Promoting a Circular Economy in the Mobile Phone Product System in China

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DEGREE PROJECT

ENVIRONMENTAL ENGINEERING,

SECOND CYCLE, 30 CREDITS

,

STOCKHOLM SWEDEN 2020

Promoting a Circular Economy in

the Mobile Phone Product System

in China

SHIHUI WANG

KTH ROYAL INSTITUTE OF TECHNOLOGY

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Promoting a Circular Economy in the

Mobile Phone Product System in China

Author: Shihui Wang

Supervisor: Rajib Sinha

Examiner: Monika Olsson

Degree Project in Sustainable Technology KTH Royal Institute of Technology

School of Architecture and Built Environment

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Sammanfattning

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Abstract

The concept of the circular economy has been introduced to China and encouraged to be implemented in manufacturing industries by the government in recent years. The implementation of a circular economy in the mobile phone product system can potentially serve as a solution to reducing a significant amount of waste mobile phones. However, the development of a circular economy in China is still at the beginning phase. To help with the promotion of a circular economy, this thesis was proposed. The aim is to explore the possibility to promote a circular economy in the mobile phone product system in China and the main target group is mobile phone producers. The main methodology of this thesis was system dynamics modeling. A system dynamic model was developed to analyze the potential sustainability profits and economic profits. A questionnaire and a literature review were conducted to collect relevant data for the model. The study proposed three strategies (old-for-new, eco-design, and product service system) for producers to promote a circular economy. The profitability of the three scenarios was evaluated and then a sensitivity analysis of the parameters in the model was conducted. According to the model results, the old-for-new strategy was the most profitable and the strategy of the product-service system could not bring additional profit to producers if only economic profits were considered. The general suggestion for producers on maximizing the profitability was propagandizing the significance of mobile phone collection and recycling to increase consumers’ awareness.

Keywords

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Acknowledgments

This thesis is written at the end of the master's program Sustainable Technology as an ending of my master's study. My deepest gratitude is to my supervisor at KTH, Dr. Rajib Sinha, for not only his support in this thesis but also his guidance during the two years so that I could be equipped with the capacity to conduct the project. He allowed me to be free to explore what I am interested in and provided necessary help when I was in a struggle. I also thank my friends and colleagues in Shenzhen, who helped me a lot with the distribution of the questionnaire. In particular, I would like to express my appreciation to Mr. Huiyu Lu, who works in a mobile phone enterprise in Shenzhen. During my thesis, he provided helpful suggestions and kind support generously.

It is a pity that I cannot return to Stockholm to present my thesis and meet the professors who taught me a lot and the friends in Sweden who accompanied me for one and a half years physically. However, it is still a wonderful time for me to learn at KTH and to end up with this thesis.

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Abbreviations

BAU: business as usual CE: circular economy CLD: causal loop diagram CLSC: closed-loop supply chain

CPPCC: the Chinese People’s Political Consultative Conference EoL: end of life

EPR: Extended Producer Responsibility

GBA: Guangdong-Hong Kong-Macao Greater Bay Area LCA: life cycle assessment

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1. Introduction

In the last decades, the use of electronic devices and appliances has significantly increased in both industrialized and developing countries with an expanding market (Wang et al., 2018a). Meanwhile, the obsolescence rate of electronic equipment is rising. As a consequence, the generation of electronic waste (e-waste) has increased rapidly and become the fastest-growing component of the solid waste stream (Cao et al., 2016a). It has been estimated that the worldwide annual generation of e-waste is 30~50 million tons, and only e-waste generation in China has reached 6.7 million tons per annum (Wang et al., 2018a). The significant amount of e-waste would result in different impacts on ecosystems and human societies, depending on the way of treatment.

On one hand, if dumped without any other treatment, e-waste would lead to severe health risks and environmental degradation. For instance, electronic products usually consist of some harmful materials such as lead, cadmium, chromium, and polychlorinated biphenyls (PCBs) which can accumulate in soil and water, affecting human health by accumulation effect though food chain or radiation (Cao et al., 2016a). On the other hand, the reuse, recovery, and recycling of obsolete electronic products is beneficial to not only ecosystems but also human society. With the rapid depletion of virgin resources, alternate resources are in urgent demand. E-waste which contains many valuable and recyclable materials such as aluminum, copper, gold, silver, and ferrous materials is an alternative. Taking copper as an example, the ratio of recycled copper from waste mobile phones to global copper production would have grown at a rate of 0.07~0.19% from 2010 to 2015 if all the waste mobile phones in China are 100% recycled (Tan et al., 2017). Another example of environmental benefits reveals that compared with the extraction of raw materials, the energy-saving of recycling materials from e-waste generated in the two years in China is equal to save 120 thousand tons of standard coal (Yu et al., 2014). Meanwhile, recycling entities together with electronic product producers can make a profit by recovering valuable materials or components from e-waste and selling refurbished products. It is estimated that the profit of metal recycling from the waste mobile phones in China can reach 300 million dollars by 2025 (Tan et al., 2017). Hence, for the sake of ecosystems and multiple stakeholders involved in electronic product systems, e-waste recycling should be promoted.

A mobile phone is a necessary electronic product in many people’s daily life as well as a significant part of e-waste because the average number of idle mobile phones in households is larger than that of any other electronic product (Cao et al., 2016a). China is a major contributor to global mobile phone subscribers, with an 18% market share, and the main generator of waste mobile phones meanwhile (Li et al., 2015). It is estimated that the total possession number of mobile phones in 2025 would grow up to 937 million units in China and the average lifespan of a mobile phone in China is only 1.73 years, which is far shorter than it could have been used (Guo and Yan, 2017). A significant amount of possession and the high obsolescence rate have made waste mobile phones a serious problem. However, mobile phone take-back and processing systems are still developing at the beginning phase in current China, and the responsibility allocation regarding waste mobile phone treatment is vague (Wang et al., 2018a). Most of the consumers reckon that the government should be responsible for dealing with waste mobile phones, including promulgating relevant laws and regulations, constructing infrastructure used for e-waste treatment, and enforcing waste mobile phone disposal projects (Yin et al., 2014). On the other hand, the government tends to encourage mobile phone producers to take more responsibility for the treatment of post-consumer products, for example, in the form of additional levy (Wang et al., 2018a). Both the government and mobile phone producers are a dominant stakeholder in closing the loop of the mobile phone product system and achieving a circular economy. Thus, the thesis was proposed to look into the possibility of promoting a circular economy in the mobile phone product system in China from the producers’ perspective.

1.1. Research gap

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usually recovering the most valuable metals and landfilling the remaining parts, which reduces the potential profits of producers from recycling waste mobile phones, requires a significant amount of labor, and results in value leakage of the product system (Qu et al., 2013). In order to solve the problem of low profitability, heavy workload, and losses caused by the unreasonable distribution of waste mobile phone collection, a more effective collection and recycling system is required.

When it comes to the research of optimizing waste mobile phone collection and recycling systems in China, the first research gap is the limitation of target groups of existing studies. Previous research has investigated the actions of the government to promote formal recycling sectors. Detailed literature review regarding the current situation of e-waste recycling and the promotion of formal sectors is provided in 2.1. However, the participation and effect of mobile phone producers in the establishment of a more controllable and more effective recycling system are less noticed. Producers are essential to solving recycling problems. For instance, to optimize the formal collection and recycling systems, Zeng et al. (2017) revealed that the most effective regulations regarding e-waste recycling in China, different from the situation in developed countries, were the old-for-new policies and the producer-pays regulations, both of which required the support of producers. However, the possibility that mobile phone producers are willing to promote a CE in the product system can be complex to analyze because enterprises of different sizes have varied concerns. Large companies may be more willing to undertake social responsibility to increase their reputation, while the emphasis of small companies is still on financial profit. As a result, a study of analyzing the profitability for mobile phone producers to promote a CE in the product system with detailed discussion considering various demands of companies is needed.

The second research gap is concerning the geographical scope. Although some case studies on obsolete mobile phone recycling programs in China have been done before, the geographical delimitation of these case studies is mainly on northern provinces (Qu et al., 2013; Wang et al., 2017a; Wang et al., 2018b), and the eastern area (Chi et al., 2014; Cao et al., 2016b; Wang et al., 2018a). Studies on southern parts, for example Guangdong province, are relatively insufficient. Since China is a large country with diverse contexts in different areas, it is important to fill the gap with research on the possibilities of promoting a CE in the mobile phone product system in southern cities. Shenzhen, located in Guangdong Province in the south of China and connected with Hong Kong to the south, is one of the four major cities in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Selected as the first special economic zone of China in 1980, it has always been the window of China’s reform and opening up and a new immigrant city, known as the “Silicon Valley of China”. It was selected as the case in this study due to the following reasons. First of all, Shenzhen is regarded as a pioneer city for sustainable development and it is home to many e-waste recycling entities (Cao et al., 2016a). Secondly, many Chinese mobile phone producers are based in Shenzhen. Thirdly, the mobile phone recycling system in Shenzhen not only recycles the mobile phone discarded in Shenzhen but also undertakes the recycling of most of the waste mobile phones from Hong Kong (Deng et al., 2017). So, the effectiveness of the recycling system in Shenzhen can have a wide impact.

Another research gap is the lack of the latest data. Considering that the data used in previous models are old and mostly the national average which cannot represent the status quo of Shenzhen, recent data are needed for a targeted analysis to the mobile phone producers based in the city. In order to bridge the gaps, a model combining the three sustainability pillars (environmental, economic, and social) with the latest data to evaluate the potential profits of the producers from promoting a CE in the product system in Shenzhen is needed.

1.2. Aim and objective

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2. Background and literature review

In order to develop a holistic picture of the status quo of the mobile phone product system in China, a literature review was conducted. The literature review consisted of four aspects. Firstly, the current e-waste collection and recycling systems in China were explored to clarify the pathways of e-waste mobile phone treatment. Secondly, previous research about potential profitability of collecting and recycling obsolete mobile phones were reviewed. Thirdly, investigation and selection of strategies of promoting a CE in the mobile phone product system in China was conducted. Lastly, previous models on the mobile phone product system were explored, which were the foundation of the thesis.

2.1. E-waste collection and recycling in China

In the past decades, China has made progress on e-waste management and treatment. Qu et al. (2013) reviewed the development of e-waste collection systems in China. Currently, the e-waste collectors could be divided into four types in general: peddlers, dealers/retailers, specialized collectors, and secondhand markets. Approximately 88% of the collected e-waste was collected by peddlers, the informal individual collectors. It was actually an inefficient way of e-waste collection because only the most valuable materials such as gold and copper were recycled while the valueless parts of e-waste were usually landfilled without regulatory control. However, consumers were more used to selling their idle electronic appliances to peddlers. The habit had become a key barrier to the implementation of formal collection systems. About 6% of the e-waste was taken back by retailers. Specialized collectors such as registered dismantling plants cooperated with communities and enterprises to help with the collection and treatment of 3% e-waste. The remaining 3% e-waste was sold to secondhand markets directly by consumers. In reality, the efficiency of current collection systems was not satisfactory due to the unreasonable distribution of e-waste collection.

In order to clarify the responsibilities of collecting and recycling e-waste and promote formal recycling, the national government has done a series of work. Yu et al. (2014) summarized legislation and regulations related to e-waste recycling in China enacted between 2001 and 2012:

● From 2001 to 2008, a prohibition on the importation of e-waste was proposed and relevant administrative measures on pollution of e-waste were gradually implemented.

● Approved in 2008 by the State Council, the Collection and Treatment Decree on Wastes of Electric and Electronic Equipment stipulated that all e-wastes in the catalog defined by the Minister of Environment Protection should be taken back, recycled and disposed of according to the administrative guidance. The registered recycling entities could receive funding from the government for their collection and treatment of the types of e-waste in the catalog.

● In 2009-2012, the Ministry of Finance phased in the e-waste old-for-new policy to encourage producers and formal recyclers to recycle obsolete electronic products. Besides, the Circular Economy Promotion Law of the People’s Republic of China was enacted in 2009 which specified provisions on reducing, reusing, and recycling electronic products during manufacturing and using phase.

● In 2011, the Management Regulation on the Recycling of Waste Electrical and Electronic Products was implemented with the support of technical guidelines. Later, as more detailed regulations regarding e-waste treatment were legislated, an extensive formal collection and recycling system was gradually set up with technical guidance and financial support from the government.

According to the research of Wang et al. (2018b), in 2015, the new catalog of e-waste recycling was issued by the Minister of Environment Protection to guide recyclers. Waste mobile phones were then included in the catalog for which formal recyclers could be financially supported by the government. Moreover, in 2015, the State Council issued the action plan of Made in China 2025 which clearly stated the vision of enhancing green manufacturing. In the following year, the Ministry of Industry and Information Technology issued the Implementation Guide for Green Manufacturing Engineering (2016-2020), which was a companion to the initiative of Made in China 2025. The guideline pointed out that it was an emphasis to disassemble and recycle waste electrical and electronic products and stressed that the EPR system should “make substantial progress” by 2020 which had put stress on the producers.

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of information publicity of the government on consumers’ behavior intentions on e-waste recycling with a geographic scope within Jiangsu Province, in the east of China. In December 2016, the Environmental Protection Office in Jiangsu Province held an e-waste recycling public welfare activity spontaneously and obtained effectiveness. Wang et al. (2018a) found that in the project, information publicity did not have a direct effect on consumers’ behavior intentions but indirectly affected consumers’ intentions through personal norms and recycling attitude. They concluded that the government should increase the frequency of publicity events and improve the publicity content to promote e-waste recycling more effectively. The research in Hong Kong by Deng et al. (2017) supported these suggestions. Although e-waste collection points had been set up in most districts in Hong Kong by mobile phone producers, the recycling rate was not to their satisfaction due to consumers’ unawareness with little publicity from the government. Gu et al. (2017) and Shih (2017) explored the influence of local e-waste fund systems. The funding came from the fiscal revenue of the local government and the additional levy of the producers. The registered formal e-waste dismantling and recycling companies were subsidized. However, Gu et al. (2017) found that the campaign in the Chinese Mainland usually ended with an accumulating government deficit, and thus a new operation mode was needed. Research in Taiwan demonstrated that the best mode of funding for e-waste recycling was an earmarked fund with the multi-period model, which meant the fund and the profit would be counted within a period and accumulated along with time rather than annual settlement (Shih, 2017).

Different from the policy research, Cao et al. (2016a) examined the possibility of promoting formal e-waste recycling on a technical level. They found that formal recycling companies and large electronic product producers had been carrying out research on e-waste treatment technologies, such as waste cathode ray tube recycling technology, waste printed circuit board recycling technology, waste plastics recycling technology, waste refrigerators treatment technology and waste liquid crystal display treatment technology. Theoretically, the capacity of these formal entities was enough for the treatment of e-waste. However, they claimed that although the recycling and treatment capacity was considerable, there still existed many difficulties for the factories to have adequate quantities of e-waste to be treated economically. In other words, the profit from e-waste treatment could not cover the operation cost due to the inadequate amount of e-waste collection. Moreover, it was indicated that rather than waste treatment technology problems, the most serious challenge was e-waste collection with unclear responsibility allocation, high collection costs for formal e-waste treatment plants, and the lack of appropriate infrastructure.

Although formal recycling channels have been encouraged to widely spread in China, it is hard to suppress informal collectors in a short time (Chi et al., 2014). Chi et al. (2014) analyzed the reasons of consumers’ preference on informal e-waste recyclers and found the informal collectors were advantageous in the convenience of service, flexibility, accessibility, and collection scope. Liu et al. (2016) examined the two channels, informal and formal, under quality-based price competition and found that at a higher quality level of e-waste, the marginal effect of subsidy from the government was not as promising. However, when the e-waste quality was high, formal recycling entities with unsubstantial subsidy were less competitive than informal collectors who could provide better acquisition price because the operation cost of informal ones was lower. As a result, informal collectors could capture a larger market share of high-quality e-waste. Otto et al. (2018) found that environmental motivation and behavioral costs were the two determinants of e-waste recycling from the perspective of consumers so that the behavioral costs should be reduced in order to promote formal collection and recycling systems. They suggested that to fit with the recycling habits of Chinese households and the socioeconomic conditions, an integrated collection and recycling system should be designed for the transition period and formal channels should be consummated to take over the share of informal collectors gradually.

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2.2. Profit of waste mobile phone collection and recycling

From the perspective of national economics, Awasthi et al., (2018) indicated a strong linear correlation among global e-waste generation and Gross Domestic Product (GDP). Furthermore, they stated that a better collection of e-waste contributed a lot to the circular economy and could be beneficial to the economy in turn. As mentioned before, mobile phones have a shorter lifetime compared with their designed lifetime. The underuse may result in value leakage to both consumer and producers. According to the research of Sabbaghi and Behdad (2018), the value leakage was defined as economic loss, environmental degradation, or social harm caused by any intentional or unintentional deviation from the best-known existing recovery method for an EoL product. They adopted a probabilistic approach to calculate the leakage risk of producers. It was estimated that a mobile phone producer in the US may lose up to 331 million dollars for 5 years due to consumers’ decisions to buy a new mobile phone from another brand without any treatment of the old one when the old one’s screen was broken.

To calculate the potential profit of mobile phone producers, Yeh and Xu (2013) pointed out that the benefit of a company from the collection and recycling of waste mobile phones can be evaluated in the three corporate sustainability dimensions (environmental, economic, social) and in turn the evaluation should be incorporated into the company’s iterative regular planning decisions. Geyer and Blass (2010) investigated economic revenue and cost of reuse, recycle, and refurbish of old mobile phones. Wang et al. (2012) introduced two dominant factors to calculate the additional profit from promoting mobile phone recycling programs, market prices of resources and labor costs, which served as an environmental indicator and a social indicator, respectively. Another insight from Said et al. (2013) explored the profit from the perspective of investors. They found investors valued the disclosure of environmental information. In other words, investors were more willing to invest in companies with high transparency of their environmental impacts. The influence of environmental issues on investors’ decision-making increased with the improvement of investors’ education and professional training level. As Wang et al. (2018b) stated, the government put financial pressure on producers with additional levy so that not dealing with the obsolete mobile phones might result in negative economic impacts on producers. On the other hand, actively acting on waste mobile phone recycling and promoting a CE of the mobile phone product system can help producers save costs.

Wang et al. (2017b) explored the collaboration mode between mobile phone producers and specialized recycling entities. When cooperating with other recycling entities, producers had asymmetric information on the collection effort level of recyclers and may offer lower wholesale prices and higher buy-back prices which made collaboration not the most cost-effective way for producers to recycle the obsolete products. Cao et al. (2016b) investigated some strategies for mobile phone producers to stimulate recycling. According to their research, among the practices that mobile phone producers could take by themselves to contribute to a CE of the whole system, the old-for-new activity launched by producers was the first choice for Chinese citizens when they considered disposing of waste mobile phones through a formal channel. The old-for-new policy had been widely used because it was a strategy for increasing sales for the latest products and a kind of advertising for brand promotion. Other choices included eco-design and product service systems, which have not been widely adopted in China.

2.3. Strategies of promoting a circular economy

As Cao et al. (2016b) stated, after the old-for-new policy was conducted by the Chinese government in 2009, some mobile phone producers had implemented old-for-new activities with recycling entities for the collection of old mobile phones and the promotion of new mobile phones. In the old-for-new activities, consumers are encouraged to trade in waste mobile phones for new products with a subsidy. In the field research of Cao et al. (2016b) from 2014 to 2015, the old-for-new programs were implemented by after-sales repair stations and moving recycling entities around the year while the electronic product producers surveyed in their research conducted the activities one to three times annually, each time for about one month. Their questionnaire revealed that the old-for-new activity was the most popular formal recycling pathway among consumers. The research of Cao et al. (2016a) found that a high recycling rate of e-waste, which included television, refrigerator, washing machine, air conditioner, and desktop and laptop computer, was achieved by the implementation of the old-for-new policy in 2011. Moreover, they found 30% of the enterprises which had implemented the old-for-new policy by 2012 were electronic product producers. Zhang and Yuan (2016) found that the old-for-new policy could reduce the bullwhip effect in the producers and thus increased the profitability.

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with living processes, which requires producers to design and develop new products with the aim of reducing environmental impacts through the whole life cycle of products (Andrae et al., 2016). The aim of eco-design is not only improving the energy efficiency during the manufacturing phase, transportation, and use phase, but also enhancing the recyclability, recoverability, reuse-ability, and disassemble-ability of the product (Zeng and Li, 2016). Vinodh and Manjunatheshwara (2017) investigated the application of Fuzzy Quality Function Deployment, which is a design technique that can integrate consumers’ interests with sustainability issues, for the eco-design of mobile phones. They created a generic model that allowed designers to easily apply the design theory to real conditions. Andrae et al. (2016) considered how to implement eco-design in a more practical way for mobile phone producers and provided specific steps for producers to conduct eco-design. However, they found it difficult to promote eco-design in developing countries where the relevant legislation was inadequate, and consumers’ awareness was insufficient. MacDonald and She (2015) concluded seven cognitive concepts related to successful eco-design, including responsibility, complex decision-making skills, decision heuristics, the altruism-sacrifice link, trust, cognitive dissonance, and motivation. They suggested future eco-design studies must focus on achieving positive changes in consumers’ behavior for success in eco-design.

Last but not least, the application of product service systems is a useful approach to promoting a CE and reducing environmental impacts, which have been adopted in the areas of the vehicle, furniture, and large electronic appliances (Beuren et al., 2013). The definition of the product service system is the combination of products and services in a system that provides functionality for consumers and reduces environmental and social impact (Beuren et al., 2013). According to the categories proposed by Tukker (2004), product service systems can be grouped into three types based on orientation. The first one is product oriented, in which services are provided to improve the functionality of the product. The second one is use oriented, in which the ownership belongs to the producer or is shared by a group of users. Sharing services such as vehicle sharing is an example of a use oriented product service system. The third type is result oriented, in which products are considered as a tool to achieve the desired results. For instance, Electrolux, a washing machine producer, offers functional sales, which means consumers pay according to how much they use the washing machine instead of buying a product (Beuren et al., 2013). When it comes to the product service system of mobile phones, according to the research of Wilhelm et al. (2011), most consumers are not willing to share mobile phones. Another barrier they revealed is that mobile phones are designed less durable than other products which were more suitable for sharing, such as cars and houses. Hobson et al. (2018) proposed a transforming mobile phone product service system in which the skin of a mobile phone is owned by consumers and the organs and the skeleton are leased from producers. The product-oriented product service system reduces environmental impacts during the manufacturing phase because it potentially reduces the amount of new product to be manufactured.

2.4. Previous models

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In order to further explore the impacts of specific strategies of promoting a CE, Zhang and Yuan (2016) built an SD model to analyze the impacts of the old-for-new policy and three electronic product recovery ways (remanufacturing of electronic products, reuse and remanufacturing of the electronic component, and recovery of electronic raw material) on electronic product closed-loop supply chain (CLSC). They instructed that the old-for-new policy and the electronic product recovery could reduce the bullwhip effect in the producers and increase the profitability of the whole CLSC distribution network. Golroudbary and Zahraee (2015) introduced a collection center to previous SD models for CLSC so that consumers’ satisfaction was included in the model and found that consumers’ willingness to support the collection and recycling system had a positive impact on the implementation. They stated the model could be used to investigate the effects of various CLSC systems before they were implemented in real life. When it comes to consumers’ awareness and actual behaviors, the research of Echegaray and Hansstein (2017) revealed a gap between cognition and actions. They found that only a minority of respondents in Brazil who held a positive intention to recycling electronic appliances actually adopted adequate recycling practices. They suggested that infrastructure and convenience for consumers’ recycling e-waste should be promoted in order to bridge the gap.

The way of producers to select strategies and to create, deliver, and capture value in specific economic, social, and cultural contexts depends on the market mechanism (Tong et al., 2017). Tong et al. (2017) applied business models for post-consumer recycling in Chinese cities. In their work, five variables were involved which were a convenience for consumers, traceability for producers, profitability for recyclers, hybridity for collection, and reliability for the public. They highlighted the governance challenge of integrating the EPR scheme into the current e-waste management system. Moreover, Bhattacharjee and Cruz (2015) developed an end-to-end model of a closed-loop supply chain that simulated the life cycle of electronic products driven by market demands. They found that a sustainable return policy could increase sales. Furthermore, they suggested that product design for convenience of recycling was beneficial to the economic sustainability of producers or other recyclers. They noted that the promotion of a CE required a well-calibrated return rate. To demonstrate the recyclability and promote qualitative to quantitative eco-design of electronic product systems, Zeng and Li (2016) proposed a mathematical model with the rules of grade determination for materials in electronic products and the Statistical Entropy function.

In order to run models concerning closing the loop of mobile phone product systems properly, one major difficulty is the precious estimation of the generation of retired mobile phones in China. Li et al. (2015) proposed a sales&new method for reasonable estimation. The model presented an increasing tendency with some fluctuations clearly and the results in 2002 and 2012 matched the actual situation well.

Table 1 Summary of previous studies on mobile phone product system models.

Author(s) and year Method Short description

Bhattacharjee and

Cruz, 2015 SD

This study identified the system decision making required for the economic viability of multiple stakeholders in the closed-loop supply chain of electronic products and examined the complex interactions among different

stakeholders and their decisions. The study emphasized the significance of product design and marketing on the economic sustainability of refurbishing entities and recyclers. It was found that a sustainable return policy could increase sales significantly, and promotion of policies required a well-calibrated return rate among new and refurbished products and different types of consumers.

Golroudbary and

Zahraee, 2015 SD

This study implemented consumer satisfaction and Green Image Factor to the previous electronic product system for the optimization of producers’ decision making. It was recommended that companies should develop more efficient reverse supply chains to take advantage of recycling, fight negative impacts of climate change, and gain customer satisfaction and brand loyalty.

Li et al., 2015 Mathematical _model

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This study evaluated the recyclability of e-waste with a mathematical model, emphasizing the product design stage to promote eco-design. The model partitioned e-waste recycling into three levels according to difficulty and divided the responsibility of recycling between producers and recyclers.

Zhang and Yuan, 2016 SD

This study investigated the significance of multiple factors concerning electronic product closed-loop supply chain, including the old-for-new policy, the processes of collection and remanufacturing, interactions of different stakeholders and their impacts on a bullwhip, and profitability.

Echegaray and Hansstein, 2017 Questionnair e & Statistical analysis

This study conducted a Theory of Planned Behavior oriented survey to explore Brazilian consumers’ intention, behavior, awareness, and attitude regarding electronic product recycling.

Chaudhary and Vrat,

2018 SD

This study investigated the sustainable benefits of circular flow of gold in the mobile phone supply chain in different scenarios. The major parameters in the model included gold reserve, collection efficiency of the organized sector, gold from E-waste, demand for gold, economic benefits, environmental benefits, and social benefits. The key driver to the success of the circular economy was the collection efficiency of the organized sector, which could be improved by increasing collection capacity.

Nikabadi and Hajihoseinali, 2018 SD & Fuzzy DEMATEL technique & Questionnair e

This study analyzed the influences of technology growth, processes of life cycle of devices, and other tendencies for buying new devices on the electronic waste recycling system by comparing multiple parameters in previous research from literature review. The sensitivity of the recycling system to these factors was analyzed.

Yao et al., 2018 LCA & SD

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3. Methods

The major methodology of the thesis was system dynamics modelling. The exploration of promoting a CE in the mobile phone product system involves multiple factors. System dynamics modelling is a method of investigating the dynamic behaviors of multiple parameters so that it was selected as the method of the thesis. It could be used to evaluate the profitability under the influence of market changes, consumers’ attitude and behaviors, and producers’ strategies. In order to propose potential suggestions, analysis of the modelling results was further conducted.

3.1. System dynamics model

3.1.1. Scope

The first step of conducting a system dynamics study was to define the research question and the scope. In this study, the research question involved the possibility of promoting a CE in the mobile phone product system. The key to achieving the CE is to close the loop by recycling waste mobile phones to control the value leakage and reduce environmental impacts. As Figure 1 illustrates, there are generally three pathways of dealing with obsolete mobile phones. The first pathway is to be treated by consumers themselves, which is the most uncontrollable approach. Consumers might leave the idle mobile phones without any treatment, offer the phones to their families (especially senior members) or friends, or throw away with other municipal solid waste. The second flow of obsolete mobile phones is recycling entities, including formal recycling enterprises and informal recycling sectors like peddlers. Sent to these recycling entities, some mobile phones which are beyond economic recycling are treated as waste or used for metal recovery. Since formal recycling enterprises often have cooperation with mobile phone producers, some recyclable mobile phones are sent to producers for refurbishing. The third choice of dealing with obsolete mobile phones is to bring them back to mobile phone producers directly, which was the focus of this study. Having collected the recyclable idle mobile phones, producers are expected to refurbish them and sell the refurbished products in the market.

The study concerned the profitability of mobile phone producers in the promotion of a CE in the product system. Three strategies were considered: old-for-new program, eco-design, and product service system. The sustainability profits under the three different scenarios were evaluated, respectively, from environmental, economic, and social aspects. Recycling waste mobile phones by producers leads to some environmental benefits, such as saving energy or producing new products in the manufacturing phase. Furthermore, the strategies were expected to bring direct economic value and social profit to producers. For example, a successful recycling program could present the company’s social responsibility and thus increase its reputation among consumers. All of the three sustainability pillars were considered in this study. Besides, the direct economic profits with the three strategies were calculated as supplementary. The temporal scope of this study was 20 years, from 2021 to 2040 and the geography scope was within Shenzhen, China.

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Figure 2 defines the responsibility of recycling entities and producers in the BAU scenario and the three scenarios of promoting a CE. In the BAU scenario, recycling entities are responsible for collecting hibernated mobile phones from consumers. They select the old mobile phones in good condition that could be refurbished for producers and producers refurbish mobile phones for selling. The profit from selling refurbished mobile phones is shared between producers and recycling entities. Other collected mobile phones in worse condition are dismantled and recycled by recycling entities. The end product is valuable materials and the remaining parts are treated as waste. Different from the BAU scenario, in the old-for-new scenarios, producers collect waste mobile phones directly with subsidy or coupons when consumers buy another mobile phone from producers.

According to the research of Andare et al. (2016), the first step of eco-design is drafting of design concepts for the new mobile phone. An LCA of the old mobile phone should be conducted. LCA scores of the eco-metrics of old mobile phones are used to develop a concept of a new model. The second step is planning for the new mobile phone with sharp environmental requirement targets in the design of the new product. The third step is the development of the new mobile phone and selling of the new product. The fourth step is consumer validation of the new product among a small group of consumers. Sometimes the testers are mainly employees of the producer. The feedback can be used in the design of the next generation. The final step is closing the new product design project when the LCA scores of new mobile phones are satisfactory. Due to the iterative optimization, mobile phones finally sold to consumers are the version of high energy efficiency and high recyclability. The green arrow from Eco-design to Mobile phones in use in Figure 2 represents the impacts of eco-Eco-design on the mobile phones eventually owned by consumers. When this batch of mobile phones is hibernated and then collected for refurbishing, the refurbishing cost would be lower than the traditional types.

A product-based product service system was proposed in the third scenario. Mobile phone producers provide service to enhance the functionality of the product when necessary to stimulate consumers to extend the use time. In the product service system scenario, producers provide free repair if consumers have bought insurance with relatively lower price when they buy the new product, in order to encourage consumers to repair their broken mobile phones instead of changing to a new one. The blue arrow from Service back to Mobile phones in use means that after the service consumers would use the mobile phone for a longer time, and then mobile phones become hibernated.

Figure 2 Simplified description of the pathways of hibernated mobile phones in the three scenarios and the BAU scenario.

3.1.2. Causal loop diagram and system dynamic model

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among these factors. It was developed based on insights from previous studies provided in 2.4. Figure 3 presents the CLD of this study involving four causal loops. The polarity of links represents whether one factor influences the other in a positive or negative way. “B” represents a balancing loop and “R” represents a reinforcing loop.

The first loop described the mobile phone flows which was a balancing loop. If the CE was achieved in the mobile phone product system, the effective recycling of obsolete mobile phones and the use of refurbished products tended to offset part of the demand for new mobile phones. The second one was the loop of market demand, which represented the market mechanism of new and refurbished mobile phones. It was a balancing loop to keep a dynamic balance between demand for new mobile phones and refurbished ones. The third was the loop of social impact on mobile phone recycling programs and the fourth was the loop of environmental impact. These two loops were reinforcing loops, which indicated that social and environmental benefits gained from implementing CE strategies in the mobile phone product system could stimulate producers to promote the projects further.

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As Figure 4 illustrates, the model consisted of three parts: the flow of mobile phones (the implementation of Loop 1 in the CLD), the mechanism of market demand (the implementation of Loop 2), and the promotion of mobile phone recycling by producers (the implementation of Loop 3 and Loop 4). The three parts had connections with each other. The loop of mobile phone product systems began with manufacturing new products, which was affected by the demand of the market. On the other hand, the demands for new and refurbished mobile phones were influenced by the stocks of new and refurbished products on the consumers’ side. The profitability of mobile phone producers was affected by the number of obsolete mobile phones collected by producers and the number of refurbished products owned by consumers. In turn, the potential profit tended to drive producers to collect more recyclable waste mobile phones.

The main body of the model was the flow of mobile phones, which illustrated the direction and quantity of mobile phone flowing from manufacturing to usage, recycling, and end of life. The stocks represented the number of mobile phones in each stage every year and the flows revealed how the mobile phones were transferred from one stage to another with relevant factors. In this model, there were three different pathways for mobile phones ready for collection. Firstly, they could be disposed of by consumers themselves, for example, being in hibernation forever or thrown as e-waste with other types of waste. This fraction of obsolete phones was considered a loss from the mobile phone product system because they did not return to the mobile phone flow. Secondly, mobile phones could be collected by other collection systems except for producers. In this case, the waste mobile phones which could be refurbished were sent to producers in collaboration with recycling entities and the other parts were recycled or landfilled. Thirdly, the obsolete mobile phones could be collected by producers after they decided on participation in the promotion of a CE. It was assumed that producers adopting any of the three strategies would take part in the collection of old mobile phones. However, the competitiveness compared with specialized recycling entities depended on the profit from the strategies. For simplicity, the refurbished phones in storage were considered the end of the flow.

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The third part, which was concerning the core results of this study, was the producers’ profits from the strategies they had adopted. In the model, the total expected profit was the sum of direct profit and indirect profit. Direct profit corresponded to economic sustainability benefits and indirect profit included social and environmental sustainability benefits. The economic benefit was mainly from the selling of refurbished mobile phones. The social benefit was evaluated by the consumers’ WTP on mobile phone recycling, which was regarded as the potential financial benefit from reputation improvement. As for the environmental benefit, energy saving was considered in the study.

3.2. Data collection

Data collection was conducted mainly through questionnaire and literature review for the inputs of the SD model. Primary data were collected through a questionnaire to supplement the lack of the latest data of some parameters in the literature, of which the target group was residents of all ages who had lived in Shenzhen for more than two years and had no plans to leave in the next three years. The questionnaire was sent through a professional online questionnaire survey platform in China, called Questionnaire Star. Considering that there are approximately 13 million residents currently in Shenzhen, if the confidence interval was 5% and the confidence level was 95%, the sample size was suggested to be 384 with the help of a sample size calculator (Creative Research Systems, 2012). However, due to the restrictions on the time and approach of publicity, eventually, 198 valid questionnaires were returned. It led to a confidence interval of 6.96% when the confidence level remained 95%, which was still acceptable. The questionnaire used in this study is provided in Appendix B. Responses from the questionnaire were further used to analyze possible reasons of some phenomenon occurring in the model results. Apart from the questionnaire, surveys of real-time information on official websites of some mobile phone producers were conducted when necessary. Through literature review on reliable sources including peer-reviewed scientific publications in the last decade and official reports of mobile phone producers and relevant authorities, secondary data were collected.

3.3. Model setting

The setting of parameters of this model included two parts. One was the setting of initial inputs of variables, which were the default values to describe the BAU scenario. The other was the setting of parameters describing the different scenarios if mobile phone producers adopted the certain strategy. The setting of scenarios depended on previous literature and assumptions based on the socio-economic environment.

3.3.1. Initial inputs of variables

Table 2 presents the default values of parameters used in the model and their references. The default value settings referred to the BAU scenario in which mobile phone producers took no participation in waste mobile phone collection while they still cooperated with recycling entities and took responsibilities of old phone refurbishing and refurbished product selling. Table 3 provides the initial values of stocks in the model and the unmentioned stocks were set to 0 as their initial values.

In this model, Base price of new product and Ratio of refurbished product price were normalized parameters to represent the difference in prices between new and refurbished products. According to the market mechanism described in the work of Bhattacharjee and Cruz (2015), it was the price difference rather than the exact price that affected consumers’ decision-making on buying a refurbished product, therefore Base price of new product was always set to 1 as a baseline. Currently, Chinese mobile phone producers have not provided official refurbished mobile phones yet. To decide on the discount of refurbished mobile phones, the price list of official refurbished products on the website of Apple (2020) was used as a reference in this study. Considering the 9 modes presented on the website, the depreciation rate ranged from 15% to 35%. In the model, the range of Ratio of refurbished product

price was set to [65%, 85%] and the default value was set to the median. Perceived difference reflected

consumers’ cognition on the difference between new and refurbished products, which was another factor influencing their choices of buying a mobile phone. It was measured on a scale of 0 to 10 and the default value depended on the questionnaire among consumers in Shenzhen. Population growth described the growth rate of the residents in Shenzhen. The population growth would lead to an expansion of market demand.

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incite consumers to deliver their obsolete mobile phones for collection. A reasonable range of Incentive

cost was from 7.7 USD to 11 USD and the median was selected as a default value. Based on the work of

Afroz et al. (2013), the willingness-to-pay of consumers to share the cost of mobile phone recycling programs could be regarded as a monetary indicator of potential social benefits from reputation growth. In the model, it was represented by the parameter WTP. As for the environmental profit, Energy saving, which was how much cost on energy would be saved if a refurbished mobile phone replaced a new one in manufacturing phases, was used as an indicator. It was the product of the energy saved from refurbishing processes and the financial cost per unit of energy.

Collection cost was the financial cost on the collection of waste mobile phones which mainly consisted

of the collection price on buying old mobile phones from consumers and advertising costs for publicity. It was assumed that the former accounted for 80% of the total expenses on the collection and the latter accounted for 20%. The official website of Aihuishou, an electronic product recycling entity in China, provides collection prices of obsolete mobile phones. For an old smartphone in good condition, the recycling prices of popular models vary from 42 to 493 USD due to differences in brand and model (Aihuishou, 2020). The requirements for “good condition” describe the condition in which: (1) the old mobile phone could be normally turned on; (2) the personal account could be logged out; (3) the boot password would be removed; (4) the shell and the screen was flawless. The prices of 50 types of popular mobile phones were selected to calculate the average collection price, the result of which was 200 USD. Among the selected mobile phones, the collection prices of 11 types were lower than 100 USD, and 4 types required over 400 USD to be collected. Over half of the selected types needed 100~300 USD to be collected. Taking the advertising cost into account, the range of Collection cost was set to 50~620 USD and the default value was 250 USD.

Refurbishing cost represented the financial cost of refurbishing processes. According to the research of

Geyer and Blass (2010), the average refurbishing cost in the US was 2.1 USD in 2006. Considering the different socio-economic environments in China and inflation during these years with a 5% inflation rate, Refurbishing cost in the model was set to 3.74 USD, with a 20% fluctuation. Retailing profit of

refurbished product represented the gross revenue from selling the refurbished mobile phones. It was

assumed that the depreciation rate of domestic mobile phones was 30%. A market survey about the prices of new mobile phones of 5 domestic brands that are most familiar to consumers in China was conducted. It was found that the prices were in the range from 120 to 1220 USD and the average was 506 USD. Taking the 17% added-value tax in China into account, the default value of Retailing profit of

refurbished product was set to 294 USD with a range from 70 to 709 USD.

Table 2 Default values and value ranges of parameters.

Parameters Values Ranges References

Base price of new product 1 Bhattacharjee and Cruz, 2015 Ratio of refurbished

product price 75% [65%, 85%] Apple, 2020

Perceived difference 5.66 (0, 10] Estimated from the questionnaire _{and Bhattacharjee and Cruz (2015)} Population growth 3% Statistics Bureau of Shenzhen _{municipality, 2019} Use time of new product 2.32 year (0, 5] Questionnaire

Use time of refurbished

product 1.86 year (0, 4]

Assumed (80% of that of new product)

Storage time 1.82 year Questionnaire

Awareness 0.5 (0, 1] Bollinger and Blass, 2012

Accessibility 0.5 (0, 1] Bollinger and Blass, 2012 Incentive cost 9.35 USD [7.7, 11] Bollinger and Blass, 2012

WTP 2.93% [0, 100%] Estimated from the questionnaire

Fraction of recyclable

phones 80% (0, 100%) Assumed

Energy Saving 3.6 USD/phone Socolof et al., 2007

Collection cost 250 USD/phone [50, 620] Estimated from the survey on the _{official website of a recycling entity} Refurbishing cost 3.74 USD/phone [2.99, 4.49] Geyer and Blass, 2010

Retailing profit of

refurbished product 294 USD/phone [70, 709]

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The initial value of Market demand, New product in consumption, and Phones put in storage was estimated from the report of the Statistics Bureau of Shenzhen municipality (2019) which provided information on population and the questionnaire which involved consumers’ demand and ownership of mobile phones in Shenzhen. According to the annual report of Huawei (2020), the annual output of mobile phones was 27 million, of which 59% were manufactured and sold in China and Shenzhen accounted for about half of China’s mobile phone production. Considering the market share in China of Huawei was 38.5%, the total production of new mobile phones in Shenzhen was about 20 million. New

product in stock represented the stock of mobile phones stored by mobile phone producers which was

assumed to be 10% of the production. Taking the output expansion from 2010 to 2019 into account, the initial value of New product in stock was set to 0.97 million.

Table 3 Initial stock values for the SD model. (All other stocks were set to 0.)

Stocks Values Reference

Market demand 6.2 million Statistics Bureau of Shenzhen municipality, ₂₀₁₉ New product in stock 0.97 million Huawei, 2020

New product in consumption 3.53 million Estimated from questionnaire and Statistics _{Bureau of Shenzhen municipality (2019)} Phones put in storage 5.13 million Estimated from questionnaire and Statistics _{Bureau of Shenzhen municipality (2019)}

3.3.2. The setting of three scenarios

The specific value settings under the three scenarios are provided in Table 4, with a comparison with the BAU scenario. The three strategies were selected in the study because they contributed to the promotion of a CE and there were legislation bases for the strategies. Since the exact values of these variables vary from brands, modes, target groups of consumers, and other factors, this study only provided a rough estimation of the trend of profits if mobile phone producers adopted the strategy. The first strategy was to launch an old-for-new program by producers themselves, without the help of recycling entities for waste mobile phone collection. Since the old-for-new policy was issued in 2009, old-for-new has been relatively widely used in China (Zeng et al., 2017). Old-for-new programs allow materials to be used again, which is one of the principles of the CE. By now, 29 Chinese mobile phone producers have participated in an old-for-new program launched by the recycling organization Aihuishou (Aihuishou, 2020). Consumers can either contact the recycling entity online or bring obsolete mobile phones to offline stores which are often located in subway stations and shopping malls with high passenger flow. Among these mobile phone companies, more than 5 have promoted their own old-for-new program on their own official website (Aihuishou, 2020). Different from specific recycling entities, producers only accept obsolete mobile phones in good condition which can be refurbished. Currently, collecting old mobile phones by producers themselves is only achieved online, with no collecting centers offline. Consequently, producers tend to cover reverse logistics fees.

To simulate Scenario 1, Incentive cost was selected to a relatively low value because the old-for-new policy was related to consumers’ financial benefit directly, and for producers Retailing profit of

refurbished product and Collection cost were low because in this scenario, producers were expected to

provide more discounts on the products to attract consumers but collection cost for buying the old mobile phones from consumers could be reduced. The old-for-new program provides consumers with a clear pathway to deal with their idle mobile phones so that the value of Accessibility in the model was higher than usual.

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the next generation of phones and how changes in legislation affect product development. The features are then translated into specific requirements and designers come up with new models to satisfy these requirements.

The goal of eco-design was to improve recyclability, recoverability, reuse-ability, and disassemble-ability (Zeng and Li, 2016). As a result, the refurbishing of the collected old mobile phones was expected to be easier and cheaper, and the quality of the refurbished mobile phones was expected to be better. In Scenario 2, Refurbishing cost was set to a low value and Retailing profit of refurbished product was high. Besides, eco-design would increase energy efficiency during the manufacturing phase and the refurbishing phase. The energy reduction in both of the two processes was assumed to be 20% so that the difference in the energy consumption between refurbishing an old mobile phone and manufacturing a new one would become 80% of that of the BAU. In other words, the value of Energy saving was 80% of that in the BAU scenario.

The third strategy was to enhance the product service system for mobile phones. Implementing a product service system may lead to fewer product sales and more provided service of producers so that stakeholders would face new responsibilities (Beuren et al., 2013). In current China, product service systems implemented into the mobile phone product system are mainly achieved by promoting more convenient repairing services to consumers to enhance the functionality of mobile phones (Liang et al., 2013). As a result, keeping products in use could be potentially achieved. However, as Liang et al. (2013) stated, the development of mobile phone product systems in China lacked consumers’ acceptance. For instance, the lease service of mobile phones or components of mobile phones was accepted by a minority of consumers. Consequently, mobile phone producers were recommended to begin with repair service of higher convenience and lower prices to increase consumers’ trust and their reputation among consumers (Liang et al., 2013).

In Scenario 3, the Use time of new and refurbished mobile phones was extended but Fraction of

recyclable mobile phones was reduced because it was assumed that when the mobile phone was slightly

broken, consumers tended to choose the repair service instead of recycling so that the collected mobile phones by recyclers were more likely to be beyond economic recycling. For producers, enhancing the product service system led to lower Collection cost because the recycling price of repaired mobile phones was lower than those without any repair, and higher Refurbishing cost due to the expected lower quality of collected waste mobile phones.

Table 4 Scenario setting. "/" means the value under this scenario was the same as that in the base case.

BAU _Old-for-newScenario 1: Scenario 2: _Eco-design _{Product service system}Scenario 3:

Incentive cost (USD) 9.35 7.7 / /

Accessibility 0.5 0.8 / /

Fraction of recyclable phones 0.8 / / 0.64

Collection cost (USD) 250 100 / 150

Refurbishing cost (USD) 3.74 / 2.99 4.49

Retailing profit of refurbished

product (USD) 294 235 353 /

Use time of new product (years) 2.32 / / 5

Use time of refurbished product

(years) 1.86 / / 4

Energy saving (USD) 3.6 / 2.88 /

3.4. Model testing

Firstly, the model was verified according to the causal loop in Figure 2 to check whether the model could output what it was expected to do. Verification can be conducted with the following methods (Golroudbary and Zahraee, 2015):

● To present the exact definition and purpose of variables and their relative equations. ● To have the model including flows and equations peer reviewed.

● To draw another flowchart according to the flows in the model and then to compare it with the original CLD.

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In this study, verification was achieved by examining the statistical structure of the model, including all relevant variables and the whole process, to check whether the logic in the CLD was followed. Next, the dynamic behavior of the model was examined through the structure-oriented behavior test in which extreme values of some selected parameters were applied to the model to inspect the plausibility of the responses in extreme cases. For example, the extremely low consumers’ perceived difference of which the value was close to zero, no hibernation time, no recycling cost (under this circumstance the parameter values of Perceived difference, Storage time, and Collection cost were set to 0.001) were checked as well as the exact opposite (under this circumstance, the value of Perceived difference was 10 which was the upper limit of the range, Storage time was assumed to be 50 years, and Collection cost was set to 620 which was the upper limit of the actual range of recycling cost). The model worked as usual under the extreme circumstances with no bugs, demonstrating compliance with the results of the structure-oriented behavior test.

Then, the model was validated with field data on market demand and EoL scenarios. Figure 4 presents the annual market demand for mobile phones including new products and refurbished ones from 2011 to 2018. The solid line represents the outputs of this model. In the simulation, the initial (2010) market demand was set to 6.2 million in total (Statistics Bureau of Shenzhen municipality, 2019) and the annual market demand in the following years was calculated as the sum of the unmet demand of the previous year and the new demand caused by population growth (Cao et al., 2016b). The symbols represent model-independent observations from the report of the Statistics Bureau of Shenzhen municipality (2019). The average deviation between modeled and observed amount of market demand was around 5.8% which was acceptable.

Figure 5 Annual market demand from 2011 to 2018. Symbols represent statistics from the Statistics Bureau of Shenzhen municipality (2019) while solid lines represent model estimation from this study.

The comparison of EoL scenarios between the model outputs and observation is demonstrated in Table 5. The model average values were calculated under the condition that the producers’ recycling cost was low with moderate consumers’ willingness. The model-independent data for testing were from Qu et al. (2013) for the situation from 2011 to 2012 and the analysis of Shenzhen Mobile Communication Association (2018) for the situation from 2012 to 2018. As Table 5 presents, the model outputs were within reasonable limits. As a result, the model performance was considered satisfactory for the study purpose.

Table 5 EoL scenarios distribution from model outputs and field observations.

EoL scenarios Model average _(2011-2018) _(2011-2018)Field range

Disposed by consumers themselves 66% 50-80%

Collected by recycling entities 34% 15-40%

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3.5. Assumptions and limitations

Simplified from the real situation, the model was established based on some assumptions:

1. After the Collection and Treatment Decree on Wastes of Electric and Electronic Equipment was enacted in 2011, formal collection and recycling entities and consumers began paying attention to mobile phone recycling. In other words, the baseline of the model was 2010. As this is a forward model study, mobile phone producers were assumed to take actions from 2021, which meant from 2010 to 2020, producers did not participate in waste mobile phone collection. 2. In general, the end of life of obsolete mobile phones goes to four different pathways: collected

by mobile phone producers themselves, collected by peddlers, collected by specialized collectors, and sold directly in secondhand markets (Qu et al., 2013). Considering the major target group of this work was mobile phone companies, i.e. mobile phone producers, the phones collected in other ways were assumed to be treated in the same way and the average data in these cases are used. Meanwhile, it was assumed there was cooperation between producers and other recycling sectors. The refurbished mobile phones from other recycling entities still flowed to producers to be sold.

3. Possible fates of EoL phones include recycling, parts reuse, slight repair, and full refurbishing (Bollinger and Blass, 2012). However, only full refurbishing with metal or component recovery was considered in the pathway of phones collected by producers.

4. Taking the breakage of mobile phones during recycling and the simplicity of the model into account, multiple recycling was neglected.

5. Mobile phone producers were assumed to have abundant space to store the unsold refurbished mobile phones when the market demand for refurbished products was less than the stock. 6. As for the demand factors, the demand of retailers for new phones was assumed to be 120% of

that of consumers. It was the same as the demand for refurbished phones.

7. The use time of new phones is always shorter than the expected lifetime, which means that mobile phones are put in hibernation before they break down (Li et al., 2015). It was assumed the use time of refurbished phones was 80% of that of new ones since consumers tended to believe the quality of refurbished mobile phones was poorer and the use time should be shorter. On the other hand, the storage time of new products and refurbished ones was the same. 8. It is assumed in the BAU scenario, the recycling entities in collaboration with producers shared

20% of the profit from selling the refurbished mobile phones.

Moreover, there are some limitations of the method used in this work due to the limited time and other factors:

1. The model can be only used to represent and predict the situation in the short term because the long-term market changes can be hard to predict. Considering that the wide promotion of any of the three strategies took some time to obtain a steady potential profit, the definition of a short term was 20 years (from 2021 to 2040) in this study.

2. When conducting the questionnaire, everyone had only one mobile phone in use by default and other phones were considered to be in hibernation. However, some people need two or more mobile phones in use in the meanwhile as required by their work. As a consequence, the results of the model might not fully reflect the actual situation.