1. Introduction
Recent years have witnessed an increase in e-waste with rapid advances in electronic products. Global E-waste Monitoring 2020 reported that 53.6 million metric tons of e-waste were generated globally in 2019 (
https://news.un.org/zh/story/2020/07/1061272 (accessed on 10 October 2021)). Recycling of used mobile phones has attracted great attention of society due to the corresponding economic and environmental benefits [
1,
2]. With accelerated replacement of mobile phones, massive quantities of used mobile phones are recyclable. An online report estimated the scrap volume of China’s mobile phones to be 303.933 million in 2018 (
https://www.boolv.com/html/news/5452.html (accessed on 10 October 2021)). Incidentally, there is an urgent need to innovate the recycling channels for used mobile phones, encourage customers to actively participate in recycling, and realize the recycling and reuse of used mobile phones [
3,
4]. In this context, online recycling, which combines the used mobile phone recycling business with the Internet, is developing rapidly.
In the booming Internet economy, many online recycling platforms (ORPs) dedicated to the recycling business, e.g., European Recycling Platform, Aihuishou (China), and the ecoATM, have sprung up [
5,
6,
7]. The recycling service covering inspection of the mobile phone’s conditions and house-call has become an important competitive advantage of an ORP [
8,
9]. However, online recycling lacks standards and rules and has a low market share. In its Second-hand Mobile Phone Industry Research Report released in 2019 (
http://www.199it.com/archives/822527.html (accessed on 1 October 2021)), 36kr.com (accessed on 1 September 2021) (an Internet media) estimated that only 20% of second-hand mobile phone transactions in China were completed online. The main reasons are: (1) it is difficult for customers to participate in recycling bargaining as the pricing power of used mobile phones is in the hands of the recycling firms, and (2) customers are reluctant to participate in online recycling due to a lack of convenient recycling scenarios and costumers’ distrust of the recycling platforms (
https://www.sohu.com/a/428062874_100014482 (accessed on 10 October 2021)). Thus, addressing the two problems of recycling pricing and recycling service is key to developing online recycling. Although the online recycling price is relatively open and transparent, customers have to make a quick decision whether or not to recycle their phones once the price is given, and they have no opportunity to negotiate with the recyclers. Without reasonable pricing of used mobile phones, customers are unwilling to recycle, which depresses the recycling rate. Moreover, the ORP, which directly interacts with customers, should provide customers with a satisfactory recycling service; otherwise, the recycling experience of customers will be adversely affected, leading to diminished recycling transactions. Thus, a better understanding of the pricing and the service strategy for online recycling will benefit the members of the online reverse supply chain.
Currently, most online recycling studies focus on the manufacturer’s choice of dual recycling channels [
10,
11], pricing strategies for the traditional and online recycling channels [
12,
13], and impacts of customer preferences of the choice of the dual recycling channel and recycling pricing strategy [
9,
14]. Meanwhile, customers’ willingness of online recycling (CWOR) is another driver of recycling of used mobile phones [
15]. From the development law of the Internet economy, customers’ involvement is crucial for the success of the online economy. Different from the forward sales channels, used mobile phone recycling is not a solid demand of customers and the frequency of recycling is limited, and it is not worthy of attracting customers through the high-price recycling strategy. To stimulate customers’ participation in recycling, the influencing factors of CWOR must be explored. Additionally, Previous studies consider customers’ recycling behavior from the perspectives of information security, service convenience, and platforms’ transaction behavior [
8,
16,
17,
18]. However, these studies did not verify the relationship between recycling service and recycling willingness.
Therefore, in the context of online recycling, on the one hand, the paper develops a game model of a supply chain comprising a mobile phone manufacturer (MPM) and an ORP incorporating the recycling service as the decision variable, and analyzes the correlation between recycling service decisions and system operation. On the other hand, the study empirically explores the moderating effects of consumers’ demographic characteristics and mobile phone usage on the relationship of recycling service and CWOR. Notably, in terms of empirical researches, Yuan et al. [
18] and Yin et al. [
19] also explored the factors influencing CWOR to recycle used mobile phones. Among them, Yuan et al. [
18] analyzed whether recycling facilities and services affect consumers’ reusable mobile phone transaction behavior, but did not further explore the impact of recycling services on the reverse supply chain or what factors affect recycling services. Yin et al. [
19] examined the influence of consumers’ personal characteristics on CWOR and did not consider the possible influence of the market environment, including recycling services. In the study of the theoretical model, Wei et al. [
20] consider recycling service costs in their theoretical model, but they do not explore the effect of recycler services on CWOR. Pourhejazy et al. [
21] consider two types of waste electrical and electronic equipment (WEEE) recycling services in their model, but they focus on the trade-off between profit and service tubes for collectors. Giri et al. [
22] examines pricing and product recycling strategies that include online channels, but they focus on the impact of recycling channels and dominant models on supply chain performance.
Developing a game model and an empirical model to study the influencing factors of CWOR, we seek to address three research questions as follows:
How does the recycling service affect CWOR?
What other factors affect CWOR?
Do customers’ demographic characteristics and mobile phone usage pattern moderate the recycling service–CWOR link?
The innovation of our study lies in the game model we develop to analyze the service strategy for online recycling from the perspective of operations management. Based on the analytical findings, we apply structural equation modelling (SEM) to empirically examine the influencing factors of CWOR from the perspective of customers. We find that recycling services directly and indirectly affect CWOR of used mobile phones. Specifically, our major findings are as follows:
First, the MPM’s profit mainly depends on the quantity of mobile phones recycled. When the recycling commission changes, the MPM’s profit and recycling quantity are affected by customers’ preference of recycling and the ORP’s service cost coefficient. In addition, the impacts of customers’ preferences of the recycling price and recycling service on the MPM’s profit and recycling quantity depend on the service cost coefficient. The MPM can use a high recycling price to directly promote the recycling of used mobile phones. The MPM can offer a higher recycling commission to induce the ORP to provide customers with a better recycling service, which indirectly stimulates customers’ recycling activity. However, the effectiveness of these methods depends on the ORP’s service cost coefficient, and customers’ preferences of the recycling price and recycling service.
Second, the ORP’s profit is independent of the service cost coefficient and customers’ preference of the recycling service, but is associated with customers’ preferences of the external factors of the ORP. The ORP’s profit increases with customers’ voluntary recycling quantity and customers’ preference of the recycling price. Counterintuitively, increasing the recycling commission is not always beneficial to the ORP. The impact of the recycling commission on the ORP’s profit depends on customers’ preference of the recycling price. Therefore, instead of only considering its own cost constraints, the ORP should consider customers’ preference of the recycling price in deciding its recycling commission.
Finally, the recycling service level and customers’ environmental consciousness positively affect CWOR, and EP enhances environmental consciousness. Moreover, in terms of customers’ demographic characteristics and mobile phone usage pattern, we find that customers’ age, usage time of current mobile phones, and cumulative numbers of mobile phones owned are significantly related to their level of environmental consciousness. There are significant differences in CWOR of customers with different education levels and cumulative numbers of mobile phones owned. Customers’ age and income moderate the recycling service–CWOR link. The implication is that the online reverse supply chain should focus on improving the recycling service quality in view of the heterogeneity of customers and on strengthening recycling promotion.
We organize the rest of the paper as follows: In
Section 2, we review the related studies to identify the research gap and position our study in the literature. In
Section 3, we introduce the model of online recycling of used mobile phones, present the notation, and discuss the assumptions. In
Section 4, we analyze the model and derive the analytical results. In
Section 5, we present the empirical research and discuss the empirical findings. Finally, in
Section 6, we conclude the paper, discuss the management insights of the research findings, and suggest topics for future research. We present the proofs of all the results in the
Appendix A and
Appendix B.
3. Model of Online Recycling of Used Mobile Phones
3.1. Model Description
We consider an online reverse supply chain comprising an MPM and an ORP, where the former relies on the latter to recycle used mobile phones with a certain residual value, as shown in
Figure 1. The MPM focus on residual value of used mobile phones and publishes the information about recycling phones on the ORP, including the phone type, phone quality requirements, and recycling price. The customer browses the recycling information on the ORP and submits information about their used mobile phone (e.g., the shell condition and the mobile phone performance) that he wants to recycle. The customer can mail their used mobile phone to the ORP or wait for the staff from the OPR to pick up the phone. The customer’s recycling can be completed only after completion of the inspection of the used mobile phone. In this process, the MPM pays a commission to the ORP based on the quantity and quality of the recycled phones and benefits from the residual value of the used mobile phone. The ORP is responsible for the services during the recycling process.
The MPM entrusts the ORP to recycle used mobile phones and the revenue of the ORP mainly depends on recycling, which disadvantages the OPR in the system’s decision-making process. So, we make the following major assumptions.
- (1)
The MPM dominates the decision-making in the online reverse supply chain.
- (2)
Both the MPM and ORP are rational and have symmetrical information.
- (3)
The ORP strictly evaluates the recycled phone to ensure that it has the recycling value.
We use following notation throughout the paper.
: Residual value of a used mobile phone.
: Recycling price of used mobile phone. It is the decision variable of the MPM.
: Recycling commission charged by the ORP. so that it is profitable for the MPM to recycle mobile phones. Given that aihuishou.com settles the commission payment with the MPM once a month, we take the recycling commission as an exogenous variable in this study in order to focus on the recycling service.
: Recycling service level provided by the ORP for the MPM. It is a decision variable of the ORP. Following Bakal and Akcali [
45], we assume that the service cost is
, where
is the service cost coefficient.
: Recycling quantity of used mobile phones, which is positively affected by the recycling price and recycling service level. Following Wu [
46], we assume that the recycling quantity satisfies the following condition
where
represents the voluntary recycling quantity, i.e., the quantity of used mobile phones recycled for free due to customers’ environmental consciousness; and
and
denote customers’ preferences of the recycling price and recycling service, respectively, i.e., the price and service elasticities of the recycling quantity.
It follows that the MPM’s profit is
and the ORP’s profit is
3.2. Model Solution
As independent economic entities, the MPM and ORP interact and make decisions to maximize their own profits, constituting a Stackelberg game. First, the MPM sets the recycling price
, then the ORP determines the corresponding recycling service level
. We use the backward induction approach to derive the optimal decisions of the game players [
47].
From Equation (3), we have
, so
is a concave function in
. Solving
yields
Substituting Equation (4) into Equation (2) yields
From Equation (5), we have
, so
is concave in
. Solving
yields
So, the optimal decisions are as follows: The recycling price is , the recycling service level is , the recycling quantity is , the MPM’s profit is , and the ORP’s profit is . Accordingly, we derive the following result.
Lemma 1. (1) The recycling commission should be reasonably set at , and (2) The residual value of the used mobile phone should be.
We derive Lemma 1 from the fact that the recycling price, recycling service level, recycling quantity, recycling quantity, MPM’s profit, and ORP’s profit are positive. Lemma 1 shows that the recycling commission should be in a proper range to ensure normal operations of the ORP. An excessive recycling commission is not conducive to cooperation between the MPM and ORP, and is detrimental to the ORP. The greater the voluntary recycling quantity is, the smaller is the range of the recycling commission for the ORP, i.e., the upper limit of the recycling commission is reduced. Therefore, increasing the voluntary recycling quantity enables the MPM to squeeze the recycling commission, raising the MPM’s recycling enthusiasm.
On the other hand, Lemma 1 signifies that not all used mobile phones have recycling value, and the MPM should identify the types of acceptable used mobile phones and publishing the corresponding recycling information. This also explains the phenomenon in real practice that the MPM is more willing to recycle recent mobile phone models than old models. This is because the parts of old mobile phones are obsolete and cannot be utilized in the development and production of new mobile phones. This also reminds the customer that they should recycle their used mobile phone as soon as possible to secure the returns.
Lemma 2. (1) When , increases with , but the increasing trend becomes flat, and (2) when , decreases with and the decrease becomes more evident.
We derive Lemma 2 from the ORP’s profit function, i.e., Equation (3). The ORP’s profit is concave in the recycling service level. When the recycling service level is low, the ORP can improve its service to increase the recycling quantity and increase its profit, but the marginal effect will gradually decrease with the improvement of the service level. When the service level is high, e.g., , although a better service can promote the recycling of used mobile phones, the ORP will incur a higher service cost, so the profit decreases with the improvement of service.
4. Model Analysis
4.1. Theoretical Analysis
Proposition 1. (1) The optimal recycling service level is positively related to customers’ preferences of the recycling serviceand recycling commission. (2) The optimal recycling priceis negatively related to the recycling commission.
(Proposition is obtained by finding partial derivative for and the partial derivative of for and , respectively.)
With an increase in , the customer becomes sensitive to the recycling service. To improve the recycling quantity and recycling profit, the ORP should provide a better recycling service to attract more customers. An increase in the recycling commission means that the ORP can obtain more commission income, which offsets the recycling service cost, so the recycling service will be improved. Moreover, an improvement in the recycling service can attract more customers to participate in recycling, so the MPM will reduce the recycling price to cope with the cost pressure caused by the increased recycling commission.
As the recycling commission increases, the MPM’s pricing strategy and the ORP’s service strategy show opposite changes. This is mainly because the two strategies are mutually substituting in terms of attracting customers to recycle used mobile phones. The MPM as the dominant player can change its pricing strategy in the opposite direction of the OPR’s service to maximize the MPM’s profit.
Proposition 2. (1) The optimal recycling quantity and the MPM’s optimal profit are positively correlated with the voluntary recycling quantity , and customers’ preferences of the recycling price and the recycling service. When , the recycling quantity and the MPM’s profit are positively correlated with the recycling commission ; when , the recycling quantity and the MPM’s profit are negatively correlated with the recycling commission.
(2) Customers’ preferences of the recycling price and recycling service and have different degrees of impact on the optimal recycling quantity and the MPM’s optimal profit . When , where , the recycling quantity is more affected by costumers’ preference of the recycling price; when , the recycling quantity is more affected by customers’ preference of the recycling service. Similarly, when , where, the MPM’s profit is more affected by costumers’ preference of the recycling price; when , the MPM’s profit is more affected by customers’ preference of the recycling service.
It is noted that the MPM’s profit is mainly decided by the quantity of recycled phones. Both the MPM’s profit and the quantity of recycled phones are affected by system parameters. Specifically, the higher the customers’ voluntary recycling quantity is, the higher are the recycling quantity and the MPM’s profit. When customers’ recycling behavior is more susceptible to the recycling price and recycling service, the MPM and ORP gain more flexibility in adjusting their recycling pricing and service strategies. Therefore, the recycling quantity and the MPM’s profit increase with customers’ preferences of the recycling price and recycling service.
Although customers’ preferences of the recycling price and recycling service can increase the recycling quantity and the MPM’s profit, their effects are different. When the service cost coefficient is large (), the recycling quantity and the MPM’s profit are more affected by the preference of the recycling price; but when the service cost coefficient is small (), the recycling quantity and the MPM’s profit are more affected by the preference of the recycling service. Therefore, the MPM can directly stimulate the customer to recycle their used mobile phone by increasing the recycling price. The MPM can also encourage the ORP to provide a higher recycling service level by accepting a higher recycling commission to indirectly increase the recycling quantity.
Since increasing the recycling commission can increase the recycling service level and reduce the recycling price, the impacts of the recycling commission on the recycling quantity and the MPM’s profit are uncertain. When the customer has a higher preference for the recycling service, e.g., , it is effective to indirectly increase the recycling quantity through a higher recycling commission because the recycling quantity and the MPM’s profit increase with the recycling commission. However, when customers preference of the recycling service is low, e.g., , the indirect method of a higher recycling commission is not helpful because the recycling quantity and the MPM’s profit decrease with the recycling commission.
Proposition 3. The ORP’s profit is positively related to customers’ voluntary recycling quantityand preference of the recycling price. When, the ORP’s profit is positively related to the recycling commission; when, the ORP’s profit first increases and then decreases with the recycling commission, and maximum profit is obtained when, where.
The ORP’s profit is independent of the service cost coefficient and customers’ preference of the recycling service , but depends on customers’ voluntary recycling quantity and preference of the recycling price . With an increase in preference of the recycling price, the recycling service remains unchanged, but an increase in the recycling price helps improve the recycling quantity, so the ORP’s profit increases. Similarly, when the voluntary recycling quantity increases, the ORP obtains additional recycling quantity and profit.
Besides, an increase in the recycling commission inevitably causes the MPM to reduce the recycling price, while also stimulating the ORP to improve the recycling service level and increase the service cost. Therefore, the impact of the recycling commission on the ORP’s profit is not certain. When the customer is not sensitive to the recycling price, i.e., , although an increase in the recycling commission reduces the recycling price, the recycling quantity is less affected. An improvement in the recycling service helps increase the recycling quantity, so the ORP profits more as the recycling commission increases. When the customer is sensitive to the recycling price, i.e., , although an increase in the recycling commission brings a short-term increase in the ORP’s profit, the decline in the recycling price makes the recycling quantity decrease and the service cost rises due to the higher recycling service level, ultimately reducing the ORP’s profit as the recycling commission increases. Therefore, in real practice, the ORP needs to consider customers’ recycling preference when setting the recycling commission.
4.2. Numerical Studies
We conducted numerical studies to verify the analytical findings and ascertain the impacts of different model parameters on the optimal decisions. The values of the parameters should match the model description and fit the conditions in the lemmas and propositions. Setting
,
,
, and
, we analyze the impacts of the recycling commission on the MPM’s profit in two cases where we set customers’ preference of the recycling service as
and
to denote the customer with a strong and a weak preference for the recycling service, respectively. We show in
Figure 2 changes in the MPM’s profit with the recycling commission in the two cases (the ranges of the recycling commission are different in the two cases and we round down the upper limit).
Then, we set
,
,
, and
to analyze the impacts of the recycling commission on the MPM’s profit under different customers’ preference of the recycling price. When
, it denotes that the customer has a weak preference for the recycling price, while
denotes that the customer has a strong preference for the recycling price. We show in
Figure 3 the relationships between the ORP’s profit and the recycling commission in the two cases (the ranges of the recycling commission are different in the two cases and we round down the upper limit).
Figure 2 and
Figure 3 show that the recycling commission, the setting of which involves customers’ preferences of the recycling price and recycling service, is an important factor affecting the MPM’s and ORP’s profits. For the MPM, the impact of the recycling commission on profit depends on customers’ preference of the recycling service. A higher recycling commission will produce more profit when the customer has a high preference for the recycling services while it hurts the profit if customers’ preference is low. For the ORP, the impact of the recycling commission mainly depends on customers’ preference of the recycling price. When customers’ preference of the recycling price is low, increasing the recycling commission helps increase the ORP’s profit, but the growth gradually decreases. When customers’ preference of the recycling price is high, an increase in the recycling commission does not always help improve the ORP’s profit, which renders the ORP’s profit decrease if the recycling commission exceeds a particular value, i.e.,
in
Figure 3b.
Although the above analysis shows that customers preferences of both the recycling price and recycling service have impacts on the MPM’s profit, understanding of the differences between these two types is limited. In this subsection, we conduct a comparative analysis through numerical studies. Letting
,
, and
, we assume that
,
, and
. Suppose the service cost coefficient satisfies
and
for the two cases where the service cost coefficient is small and large, respectively. We show in
Figure 4 changes in the MPM’s profit under different service cost coefficients.
We see that customers’ preferences of the recycling price and recycling service have different degrees of impact on the MPM’s profit. When the service cost coefficient is small, customers’ preference of the recycling service has a greater impact on the MPM’s profit than customers’ preference of the recycling price. The main reason is that the recycling service is better when the service cost coefficient is small, which is conducive to promoting the recycling of used mobile phones. However, when the service cost coefficient is large, customers’ preference of the recycling price has a greater impact on the MPM’s profit because the recycling service is worse, and the online reverse supply chain cannot effectively respond to customers’ service demand.
In addition to the above model parameters, customers’ voluntary recycling quantity also affects the process of recycling used mobile phones. Setting
,
,
,
, and
, we show in
Figure 5 the impacts of the voluntary recycling quantity on the recycling quantity, and the MPM’s and the ORP’s profits.
The recycling quantity of used mobile phones increases with the voluntary recycling quantity. Moreover, an increase in the voluntary recycling quantity increases the MPM’s and ORP’s profits, which means that it is always beneficial to increase customers’ voluntary recycling quantity from the perspectives of environmental protection and the online reverse supply chain.
The voluntary recycling quantity, and customers’ preferences of the recycling price and recycling service are related to customers and reflect customers’ attitude towards online recycling and their recycling behaviors, so we refer to them as parameters of CWOR. We see that an increase in any of the parameters of CWOR increases the quantity of recycled mobile phones (arrowheads with solid lines in
Figure 6).
In
Figure 6, the direct impact of the recycling service level as well as CWOR (including
,
, and
) on recycling is straightforward. As the main factor studied in the theoretical model, the service level can be regulated by ORP, and it is easy to achieve the optimal service strategy given by the model. However, consumer intention, also a major factor, on the one hand, cannot be analyzed in depth as an exogenous variable in the theoretical model. On the other hand, it is difficult for MPM and ORP to regulate it to a level beneficial to the reverse supply chain. Therefore, based on the theoretical model, this paper constructs a structural equation model to further explore CWOR and mainly answer the following questions. What factors affect CWOR? How can MPM and ORP effectively contribute to CWOR? The empirical analysis is presented in the next section as a further extension of the theoretical analysis and numerical studies.
6. Conclusions
Currently, many ORPs participate in recycling and the online recycling of used mobile phones is especially popular. We constructed a game model of online recycling of used mobile phones to explore the MPM’s and ORP’s recycling decisions. We also examined the influencing factors of CWOR from the perspective of customers. We observed the following findings.
First, from the perspective of the MPM, the profit mainly depends on the recycling quantity of mobile phones. Both the recycling quantity and the MPM’s profit increase with the voluntary recycling quantity and customers’ preferences of the recycling price and recycling service. Moreover, the impacts of customers’ preferences of the recycling price and recycling service on the MPM’s profit and recycling quantity depend on the service cost coefficient. A larger service cost coefficient represents a greater impact of customers’ preference of the recycling service, while a smaller service cost coefficient corresponds to a greater impact of customers’ preference of the recycling price.
Second, the ORP’s profit is independent of the service cost coefficient and customers’ preference of the recycling service. The ORP can benefit more from increases in customers’ voluntary recycling quantity and customers’ preference of the recycling price. When customers’ preference of the recycling price is low, the ORP should increase the recycling commission to guarantee its profit. When customers have a high preference for the recycling price, since the recycling quantity decreases due to the negative correlation between the recycling price and recycling commission, the ORP’s profit increases first and then declines with the recycling commission. Therefore, the ORP should set an appropriate recycling commission according to customers’ preference of the recycling price.
The empirical research on the influencing factors of CWOR illustrates that the recycling service and customer environmental consciousness have significant positive impacts on CWOR, and EP has a significant positive impact on customers’ environmental consciousness. Customers of different ages, current mobile phone usage times, and cumulative numbers of mobile phones owned have significant different impacts on environmental consciousness. Customers with different education levels and cumulative numbers of mobile phones owned have significant differences in CWOR. Age and income moderate the relationship between the recycling service–CWOR link.
For supply chain firms, the recycling of used mobile phones is not only a pathway to reduce their production costs but also a manifestation of their corporate social responsibility. Online recycling has shown promising development prospects, so cooperation between the MPM and ORP should be strengthened to encourage customers to actively participate in online recycling. Specifically, the management implications of our research findings are as follows:
(1) The MPM can encourage customers to recycle used mobile phones in two ways: directly increase the recycling price or indirectly encourage customers to recycle by accepting a higher recycling commission to improve the recycling service level. The MPM needs to find the most effective method and make rational decisions based on the ORP’s service cost coefficient and customers’ preferences of the recycling price and recycling service.
(2) Playing an important role in online recycling of used mobile phones, the ORP should not be constrained by its service cost coefficient but should have an overall view and pay attention to customers for long-term development. The ORP should analyze customers’ preferences of the recycling service and recycling price through market research, and the ORP should set a reasonable recycling commission to strengthen cooperation with the MPM. Moreover, the recycling service positively affects CWOR, which can indirectly increase the recycling quantity. Therefore, the ORP should focus on providing a high-quality and reliable recycling service.
(3) From the perspective of customers, raising customers’ awareness of environmental protection is conducive to increasing CWOR, thereby promoting recycling and sustainability development. Therefore, the MPM, ORP, and relevant government departments involved in used mobile phones recycling need to strengthen the publicity of online recycling of used mobile phones, innovate the publicity methods, and enrich the publicity content.
We conducted a theoretical analysis of the recycling service strategy for the online reverse supply chain for used mobile phones and an empirical analysis of the influencing factors of CWOR. There are still some limitations in this paper, and we will explore the following three perspectives in the future: (1) in the reverse recycling process of used mobile phones, ORP and the MPM may have a cooperative relationship that shares the recycling revenue, similar to a revenue-sharing contract. This contract will affect the recycling service level and the recycling motivation of supply chain participants. In the future, we will reflect this cooperative relationship in our theoretical model and further explore the service strategy of the reverse recycling supply chain. (2) In the real reverse recycling supply chain, ORP often cooperate with multiple MPMs, and there may be MPMs with greater channel power, and we will consider this situation in our future research. (3) This paper demonstrated the influence of CWOR on the recycling volume of used mobile phones. How the government can make use of CWOR’s influencing factors for subsidies or policy settings to regulate the used mobile phone recycling industry and reduce the environmental pollution caused by mobile phone disposal is also a question we would like to explore in the future.