Return Strategy of E-Commerce Platform Based on Green and Sustainable Development

Abstract

The secondary packaging and secondary transportation caused by products’ online return lead to a large amount of resource waste and environmental damage, which are not conducive to the green and sustainable development of enterprises. As consumers become more aware of environmental protection, their purchase and return behaviors will also change, prompting e-commerce platforms to adjust their return strategies. In this context, this paper aims to study the optimal return strategy that balances enterprises’ social benefits and environmental impact. The Stackelberg game models are constructed based on two behaviors: environmental protection publicity of e-commerce platforms and consumer return. The impacts of return strategies on the environment and the benefits of supply chain members are investigated. Results show that environmental protection publicity and return compensation can stimulate the expected sales volume. The optimal environmental protection publicity depends on the return rate. When the return rate is high, and the repurchase price is low, the optimal decision of the e-commerce platform is not to introduce return freight insurance so as to maintain its own benefits and reduce the environmental impact.

1. Introduction

The development of e-commerce has made a great contribution to the convenience of consumers’ life and the prosperity of the market [1]. Nowadays, more and more consumers prefer online shopping, which not only saves consumers’ shopping time but also saves certain costs for e-commerce platforms [2]. However, due to the distortion of the seller’s description and the lack of actual touches with the products, some consumers cannot accurately evaluate the value of the products before purchase. In order to alleviate the problems caused by such uncertainty, e-commerce platforms have introduced return strategies to provide better services for consumers [3]. The return strategies have promoted the demand for products to some extent but invisibly stimulated consumers to make impulse purchases, increasing the possibility of online returns [4]. In the process of consumers′ online return, e-commerce platforms need to carry out secondary packaging (such as using tape, foam, plastic bags, etc.) and secondary transportation of returned products, which increases the waste of resources. A large number of returns have put pressure on the environment, resulting in increasingly severe environmental problems, which have aroused serious concern in countries around the world.

In recent years, in the context of countries vigorously advocating ecological and environmental protection, more and more consumers have paid attention to environmental protection [5]. The survey shows that 81% of respondents hope that companies show the environmental characteristics of products in their advertisements, and 69% of respondents say that they are trying to minimize their carbon footprint [6]. The enhancement of consumers’ awareness of environmental protection makes enterprises pay more attention to the environmental protection publicity of products in the sales link [7]. In the case of consumers with low environmental protection awareness, in order to ensure their own profits, e-commerce platforms can weaken environmental protection publicity. In the case of consumers with high environmental protection awareness, e-commerce platforms can intensify environmental protection publicity and meet the needs of consumers for green products. At the same time, they can also introduce return freight insurance to expand market demand. With the increasing attention paid to ecological and environmental issues, environmental consumption is bound to become a trend [8]. On the one hand, e-commerce platforms should consider the changes in purchase and return behaviors brought about by consumers’ environmental protection awareness. On the other hand, they need to ensure their own profits. Therefore, e-commerce platforms should make decisions from the perspective of protecting social benefits and satisfying consumers’ environmental protection awareness.

In summary, secondary transportation and packaging of products caused by online returns lead to a large amount of resource waste and environmental damage, which are not conducive to the green and sustainable development of enterprises [9]. Moreover, as consumers become more aware of environmental protection, their purchase and return behaviors will also change, prompting e-commerce platforms to adjust their return strategies [10]. Few studies have considered environmental impact in the research of return supply chains. Therefore, this study has important research significance for guiding the decision-making of supply chain members and improving our environment. And enriching the research scope of the return supply chain.

Based on the background, this paper considers that consumers have a consumption tendency of environmental protection, analyzes consumers’ online purchase and return behaviors, and investigates the optimal environmental protection publicity and return strategy of the e-commerce platform and their impacts on the environment. This paper mainly studies the following problems:

(1)

With the enhancement of consumers’ environmental protection awareness, consumers’ purchase and return behaviors change. How should e-commerce platforms decide the optimal environmental protection publicity and the optimal return strategy?

(2)

The secondary packaging and transportation caused by consumers’ return behaviors greatly increase the waste of resources. Which return strategy is suitable to ensure the effective use of resources, as well as the social benefits of manufacturers and e-commerce platforms?

(3)

What are the changes in the supply chain’s decisions, profits, and environmental impact under different return strategies?

In order to answer the above questions, this paper intends to conduct research on the return strategies of e-commerce platforms and their impact on the environment. Firstly, by constructing profit function models of manufacturers and e-commerce platforms under different return strategies, the optimal decisions of each member are obtained. Secondly, the comparison of the optimal decision-making under different return strategies is analyzed. In addition, in order to explore the impact on the environment caused by the uncertainty of consumers’ return behaviors, this paper introduces the reduction coefficient of environmental impact to obtain the optimal return strategy of the e-commerce platform under green and sustainable development. Finally, the influence of relevant parameters on the supply chain is analyzed numerically to verify the accuracy of the theoretical research. The results of this study are of great significance for enterprises to choose reasonable return strategies, balance the contradiction between consumers’ return behavior and environmental impact, and guide non-environmental consumers to transform into environmental consumers.

The rest of this paper is organized as follows: Section 2 reviews some of the relevant literature. Section 3 describes the systems and assumptions. In Section 4, Stackelberg game models are constructed and analyzed. Section 5 provides numerical simulations. Finally, the conclusions are given in Section 6.

2. Literature Review

This paper studies the return strategies of e-commerce platforms under green and sustainable development and focuses on environmental protection publicity, return freight insurance, and green and sustainable supply chain. Therefore, we reviewed the existing literature related to these three aspects.

2.1. Environmental Protection Publicity

With the improvement of consumers’ environmental protection awareness, consumers are more inclined to green consumption, which affects the decision-making of enterprises. In recent years, many scholars have undertaken research on consumers’ environmental protection awareness. Katherine et al. conclude that consumers with environmental consciousness are less sensitive to prices compared with consumers with no environmental consciousness [11]. Shah et al. analyze the influence of the coordination contract on decision-making based on consumers’ environmental protection awareness, and the results show that with the enhancement of environmental protection awareness, the products′ greening level and selling prices would both increase [12]. Jafar et al. establish an optimization decision model of a complex supply chain and find that distributors’ channel choice is influenced by consumers’ environmental protection awareness [13]. Januardi et al. propose a response surface method for uncertain green supply chain decision-making. The results show that the changes in profits and prices are significantly affected by consumers’ environmental protection awareness, and the overall profit under a centralized system is higher than that under a decentralized system [14]. Mondal et al. study environmental protection awareness and channel preference [15]. Yu et al. set up an optimization model aiming at analyzing the relationship between environmental protection awareness and supply chain performance [16]. Walter et al. establish a vertical differentiation model to study the choices of consumers with heterogeneous environmental protection awareness between different products. The research shows that the number of green consumers significantly affects social benefits, and the higher the proportion, the greater the demand for green products [17]. Xue et al. find that the enhancement of consumers’ environmental protection awareness is conducive to enterprises’ green development [18]. Fairchild et al. discuss how manufacturers could incorporate green production techniques to attract consumers with environmental consciousness in the market [19].

The above research analyzes the optimal decision-making of the supply chain from the perspective of consumers’ environmental protection awareness, proving that the enhancement of consumer environmental protection awareness is conducive to the improvement of social benefits. At present, there is no research that considers the optimal decision of the supply chain members from the perspective of the seller’s environmental protection publicity. This paper, aiming at consumers with environmental protection awareness, studies how manufacturers of environmental products cooperate with e-commerce platforms that provide environmental protection publicity, to promote the demand for environmental protection products through advertising or other means. This paper conducts profit function models and finds that e-commerce platforms can benefit themselves and manufacturers by intensifying environmental protection publicity while improving consumers’ environmental protection awareness.

2.2. Return Freight Insurance

The introduction of return freight insurance has helped boost sales for online retailers. Many scholars have studied return freight insurance. Zhang et al. provide decision-making recommendations for offline manufacturers and consumers in live streaming in the aspect of return-freight insurance and cross-channel return [20]. Fan et al. study the seller’s return freight insurance policy and the consumers’ return and find that consumers’ return is related to the seller’s return freight insurance policy, product validity, and opportunity costs [21]. Lin et al. study the seller’s return freight insurance market and find that the return strategy of retailers is influenced by the unit insurance premium and the return freight cost [22]. Shi et al. conclude that when the return freight compensation received is low, it should be purchased by the manufacturer, and when the return freight compensation received is high, it would be better for the consumers to purchase return freight insurance [23]. Li et al. find that the decisions of retailers, whether to offer return freight insurance depended on the impacts of market competition and return compensation on consumers’ demand [24]. Hua et al. develop a theoretical model to obtain the optimal transportation strategy and return service fee for the online retailers under joint and separate decision-making [25]. Radhi et al. study the dual-channel retailers provide single-channel return strategy and cross-channel return strategy and put forward opinions about the return policy for different channels [26]. Li et al. conclude that return freight insurance can provide an imperfect quality signal for consumers in mitigating quality uncertainty [27]. Product categories and product prices can cushion the negative impact of return freight insurance on consumers’ impulse purchases [28]. Li et al. investigate the seller’s return freight insurance and the buyer’s return freight insurance and show that the buyer’s return freight insurance can achieve a “win-win” situation for both sellers and consumers [29].

Most of the literature mainly studies how enterprises adjust the optimal price and return freight strategy to maximize profits. However, fewer of them considered the environmental impact caused by consumer return behaviors. In our study, we add environmental factors into our model, analyze the impact of return behaviors on the environment, and study how e-commerce platforms should make decisions to maximize their own benefits while minimizing the environmental impact.

2.3. Green and Sustainable Supply Chain

The research scope of the green supply chain has kept expanding in recent years, involving product pricing, contract coordination, and other aspects. Among them, Mandal et al. considers that consumers’ demand is affected by green level, promotion level, and retail prices. And build centralized and decentralized decision models in the dual-channel closed-loop supply chain [30]. Shen et al. analyze the impact of green level, confidence level, and government intervention and find that the supply chain members could realize maximum profits by adopting conservative risk attitudes [31]. Qi et al. show that the green closed-loop supply chain combined with manufacturers, recyclers, and retailers is a sustainable supply chain model in efficiency [32]. Barman et al. built a green dual-channel supply chain model composed of a supplier, a retailer, and a manufacturer [33]. Liu et al. propose two ways of government subsidies to improve the green level, supply benefits, and to guide supply chain members’ performance [34]. Hu et al. conclude that government needs to give green subsidies to both manufacturers and retailers to improve supply chain performance and environmental impact [35]. Das et al. propose a duopoly structure model in the green supply chain, in which green manufacturers and non-green manufacturers sell items through a common retailer [36]. Wang et al. analyze two different government subsidies: subsidizing the costs of green products’ production or manufacturers’ R & D and showing the green supply chain’s optimal decisions [37]. Xing et al. study the investment in product greenness and supply chain sustainability cooperation and find that by setting an appropriate investment sharing ratio, sustainable cooperation can be promoted, and supply chain profits can be improved [38]. Feng et al. compare three green R & D strategies and find that with the increase of price competition intensity and green R & D costs, the green level and the profits of the supply chain decrease [39]. Cai et al. find that the supplier’s preference depends on mandatory disclosure, while the retailer’s preference depends on the impact of greenness level on demand [40].

The above studies on green and sustainable supply chains mainly focus on product pricing and government subsidies, while few articles focus on the impact of product return on green and sustainable supply chains. This paper considers the impact of return behaviors on the environment based on consumers’ environmental protection awareness and introduces repurchase contracts to study the decision-making of manufacturers and e-commerce platforms.

2.4. Research Gap

As can be seen from the above literature, the green improvement of the supply chain has attracted widespread attention from scholars. However, at present, few articles have studied the issue of the return supply chain from the perspective of environmental protection. Therefore, this paper chooses a common phenomenon in reality (manufacturers give subsidies to e-commerce platforms for environmental protection publicity, e-commerce platforms carry out environmental protection publicity, and consumers return unsatisfactory products) to study and analyze the decision-making of e-commerce platforms. Compared with previous studies, the main innovation points of this paper are as follows: (1) Considering the return strategies of e-commerce platforms from the perspective of environmental protection publicity, taking environmental protection publicity as an important research object; (2) Constructing profit function models of manufacturers and e-commerce platforms under different return strategies, and studying the optimal order quantity and environmental protection publicity of the supply chain; (3) Analyzing the impact of environmental protection publicity and return freight insurance on the profits of supply chain members, and study the impact of different return strategies on the environment.

3. System Description

3.1. Problem Description

Based on consumers’ environmental awareness, this paper studies the supply chain system composed of a manufacturer M and an e-commerce platform R, the manufacturer sells products to the e-commerce platform that provides environmental protection publicity at the wholesale price $w$. Then the e-commerce platform sells products to consumers at price $p$. In order to encourage the e-commerce platform to enhance environmental protection publicity and expand the market demand, the manufacturer gives the e-commerce platform a certain environmental protection publicity subsidy $\phi$. In addition, the manufacturer repurchases returned products from the e-commerce platform at price $r$. The relationships between factors are shown in Figure 1. The environmental protection publicity and return compensation of the e-commerce platform has the same promoting effects on the market demand but the opposite effects on the return rate. Therefore, their effects on the environment are also different. Thus, how should the e-commerce platform make decisions to maximize its own profits while minimizing the environmental impact is worth investigating?

This paper considers the optimal environmental protection publicity and order quantity of the e-commerce platform, as well as the optimal environmental protection publicity subsidy of the manufacturer under different return freight insurance markets. There are three kinds of return freight insurance markets: (1) seller’s return freight insurance market; (2) buyers’ return freight insurance market; (3) no return freight insurance market.

3.2. Parameter Setting and Definition

The corresponding parameters of this paper are shown in

Table 1. Description of parameters.

Parameter	Description
$w$	Wholesale price
$p$	Sales price
$\overline{p}$	Products’ average value obtained by consumers
$t_n$	$\mathrm{Consumers}’\mathrm{return}\mathrm{compensation}(n=0,1,2)$
$m$	Impact of return compensation on demand
$\alpha$	Impact of environmental protection publicity on demand
$\lambda$	$\mathrm{Return}\mathrm{rate}(0\le \lambda \le 1)$
$k$	Impact of environmental protection publicity on cost
$\delta$	Fixed market demand
$r$	Repurchase price
$t$	Processing cost of returned products
$\theta$	Proportion of consumers purchasing return freight insurance
$c$	Production cost
$\mu$	Reduction coefficient of environmental impact
$\epsilon$	Unit environmental impact
$\overline{h}$	Seller’s return freight insurance cost
$\widehat{h}$	Buyer’s return freight insurance cost
$h$	$\mathrm{Return}\mathrm{freight}(\overline{h}<\widehat{h}<h)$
$\epsilon (e)$	Unit product’s environmental impact
$E[\min (x,q)]$	The expected sales volume
$E(e)$	Environmental impact
$E({\pi }_R)$	Profit of e-commerce platform
$E({\pi }_M)$	Profit of manufacturer
$E({\pi }_C)$	Consumer surplus
Decision Variable	Description
$q$	Order quantity
$e$	Environmental protection publicity
$\phi$	Environmental protection publicity subsidy

.

In addition, subscripts 1, 2, and 3 represent the seller’s return freight insurance market, the buyer’s return freight insurance market, and the no-return freight insurance market, respectively. The superscript “*” represents the optimal solution.

The compensation given by the manufacturer is $\phi e$ [41,42,43], and the e-commerce platform needs to pay corresponding costs to enhance the environmental protection publicity [44], it is assumed that the relationship between the costs and the environmental protection publicity is quadratic [45]. Thus, the cost of the e-commerce platform is $\frac{1}{2}k{e}^2$. The environmental impact [46] caused by the unit returned product of the e-commerce platform is $\epsilon (e)=(1-\mu e)\epsilon$.

According to the references [47,48], the demand function of the e-commerce platform is divided into two parts: linear demand $d$ affected by price, environmental protection publicity and consumer return compensation, and exogenous uncertain demand $\xi$. The Linear demand is $d=\delta +\alpha e-p+m{t}_n$, the exogenous uncertain demand $\xi$ suits the uniform distribution, and its approximate density function is:

$$f_{\xi }(y)=\left\{\begin{array}{cc}\frac{1}{b-a}& a\le y\le b\\ 0& \mathrm{else}\end{array}\right.$$

(1)

thus, the demand function of the e-commerce platform is $D=\delta +\alpha e-p+m{t}_n+\xi$, and the demand interval is: $[\delta +\alpha e-p+m{t}_n+a,\delta +\alpha e-p+m{t}_n+b]$, the approximate distribution function of the demand is:

$$f_d(x)=\left\{\begin{array}{cc}\frac{1}{b-a}& \delta +\alpha e-p+m{t}_n+a\le x\le \delta +\alpha e-p+m{t}_n+b\\ 0& \mathrm{else}\end{array}\right.$$

(2)

briefly, this paper makes $d_1=\delta +\alpha e-p+m{t}_n+a$,$d_2=\delta +\alpha e-p+m{t}_n+b$. The expected sales volume of the e-commerce platform is: $E[\min (x,q)]=\frac{1}{b-a}[{\displaystyle {\int }_{d_1}^{q}xdx}+{\displaystyle {\int }_q^{d_2}qdx}]$, after simplification, the expected sales volume of the e-commerce platform is:

$$E[\min (x,q)]=\frac{[-q^2-{(\delta +\alpha e-p+m{t}_n+a)}^2+2q(\delta +\alpha e-p+m{t}_n+b)]}{2(b-a)}$$

(3)

4. Model Establishment and Analysis

4.1. Seller’s Return Freight Insurance Market

Under the seller’s return freight insurance market, the e-commerce platform introduces return freight insurance to stimulate market demand. At this time, the return compensation of consumers is $(t_0=p)$, and each member of the supply chain makes decisions based on profit maximization. The profits of each member of the supply chain are, respectively:

$$E({\pi }_{R0})=(1-\lambda )pE[\min (x,q_0)]+\lambda (r-t)E[\min (x,q_0)]-w{q}_0-\frac{1}{2}k{e}_0{}^2+{\phi }_0{e}_0$$

(4)

$$E({\pi }_{M0})=(w-c)q_0-\lambda rE[\min (x,q_0)]-{\phi }_0{e}_0$$

(5)

Proposition 1. 

The optimal environmental protection publicity, optimal order quantity, and optimal subsidy under the seller’s return freight insurance market are:

$$e_0{}^{*}=\frac{\alpha (A(b-a)-c-r\lambda )}{2k}$$

(6)

$$q_0{}^{*}=\delta +(m-1)p+b+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}-\frac{w}{A}$$

(7)

$${\phi }_0{}^{*}=\alpha w-\frac{\alpha (A(b-a)+c+r\lambda )}{2}$$

(8)

where $A=\frac{(1-\lambda )p+\lambda (r-t)}{b-a}$. The profits of the e-commerce platform and the manufacturer, the consumer surplus, and the environmental impact under the seller’s return freight insurance market are:

$$E({\pi }_{R0})=(\delta +(m-1)p)(A(b-a)-w)+\frac{{\alpha }^2{(A(b-a)-c-r\lambda )}^2}{8k}+wb+\frac{w^2}{2A}+\frac{A(b^2-a^2)}{2}$$

(9)

$$\begin{array}{c}E({\pi }_{M0})=(w-c-r\lambda )(\delta +(m-1)p)-r\lambda \left(\frac{a+b}{2}+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}\right)+\frac{r\lambda w^2}{2A^2(b-a)}\\ -\frac{{\alpha }^2}{4k}(2w-A(b-a)-c-r\lambda )(c+r\lambda -A(b-a))+\frac{(w-c)({\alpha }^{2}A(A(b-a)-2k(c+r\lambda )+2k(Ab-w))}{2Ak}\end{array}$$

(10)

$$E({\pi }_{C0})=(\overline{p}-p)(1-\lambda )\left(\delta +(m-1)p+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}+\frac{b-a}{2}-\frac{w^2}{2A^2(b-a)}\right)$$

(11)

$$E(e_0)=\frac{2k-\mu \alpha (A(b-a)-c-r\lambda ))\epsilon \lambda }{2k}\left(\delta +(m-1)p+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}+\frac{b-a}{2}-\frac{w^2}{2A^2(b-a)}\right)$$

(12)

Details of the certification are shown in Appendix A.

4.2. Buyer’s Return Freight Insurance Market

In the buyer’s return freight insurance market, return freight insurance is voluntarily purchased by the consumer and is lower than return freight. This article assumes that the percentage of consumers to buy return freight insurance is $\theta$, not to buy return freight insurance is $(1-\theta )$, consumers′ return compensation is $\left(t_1=p-\left(\theta \widehat{h}+(1-\theta )h\right)\right)$, and the profits of each member of the supply chain are, respectively:

$$E({\pi }_{R1})=(1-\lambda )pE[\min (x,q_1)]+\lambda (r-t)E[\min (x,q_1)]-w{q}_1-\frac{1}{2}k{e}_1{}^2+{\phi }_1{e}_1$$

(13)

$$E({\pi }_{M1})=(w-c)q_1-\lambda rE[\min (x,q_1)]-{\phi }_1{e}_1$$

(14)

Proposition 2. 

The optimal environmental protection publicity, optimal order quantity, and optimal subsidy under the buyer’s return freight insurance market are:

$$e_1{}^{*}=\frac{\alpha (A(b-a)-c-r\lambda )}{2k}$$

(15)

$$q_1{}^{*}=\delta +m\left(p-(\theta \widehat{h}-(1-\theta )h)\right)+b-p+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}-\frac{w}{A}$$

(16)

$${\phi }_1{}^{*}=\alpha w-\frac{\alpha (A(b-a)+c+r\lambda )}{2}$$

(17)

the profits of the e-commerce platform and the manufacturer, the consumer surplus, and the environmental impact under the buyer’s return freight insurance market are:

$$E({\pi }_{R1})=\left(\delta +m\left(p-(\theta \widehat{h}-(1-\theta )h\right)-p\right)(A(b-a)-w)+\frac{{\alpha }^2{(A(b-a)-c-r\lambda )}^2}{8k}+wb+\frac{w^2}{2A}+\frac{A(b^2-a^2)}{2}$$

(18)

$$\begin{array}{c}E({\pi }_{M1})=(w-c-r\lambda )(\delta +m\left(p-(\theta \widehat{h}-(1-\theta )h\right)-p)-r\lambda \left(\frac{a+b}{2}+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}\right)\\ +\frac{r\lambda w^2}{2A^2(b-a)}-\frac{{\alpha }^2}{4k}(2w-A(b-a)-c-r\lambda )(c+r\lambda -A(b-a))\end{array}$$

(19)

$$E({\pi }_{C1})=(\overline{p}-p)(1-\lambda )\left(\delta +m\left(p-(\theta \widehat{h}-(1-\theta )h\right)-p+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}+\frac{b-a}{2}-\frac{w^2}{2A^2(b-a)}\right)$$

(20)

$$E(e_1)=\frac{2k-\mu \alpha (A(b-a)-c-r\lambda ))\epsilon \lambda }{2k}\left(\delta +m\left(p-(\theta \widehat{h}-(1-\theta )h\right)-p+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}+\frac{b-a}{2}-\frac{w^2}{2A^2(b-a)}\right)$$

(21)

Details of the certification are similar to Appendix A.

4.3. No Return Freight Insurance Market

In the no-return freight insurance market, the return freight is borne by the consumers themselves. In this case, the consumers′ return compensation is $(t_2=p-h)$, and the profits of each member of the supply chain are, respectively:

$$E({\pi }_{R2})=(1-\lambda )pE[\min (x,q_2)]+\lambda (r-t)E[\min (x,q_2)]-w{q}_2-\frac{1}{2}k{e}_2{}^2+{\phi }_2{e}_2$$

(22)

$$E({\pi }_{M2})=(w-c)q_2-\lambda rE[\min (x,q_2)]-{\phi }_2{e}_2$$

(23)

Proposition 3. 

The optimal environmental protection publicity, optimal order quantity, and optimal subsidy under the no-return freight insurance market are:

$$e_2{}^{*}=\frac{\alpha (A(b-a)-c-r\lambda )}{2k}$$

(24)

$$q_2{}^{*}=\delta +(m-1)p+b-mh+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}-\frac{w}{A}$$

(25)

$${\phi }_2{}^{*}=\alpha w-\frac{\alpha (A(b-a)+c+r\lambda )}{2}$$

(26)

the profits of the e-commerce platform and the manufacturer, the consumer surplus, and the environmental impact under the no-return freight insurance market are:

$$E({\pi }_{R2})=\left(\delta +(m-1)p-mh\right)(A(b-a)-w)+\frac{{\alpha }^2{(A(b-a)-c-r\lambda )}^2}{8k}+wb+\frac{w^2}{2A}+\frac{A(b^2-a^2)}{2}$$

(27)

$$\begin{array}{c}E({\pi }_{M2})=(w-c-r\lambda )(\delta +(m-1)p-mh)-r\lambda \left(\frac{a+b}{2}+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}\right)\\ +\frac{r\lambda w^2}{2A^2(b-a)}-\frac{{\alpha }^2}{4k}(2w-A(b-a)-c-r\lambda )(c+r\lambda -A(b-a))\end{array}$$

(28)

$$E({\pi }_{C2})=(\overline{p}-p)(1-\lambda )\left(\delta +(m-1)p-mh+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}+\frac{b-a}{2}-\frac{w^2}{2A^2(b-a)}\right)$$

(29)

$$E(e_2)=\frac{2k-\mu \alpha (A(b-a)-c-r\lambda ))\epsilon \lambda }{2k}\left(\delta +(m-1)p-mh+\frac{{\alpha }^2(A(b-a)-c-r\lambda )}{2k}+\frac{b-a}{2}-\frac{w^2}{2A^2(b-a)}\right)$$

(30)

Details of the certification are similar to Appendix A.

4.4. Comparative Analysis of Different Return Freight Insurance Market Models

By comparing the above three return freight insurance market models, the impacts of return strategies on sellers and buyers are comprehensively considered from the perspective of environmental protection publicity, order quantity, environmental protection publicity subsidy, profits of supply chain members, and environmental impact. The following theorems are obtained:

Theorem 1. 

$e_0{}^{*}=e_1{}^{*}=e_2{}^{*}$, ${\phi }_0{}^{*}={\phi }_1{}^{*}={\phi }_2{}^{*}$, $q_0{}^{*}>q_1{}^{*}>q_2{}^{*}$.

Theorem 1 shows that no matter in which return freight insurance market, the optimal environmental protection publicity and environmental publicity subsidy are equal, and the optimal order quantity of the e-commerce platform is the highest in the seller’s return freight insurance market, followed by the buyer’s return freight insurance market, and the lowest in the no return freight insurance market. The reason is that the manufacturer’s environmental publicity subsidy depends on the effort the e-commerce platform paid. When the environmental protection publicity effort is determined, the environmental publicity subsidy keeps consistent. In addition, the introduction of return freight insurance on the e-commerce platform has stimulated market demand and led to an increase in orders.

Theorem 2. 

$E(e_0)>E(e_1)>E(e_2)$.

Theorem 2 shows that the environmental impact is the highest in the seller’s return freight insurance market, followed by the buyer’s return freight insurance market, and the lowest in the no-return freight insurance market. That is, the introduction of return freight insurance on the e-commerce platform can stimulate market demand, but the probability of consumers′ return is also kept at a high level. Thus, the e-commerce platform should appropriately introduce return freight insurance to stimulate consumer demand and pay attention to the environmental impact at the same time in order to ensure the effective use of resources and achieve green and sustainable development, as well as the social benefits of the manufacturer and the e-commerce platform.

Theorem 3. 

When $\lambda <\frac{p-w}{p-(r-t)}$, $E({\pi }_{R0})>E({\pi }_{R1})>E({\pi }_{R2})$; when $\lambda >\frac{p-w}{p-(r-t)}$, $E({\pi }_{R0})<E({\pi }_{R1})<E({\pi }_{R2})$; when $\lambda <\frac{w-c}{r}$, $E({\pi }_{M0})>E({\pi }_{M1})>E({\pi }_{M2})$; When $\lambda >\frac{w-c}{r}$, $E({\pi }_{M0})<E({\pi }_{M1})<E({\pi }_{M2})$.

Theorem 3 shows that when the return rate is low, the profits of both the e-commerce platform and the manufacturer are highest in the seller’s return freight insurance market, followed by the buyer’s return freight insurance market, and the lowest in the no-return freight insurance market. But when the return rate is high, the profits of both the e-commerce and the manufacturer are highest in the no-return freight insurance market, followed by the buyer’s return freight insurance market, and the lowest in the seller’s return freight insurance market. That is, the e-commerce to introduce the return freight insurance depends on the return rate.

Theorem 4. 

When the return rate $\lambda$ satisfies condition $E>0$, $E({\pi }_{C0})>E({\pi }_{C1})>E({\pi }_{C2})$; When the return rate $\lambda$ satisfies condition $E<0$, $E({\pi }_{C0})>E({\pi }_{C2})<E({\pi }_{C1})$, $E=\theta m\left(\overline{p}-p\right)\left(1-\lambda \right)\left(h-\widehat{h}\right)+\theta \left(\lambda h-\widehat{h}\right)\left(\delta +\left(m-1\right)p+\frac{{\alpha }^2\left(A\left(b-a\right)-c-r\lambda \right)}{2k}+\frac{b-a}{2}-\frac{w^2}{2A^2\left(b-a\right)}\right)-m{h}^2\lambda +m\left(\left(1-\theta \right)h\lambda +\theta \widehat{h}\right)\left(\theta \widehat{h}+\left(1-\theta \right)h\right)$.

Theorem 4 shows that the consumer surplus is always the highest in the seller’s return freight insurance market, but when $E>0$, the consumer surplus is higher in the buyer’s return freight insurance market and lower in the no-return freight insurance market, when $E<0$, the consumer surplus in the no return freight insurance market is higher than in the buyer’s return freight insurance market.

The proof of Theorem 1 to Theorem 4 is shown in Appendix B.

5. Numerical Simulation Analysis

In this section, examples are used to verify the results, and the influences of some important parameters on the decisions and profits of supply chain members are analyzed in order to obtain more management enlightenment. It is assumed that the relevant parameters are $p=120$, $w=100$, $c=80$, $k=2$, $t=10$, $\alpha =2$, $m=2$, $h=10$, $\widehat{h}=5$, $\delta =1000$, $\mu =0.02$, $\epsilon =2$.

When the return rate is $\{0.1,0.2,0.3\}$, and the repurchase is $\{10,20,30\}$, the value changes of the optimal decisions are shown in

Table 2. Optimal decisions of supply chain members.

$\mathit{\lambda }$	$\mathit{r}$	${\mathit{e}}_0{}^{*}$	${\mathit{e}}_1{}^{*}$	${\mathit{e}}_2{}^{*}$	${\mathit{\phi }}_0{}^{*}$	${\mathit{\phi }}_1{}^{*}$	${\mathit{\phi }}_2{}^{*}$	${\mathit{q}}_0{}^{*}$	${\mathit{q}}_1{}^{*}$	${\mathit{q}}_2{}^{*}$	E(e0)	E(e1)	E(e2)
$0.1$	10	13.5	13.5	13.5	11	11	11	1679	1669	1664	17,194	17,048	16,975
	20	13.5	13.5	13.5	9	9	9	1683.3	1673.3	1668.3	33,557	33,273	33,131
	30	13.5	13.5	13.5	7	7	7	1687.5	1677.5	1672.5	49,787	49,367	49,157
$0.2$	10	7	7	7	22	22	22	1608.2	1598,2	1593.2	19,052	18,880	18,794
	20	7	7	7	18	18	18	1618.8	1608.8	1603.8	36,693	36,365	36,201
	30	7	7	7	14	14	14	1629	1619	1614	54,192	53,712	53,472
$0.3$	10	0.5	0.5	0.5	33	33	33	1520.8	1510.8	1505.8	20,031	19,834	19,734
	20	0.5	0.5	0.5	27	27	27	1541.3	1531.3	1526.3	38,528	38,156	37,970
	30	0.5	0.5	0.5	21	21	21	1560.4	1550.4	1545.4	57,100	56,560	56,290

, and the profits of the supply chain members and the environmental impact are shown in

Table 3. Profits of the supply chain members and the environmental impact.

$\mathit{\lambda }$	$\mathit{r}$	E(πR0)	E(πR1)	E(πR2)	E(πM0)	E(πM1)	E(πM2)	E(πC0)	E(πC1)	E(πC2)
$0.1$	10	213,250	213,170	213,130	27,192	27,002	26,907	31,798	30,944	30,229
	20	214,905	214,815	214,770	25,534	25,334	25,234	35,448	35,148	30,331
	30	216,560	216,460	216,410	23,852	23,652	23,552	35,562	35,262	30,430
$0.2$	10	193,630	193,670	193,690	24,182	24,002	23,912	26,585	25,247	24,040
	20	197,160	196,960	196,860	21,047	20,847	20,747	33,561	33,261	24,281
	30	200,349	200,149	200,049	17,834	17,634	17,534	33,870	33,570	24,508
$0.3$	10	174,920	175,080	175,160	20,917	20,747	20,662	21,245	19,533	17,940
	20	179,990	179,790	179,690	16,555	16,355	16,255	31,071	30,771	18,373
	30	184,580	184,380	184,280	11,998	11,798	11,698	31,722	31,422	18,762

.

Table 2 shows that the optimal environmental protection publicity is not affected by the repurchase price, and with the increase of the return rate, the optimal environmental protection publicity decreases. This is because when the return rate increases, the expected sales volume of the e-commerce platform decreases. In order to maintain their own benefits, the optimal decision of the e-commerce platform is to reduce the environmental protection publicity to minimize the total costs. Meanwhile, in order to encourage the e-commerce platform to enhance environmental publicity, the manufacturer increases the environmental publicity subsidy to avoid the unmarketable product surplus and reduce the environmental impact due to low environmental publicity.

Table 3 shows that, with the increase of the return rate, the profits of the supply chain members are all decreased, and with the increase of the repurchase price, the e-commerce platform’s profit, and the consumer surplus increase, while the manufacturer’s profit decreased. Meanwhile, when $\lambda =\{0.2,0.3\}$, $r=10$, the relationship of the e-commerce’s profit is $E({\pi }_{R0})<E({\pi }_{R1})<E({\pi }_{R2})$, else, the relationship of the e-commerce’s profit is $E({\pi }_{R0})>E({\pi }_{R1})>E({\pi }_{R2})$, this is because when $\lambda =\{0.2,0.3\}$, $r=10$, there is $\lambda >\frac{p-w}{p-(r-t)}$, according to theorem 3, we obtain that $E({\pi }_{R0})<E({\pi }_{R1})<E({\pi }_{R2})$. Table 3 states that when the return rate is high and the repurchase price is low, the optimal decision of the e-commerce platform is not to introduce return freight insurance, and the manufacturer should make a reasonable repurchase price to balance the profit distribution.

In order to analyze the impacts of the environmental protection publicity and the return compensation correlation coefficients, assume that $\lambda =0.2,r=20$, the impact on the expected sales volume is shown in Figure 2, Figure 3 and Figure 4.

Figure 2 shows that with the increase of the correlation coefficient $\alpha$ of the environmental protection publicity on demand, the expected sales volume of the e-commerce platform increases and is highest in the seller’s return freight insurance market, followed by the buyer’s return freight insurance market, and is the lowest in the no return freight insurance market. That is, the e-commerce platform enhances the environmental protection publicity and can incentivize the purchase willingness of consumers with environmentally friendly conscious, and meanwhile, indirectly promote the transformation of non-environmentally friendly consumers to environmentally friendly consumers.

Figure 3 shows that with the increase of the correlation coefficient $m$ of return compensation on demand, the expected sales volume of the e-commerce platform increases and is highest in the seller’s return freight insurance market, followed by the buyer’s return freight insurance market and is the lowest in the no return freight insurance market. That is, the higher the return compensation is, the more benefits the consumers can get. Thus, consumers’ demand for environmental protection products is surging.

Figure 4 shows that with the increase of the correlation coefficient $k$ of the environmental protection publicity cost, the expected sales volume of the e-commerce platform decreases but is still highest in the seller’s return freight insurance market, followed by the buyer’s return freight insurance market, and is the lowest in the no return freight insurance market. That is, when the costs the e-commerce platform pays are high, the profit of the e-commerce platform itself is affected, and the optimal decision for the e-commerce platform is to reduce the environmental protection publicity in order to maintain its own benefit.

Combined with the conclusion obtained from the numerical simulation analysis, the optimal return strategy and environmental protection publicity of the e-commerce platform and the corresponding environmental impact can be obtained, as shown in Figure 5. The arrow direction is from small to large:

6. Conclusions

The existence of return freight insurance intensifies the uncertainty of consumers’ purchase and return behaviors, which is not conducive to the sustainable development of the environment and damages the interests of e-commerce platforms. Thus, a suitable return strategy for e-commerce platforms is of great significance for improving supply chain performance, reducing resource loss caused by secondary packaging and transportation of products, and realizing sustainable development of resources. Based on this, this paper constructs profit models of manufacturers and e-commerce platforms under uncertain market demand. The Stackelberg game is used to discuss the optimal decisions of manufacturers, e-commerce platforms, and the entire supply chain under different return freight insurance markets based on environmental protection publicity. The research shows that environmental protection publicity and return compensation can stimulate the expected sales volume of the e-commerce platform. The optimal environmental protection publicity depends on the return rate. When the return rate is high and the repurchase price is low, the optimal decision of the e-commerce platform is not to introduce return freight insurance, and the manufacturer should make a reasonable repurchase price to balance the profits distribution. The introduction of return freight insurance by the e-commerce platform can stimulate market demand and improve social benefits, but it will aggravate the environmental impact. Different from other studies, this paper takes environmental impact into the return supply chain to study the impact of consumers’ return behaviors on sustainable development, which has important reference value for enterprises’ return strategies selection and the government’s supervision and management of enterprises.

To summarize, the following suggestions for enterprise management are put forward:

(1)

The increase in environmental publicity subsidies can cushion the decrease of environmental publicity of e-commerce platforms caused by the high return rate. Therefore, the government should strengthen the investment in the manufacturing of environmental protection products and, at the same time, increase the policy publicity to improve consumers’ environmental awareness and guide non-environmental protection consumers to transform into environmental protection consumers.

(2)

Consumers with high environmental awareness show great willingness to pay for environmental protection products, and such consumers often do not participate in products return. Thus, e-commerce platforms can arouse consumers’ environmental protection awareness through advertising, promotion, and other encouraging ways, to reduce the products′ return rate and achieve green and sustainable development.

(3)

Environmental products are expensive to manufacture and develop; manufacturers and e-commerce platforms should cooperate with each other and share fixed costs with a certain percentage in order to incentivize manufacturers to improve products innovation and produce more environmental protection products; therefore, the overall benefits of the supply chain can be improved while the demand of consumers with environmental protection awareness can be met.

(4)

This paper only studies the supply chain composed of manufacturers and e-commerce platforms, but in practice, there are multiple manufacturers of the same type of products, and manufacturers can improve their competitive advantages only through continuous innovation [49]. Future research may consider adding competition and innovation factors into the model and study the return supply chain decision-making considering innovation strategy under the competitive environment of manufacturers. This has important research value for enhancing a sustainable innovation ecosystem and promoting digital transformation [50].