they brought it to
recycle. These questions provided the necessary information to calculate the estimated amount of
e-waste that would be collected in 2019 from students, faculty members, and staff members at
Grand Valley State University.
Before distributing the survey, the sample size of the study was calculated according to
equation 4.1 and equation 4.2 in section 4.2.
𝑆𝑆 = (𝑍𝑠𝑐𝑜𝑟𝑒)+
× 𝑝 ×
1 − 𝑝
(𝑚𝑎𝑟𝑔𝑖𝑛 𝑜𝑓 𝑒𝑟𝑟𝑜𝑟)+
(4.1)
𝑆𝑆𝑎𝑑𝑗𝑢𝑠𝑡𝑒𝑑 =
𝑆𝑆
1 + [
𝑆𝑆 − 1
𝑝𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛]
(4.2)
In this thesis, the Zscore was chosen as 1.96 for 95% confidence level, and the margin of
error was chosen as 5% for 95% confidence level. The standard deviation, p, was chosen as 0.5 to
ensure a large sample. Also, the population is the total number of students, faculty members, and
staff members at Grand Valley State University. According to the university’s website, there are

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