The Illegal Trade of Electronic and Electrical Waste: Should WEEE Pay to Avoid the Environmental and Public Health Costs? The Case of the United Kingdom
e Journal of International Relations
Public Kingdo m
Studies 0 1
Development 0 1
Abderrahim Assab 0 1
Alexandra Imirziadis 0 1
Electrical Waste: Should WEEE Pay to Avoid the Environmental and Public Health Costs? The Case of the United Kingdom," Th e
0 Assab , Abderrahim; Imirziadis, Alexandra; Heintzman, Laura; and Rahardjo, Astrid (2017) "The Illegal Trade of Electronic
1 The Journal of International Relations, Peace and Development Studies A publication by Arcadia University and the American Graduate School in Paris
Avoid the T he
Environ m ental and
Arcadia University has made this article openly available. Please share how this access benefits you.
Your story matters. Thank you.
Follow this and additional works at: http://scholarworks.arcadia.edu/agsjournal Recommended Citation
The Illegal Trade of Electronic and Electrical Waste:
Should WEEE Pay to Avoid the Environmental and Public Health Costs?
The Case of the United Kingdom
The present article as has been adapted from a paper written under the supervision of Dr. Ionnis
Kountouris of the Centre for Environmental Policy at Imperial College London, from March 20, 2016,
with the permission of all authors.1
The electrical and electronic waste generated by consumers in developed economies is often illegally
exported to countries such as India, Ghana, or Nigeria, where it is inadequately treated in ways that
harm local populations. A number of developed economies have constituted legislation to address
current increases in electronic waste. The European Union and the United Kingdom (UK) have, for
example, adopted the Waste Electrical and Electronic Equipment (WEEE) Directive. Despite this
Directive, there are still significant environmental and health impacts experienced in the
aforementioned recipient countries. Different approaches to address this problem are apparent; though,
each approach comes with significant financial costs that are linked to investments in facilities, such
as recycling infrastructure. The authors of this article aim to add to the understanding of the problem
and to enhance the literature by seeking answers to two key questions: (1) Are consumers of electronic
goods willing to bear the costs of proper disposal? and (2) To what extent does information influence
electronic goods consumers’ willingness to pay (WTP)? Using the contingent valuation method
(CVM), the authors developed four hypothetical market scenarios outlining different strategies to
tackle the electronic waste treatment problem. These scenarios were then tested on a representative
sample of the UK population. The findings of this study show a decrease in median WTP after
information was provided in each treatment. In addition, the results from the regression analysis
suggest a positive correlation between information and WTP for scenarios where the proceeds of the
electronic waste tax are used in a way that is personally relevant to the consumer.
1 For all questions, including requesting a copy of the survey, please contact Abderrahim Assab at and Alexandra
Imirziadis at .
101, boulevard Raspail, 75006 Paris – France Tel: +33(0)1 47 20 00 94 – Fax: +33 (0)1 47 20 81 89 Website: www.ags.edu (Please cite this paper as the
following: Abderrahim Assab, Alexandra Imirziadis, Laura Heintzman, Astrid Rahardjo (2017). The Illegal Trade of Electronic and Electrical Waste:
Should WEEE Pay to Avoid the Environmental and Public Health Costs? The Case of the United Kingdom. The Journal of International Relations,
Peace and Development Studies. Volume 3. Available from: Link TBD)
Negative Externalities from Electrical and Electronic Equipment Waste Treatment
Electrical and electronic waste is one of the fastest growing sources of waste streams in the European
(European Commission 2015)
, as well as a pollution externality of Information Technologies
(IT) industries (Baldé et al. 2015)2. Electrical and electronic equipment is generally comprised of
components with high economic value that can be recovered and recycled (Ongondo, Williams, and
Cherrett 2011). However, increasing demands for electrical and electronic equipment—due to
worldwide population growth, higher levels of income, higher standards of living, and more
widespread access to technology
(Osslbanjo and Nnorom 2007)
—coupled with persistent waste
management problems, suggest that greater attention should be paid to such waste and its disposal.
In many cases, electrical and electronic waste is sent abroad to countries with less developed
economies and used by the informal recycling sector (The Basel Action Network 2005). These cases
trigger concern over environmental (Robinson 2009) and public health impacts (Perkins et al. 2014)
caused by the hazardous materials contained within these types of equipment. Lack of coherence,
ineffective enforcement strategy, as well as weak top-down approaches are regulatory issues that are
identified as exacerbating the problems associated with electrical and electronic waste disposal
(Widmer et al. 2005).
The aim of this article is to examine the effect of information on individuals’ willingness to pay
(WTP) for different electronic waste management strategies. We seek to add to the understanding of
the problem of electrical and electronic waste disposal and to enhance the literature by seeking
answers to two key questions: (1) Are consumers of electronic goods willing to bear the costs of
proper disposal? and (2) To what extent does information influence electronic goods consumers’
willingness to pay (WTP)? In order to determine the effect of information on WTP for electrical and
electronic waste management, we present a study where the United Kingdom (UK) is the treated case
and the null hypothesis is as follows: information has no effect on respondents’ WTP.
In the remainder of Section I, we introduce important background to the electrical and electronic waste
problem and areas of research that suggest paths to better addressing the associated challenges. In
Section II, we provide our research methods. In Section III, we present the results of our econometric
analysis. In Section IV, we describe the limitations of the study and areas for further research. In
Section V, we provide concluding remarks and recommendations.
Electrical and Electronic Equipment Waste: A Fast Growing Waste Stream with High
Economic Value, Limited Oversight, and Significant Risks
Electrical and electronic equipment waste, which includes computers, televisions, mobile phones and
refrigerators, is expected to reach 12 million tonnes in the European Union by 2020
. This waste stream contains components and materials that have economic value
(such as copper and the platinum group) when recycled (Basel Action Network 2005). However, what
differentiates electrical and electronic waste from other waste is that the majority of the components
and materials in the former contain hazardous materials (such as lead, PCBs, PBDE) that cause
adverse effects to the environment and public health (Perkins et al. 2014). Furthermore, most electrical
and electronic waste is disposed of in landfills, as effective reprocessing technologies that recover the
2 Please note that at the time of the two publications cited here, the United Kingdom was part of the European Union.
valuable materials with minimal environmental impact are usually expensive (Robinson 2009). This
lack of cost-effective and environmentally responsible reprocessing options poses a problem as it
creates negative environmental impacts not only to surrounding soil, but also to water sources and the
atmosphere when toxic materials are leaked during the burning process (Baldé et al. 2015).
Furthermore, as much of the electrical and electronic waste generated by consumers in developed
economies is illegally exported to countries such as India, Ghana, or Nigeria, where it is treated in way
that harms local populations, (J. Li et al. 2013) questions of global environmental responsibility and
Legislative Attempts to Limit the Illegal International Trade of Electrical and Electronic
The European Union has enacted legislation to address current increases in electronic waste, including
the Waste Electrical and Electronic Equipment (WEEE) and the Restriction of Hazardous Substances
(RoHS) directives. These directives aim to alleviate negative environmental impacts of electrical and
electronic waste management processes (Baird, Curry, and Cruz 2014) and largely place the
responsibility on manufacturers to cover the recycling costs of products they sell. In addition, the
Basel Convention, which restricts the trans-boundary movement of hazardous wastes, including
electronic waste between developed and developing economies, has been signed by the members of
the European Union and UK as well as most developing economies.
Diverging national legislations, however, create gaps in the electrical and electronic management
system. Namely, there is weak or non-existent national enforcement in many developing economies
regarding electrical and electronic waste importation and imports. Taking the case of the UK,
recycling facilities face serious logistical problems with the management of electrical and electronic
waste, especially as there is insufficient storage space to hold waste before it goes into treatment
(Altvater and Brandmann 2012). Such bottlenecks create an incentive for these recycling facilities to
dispose of waste at cheaper prices by exporting to regions where environmental legislation is not as
In addition, donations of used and functioning electrical and electronic goods flowing from the UK
and other developed economies to developing economies is a standard practice. The original aim of
such transfers was to assist in the growth of technology markets. However, with the incentive for
waste facilities to cut costs, the donation system has become corrupt and recycling plants are exporting
obsolete electrical and electronic products (Perkins et al. 2014). This sub-optimal transfer of goods is
further encouraged by recipient countries, where there is a high demand for inexpensive secondary
products, given their potential to be a major source of income for poor, unemployed and low-skilled
persons (Nnorom, Ohakwe, and Osibanjo 2008).
However, as these donated products cannot be sold on the second-hand electrical and electronic
markets and recipient countries lack adequate infrastructure to manage electronic waste safely, the
population who demands these products engage in crude recycling methods to extract valuable
materials. These practices can be attributed to general low environmental awareness of the population
engaging in these activities who must prioritize the meeting of basic needs
(Nnorom, Ohakwe and
. The crude recycling is done in the form of open burning and dissolution in strong
acids, which releases dangerous environmental contaminants. With few measures to protect human
health and the environment, such methods result in extreme localized contamination and migration of
contamination into waters, soil and food chains (Nnorom, Ohakwe and, Osibanjo 2008). Electrical and
electronic waste workers in these conditions suffer major negative health effects through skin contact
and inhalation, although the long-term health effects are still unknown (Robinson 2009).
As new legislation attempts to institutionalize higher environmental standards for electrical and
electronic treatment, costs of waste treatment increase, making illegal operations more attractive.
Effective waste management in the UK and electrical and electronic waste recipient nations can
facilitate returns of valuable resources into the economic product cycle, and also improve the health
and environment created by unsafe waste management. However, to assist in a transition to this
outcome, funding is required (Ongondo, Williams, and Cherret 2012), and, in a highly competitive
electronic market, producers are reluctant to increase what is included in their costs in order to
maintain lower standard prices. The incentive for contractors to undercut legal and safe waste
processing operators is strong, as they can achieve savings of 200-300% with the exportation of
electronic waste (Ongondo, Williams, and Cherret 2012) and producers are not shying away with their
demand. Furthermore, waste producers are also not directly involved in the services provided by their
waste contractors, which contributes to a lack of awareness and weak potential for prevention.
The UK recycling facilities are not sufficient to meet the demands of increasing electrical and
electronic waste and this has resulted in illegal waste management of these materials, and the threat of
environmental and health damages. As present legislation has not alleviated these issues, and costs to
producers and manufacturers remain a major barrier, a complementary market-based mechanism is
necessary to allocate these costs in an optimal way. Following the “polluter pays principle”, the costs
of electrical and electronic waste could be transferred to the end-users of the products and internalized
within the product's life cycle. For these reasons, we chose the UK as a case study to begin exploring
the question of WTP for different electronic waste management strategies.
Changing Behaviours and Transitioning to a Circular Economy
Market-based instruments, such as pollution taxes and subsidies, are often used to address the problem
of so-called market failure and are deemed efficient due to their ability to incentivize reductions in
emissions to a predetermined level at minimum abatement costs (Norregaard and Reppelin-Hill 2000).
An electrical and electronic waste tax is one example of a market-based instrument used to address
market failures within the electronic industry, whereby a fee is imposed by the government on new
purchases of electronic products.
Several countries have already successfully implemented taxes on consumers’ purchase of electronic
products; specifically, countries such as Japan (Chung and Murakami-Suzuki 2008) and Ireland
(Davies 2007). Furthermore, waste taxes have been reported to measurably affect consumers' waste
disposal behaviour, (see, for example, Benoit 2004 for a study on solid waste taxes in Vermont). Such
a tax can be used to pay for future recycling and recovery of electrical and electronic waste, as well as
for funding infrastructure needed to transition to a circular economy. The circular economy, a concept
which has gained significant attention in environmental and mainstream economic literature, can be
described as an economy that “preserves and enhances natural capital, optimises resource yields and
minimises systems risks by managing finite stocks and renewable flows.” (EllenMacArthur
Foundation 2017). The concept is relevant for the present study insofar as it focuses on the
optimization of resource yields, which is also the underlying assumption and objective of the trade of
electrical and electronical waste. This aspect of the concept means that circulating products, including
electrical and electronical, must be designed in order to be remanufactured, refurbished, recycled in
order to “keep components and materials circulating in and contributing to the economy”
(EllenMacArthur Foundation 2017). Building up the appropriate infrastructure, for collection and
recycling for example, is a prerequisite to the mainstreaming of the circular economy. This concept
associates the recycling of electrical and electronic waste with a larger paradigm shift. By introducing
information about the circular economy, the present study aims at assessing UK end-users WTP for an
approach that intends to address the resource optimization issue in a holistic way.
Behavioural Economics, Altruism, and the Willingness to Pay
Orthodox economic theory holds that the consumer is a rational, self-interested agent looking to
maximize their preference-satisfaction (utility), and is consistent in their choices. Most policy designs
from economists are based on this model of human behaviour
(Henrich et al. 2001)
. In contrast,
behavioural economics addresses the limitations of neoclassical economics in determining underlying
motives of human behaviour. This alternative, which has gained a resurgence of attention in recent
years, takes into account the social, cognitive, psychological and emotional factors that influence
economic decision-making, such as altruism (Samson 2014).
Altruism broadly refers to actions motivated solely based on the utility and benefit of others, without
receiving any personal utility from the action. Within the theory of altruism in behavioural
economics, it is believed that the individual will get their preferences satisfied by consuming the ‘good
feeling’ that giving to charity provides (Simon 1993). The value given by the natural environment or
the well-being of others, are perceived as separate from the individual. Simply put, the individual
gains, but not on the basis of monetary value
. In contrast, others such as
White and Peloza (2007) conclude that altruistic behavior may be driven by the benefit to the self that
is related to public self-image, rather than a motivation to help others benefit.
Previous studies have found that altruism influences responses in stated preference studies on values
that are external to the person, such as the environment
(Madariaga and McConnell 1987)
Accordingly, the purchasing of pro-environmental products is perceived as altruistic, however as such
products cost more than conventional substitutes, their purchase is seen as an increased willingness to
pay for others' benefit
(Grsikevicius, Tyber, and Van den Bergh 2010)
Values attributed to goods have also been found to increase under conditions of higher personal
relevance; while, under conditions of lower personal relevance, the values are high when altruistic
motives were introduced. The nature of the information provided in the contingent market, however,
can have strong effects on WTP estimates, creating biased estimates, particularly in conditions of low
personal relevance (Ajzen, Brown, and Rosenthal 1996).
In 2017, the OECD reviewed policy interventions that try to tackle environmental problems using
behavioural insights. Among the areas explored, the review looks at the behavioural interventions
implemented to improve waste management and resource efficiency policies. The policy interventions
targeted a specific set of behavioural biases that affect individual choices relative to “waste
generation, sorting and recycling, as well as product reuse” (OECD, 2017). The policy interventions
reviewed have mainly relied on “the framing and simplification of information” (labelling) and “the
changes to the physical environment” (signs describing the correct disposal) when dealing with
resource efficiency and waste management. The following section takes a closer look at information’s
effect on consumer behaviour, in particular when it comes to the sustainable consumption of electrical
and electronic goods.
Information Effects on Consumer Behaviour
Increased information and understanding of a particular cause for donation, such as through the use of
imagery or scenario, has shown to have an increasingly positive effect on an actor’s desire to support
(Hung and Wyer 2009)
. In addition to information facilitating increased awareness, the
method used to disclose the information also influences the valuation processes of non-market goods;
as shown by Tkac (1998) in his study treating endangered species.
Several psychological studies have also shown that information available to an individual can
influence not only their valuation processes, but also their attitude toward a particular contested issue
(Lange et al. 2002; Gao and Schroeder 2009; Napolitano et al. 2010)
. Similarly, according to Bateman
and Mawby (2004), additional information about the less familiar non-use aspects of an environmental
good can result in an increase in the stated value of the good. This additional information can be, for
example, about environmental resource quality.
Cameron and Englin (1997) show that information can influence contingent valuation estimates for
environmental goods. They demonstrate that respondents’ familiarity, experience, and information
about the environmental good affect the valuation of the environmental good. In their study,
individuals start the valuation process in contingent valuations without a clear prior idea of their WTP
Beyond the valuation aspect, information can directly affect consumers behaviour. One of the most
relevant behavioural biases influencing consumer decisions is status-quo bias, which refers to the
consumer tendency to select default or standard options. A study by Steffansdotter et al. (2016),
commissioned by the Nordic Council3, explored the use of behavioural techniques to incentivize a
“sustainable consumption of electronic good”. Sustainable consumption refers here to the choice of
reuse, recycling or the purchase of long-living models.
The Steffansdotter et al. (2016) recognises that consumer behavioural might depend on demographic
factors as well as the specific electrical and electronic good. The study therefore focuses on mobile
phone consumers aged between 19 and 28 and living in Nordic countries. It surveyed Danish
electronics shop consumers that initially intended to replace broken phones and was based on two
stated choice experiments that both changed the default option. The first presenting consumers with
the possibility of repairing their phone, or buying a used phone, as opposed the buying a new one. The
results showed that 87 percent of respondents would opt for the repair option if it was available in the
store (20 percentage points more than in the baseline scenario). The second choice experiment
attempted to encourage users to choose to lease their mobile, instead of buying a new one, through
introducing a third “clearly undesirable option (a more expensive leasing option)”. As a result, 62
percent of the consumers chose to lease their phones, 24 percentage points above the baseline
scenario. All these results were statistically significant and indicated that young consumers would
consider sustainable consumption options when it comes to mobile phones.
When it comes to the sustainable consumption of electronic goods another possible choice is to select
long-living products. A study by the European Economic and Social Committee (2016) assessed,
through a stated choice experiment, the extent to which consumer choices would be affected by
lifespan labelling – the study highlighted the information asymmetry between consumer and producers
regarding products’ lifespan. The study presented the consumers with four different visual displays for
nine categories of products in four different geographies. It showed that lifespan encourages the
purchasing of long-living products.
The above research indicates that the respondents’ preference is constructed during the valuation
process. Information plays a particularly relevant role in this process for non-use characteristics of
environmental goods, as well as any aspect with which the respondents are not familiar or have limited
In the context of electronic and electrical waste, information has also proven to be influential in
steering consumers toward sustainable behavioural. The question is whether or not it is going to have
the same effect on consumers’ willingness to pay for solutions that address the electrical and
electronical waste issue. It is important to distinguish the role of information in reducing behavioural
bias in the behavioural insight-based policies mentioned above, and its impact on willingness to pay.
II. Research Methods
Experimental Survey and Design
For our study, we use an online survey (generated and powered by Qualtrics) to gather data. We
distributed the survey to respondents via a third party panel company. The aim was to get 500
responses, a representative UK-wide sample. The survey includes introductory questions eliciting
gender, age, employment status and environmental awareness. The question regarding employment
status is used as a proxy for income, as consumers are more inclined to disclose their employment
status rather than level of income. Debriefing questions are included in the final section of the survey
to ascertain the reasoning for given responses and gain access to opinions on the scenarios provided.
The debriefing questions and environmental awareness questions employ a 5-point Likert scale, with
response options ranging from “strongly disagree” to “strongly agree.”
Four different information treatments were designed (Figure 1). The first treatment is a baseline
treatment, with limited information on electrical and electronic waste. The second treatment informs
respondents that the tax would contribute to improving UK recycling facilities to become more
efficient. The third treatment informs respondents about illegal exportation of electrical and electronic
waste that is causing environmental and health damages abroad, and communicates to respondents that
the waste tax would contribute to alleviating such damage. Finally, the fourth treatment describes the
concept of a circular economy and explains that the waste tax would contribute to initial investments
in such an economy.
Contingent Valuation Method (CVM)
Qualitative data was collected using the contingent valuation method (CVM) by conducting a survey.
A payment card was given to respondents in order to elicit their WTP for different electronic waste
management scenarios. This method was chosen to obtain the WTP for a non-market good, using a
waste tax as a payment vehicle. Therefore, hypothetical markets had to be created with the
descriptions outlined below. As in most contingent valuation studies, respondents often have little, if
any, prior experience with the proposed good or service (Ajzen, Brown, and Rosenthal 1996).
Four different survey questionnaires were used, each outlining a hypothetical market, as indicated in
the table below.
Table 1 - Hypothetical Markets Used for the Different Survey questionnaires
Questionnaire Hypothetical Market Description
1) Baseline; “…a significant proportion of the electronic waste generated in the
Limited Information UK is exported abroad for reuse and recycling. The UK government is
designing an electronic waste management policy to improve the
country’s facilities for properly recycling electronic waste. As a
result, laptop manufacturers will be required to add the associated
costs to the price of their products, in the form of a waste tax.
The implementation of this new waste tax will raise the price of your
next laptop purchase.”
2) Information on “The UK government is designing an electronic waste management
UK Recycling policy to improve recycling facilities in the developing countries that
Inefficiencies import used laptops and electronic waste. As a result, laptop
manufacturers will be required to add the associated costs to the price
of their products, in the form of a waste tax. This waste tax will
contribute to improving electronic waste recycling facilities in
recipient nations, and therefore improving human and environmental
health of those managing the waste.”
3) Information on “The UK government is designing an electronic waste management
Illegal Electrical policy to improve the country’s facilities for properly recycling
and Electronic electronic waste. As a result, laptop manufacturers will be required to
Waste Export add the associated costs to the price of their products, in the form of a
waste tax. This waste tax will contribute to improving facilities and
expanding space to meet the increased demand of electronic waste
4) Information on “The UK government is designing an electronic waste management
Circular Economy policy to improve the country’s recycling facilities, with the goal of
Investment transitioning to a circular economy. As a result, laptop manufacturers
will be required to add the associated costs to the price of their
products, in the form of a waste tax. The waste tax will fund the
infrastructure for the circular economy described above.”
In order to elicit the respondents’ WTP, a payment card method was used for each treatment. Payment
cards generate fewer outliers than open-ended questions (Bateman and Mawby 2002), but have
limitations, such as starting point bias, due to the amounts provided on the cards. The design of the
payment card is as follows: The survey respondents are asked to state the maximum value that they are
not willing to pay for the waste tax, as well as the minimum value that they are willing to pay.
The values used on the payment card were chosen using the following rationale. According to
CalRecycle (2015), the average cost of recycling a laptop is US$4 (hereafter $), and using the currency
converter XE (2016) to account for income adjustment in the UK, the average estimated cost of
recycling a laptop in the UK would be GB£2.77 (hereafter £) . This figure is used as a lower end value
in the payment card, stated as £3. In an article by
, electrical goods companies in the
US charge a fee of $25 to recycle used electronic goods, such as TVs and laptops. We again used the
currency converter XE (2016) to adjust the figure for the UK, finding that UK consumers would have
to pay a £17.35 recycling fee to recycle their laptops. This latter value was used as the higher end
value on the payment card rounded up to £20. Thus, the range of numbers on the payment card
includes the following values: £0, £3, £8, £14, £20.
The £0 value was included in order to single out the protest responses, and we included a section to
allow respondents to state why they selected £0. According to Ryan and Watson (2009), it is important
to identify protest responses and remove them from the analysis. In addition, a section was added in
each scenario asking respondents who selected £20 if they are willing to pay more than £20, and if so,
the total amount.
Estimating Willingness-to-Pay and Information Effects
To obtain our willingness-to-pay (WTP) value, we used the median WTP values from the payment
cards. Furthermore, in order to test the significance of the effects of information on WTP, we used the
WTP = F(Age, Gender, Employment Status, Laptops, Environmental Awareness Indicator,
We also used the following additional function to assess the impacts of the independent variables
(socio-economic characteristics) for each of the treatment effects:
WTP = F(Age, Gender, Employment Status, Laptops, Environmental Awareness Indicator) .
Environmental Awareness Indicator
The environmental awareness indicator was constructed to capture respondents’ attitudes toward the
environment and awareness of electronic waste management strategies. It is also used to analyse data
to understand the variable’s effects on WTP. The indicator was developed utilising the individuals’
responses that indicated the extent to which they agree with pro-environmental statements and
environmental behaviour, as well as their responses to questions on overall environmental awareness.
For the environmental awareness questions, respondents indicated the extent to which they agreed
with six statements. A Likert scale, ranging from one to five, was used to capture individual attitudes
toward general environmental concerns. In addition, the respondents answered two questions assessing
their knowledge of the end-of-life processes of their laptops.
To derive the environmental awareness indicator, each question in the environmental awareness
section was reflected through a function. The function is as follows:
En = (∑k (ank – a*))/K + An + Bn
where n is the environmental awareness indicator for the n-th respondent, ank represents the number
associated with the n-th individual response to the k statement, a* is the midpoint of each Likert scale,
and K is the total number of statements. An and Bn represent the two additional questions on
respondents' knowledge of laptops’ end-of-life.
Figure 2 indicates the environmental awareness results of the respondents.
Semi-structured interviews were carried out as a diagnostic tool to add more information and depth to
how the responsibility of the consumer is perceived. We mapped out experts’ responses regarding the
electrical and electronic waste management industry in the UK. These included:
• Extended Producer Responsibility (EPR) and WEEE Experts
• WEEE Regulation Authorities
• WEEE Professional Association
In a semi-structured interview, the interviewer develops and uses a list of questions and topics, but is
able to stray from the guide when he or she feels appropriate (Cohen and Crabtree 2006). Most of the
questions asked are open-ended, such as: “How does the WEEE management being carried out in the
UK?” or “Why isn't e-waste in the UK segregated within the household level?” Open-ended questions
are used, rather than close-ended questions, to get lengthy and descriptive answers.
Prompts are also used within the interview to encourage people to expand on topics of interest and to
probe more information when the responses are unclear. The prompts are not scripted because every
interview is different and the list of possible probes is unlimited
. Examples of the
prompts include reassuring noises and interjections that people make during any conversation to show
that they are listening and interested, as well as repeating the key term of the respondent's last remark
as a question.
The interviews were used to inform the contingent valuation study, and to support and analyze the
III. Results: The Effect of Information on the Willingness to Finance Electrical and Electronic
Equipment Waste Management Strategies at Home in the UK and in Recipient Countries
Information Effects on Willingness-to-Pay
Figure 7 shows that the median WTP varied between information treatments. For treatments 1, 2 and
3, the median WTP decreased once the information for each treatment was given. For treatment 4,
there was no change in the stated WTP.
Regressions and Willingness-To-Pay Results
Two econometric models were used to test the significance of the results. The first model,
“Determinants for Each Scenario” section, assessed the relationship between the socio-economic
characteristics and environmental awareness on WTP for each treatment, and the second model,
”Determining Information Effects” section, assessed the relationship between information and WTP
for the entire data set. The independent variables were both continuous and categorical. The
categorical variables included age, gender, employment status and environmental awareness; where a
number was assigned to each category. The only continuous variable in our analysis was number of
laptops. The dependent variable used was median WTP. The regressions were run using the data
analysis and statistical software Stata.
Determinants for Each Scenario
For each treatment, the following linear regression equation was used to observe and test the
significance of the socio-economic characteristics and environmental awareness on WTP:
Y = α + β1χ1 + β2χ2 + β3χ3 + .... + βixi
WTPTreatment = α + β1Age + β2Gender + β3Job + β4Laptops + β5Awareness
In Treatment 1 (baseline with limited information), there was one statistically significant coefficient,
which was employment status, more specifically category 4, where P>|t| = 0.017 [<p = 0.05]. Category
4 was the number assigned to respondents in full-time employment. This indicated that there is a
positive correlation between respondents in full-time employment and WTP. In addition, the result
indicates that a one unit increase in full-time employment, results in a 2.56 unit increase in WTP. This
is derived from the coefficient value.
Regarding Treatment 2, the statistically significant coefficient is gender, category 1 (females), where
P>|t| = 0.004 [<p = 0.05]. Indicating a positive correlation between respondent’s being female and
WTP. Moreover, the results suggest that with one unit increase in females would result in positive
3.36 unit increase in WTP.
Interestingly in Treatment 3, the statistically significant coefficient, was employment status category
2, which were students; where P>|t| = 0.036 [<p = 0.05]. This implies a positive correlation between
students and WTP; and that with one unit increase in students, there is a positive 6.23 unit increase in
In Treatment 4, the coefficient which is statistically significant is the number of laptops per
household, where P>|t| = 0.002 [< p = 0.05]. The results indicate that there is a positive correlation
between number of laptops per household and WTP. Furthermore, one unit increase in the number of
laptops per household will positively impact WTP for the circular economy by 1.58 units.
Determining Information Effects
To further assess the impacts of information on willingness to pay, the information treatments were
added to the following linear regression equation:
Y = α + β1χ1 + β2χ2 + β3χ3 + .... + βixi
WTPTotal = α + β1Age + β2Gender + β3Job + β4Laptops + β5Awareness + β6Information.
The results are depicted in Table 1. The information scenarios, which showed a positive correlation
between information and WTP, were treatment 2 and 4 (P>|t| = 0.012 [< p = 0.05] and P>|t| = 0.05 [<p
= 0.05] respectively). Treatment 2 disclosed information on enhancing recycling facilities in the UK,
and Treatment 4 disclosed information on investing toward a circular economy. Thus, one unit
increase in information regarding recycling in the UK would increase WTP by 1.62 units, and one unit
increase in information on the circular economy would also increase WTP by 1.24 units.
Semi-structured interviews were carried out with experts of the WEEE industry. The most significant
finding was that consumers are largely unaware of their role and the responsibilities that come with it.
This is particularly problematic in the case of small WEEE, including laptops, as consumers are relied
upon to bring their WEEE to collection points. However, for the consumer, this is neither efficient nor
Absence of communication is believed to be the cause of low consumer awareness. This might have
negative implications on their WTP for visible fees, such as a waste tax. Consumers would not agree
to these imposed costs as they would view them as outside of their scope of responsibility, and that it
is the responsibility of the producers to cover these costs.
The median WTP results for all information treatments demonstrate a decrease in median WTP the
second time the respondents were asked their WTP for a tax. This may be due to the respondents’
negative perceptions toward tax and the overall presentation of questions in the survey.
The regression analyses demonstrate positive correlations between information Treatment 2 and WTP
and information Treatment 4 and WTP. Treatment 2 included information on how the tax is needed to
address recycling facilities in the UK, and Treatment 4 outlined how tax can be used to transition to a
circular economy in the UK. As correlation does not prove causation, we hypothesize that the results
described above may be due the fact that they are of high personal relevance, as our sample based in
the UK. Respondents willingness to pay for personally relevant scenarios supports the neoclassical
assumption that an agent is rational and out to maximise his own utility.
There is no correlation between the information provided in Treatment 3 and WTP. This may be due
to the fact that it was of low personal relevance to respondents. The resulting benefits of the tax will
not be experienced by the consumer and it is likely that they do not feel it is their responsibility to
address this problem. That respondents do not believe they should be responsible was indicated in
their responses when asked why they chose £0 on the payment card. Therefore, the results do not
demonstrate any intention for altruistic behaviour.
The qualitative results support these findings, reasoning that the low general WTP for the waste tax is
due to the lack of consumer awareness of their role in the disposal of electronic waste.
IV. Limitations of the Study and Potential for Further Research
Limitations of the Study
As with most studies, this study is not without limitations. The biggest limitation to the study is that
the respondents in each treatment group are not a representative sample of the UK population. This is
due to the fact that the total number of respondents, which is a representative sample, was split into
four treatment groups. Additionally, the sample was obtained through a third party panel company,
using paid respondents to answer the questionnaire, potentially introducing strategic bias.
In terms of representation, it is important to note how the sample population demographics compare
with the UK population. A large proportion of our sample is unemployed: 15% compared to 5.1% of
the general population (Office for National Statistics 2016). Other differences include: 22% of the
sample is in retirement compared to 13.1% throughout the UK; 47% of the sample is in full-time
employment compared to 74.1% for the UK population. Despite these differences, however, the
sample's average number of laptops per household is similar to the UK average of 1.3 (The Guardian
In order to improve the reliability of our results, it is necessary to increase the number of respondents
in all information treatments. In addition, we did not clarify if our respondents were solely responsible
for purchasing their laptops or whether they were purchasing a laptop in the near future; therefore, we
cannot ensure their stated preferences reflect their true consumer behaviour. Furthermore, there is no
data available on the UK population's environmental awareness levels as measured in our
environmental awareness indicator, which combines environmental attitudes and awareness of
electronic waste management processes. Such information would be helpful in determining the extent
to which our sample is representative. Instead, our analysis included an environmental awareness
indicator that we developed. Respondents were categorised according to levels of environmental
awareness, and the distribution of respondents within these categories would have been different
depending on the choice of methodology (thresholds).
Our survey methods were inherently biased due to the challenges in the creation of hypothetical
markets. The biggest flaw in the hypothetical markets used was the use of the term “waste tax”.
Studies have shown that taxes can induce negative responses. Our survey findings from the
openended debriefing questions strongly demonstrated negative responses to taxes. Our qualitative findings
also support this, where it was discovered that the perception of a hypothetical market with “increased
prices” or a less visible cost may have resulted in more neutral responses. It was difficult to
objectively measure and assess the level of neutrality of the hypothetical markets provided and assess
uncontrolled responses, regardless of omitting any explicit emotional or influential language. In real
life market transactions, people usually face discrete choices.
) study on contingent
valuation showed that open-ended willingness-to-pay questions are more difficult for respondents than
closed-ended ones. Also, when people are asked twice about their WTP, they may lose trust in the
survey, as it may seem less realistic and less reliable.
The aforementioned limitations were addressed in the debriefing section of the survey. Validation
questions were included to test for protest zeros, bias, and to check the respondents' understanding and
acceptance of the key parts of the valuation scenarios provided. These questions also probed the
respondents' motives behind their answers. From this, we negated any responses that showed lack of
understanding, "yes-sayers" and protest zero responses. However, as we carried out the survey online,
we were unable to gage the respondents' emotions toward the tax before and after the information
effect. Assessing respondents’ emotional response may have been more effective if the information
was handed out in person directly, as well as if the survey had been carried out in a workshop.
Our study uses values based on individual laptop recycling costs outside of the UK, as there was
insufficient UK data available. Although adjusted for income using current exchange rates, it may not
reflect the true value recycling costs for the UK. Additionally, the waste tax value was solely
determined by recycling costs; it was not increased to retroactively include cost recovery for
environmental damage, caused by the current insufficient facilities in the UK or abroad. Therefore, the
values used may not reflect reality.
Finally, the level of information in each scenario was not quantified. The respondents’ answers might
be impacted by the difference in each scenario from a pure quantitative stand point.
Potential for Further Research
In light of the current study's limitations and findings, follow-up study topics to expand findings could
first include an in-depth study on consumer awareness of their roles in the electronic waste disposal
process. It would also be beneficial to repeat the study with a modified hypothetical market, using
other payment vehicles instead of a “waste tax”. Such a study would explore the subject without the
bias linked to the use of the vocabulary on tax. Similarly, a comparison of responses with the use of
varied levels of persuasive and emotive language in the information provided, as well as different
types of visual aids, would explicitly enrich research on altruism theory. Finally, replicating the study
outside the UK would be helpful in understanding the cultural dimension related to the management of
electronic waste and its economic geography.
V. Conclusions and Recommendations
The findings of this study show a decrease in median WTP after information was provided in each
treatment. However, the results from the regression analysis suggest a positive correlation between
information and WTP. Therefore, this study is able to reject the H1 hypothesis and confirm that
information has an effect on the survey respondents’ willingness to pay a waste tax in order to address
electrical and electronic waste issues.
Regarding the H0 hypothesis focusing on the willingness to pay for the cost of proper disposal of
electrical and electronic waste, the results are nuanced. The results show that respondents are only
willing to finance strategies that are targeted to the UK context directly relevant to respondents.
In addition, the studies introduced the concept of circular economy in order to assess the respondents’
willingness to pay for an approach that intends to address the resource optimization issue in a holistic
way. In particular, the possibility of using such a waste tax to support the transition to a more circular
economy. We strongly conclude that an awareness effort must be deployed before implementing such
Public awareness campaigns should, therefore, be launched. These campaigns should be personally
relevant to the consumer, and provide information on the consumer’s role in the electronic waste
disposal chain, the countries waste management system and the benefits of transitioning to a circular
In the light of the study’s nuanced results, it is important not to jump to the tempting conclusion that
consumers from developed economies are not concerned with the health and environmental impact
their electrical and electronic waste is having on host countries. First, the payment vehicle, the “tax”,
used for the study can be controversial as respondents may be unwilling to pay an additional tax in a
context dominated by fiscal pressure; especially when the proceeds are financing facilities in a
different country. Second, the scenarios provided during the study deliberately avoided excessive
emotional language; it is possible that providing images and other visual material on the
environmental and health impact of illicit electronic waste trade will have a different impact on
respondents’ willingness to pay. Finally, only 4% of the respondents were aware of their role in
disposing of electronic waste and where it goes; a sample with a higher awareness level might also
approach the survey in a different way.
Still, as mentioned in the introduction of the paper, the fact that electrical and electronical waste is
illegally moved from “source” developed economies to “host” developing economies (J.Li et al.,
2013) raises the questions of global environmental responsibility and social justice. Implementing the
awareness campaigns we suggest, and raising the level of information, requires coordinated action
across the spectrum, an effort that proves to be challenging.
Ultimately, what WEEE choose to do in the UK and beyond, remains an open question, but not one
without consequences. How we inform our decisions will be key.
The authors would like to thank Dr. Ioannis Kountouris for his support and guidance throughout the
project. They would also like to thank Dr. Margaret Bates, Derek Greedy, and Jeff Cooper for the
insights that they shared on electronic waste management in the UK.
Word Count: 7867
Ababio-Oteng, M. “When necessity begets ingenuity: e-waste scavenging as a livelihood strategy in
Accra, Ghana.” African Studies Quarterly, 13 (1/2) (2012).
Ajzen, I., T. Brown, and L. Rosenthal. “Information Bias in Contingent Valuation: Effects of Personal
Relevance, Quality Information and Motivational Orientation.” Journal of Environmental
Economics and Management, Volume 30, Issue 1, (1996). 43-57.
Altvater, M., and C. Brandmann. “Extended producer responsibility: The EU WEEE directive goes
global-strict law and order required or self-regulating market power a promising alternative?”
Electronics Goes Green 2012+(EGG), 1-2 (September 2012).
Andersen, M. 2007. “An introductory note on the environmental economics of the circular economy.”
Journal of Sustainable Science 2, 133-140.
Baird, J., Curry, R., and Cruz, P. (2014). “An overview of waste crime, its characteristics, and the
vulnerability of the EU waste sector.” Waste Management and Research, Vol. 32(2), 97-105.
Baldé, C.P., Wang, F., Kuehr, R., Huisman, J. (2015), The global e-waste monitor – 2014, United
Nations University, IAS – SCYCLE, Bonn, Germany.
Basel Action Network (2005). “The Digital Dump: Exporting High-Tech Re-use and Abuse to
Africa.” BAN Report.
Bateman, I. J., and Mawby, J. (2004). “First impressions count: interviewer appearance and
information effects in stated preference studies.” Ecological Economics, 49(1), 47-55.
Benoit, T. (2004). [www.uvm.edu/~gflomenh/GRN-TAX-VT.../Benoit-SOLIDWASTE.doc]
Accessed on 10/03/2016.
Blaine, T., Lichtkoppler, F., Jones, K. and Zondag, R. (2005) “An assessment of household
willingness to pay for curbside recycling: a comparison of payment card and referendum
approaches.” Journal of Environmental Management 76, 15-22.
Boyle, K. (1989). “Commodity Specification and the Farming of Contingent Valuation Questions.”
Land Economics, 65, 57-63.
CalRecycle (2015) Retailer Information and Electronic Waste Recycling Fee. Available online
[http://www.calrecycle.ca.gov/Electronics/Retailer/] Accessed on 11/02/2016.
Cameron, T. A., and Englin, J. (1997). “Respondent experience and contingent valuation of
environmental goods.” Journal of Environmental Economics and management, 33(3), 296-313.
Carson, R. (2012) “Contingent valuation: a practical alternative when prices aren’t available.” The
Journal of Economic Perspectives 26 (4) 27-42.
Chung, S. W., and Murakami-Suzuki, R. (2008). “A comparative study of e-waste recycling systems
in Japan, South Korea and Taiwan from the EPR perspective: implications for developing
countries.” Kojima. Chiba.
Cohen, D. and Crabtree, B. (2006) Qualitative Research Guidelines Project
[http://www.qualres.org/HomeSemi-3629.html] Accessed 16/03/2016.
Davies, A. (2007). “A wasted opportunity? Civil society and waste management in Ireland.”
Environmental Politics, 16(1), 52-72.
EIA (2011) System Failure: The UK’s harmful trade in electronic waste
Ellen MacArthur Foundation (2017). Toward the Circular Economy
[https://www.ellenmacarthurfoundation.org/assets/downloads/publications/Ellen-MacArthurFoundation-Toward-the-Circular-Economy-vol.1.pdf] Accessed 20/04/2017.
Nnorom, I.C., and Oslbanjo, O. (2008). “Overview of electronic (e-waste) management practices and
legislations, and their poor applications in the developing countries.” Resources, Conservation and
Recycling, Vol 52, 843-858.
Norregaard, J., and Reppelin-Hill, V. (2000). Taxes and tradable permits as instruments for
controlling pollution: theory and practice (No. 0-13). International Monetary Fund.
Organisation for Economic Co-operation and Development (OECD) (2017). Tackling Environmental
Problems with the Help of Behavioural Insights. OECD Publishing
Office for National Statistics. (2016). UK Labour Market: March 2016.
types/bulletins/uklabourmarket/march2016] Accessed on 03/03/2016.
Ongondo, F. O., Williams, I. D., and Cherrett, T. J. (2011). “How are WEEE doing? A global review
of the management of electrical and electronic wastes.” Waste management, 31(4), 714-730.
Peloza, J. and White, K. (2007) ,"Hey, What Gives? the Effects of Altruistic Versus Egoistic Charity
Appeals on Donation Intentions", in NA - Advances in Consumer Research Volume 34, eds.
Gavan Fitzsimons and Vicki Morwitz, Duluth, MN : Association for Consumer Research,
Perkins, D., Drisse, M., Nxele, T. and Sly, P. (2014) E-waste: a global hazard
[www.sciencedirect.com/science/article/pii/S2214999614003208] Accessed on 22/02/2016
Robinson, B. H. (2009). “E-waste: an assessment of global production and environmental impacts.”
Science of the total environment, 408(2), 183-191.
Rowe, R., Schulze, W. and Breffle, W. (1996) “A test for payment card biases.” Journal of
Environmental Economics and Management 31, 178-185.
Ryan, M., Scott, D. and Donaldson, C. (2004) “Valuing health care using willingness to pay: a
comparison of the payment card and dichotomous choice methods.” Journal of Health
Economics 23, 237-258.
Ryan, M. and Watson, V. (2009) “Comparing welfare estimates from payment card contingent
valuation and discrete choice experiments.” Journal of Health Economics 18, 389-401.
Samson, A. (2014). The Behavioral Economics Guide 2014 (With a Foreword by George Loewenstein
and Rory Sutherland).
Simon, H. A. (1993). “Altruism and economics.” The American Economic Review, 83(2), 156-161.
Stefansdotter, A. et al. (2016), Nudging för hållbar konsumtion av elektronikprodukter (Nudging the
sustainable consumption of electronic goods), executive summary in English, report for the
Nordic Council of Ministers, Copenhagen.
The Guardian (2015). Online all the time – average British household owns 7.4 internet devices
[http://www.theguardian.com/technology/2015/apr/09/online-all-the-time-average-britishhousehold-owns-74-internet-devices] Accessed on 15/02/2016.
Tkac, J. (1998). “The Effects of Information on Willingness-To-Pay Values of Endangered Species.”
American Journal Agricultural Economics, 80, Number 5, 1214-1220.
UNEP (2011) The Basel Convention at a Glance
[http://www.basel.int/TheConvention/Overview/tabid/1271/Default.aspx] Accessed on
UNEP (2015) Waste Crime – Waste Risks: Gaps in Meeting the Global Waste Challenge
Widmer, R., Oswald-Krapf, H., Sinha-Khetriwal, D., Schnellmann, M., and Böni, H. (2005). “Global
perspectives on e-waste.” Environmental Impact Assessment Review, 25 (5), 436-458.
A publication by Arcadia University and the American Graduate School in Paris
(2016) XE Currency Converter.
Accessed on 20/02/2016.
A publication by Arcadia University and the American Graduate School in Paris
STATA REGRESSION RESULTS
Regression Treatment 1: General WTP Scenario
Regression Treatment 2: Recycling in the UK Scenario
A publication by Arcadia University and the American Graduate School in Paris
Regression Treatment 3: Illegal Exportation of E-Waste Scenario
Regression Treatment 4: Circular Economy Scenario
Alexandra Imirziadis is an Environmental Sustainability Advisor for Laing O’Rourke, an international
engineering enterprise. She is also the Skills & Employment Advisor and Responsible Procurement
Manager on one of their projects; the Northern Line Extension Project in London. She holds BSc in
Environmental Geography from the University of York and an MSc in Environmental Technology from
Imperial College London.
Laura Heintzman is currently the sustainability analyst at a Canadian apparel company based in
Vancouver. With previous positions held at the United Nations Environment Programme in Nairobi
and CDP (formerly Carbon Disclosure Project). She has an MSc in Environmental Technology
specializing in Environmental Economics and Policy from Imperial College, and a BSc in
Environmental Studies and Psychology from the University of Toronto.
Astrid Rahardjo is a climate, environment and development enthusiast, currently working as a
consultant at the Green Climate Fund. Her experiences involve climate finance and environmental
impact assessments, and she has been exposed to works in public institutions, private sector, as well
as international organizations. She has a BSc in Environmental Engineering, and an MSc in
Environmental Technology from Imperial College London.
Abderrahim Assab is an analyst at European Bank for Reconstruction and Development’s (EBRD)
Energy Efficiency and Climate Change department. Prior to joining the EBRD, he was part of the
OECD’s Institutional Investors and Long Term Investment Project. He holds a Masters in Financial
Risk Management from Telecom SudParis and an MSc from Imperial College London in
European Commission ( 2015 ). Waste Electrical and Electronic Equipment (WEEE ) [http://ec.europa.eu/environment/waste/weee/index_en. htm] Accessed 12 /02/2016].
European Economic and Social Committee ( 2016 ), The influence of lifespan labelling on consumers , Brussels.
Gao , Z. , and Schroeder , T. C. ( 2009 ). “Effects of label information on consumer willingness-to-pay for food attributes .” American Journal of Agricultural Economics , 91 ( 3 ), 795 - 809 .
George , D. , Lin , B. and Chen , Y. ( 2015 ) “A circular economy model of economic growth . ” Environmental Modeling and Software 73 , 60 - 63 .
Grsikevicius , V. , Tyber , J., Van den Bergh, B. ( 2010 ). “Going green to be seen: Status, reputation and conspicuous conservation . ” Journal of Personality and Social Psychology , Vol 98 ( 3 ), 392 - 404 .
Hanneman , M. ( 1994 ) “Valuing the environment through contingent valuation . ” Journal of Economic Perspectives 8 ( 4 ) 19 - 43 .
Henrich , J. , Boyd , R. , Bowles , S. , Camerer , C. , Fehr , E. , Gintis , H. , and McElreath , R. ( 2001 ). “In search of homo economicus: behavioral experiments in 15 small-scale societies .” The American Economic Review , 91 ( 2 ), 73 - 78 .
Hung , I. W. , and Wyer Jr , R. S. ( 2009 ). “Differences in perspective and the influence of charitable appeals: When imagining oneself as the victim is not beneficial . ” Journal of Marketing Research , 46 ( 3 ), 421 - 434 .
Jaiswal , A. , Kumar , M. , Patel , B. and Samuel , C. ( 2015 ) “Go green with WEEE: Eco-friendly approach for handling e-waste .” Porcedia Computer Science ( 46 ) 1317 - 1324 .
Johansson-Stenman , O. ( 1998 ). “ The importance of ethics in environmental economics with a focus on existence values . ” Environmental and Resource Economics , 11 ( 3-4 ), 429 - 442 .
Lange , C. , Martin , C. , Chabanet , C. , Combris , P. , and Issanchou , S. ( 2002 ). “Impact of the information provided to consumers on their willingness to pay for Champagne: comparison with hedonic scores . ” Food Quality and Preference , 13 ( 7 ), 597 - 608 .
Leech , B. ( 2002 ). “Asking Questions: Techniques for Semi-structured Interviews .” PS: Political Science and Politics, ( 35 ) 665 - 668 .
Luther , L. ( 2010 ) Managing electronic waste: Issues with exporting e-waste , Congressional Research Service [FIND LINK] Accessed 20 /01/ 2016 .
Madariaga , B. , and McConnell , K. E. ( 1987 ). “Exploring existence value . ” Water Resources Research , 23 ( 5 ), 936 - 942 .
Marius , M. ( 2011 ) Laptops versus tablets, which one is better? Available online [http://www.ictpulse.com/ 2011 /06/laptops-versus -tablets-which-one-is-better] Accessed on 20/02 / 2016 .
Moriarty , Rick ( 2016 ) Best Buy now charges $25 to take used TVs for recycling . Available online [http://www.syracuse.com/businessnews/index.ssf/ 2016 /02/best_buy_now_charges_25_to_ take_used_tvs_for_recycling .html] Accessed on 11/02/ 2016 .
Napolitano , F. , Braghieri , A. , Piasentier , E. , Favotto , S. , Naspetti , S. , and Zanoli , R. ( 2010 ). “Effect of information about organic production on beef liking and consumer willingness to pay .” Food Quality and Preference , 21 ( 2 ), 207 - 212 .
Nath , P. and Ramanathan , R. ( 2016 ) E”nvironmental management practices, environmental technology portfolio, and environmental commitment: A content analytic approach for UK manufacturing firms .” International Journal of Production Economics ( 171 ) 427 - 437 .
Nnorom , I. and Oslbanjo. O. ( 2007 ) “ The challenge of electronic waste (e-waste) management in developing countries . ” Waste Management and Research ( 25 ) 489 - 501 .