Power Structure Symmetry and Strategic Green Design in Supply Chains: Environmental and Economic Implications

Abstract

This study explores the impact of symmetric and asymmetric channel power structures on green design decisions in supply chains, incorporating consumer environmental awareness (CEA). We develop a game-theoretic framework involving a manufacturer and a retailer under three distinct power configurations: manufacturer-led, retailer-led, and Nash game (symmetric power). The models examine how variations in power symmetry influence the manufacturer’s incentives to invest in green design, and their effects on pricing, demand, profit, and environmental performance. Our findings reveal that asymmetric power structures can significantly distort green design incentives. Specifically, green design does not always lead to higher prices or reduced environmental impact, depending on the interplay between power structure, investment cost, and CEA. Moreover, symmetric (Nash game) structures tend to improve overall supply chain performance when the green investment cost is high, while retailer-led structures are more effective under low-cost scenarios. Interestingly, unless green design significantly reduces per-unit environmental impact, the total environmental benefit may be offset by increased demand, highlighting the risk of a “green consumption trap”.

1. Introduction

The technological advancements and proliferation of economic globalization have led to a marked exacerbation of environmental concerns, particularly with regard to pollution and energy consumption [1,2]. How to promote enterprises to efficiently fulfill their environmental responsibilities (here, environmental responsibility mainly refers to enterprises reducing pollutant emissions in production and other processes through green technology innovation) and solve the contradiction between economic expansion and environmental degradation have become global challenges [3,4]. Green design (also termed life-cycle design or environmental design) is a product-development paradigm that requires explicit consideration, at the design stage, of a product’s environmental attributes. This involves minimizing the use of resources and hazardous substances and reducing waste generation over the entire life cycle so as to mitigate adverse effects on producers, users, and other stakeholders [5,6]. By enabling firms to jointly evaluate resource-use efficiency and anticipated life-cycle environmental impacts early in product design, green design offers a practical pathway to mutually reinforcing environmental and economic outcomes [7,8].

In recent years, an increasing number of manufacturing enterprises have embedded green design into product development and production to control resource use and pollutant emissions from production [6,9,10]. Many companies have demonstrated in practice the importance of green design in balancing production costs and environmental impacts [6]. HP, as one of the early companies to launch green design initiatives, has not only reduced material use and environmental impacts at the manufacturing stage, but also improved energy efficiency at the use stage [5]. Likewise, Canon, by incorporating green design into product planning, development, and production processes, has substantially reduced product energy consumption and pollutant emissions, thereby improving resource utilization and performance [9]. Although green design is helpful for enhancing resource utilization efficiency and can improve the brand competitiveness of enterprises, it often requires huge investment in early research and development [11,12]. At the same time, manufacturing enterprises often bear the environmental responsibility costs in product greening, and investment in green design may make other participants more profitable [11,13]. Therefore, it will become very complex and difficult for manufacturers to make decisions on whether to carry out green design and how to decide on the optimal green design level, because they not only need to balance investments and incomes, but also ponder on the actions made by other members [6,13].

The difference in the supply chain channel power structure is one of the key factors affecting channel profit distribution [14]. In different power structures, the specific order of decision-making varies, as does the impact on the optimal decision-making of other members [15]. Due to their greater bargaining power, dominant enterprises frequently affect the economic and environmental decisions of relatively weaker participants, enabling themselves to make decisions first as leaders [15,16]. In fact, most research has shown that strong retailers in the supply chain are often able to obtain more marginal retail profits, which causes the wholesale profit of manufacturers to not be enough to offset the cost of carrying out green design [11,17]. A case in point is P&G’s USD 200 million investment aimed at reducing packaging material usage, while the majority of the economic gains from this initiative were appropriated by Wal-Mart [11]. More broadly, dominant retailers often exert their positional advantage in the channel to diminish manufacturers’ pricing power and reduce their share of marginal profits, as observed in interactions involving firms such as Costco and Alibaba [16].

In this case, some manufacturers believe that the more they invest in green design/sustainability, the more their competitiveness will be further weakened [18]. The impact of channel power on manufacturers’ green design motivation and environmental performance is also a growing concern [19,20]. Therefore, shifts in channel power may hinder manufacturers from investing in green design [13,14]. When manufacturers lack sufficient channel power, they may be unable to secure adequate wholesale margins to offset the costs of green design investment [11]. A corresponding real-world example is Amazon’s Frustration-Free Packaging program, which requires manufacturers to redesign green packaging at their own expense, while Amazon captures the majority of the benefits through improved customer experience. To the best of our knowledge, only a limited number of studies have explored the impact of channel power on supply chain performance and sustainability [16,18]. However, the existing literature has largely overlooked the multifaceted effects of green design—particularly its implications for cost structures, market demand, and environmental impact [5,9]. Specifically, there is a lack of research examining how channel power influences manufacturing enterprises’ green design investment strategies, as well as the resulting trade-offs in profitability and sustainability.

To address the gap in the existing literature regarding the interplay between channel power structures and green design decisions, this study aims to explore three core research questions. First, under three channel power structures, does the manufacturer consistently have sufficient economic or environmental motivation to invest in green design initiatives? Second, how do varying channel power configurations influence the manufacturer’s green design decisions, and what are the implications for firm-level profitability, supply chain operational performance, and environmental outcomes? Third, from an environmental perspective, does green design lead to a reduction in the total environmental impact of product? By answering these questions, we seek to uncover the conditions under which green design becomes both a sustainable and strategic choice for manufacturers operating under different power structures.

Consistent with prior research, this study focuses on supply chains composed of a manufacturer and a retailer, particularly in the context of durable consumer goods such as consumer electronics, household appliances, and small-scale durable products [6,7]. In these types of supply chains, the manufacturer and retailer are the principal decision-makers, while other potential participants are often regarded as exogenous or passive players [7,8]. Green design is typically a prominent and certifiable product attribute in such settings [11,13]. The decision to center the analysis on manufacturer–retailer supply chains is grounded in both theoretical tractability and practical relevance [12,13]. In practice, manufacturers are generally the key actors responsible for product development and green design investment—examples include leading firms in the home appliance industry such as Midea and Samsung. After production, manufacturers set the wholesale price and supply products to retailers [13,14]. Retailers, in turn, serve as intermediaries who interact directly with end consumers—such as GOME or JD.com in the home appliance market—and determine the final retail prices offered to the market.

This study adopts a game-theoretic modeling approach to capture the strategic interactions among key supply chain participants and to reflect the multifaceted impact of green design on cost, demand, and environmental outcomes [16,17]. Specifically, we develop six supply chain decision models under three distinct channel power structures—manufacturer-led (e.g., Huawei, Apple, who typically dominate their supply chains [21]), retailer-led (e.g., Amazon, Tmall, which often act as dominant players [22]), and Nash game (e.g., GOME and Gree, where both parties possess comparable bargaining power [23]). In these models, the manufacturer determines the level of green design and wholesale pricing, while the retailer sets the retail price [13,14]. This structure mirrors real-world settings in which manufacturers like Huawei integrate green design into their production processes to reduce material and energy consumption from the source [9] and subsequently sell the products at a wholesale price to platforms such as JD.com. In order to facilitate the analysis of the economic and environmental performance generated by green design, we use the profit of the enterprise as the economic indicator, and the higher the profit, the more significant the economic performance [3,4]. We also use the environmental impact of the product as an environmental indicator, where lower environmental impact signifies greater environmental performance [7,9].

Compared to the existing literature on supply chain greening behavior consideration [13,16], our research both confirms the previous findings in a broader environment and expands the research perspective to provide new findings and management insights. Specifically, our research shows that under the multiple influences of green design, the following conclusions are still valid: Firstly, the enhancement of the manufacturer’s capacity to generate revenue is a possible consequence of increased power, but it is not necessarily aligned with enhancing the collective financial gains of the supply chain as a whole (here, the supply chain as a whole refers to all the participating firms within the supply chain, most commonly the manufacturer and the retailer) [16,17]. In contrast, strategies that promote green development have the potential to yield enhanced profits for the supply chain [20]. Secondly, an increase in consumer environmental awareness (CEA) consistently facilitates an increase in the market demand and the overall profits of the supply chain [12]. Finally, the increase in green design cost coefficient is likely to lower the market demand and the overall profits [1]. However, given the multifaceted nature of green design, our research results diverge as follows: Firstly, the green design behavior of the manufacturer may not always lead to higher product prices; that is, greening may not always lead to higher prices. Secondly, balanced channel power may not yield a greater capacity to augment the overall supply chain profitability when compared with that dominated by the retailer. Last but not least, an increase in both CEA and the manufacturer’s green design behavior may not contribute to a reduction in the total environmental impact, making green design the least advantageous for retailer-led power structures with regard to total environmental impact.

The subsequent sections are structured as follows. Section 2 presents a review of the relevant literature. Section 3 introduces the problem at hand. Section 4 constructs and solves the decision-making models under diverse channel power structures. Section 5 discusses the equilibrium results. Section 6 validates the findings through numerical simulation. Finally, Section 7 summarizes the research conclusions of this paper and explores potential future research directions. The proofs of the Propositions are provided in Appendix A.

2. Literature Review

Our research mainly deals with two topics: green design strategies and the power structures of supply chains.

2.1. Supply Chain Considering Green Design Strategies

A fundamental issue concerning green development of the supply chain is how to incorporate the relevant decisions of enterprises’ green investment behaviors into their operation modes, while ensuring their economic viability [16]. In previous studies, many scholars have suggested that enterprises can meet consumers’ green preferences through green innovation [24], green technology investment [25], green manufacturing [26], and other green behaviors, thus effectively improving products’ market demand, so that enterprises can achieve economic and environmental goals at the same time. Since 80%~90% of supply chain environmental performance is determined in a product’s design stage, and green design can help enterprises reduce the resource consumption of a product’s production from the source, green design has obvious benefits when contrasted with other green behaviors [5,6]. Green design has the potential to reduce waste and improve efficiency in the entire supply chain operation, making this theme a very important area of supply chain operation and management [9]. However, few studies have investigated the green design motivation of manufacturing enterprises by quantitative model analysis.

The existing literature includes a number of studies that have been conducted on green behaviors such as the green technology investment or green innovation of enterprises [2,27,28]. This kind of literature mainly discusses the relevant driving factors of enterprises’ green behavior under the market-driven mechanism or government environmental regulation policies [29,30]. As CEA continues to be strengthened, the impact of green product sales and green enterprise behavior is also increasing [3,4]. More and more scholars consider CEA an important variable to include in the research framework of green supply chain management [7,8,13]. Some studies care about the impact of CEA on supply chain operation coordination and green decision-making, like Mao et al. [31] and Shen et al. [32]. Many studies have considered the impact of enterprise competition or cooperation on supply chain greening development, such as Liu et al. [18] and Wang et al. [29]. Zhang et al. [12] conducted a further investigation into how CEA influences manufacturers’ green technology investment. They revealed that the retailer consistently stands to gain from the manufacturers’ investment in green technology. Yu et al. [26] examined how various inter-enterprise cooperation contracts affect green technology investment. Zhao et al. [33] investigated the impact of consumers’ environmental responsibility awareness on manufacturers’ product line design and pointed out that green products are always priced higher than conventional ones. With the development of digital technologies, Yan et al. [34] and Yang et al. [35] respectively investigated how emerging technologies such as blockchain and artificial intelligence promote the greening process of supply chains. Existing research primarily concentrates on examining the effect of corporate environmental responsibility on market demand yet overlooks the diverse impacts, including demand, cost, and the environment.

At present, some research has discussed the significant advantages of green design through qualitative research [36]. Raz et al. [5] pioneered the definition of green design and figured that green design may help enterprises lower production costs and environmental impact. Du et al. [1] considered green design competition among manufacturers and analyzed the conditions under which non-green manufacturers choose to enact green design in the presence of green manufacturers. Cai et al. [6] demonstrated that a zero-tax, linear-tax framework was more conducive to enhancing green design standards in comparison with a fixed tax. Yenipazarli [11] contrasted the effects of two contracts on improving green design level and system profits. Liu et al. [37] studied the interaction between green design and service input within the supply chain. Li et al. [38] examined how different demand-information-sharing strategies adopted by retailers influence manufacturers’ green design decisions.

The above papers provide important insights for further research on the manufacturer’s green design investment motivation, laying a certain theoretical foundation. However, they did not investigate whether the manufacturer has green design investment motivation in different channel power structures. In view of the diverse impacts of green design, we examine the relationship between power structures and green design and explore how it influences the economic and environmental performance of the supply chain.

2.2. Power Structure of the Supply Chain

Channel power has been widely considered as a prominent factor affecting the decision-making order and sustainability of the supply chain [16,17]. Shi et al. [39] studied channel power structure effects on supply chain decisions and performance with demand uncertainty. Luo et al. [22] showed that channel power does not affect the product standards of the whole supply chain, but it will significantly impact the pricing decisions and performance of supply chain enterprises. Liao et al. [40] checked the interaction between different price leadership and procurement structures on the retailer’s procurement quality and enterprise performance. Hong et al. [7] indicated that in terms of improving supply chain environmental performance, a retailer-led scenario outperforms a manufacturer-led one. Niu et al. [16] studied the influence of the channel power structure on the manufacturer’s decarbonizing investment decisions and found that an increase in the retailer’s power will dampen the manufacturer’s investment incentive. Based on differential games, Liu et al. [18] compared the functions of two different contracts in enhancing products’ green level under diverse power structures. Chen et al. [14] noted that a well-balanced channel power structure is better for reducing supply chain discharges and increasing general profitability. Xia et al. [41] studied the interaction between channel power and cross shareholding ratio on supply chain emission reduction effect and performance. Ma et al. [42] examined the influence of inter-firm information advantage, green optimism, and power structure differences on the performance of green decision-making in the supply chain.

Existing studies on the impact of channel power on the greening of supply chains have primarily focused on how manufacturers’ green investments influence market demand (such as Liu et al. [13], Niu et al. [16], Tao et al. [43]). However, these studies rarely incorporate the multifaceted effects of green design on cost, demand, and environmental impact within a game-theoretic framework [5,9]. This paper advances the literature by simultaneously exploring the manufacturer’s green design motivations from both economic and environmental performance perspectives. Moreover, we investigate how green design decisions affect supply chain and environmental performance under different channel power structures.

2.3. Research Gap

Our study is closely related to the works of Zheng et al. [9], Dong et al. [20], and Niu et al. [16]. Zheng et al. [9] and Dong et al. [20] focused on the green investment incentives of dominant manufacturers but did not examine how differences in channel power structures influence manufacturers’ motivations for green design. Although Niu et al. [16] analyzed manufacturers’ decarbonization investments under different power structures, they overlooked the multiple effects of green design on cost, demand, and environmental performance [5,9]. Moreover, their work did not assess how green design decisions impact supply chain performance and environmental outcomes under varying power structures. Therefore, this study contributes to the literature by incorporating the multifaceted impact of green design—which simultaneously affects product cost, demand, and environmental performance—into a game-theoretic framework. From both economic and environmental perspectives, we comprehensively explore the interactive effect between channel power and manufacturers’ green design strategies. In doing so, we identify the power structures and green design strategies that lead to win–win outcomes for both supply chain profitability and environmental sustainability. We reveal under what conditions green design leads to win–win outcomes, reducing total environmental impact while maintaining or improving supply chain profitability. This study makes a theoretical and practical contribution by revealing how channel power structures influence the economic and environmental outcomes of green design, thereby providing valuable guidance for supply chain decision-making aimed at achieving both profitability and sustainability.

3. Problem Description and Assumptions

In this paper, we consider a supply chain comprising a manufacturer and a retailer, assuming symmetric information between them [12,13]. The manufacturer is responsible for product development and production, with the opportunity to implement green design in the early stages to reduce energy consumption and the unit product’s environmental impact. The retailer is responsible for product sales. Although our model focuses on the manufacturer–retailer dyad, this structure captures the core strategic interface in many durable goods supply chains—such as consumer electronics and home appliances—where decisions on green design and pricing are predominantly driven by these two parties [16,17]. Such modeling assumptions have been widely adopted in the existing literature to capture the essential dynamics of supply chain operation [16,17,18,19,20].

Although information is symmetric, power asymmetry still exists due to differences in market position, brand influence, and bargaining ability between supply chain members [16]. For instance, electronic product manufacturers such as Lenovo and HUAWEI often lead supply chains through technological or brand dominance [21], while retailers such as Wal-Mart and Suning exert control through extensive distribution networks [22]. Additionally, in some vertically integrated or closely coordinated systems (e.g., Gome–Gree partnerships), power is more balanced [23]. To capture the influence of channel power structure on green design decisions and environmental outcomes, we consider three game structures: a manufacturer-led Stackelberg game, a retailer-led Stackelberg game, and a Nash game representing a balanced power structure. From the perspective of environmental responsibility, we explore how shifts in channel power affect manufacturers’ incentives to invest in green design, and how these changes influence the economic and environmental performance of the supply chain.

To clarify the problem, the symbol definitions are shown in

Table 1. Notation’s description.

Notation	Description
$c$	The cost of unit product when the manufacturer does not implement green design.
$a$	The potential market demand.
$\theta$	The environmental impact of the unit product when the manufacturer does not implement green design.
$r$	The degree of reduction of unit production cost caused by unit green design level [5], where $0<r<1$ implies that green design can only reduce the unit production cost to a certain extent, and this reduction is constrained by factors such as the current level of technology and manufacturing processes [5,9].
$\lambda$	Reduction degree of environmental impact of unit product caused by unit green design level [9], where $0<\lambda <1$ indicates that green design can only partially reduce the environmental impact per unit product, and the extent of this reduction is limited by current technological capabilities, production processes, and other related factors [4,9].
$c(e)$	The unit product production cost when the manufacturer implements green design.
$\theta (e)$	The environmental impact of the unit product when the manufacturer implements green design.
$b$	Consumers’ price sensitivity, where $b>0$ reflects that consumers exhibit price sensitivity toward the product [11,12].
$\beta$	CEA level, where $\beta >0$ indicates that consumers are sensitive to the product’s level of green design [11,13]
$q$	Market demand.
$E$	Total environmental impact of products. $E$ is the product of the product sales volume and the environmental impact of the unit product [5,9].
${\pi }_X^i$	The profits of members and whole, where $i=\{ME,RE,NE,MN,RN,NN\}$ represents the situation when the manufacturer implements/does not implement green design under a manufacturer-led, retailer-led, and Nash game structure, respectively; $X=\{M,R,S\}$ represents the manufacturer, retailer, and supply chain.
Decision variables
$w$	Wholesale price
$p$	Retail price
$m$	The retailer’s margin profit
$e$	The manufacturer’s green design level

, and the relevant assumptions are as follows.

Assumption 1.

When the manufacturer does not carry out green design, referring to Shi et al. [39], the product market demand function is $q=\alpha -bp$.

A global survey conducted by Accenture reveals that over 80% of consumers consider the green attributes of a product when making purchasing decisions [7]. In practice, many companies in the electronics and home appliance industries have begun to implement green design strategies to cater to growing CEA and to expand their market share. For example, Huawei has reduced CO₂ emissions by more than 30,000 tons through green design investments, while also significantly improving its product market share [9]. Therefore, green design investments can effectively meet rising CEA and enhance market demand [11,13]. Drawing on Yenipazarli [11], the product market demand function when the manufacturer carries out green design is $q=\alpha -bp+\beta e$. The manufacturer’s green investment cost is $h=\rho e^2$, where $\rho >0$ denotes the green design cost coefficient [4,16].

Assumption 2.

The manufacturer’s green design is capable of cutting down the production cost and the unit environmental impact [5,9]. In the consumer electronics supply chain, HP has adopted green design strategies that not only reduce material usage during the production process but also significantly lower pollutant emissions [5]. In the electric vehicle sector, BYD has continuously invested in green design research and development, which has reduced the production cost of new energy vehicles by 30%, improved their energy efficiency, and decreased emissions during both the production and usage stages [9]. Therefore, in the case of manufacturer’s green design, the unit production cost is $c(e)=(1-re)c$, and the unit environmental impact is $\theta (e)=(1-\lambda e)\theta$.

Assumption 3.

To ensure that all profit functions are concave and that related expressions are economically feasible, in line with prior research [13,34], the scale parameter satisfies $\rho >{\displaystyle \frac{(\alpha -bc)(bcr+\beta )+{(bcr+\beta )}^2}{6b}}$.

4. The Model and Equilibrium

In this subsection, we develop six supply chain decision models under three channel power structures—manufacturer-led, retailer-led, and Nash game—considering both green design adoption and non-adoption by the manufacturer. The corresponding equilibrium outcomes are derived through backward induction.

Both the manufacturer-led and retailer-led structures fall under the leader–follower Stackelberg game [4,6]. A Stackelberg game is a strategic game in which players make decisions sequentially [7,8]. One player (the leader) moves first, and the other player (the follower) observes the leader’s decision and then chooses the best response accordingly [12,13]. The Nash game refers to a state where both the manufacturer and the retailer simultaneously make decisions (e.g., wholesale price and retail price), and neither party can improve its own profit by unilaterally changing its strategy, given the strategy of the other [13,16]. This reflects a decentralized and symmetric power structure in the supply chain.

4.1. Game Model Under a Manufacturer-Led Structure

The game sequence is demonstrated in Figure 1.

The profit functions for the manufacturer and retailer are listed below:

When the manufacturer carries out green design (Model $ME$),

$${\pi }_M^{ME}=(w-(1-re)c)(\alpha -bp+\beta e)-\rho e^2$$

(1)

$${\pi }_R^{ME}=(p-w)(\alpha -bp+\beta e)$$

(2)

When the manufacturer does not carry out green design (Model $MN$),

$${\pi }_M^{MN}=(w-c)(\alpha -bp)$$

(3)

$${\pi }_R^{MN}=(p-w)(\alpha -bp)$$

(4)

As an example, the manufacturer’s adoption of green design is demonstrated, and an inverse recursive approach is utilized. First, from the retailer’s profit function ${\pi }_R^{ME}$, it is easily determined that $\frac{{\partial }^2{\pi }_R^{ME}}{\partial p^2}=-2b$, which is obviously less than zero. Therefore, ${\pi }_R^{ME}$ about $p$ is a strictly concave function. Then, let $\frac{\partial {\pi }_R^{ME}}{\partial p}=0$. The optimal feedback function on the retail price is $p^{ME}=\frac{\alpha +\beta e+bw}{2b}$. Furthermore, we substitute $p^{ME}$ into the manufacturer’s profit function ${\pi }_M^{ME}$. The manufacturer’s Hessian matrix is $H^{ME}=\left[\begin{array}{l}-b{\displaystyle \frac{\beta -bcr}{2}}\\ {\displaystyle \frac{\beta -bcr}{2}}\beta cr-2\rho \end{array}\right]$. When $\rho >{\displaystyle \frac{{(bcr+\beta )}^2}{8b}}$, $H^{ME}$ is negative definite, and at this time, ${\pi }_M^{ME}$ about $w,e$ is a strictly joint concave function. According to the first order conditions, the manufacturer’s optimal wholesale price $w^{ME\ast }$ and optimal green design level $e^{ME\ast }$ can be obtained. Then, we can attain the optimal retail price $p^{ME\ast }$ by substituting $w^{ME\ast }$ and $e^{ME\ast }$. Then, the maximum market demand $q^{ME\ast }$ can be obtained by function $q$. The optimal decision variables mentioned above are substituted into Equations (1) and (2), respectively, to arrive at the maximum profit for the manufacturer, retailer, and the overall system. Since the solution process is similar when the manufacturer does not carry out green design, it is omitted here. The relevant equilibrium results are summarized mathematically, as presented in

Table 2. Equilibrium results of manufacturer-led game model.

Model	$\mathbf{Model}\mathit{M}\mathit{E}(\mathit{i}=\mathit{M}\mathit{E})$	$\mathbf{Model}\mathit{M}\mathit{N}(\mathit{i}=\mathit{M}\mathit{N})$
$w^{i\ast }$	${\displaystyle \frac{4\rho (\alpha +bc)-c(\alpha r+\beta )(bcr+\beta )}{8\rho b-{(bcr+\beta )}^2}}$	${\displaystyle \frac{\alpha +bc}{2b}}$
$e^{i\ast }$	${\displaystyle \frac{(\alpha -bc)(bcr+\beta )}{8\rho b-{(bcr+\beta )}^2}}$	/
$p^{i\ast }$	${\displaystyle \frac{2k(3\alpha +bc)-c(\alpha r+\beta )(bcr+\beta )}{8\rho b-{(bcr+\beta )}^2}}$	${\displaystyle \frac{3\alpha +bc}{4b}}$
$q^{i\ast }$	${\displaystyle \frac{2\rho b(\alpha -bc)}{8\rho b-{(bcr+\beta )}^2}}$	${\displaystyle \frac{\alpha -bc}{4}}$
${\pi }_M^{i\ast }$	${\displaystyle \frac{\rho {(\alpha -bc)}^2}{8\rho b-{(bcr+\beta )}^2}}$	${\displaystyle \frac{{(\alpha -bc)}^2}{8b}}$
${\pi }_R^{i\ast }$	${\displaystyle \frac{4{\rho }^{2}b{(\alpha -bc)}^2}{{(8\rho b-{(bcr+\beta )}^2)}^2}}$	${\displaystyle \frac{{(\alpha -bc)}^2}{16b}}$
${\pi }_S^{i\ast }$	${\displaystyle \frac{\rho {(\alpha -bc)}^2(12\rho b-{(bcr+\beta )}^2)}{{(8\rho b-{(bcr+\beta )}^2)}^2}}$	${\displaystyle \frac{3{(\alpha -bc)}^2}{16b}}$

* represents the optimal equilibrium state.

.

4.2. Game Model Under a Retailer-Led Structure

The game sequence is demonstrated in Figure 2.

The profit function for the manufacturer and retailer are listed below:

When the manufacturer carries out green design (Model $RE$),

$${\pi }_M^{RE}=(w-(1-re)c)(\alpha -bw-bm+\beta e)-\rho e^2$$

(5)

$${\pi }_R^{RE}=m(\alpha -bw-bm+\beta e)$$

(6)

When the manufacturer does not carry out green design (Model $RN$),

$${\pi }_M^{RN}=(w-c)(\alpha -bw-bm)$$

(7)

$${\pi }_R^{RN}=m(\alpha -bw-bm)$$

(8)

Since the solution process of the above model is similar to Section 4.1, it is omitted here. The relevant equilibrium results are presented in

Table 3. Equilibrium results of retailer-led game model.

Model	$\mathbf{Model}\mathit{R}\mathit{E}(\mathit{i}=\mathit{R}\mathit{E})$	$\mathbf{Model}\mathit{R}\mathit{N}(\mathit{i}=\mathit{R}\mathit{N})$
$w^{i\ast }$	${\displaystyle \frac{2\rho (\alpha +3bc)-c(bcr+\beta )X}{2(4\rho b-{(bcr+\beta )}^2)}}$	${\displaystyle \frac{\alpha +3bc}{4b}}$
$e^{i\ast }$	${\displaystyle \frac{(\alpha -bc)(bcr+\beta )}{2(4\rho b-{(bcr+\beta )}^2)}}$	/
$m^{i\ast }$	${\displaystyle \frac{\alpha -bc}{2b}}$	${\displaystyle \frac{\alpha -bc}{2b}}$
$p^{i\ast }$	${\displaystyle \frac{2\rho b(3a+bc)-(bcr+\beta )Y}{2b(4\rho b-{(bcr+\beta )}^2)}}$	${\displaystyle \frac{3\alpha +bc}{4b}}$
$q^{i\ast }$	${\displaystyle \frac{\rho b(\alpha -bc)}{4\rho b-{(bcr+\beta )}^2}}$	${\displaystyle \frac{\alpha -bc}{4}}$
${\pi }_M^{i\ast }$	${\displaystyle \frac{\rho {(\alpha -bc)}^2}{4(4\rho b-{(bcr+\beta )}^2)}}$	${\displaystyle \frac{{(\alpha -bc)}^2}{16b}}$
${\pi }_R^{i\ast }$	${\displaystyle \frac{\rho {(\alpha -bc)}^2}{2(4\rho b-{(bcr+\beta )}^2)}}$	${\displaystyle \frac{{(\alpha -bc)}^2}{8b}}$
${\pi }_S^{i\ast }$	${\displaystyle \frac{3\rho {(\alpha -bc)}^2}{4(4\rho b-{(bcr+\beta )}^2)}}$	${\displaystyle \frac{3{(\alpha -bc)}^2}{16b}}$

$X=(\alpha r+bcr+2\beta )$, $Y=(\alpha (bcr+\beta )+bc(ar+\beta ))$. * represents the optimal equilibrium state.

.

4.3. Game Model Under a Nash Game Structure

The game sequence is demonstrated in Figure 3.

Although the wholesale and retail prices are determined simultaneously in the Nash game, this does not imply collaboration. Each party independently maximizes its own profit without coordinating decisions or sharing profits [13,16]. Thus, this setting represents a decentralized decision-making process, rather than a cooperative or centralized one.

The profit functions for the manufacturer and retailer are listed below:

When the manufacturer carries out green design (Model $NE$),

$${\pi }_M^{NE}=(w-(1-re)c)(\alpha -bw-bm+\beta e)-\rho e^2$$

(9)

$${\pi }_R^{NE}=m(\alpha -bw-bm+\beta e)$$

(10)

When the manufacturer does not carry out green design (Model $NN$),

$${\pi }_M^{NN}=(w-c)(\alpha -bw-bm)$$

(11)

$${\pi }_R^{NN}=m(\alpha -bw-bm)$$

(12)

The above model solving process is similar to Section 4.1 and as such is omitted here. The relevant equilibrium results are summarized mathematically, as presented in

Table 4. Equilibrium results of Nash game model.

Model	$\mathbf{Model}\mathit{N}\mathit{E}(\mathit{i}=\mathit{N}\mathit{E})$	$\mathbf{Model}\mathit{N}\mathit{N}(\mathit{i}=\mathit{N}\mathit{N})$
$w^{i\ast }$	${\displaystyle \frac{2\rho (\alpha +2bc)-c(bcr+\beta )(\alpha r+\beta )}{6\rho b-{(bcr+\beta )}^2}}$	${\displaystyle \frac{\alpha +2bc}{3b}}$
$e^{i\ast }$	${\displaystyle \frac{(\alpha -bc)(bcr+\beta )}{6\rho b-{(bcr+\beta )}^2}}$	/
$m^{i\ast }$	${\displaystyle \frac{2\rho (\alpha -bc)}{6\rho b-{(bcr+\beta )}^2}}$	${\displaystyle \frac{\alpha -bc}{3b}}$
$p^{i\ast }$	${\displaystyle \frac{2\rho (2\alpha +bc)-c(bcr+\beta )(\alpha r+\beta )}{6\rho b-{(bcr+\beta )}^2}}$	${\displaystyle \frac{2\alpha +bc}{3b}}$
$q^{i\ast }$	${\displaystyle \frac{2\rho b(\alpha -bc)}{6\rho b-{(bcr+\beta )}^2}}$	${\displaystyle \frac{\alpha -bc}{3}}$
${\pi }_M^{i\ast }$	${\displaystyle \frac{\rho {(\alpha -bc)}^2(4\rho b-{(bcr+\beta )}^2)}{{(6\rho b-{(bcr+\beta )}^2)}^2}}$	${\displaystyle \frac{{(\alpha -bc)}^2}{9b}}$
${\pi }_R^{i\ast }$	${\displaystyle \frac{4{\rho }^{2}b{(\alpha -bc)}^2}{{(6\rho b-{(bcr+\beta )}^2)}^2}}$	${\displaystyle \frac{{(\alpha -bc)}^2}{9b}}$
${\pi }_S^{i\ast }$	${\displaystyle \frac{\rho {(\alpha -bc)}^2(8\rho b-{(bcr+\beta )}^2)}{{(6\rho b-{(bcr+\beta )}^2)}^2}}$	${\displaystyle \frac{2{(\alpha -bc)}^2}{9b}}$

* represents the optimal equilibrium state.

.

5. Equilibrium Result Analyses

This study considers a supply chain consisting of a single manufacturer and a single retailer, which is a common structure in durable goods industries such as electronics and home appliances. Under this supply chain type, we first investigate whether the manufacturer has the incentive to adopt green design under different channel power structures, as well as the impact of green design implementation on supply chain decisions and environmental performance. Second, we explore how different power structures influence the manufacturer’s green design investment level, firm profitability, and environmental performance. Finally, we analyze how key cost parameters affect the optimal level of green design and the resulting supply chain decisions. All proofs of propositions are provided in the Appendix A.

5.1. The Impact of Green Design on the Operation of the Supply Chain and Environmental Performance Under Three Channel Power Structures

Proposition 1.

(1) In the case of the manufacturer-led structure, (a) when ${\displaystyle \frac{\beta }{b}}\ge cr$, $w^{ME\ast }\ge w^{MN\ast }$, and when ${\displaystyle \frac{\beta }{b}}<cr$, $w^{ME\ast }<w^{MN\ast }$; (b) when ${\displaystyle \frac{\beta }{b}}\ge {\displaystyle \frac{1}{3}}cr$, $p^{ME\ast }\ge p^{MN\ast }$, and when ${\displaystyle \frac{\beta }{b}}<{\displaystyle \frac{1}{3}}cr$, $p^{ME\ast }<p^{MN\ast }$. (2) In the case of the retailer-led structure, (a) when ${\displaystyle \frac{\beta }{b}}\ge cr$, $w^{RE\ast }\ge w^{RN\ast }$, and when ${\displaystyle \frac{\beta }{b}}<cr$, $w^{RE\ast }<w^{RN\ast }$; (b) when ${\displaystyle \frac{\beta }{b}}\ge cr$, $p^{RE\ast }\ge p^{RN\ast }$, and when ${\displaystyle \frac{\beta }{b}}<cr$, $p^{RE\ast }<p^{RN\ast }$. (3) In the case of the Nash game structure, (a) when ${\displaystyle \frac{\beta }{b}}\ge 2cr$, $w^{NE\ast }\ge w^{NN\ast }$, and when ${\displaystyle \frac{\beta }{b}}<2cr$, $w^{NE\ast }<w^{NN\ast }$; (b) when ${\displaystyle \frac{\beta }{b}}\ge {\displaystyle \frac{1}{2}}cr$, $p^{NE\ast }\ge p^{NN\ast }$, and when ${\displaystyle \frac{\beta }{b}}<{\displaystyle \frac{1}{2}}cr$, $p^{NE\ast }<p^{NN\ast }$.

Proposition 1 shows that, regardless of the channel power structure, the adoption of green design by a manufacturer does not inevitably result in increased wholesale and retail prices of products. Specifically, the manufacturer and retailer will charge higher prices for green design only if consumers are more sensitive to green design than to product price (i.e., consumers pay more attention to the environmental level of products). Conversely, both manufacturer and retailer will adopt a lower price strategy. Actually, diverse enterprises will also comprehensively deliberate the price sensitivity and CEA level of prospective consumers when formulating price strategies for ordinary products and environment-friendly products based on green design. Prospective consumers of high-end car brands such as BMW and Mercedes Benz are usually less sensitive to product prices, and the prices of the electric versions of the same series of models are much higher than those of the gasoline versions (for example, the price of the gasoline version of the BMW X5 is CNY 700,000, while the price of the electric version of the same series is CNY 860,000). The prospective consumers of Wuling Hongguang pay more attention to product price, so the price of the new electric car launched by Wuling Hongguang is only CNY 28,800, far lower than its previous gasoline car price (about CNY 50,000).

Previous studies have generally believed that when carrying out green research and development (R&D), enterprises usually increase the price of products to make up for their own investment in green R&D [1,11]. However, we show that whether enterprises will set higher product prices after adopting green design depends on the consumption concept of prospective consumers. If prospective consumers emphasize the environmentally friendly level of products more, enterprises should set higher product prices. On the contrary, in order to retain consumers, enterprises should adopt a lower product price strategy.

Proposition 2.

Under the three channel power structures, $q^{H\ast }>q^{L\ast }$, ${\pi }_M^{H\ast }>{\pi }_M^{L\ast }$, ${\pi }_R^{H\ast }>{\pi }_R^{L\ast }$, and ${\pi }_S^{H\ast }>{\pi }_S^{L\ast }$, where $H=\{ME,RE,NE\}$ and $L=\{MN,RN,NN\}$.

Proposition 2 shows that, whatever the channel power structure, compared with the case in which the manufacturer does not carry out green design, the manufacturer’s green design behavior contributes to higher product sales and increased profits for supply chain members and overall. In fact, product sales determine whether an enterprise can quickly attract consumers and occupy the market, which is also the key to the survival and profitability of the enterprise. The products produced by manufacturers after carrying out the green design strategy are more efficient and energy-saving, which can not only effectively cater to increasing CEA but also lower the use cost of consumers’ products. Therefore, compared with traditional products, consumers exhibit a greater propensity to purchase environmentally friendly and energy-efficient products based on green design. For example, GREE has always been committed to the independent R&D of green, low-carbon, and environment-friendly air conditioners, providing rosy future prospects regarding air conditioners and improving their energy efficiency by more than 10%, thereby achieving the effect of not damaging the ozone layer or contributing to the greenhouse effect, which has also been widely praised by consumers. According to the sales data of various brands of air conditioners published by HUATAI Securities Research Institute in 2020, GREE ranks first in the industry with a share of 36.9% and continues to maintain its leading position.

In combination with Propositions 1 and 2, when green design is applied, enterprises should not only consider their own investments in green design when formulating product price strategies but do so in combination with the consumption preferences of prospective consumer groups, so as to better cater to consumers and occupy the market.

Proposition 3.

(1) In the case of the manufacturer-led structure, when $0<\lambda \le {\displaystyle \frac{(bcr+\beta )(8\rho b-{(bcr+\beta )}^2)}{8\rho b(\alpha -bc)}}$, $E^{ME\ast }\ge E^{MN\ast }$, and when ${\displaystyle \frac{(bcr+\beta )(8\rho b-{(bcr+\beta )}^2)}{8\rho b(\alpha -bc)}}<\lambda <1$, $E^{ME\ast }<E^{MN\ast }$. (2) In the case of the retailer-led structure, when $0<\lambda \le {\displaystyle \frac{(bcr+\beta )(4\rho b-{(bcr+\beta )}^2)}{2\rho b(\alpha -bc)}}$, $E^{RE\ast }\ge E^{RN\ast }$, and when ${\displaystyle \frac{(bcr+\beta )(4\rho b-{(bcr+\beta )}^2)}{2\rho b(\alpha -bc)}}<\lambda <1$, $E^{RE\ast }<E^{RN\ast }$. (3) In the case of the Nash game structure, when $0<\lambda \le {\displaystyle \frac{(bcr+\beta )(6\rho b-{(bcr+\beta )}^2)}{6\rho b(\alpha -bc)}}$, $E^{NE\ast }\ge E^{NN\ast }$, and when ${\displaystyle \frac{(bcr+\beta )(6\rho b-{(bcr+\beta )}^2)}{6\rho b(\alpha -bc)}}<\lambda <1$, $E^{NE\ast }<E^{NN\ast }$.

Proposition 3 shows that, notwithstanding the prevailing channel power structure, the manufacturer’s adoption of green design does not invariably result in a diminution of products’ aggregate environmental impact compared with that in the absence of such design. Specifically, manufacturers’ green design behavior can only be efficacious in reducing the total environmental impact if green design can significantly minimize the unit environmental impact. This is due to the fact that the total environmental impact of a product is contingent upon two factors: the sales volume of the product and unit environmental impact. Despite the manufacturer’s efforts to mitigate the unit environmental impact through green design, there is a concomitant augmentation in product sales. Consequently, it is only when the manufacturer significantly lowers the unit environmental impact to a large extent through green design that this can offset the adverse environmental impact of increased product sales due to green design. At this time, the manufacturer’s green design can serve as a pivotal factor in diminishing the collective environmental impact.

Comprehensively, as shown by Propositions 1–3, a change in channel power structure has no influence on whether the manufacturer adopts green design strategies. Under the three channel power structures, a manufacturer’s green design behavior will continue to increase profits for her and the entire supply chain. However, it may not necessarily lower the total environment impact of products. Therefore, for manufacturing enterprises, when carrying out green transformation through green design, they prioritize not only the reduction of products’ production cost and the augmentation of market demand through green design but also make more green investment to lower the total environmental impact. For example, as mentioned in its 2020 Environmental Progress Report, Apple is actively working to lower the carbon footprint of its products while reducing product material and energy consumption through green design.

5.2. The Impact of Channel Power Structure on Green Design and Environment

Proposition 4.

In the case that the manufacturer carries out green design, under three distinct channel power structures, (1) when $\rho \le {\displaystyle \frac{{(bcr+\beta )}^2}{2b}}$, $e^{RE\ast }\ge e^{NE\ast }>e^{ME\ast }$ and $w^{ME\ast }>w^{RE\ast }\ge w^{NE\ast }$. (2) When $\rho >{\displaystyle \frac{{(bcr+\beta )}^2}{2b}}$, $e^{NE\ast }>e^{RE\ast }>e^{ME\ast }$ and $w^{ME\ast }>w^{NE\ast }>w^{RE\ast }$.

Proposition 4 shows that Nash game and retailer-dominated structures are more useful in lowering wholesale prices and producing higher levels of green design than manufacturer-dominated ones. Specifically, in circumstances where the green investment coefficient is comparatively minimal in relation to the retailer-led channel power structure, the capacity for the enhancement of green design and market demand is more pronounced. However, this configuration tends to impede the process of wholesale price reduction. On the contrary, when the coefficient of green investment is relatively high, the Nash game structure promotes green design improvement while hindering wholesale price reduction.

In fact, the manufacturer tends to maximize profits by raising wholesale prices and at the same time balance green design investments through adjustments to the green design level. Under manufacturer-dominated channel power structures, where the manufacturer holds stronger bargaining power, this results in consistently higher wholesale prices and lowered green design levels. Conversely, under retailer-led structures, the manufacturer’s weaker bargaining power drives a focus on green design improvements when investments are low. Therefore, when the investment coefficient of green design is relatively low, the manufacturer prioritizing enhanced green design lowers production costs, stimulates market demand, and ultimately increases profits.

Proposition 5.

In the case that the manufacturer carries out green design, under three distinct channel power structures, (1) $p^{ME\ast }>p^{RE\ast }>p^{NE\ast }$. (2) When $\rho \le {\displaystyle \frac{{(bcr+\beta )}^2}{2b}}$, $q^{RE\ast }\ge q^{NE\ast }>q^{ME\ast }$, and when $\rho >{\displaystyle \frac{{(bcr+\beta )}^2}{2b}}$, $q^{NE\ast }>q^{RE\ast }>q^{ME\ast }$.

Proposition 5 shows that, in the context of economic analysis, it has been demonstrated that the Nash game invariably results in a higher contribution to product prices, with the contributions from the manufacturer-led and retailer-led games following in sequence. If the green design investment coefficient of the manufacturer is lower than a certain critical value, the adoption of the retailer-led model will be more conducive to expanding the product market demand. When the green investment coefficient is relatively large, the Nash game structure contributes more to product market demand. Under the manufacturer-led structure, the product demand is always the least favorable.

Propositions 4 and 5 reveal that the manufacturer-led channel power structure consistently hinders improvements in green design levels and market demand. Whether green design is promoted in the context of a retailer-led or Nash game structure is contingent upon the investment coefficient. Regarding green design and market demand improvements, if the green investment coefficient is low, the retailer-led structure is better. If the opposite is the case, the Nash game structure is better.

Proposition 6.

In the case that the manufacturer carries out green design, under three distinct channel power structures, (1) ${\pi }_M^{ME\ast }>{\pi }_M^{NE\ast }>{\pi }_M^{RE\ast }$. (2) ${\pi }_R^{RE\ast }>{\pi }_R^{NE\ast }>{\pi }_R^{ME\ast }$. (3) When $\rho \le {\displaystyle \frac{{(bcr+\beta )}^2}{2b}}$, ${\pi }_S^{RE\ast }\ge {\pi }_S^{NE\ast }>{\pi }_S^{ME\ast }$, and when $\rho >{\displaystyle \frac{{(bcr+\beta )}^2}{2b}}$, ${\pi }_S^{NE\ast }>{\pi }_S^{RE\ast }>{\pi }_S^{ME\ast }$.

Proposition 6 indicates that both the manufacturer and the retailer always earn higher profits when they act as the channel leader and obtain lower profits when they act as the follower. When the cost coefficient of the manufacturer’s green design investment is relatively low, the retailer-led power structure is more conducive to improving the overall performance of the supply chain. Conversely, when the green design investment is costly, the Nash game structure is more favorable for enhancing overall supply chain performance. Moreover, under the manufacturer-led structure, the total profit of the supply chain is always the lowest. The results show that when the green investment coefficient is low, the retailer-led supply chain structure can improve the overall performance of the supply chain more efficiently. On the contrary, if the green investment coefficient is high, the Nash game model has more advantages. It is worth noting that in the manufacturer-led supply chain structure, its total profit is always at the lowest level.

Chen et al. [17] showed that the total profits of supply chain under the Nash game structure is greater than that under the channel power structure dominated by manufacturers or retailers. We further reveal that in the context of green design, when the green design investment cost coefficient is relatively small, the total profits of the supply chain under the retailer-led channel power structure is greater.

Proposition 7.

In the case that the manufacturer carries out green design, under three distinct channel power structures, (1) when $0<\lambda \le {\lambda }_1$, $E^{NE\ast }\ge E^{RE\ast }>E^{ME\ast }$; (2) when ${\lambda }_1<\lambda \le {\lambda }_2$, $E^{RE\ast }>E^{NE\ast }\ge E^{ME\ast }$; (3) when ${\lambda }_2<\lambda \le {\lambda }_3$, $E^{RE\ast }>E^{ME\ast }\ge E^{NE\ast }$; (4) when ${\lambda }_3<\lambda <1$, $E^{ME\ast }>E^{RE\ast }>E^{NE\ast }$.

Proposition 7 shows that, when the unit green design level is small, which means the reduction of the unit environmental impact can only be achieved to a minor degree, the channel power structure dominated by the manufacturer contributes more to the total environmental impact, while the Nash game channel power structure performs the worst. With an increase in $\lambda$, the channel power structure that is most useful to the reduction of the total environment impact will gradually change from a manufacturer-led to a Nash game structure. The channel power structure that is most unfavorable to reducing the total environment impact will gradually change from a Nash game to a retailer-led structure, and finally to a manufacturer-led structure. This occurs because total impact hinges on two factors: product sales volume ($q$) and per-unit environmental impact under green design. Consequently, when $\lambda$ is small, product sales volume exerts a more pronounced influence on total environmental impact. When $\lambda$ increases, the unit environmental impact reduces, and $\lambda$ exerts a more pronounced influence on the total environmental impact.

Based on the assumption that the manufacturer increases product greenness through product design, Hong et al. [7] stated that the retailer-led channel power structure is more effective in enhancing supply chain environmental performance. However, we further reveal that the retailer-led channel power structure does not really allow for a greater reduction in the product’s overall environmental impact than the manufacturer-led channel power structure.

Proposition 7 reveals that, from the perspective of reducing the total environmental impact, the channel power structure dominated by the manufacturer is better when enterprises can only lower the unit environmental impact to a small extent through green design. The opposite is true for the Nash game structure.

Table 5. Consolidated comparison of key outcomes across channel power structures.

Key Findings	Manufacturer-Led	Retailer-Led	Nash Game
Manufacturer’s incentive to implement green design	Always positive; enhances supply chain profit [Propositions 1 and 2]	Always positive; enhances supply chain profit [Propositions 1 and 2]	Always positive; enhances supply chain profit [Propositions 1 and 2]
Impact of green design on product price	May not significantly raise price [Proposition 1]	May not significantly raise price [Proposition 1]	May not significantly raise price [Proposition 1]
Impact on green design level, market demand, and profit	Moderate improvement [Propositions 4 and 5]	Highest improvement when green design cost coefficient is small [Propositions 4 and 5]	Highest improvement when green design cost coefficient is large [Propositions 4 and 5]
Effectiveness in increasing supply chain profit	Lower than other structures [Proposition 6]	Best performance when green design cost coefficient is large [Proposition 6]	Best performance when green design cost coefficient is large [Proposition 6]
Impact on total environmental impact when $\lambda$ is large	Less effective [Proposition 7]	More effective [Proposition 7]	Most effective [Proposition 7]
Impact on total environmental impact when $\lambda$ is small	Most effective [Proposition 7]	More effective [Proposition 7]	Less effective [Proposition 7]

presents a comparative summary of the key findings under three distinct channel power structures: manufacturer-led, retailer-led, and Nash game. The comparison integrates and synthesizes the results derived from the formal propositions (Proposition 1–Proposition 7) and provides a clear and intuitive understanding of how power dynamics affect supply chain decisions, economic outcomes, and environmental performance.

First, it is evident that the manufacturer always has an incentive to implement green design regardless of the power structure, as it enhances overall supply chain profit (Propositions 1 and 2). Second, the adoption of green design may not necessarily result in a significant increase in product prices under any of the three structures, which helps alleviate concerns about green premium pricing (Proposition 1).

Regarding green design level, market demand, and profit, the retailer-led structure performs best when the green design cost coefficient is small, while the Nash game structure shows the best performance when the cost coefficient is large (Propositions 4 and 5). In terms of improving supply chain profit, both the retailer-led and Nash game structures outperform the manufacturer-led structure under high green design costs (Proposition 6).

Finally, when evaluating total environmental impact, the power structure’s effectiveness varies with the parameter $\lambda$, which denotes the reduction rate of unit product impact through green design. Specifically, when $\lambda$ is large, the Nash game structure is most effective in reducing total environmental impact, whereas when $\lambda$ is small, the manufacturer-led structure performs better (Proposition 7). This reveals that while green design is broadly beneficial, the environmental outcome depends critically on both the marginal effect of green design and the underlying power structure.

This table consolidates theoretical insights into a managerial framework, facilitating better decision-making and highlighting the conditions under which each power structure is preferable from economic and environmental perspectives.

5.3. The Impact of Cost Parameters on Green Design and Supply Chain Performance

Proposition 8.

In the case that the manufacturer carries out green design, under three different distinct power structures, ${\displaystyle \frac{\partial w^{H\ast }}{\partial r}}<0$, ${\displaystyle \frac{\partial p^{H\ast }}{\partial r}}<0$, ${\displaystyle \frac{\partial e^{H\ast }}{\partial r}}>0$, ${\displaystyle \frac{\partial q^{H\ast }}{\partial r}}>0$, ${\displaystyle \frac{\partial {\pi }_M^{H\ast }}{\partial r}}>0$, ${\displaystyle \frac{\partial {\pi }_R^{H\ast }}{\partial r}}>0$, and ${\displaystyle \frac{\partial {\pi }_S^{H\ast }}{\partial r}}>0$, where $H=\{ME,RE,NE\}$.

Proposition 8 shows that, whatever the channel power structure, an increase in $r$ not only lowers wholesale and retail prices, enhances green design levels and market demand, but is also conducive to increasing the profits of supply chain members and the supply chain as a whole. This is because with an increase in $r$, improved per-unit green design efficiency more effectively lowers product production costs, motivating the manufacturer to cut wholesale prices and elevate green design levels. Meanwhile, the reduction of wholesale price and the improvement of green design level will also encourage the retailer to further increase market demand by reducing the retail price in response to the manufacturer’s efforts to increase the green design level. Finally, as the market demand grows, the manufacturer, the retailer, and the whole supply chain will benefit accordingly.

Proposition 8 reveals that when green design is carried out, the manufacturer can aim to minimize raw material usage without compromising product quality and performance, enabling more efficient production cost reduction through green design. This approach not only elevates their own profits but also strengthens overall supply chain performance. For example, by means of green design, Chrysler lowered material consumption and eradicated inefficient and redundant processes in manufacturing, thereby saving billions of dollars.

Proposition 9.

(1) In the case of the manufacturer-led structure, (a) when $\beta >bcr$, ${\displaystyle \frac{\partial w^{ME\ast }}{\partial \rho }}<0$, and when $\beta <bcr$, ${\displaystyle \frac{\partial w^{ME\ast }}{\partial \rho }}>0$; (b) when $\beta >{\displaystyle \frac{1}{3}}bcr$, ${\displaystyle \frac{\partial p^{ME\ast }}{\partial \rho }}<0$, and when $\beta <{\displaystyle \frac{1}{3}}bcr$, ${\displaystyle \frac{\partial p^{ME\ast }}{\partial \rho }}>0$. (2) In the case of the retailer-led structure, when $\beta >bcr$, ${\displaystyle \frac{\partial w^{RE\ast }}{\partial k}}<0$, ${\displaystyle \frac{\partial p^{RE\ast }}{\partial \rho }}<0$, and when $\beta <bcr$, ${\displaystyle \frac{\partial w^{RE\ast }}{\partial \rho }}>0$, ${\displaystyle \frac{\partial p^{RE\ast }}{\partial \rho }}>0$. (3) In the case of the Nash game structure, (a) when $\beta >2bcr$, ${\displaystyle \frac{\partial w^{NE\ast }}{\partial \rho }}<0$, and when $\beta <2bcr$, ${\displaystyle \frac{\partial w^{NE\ast }}{\partial \rho }}>0$; (b) when $\beta >{\displaystyle \frac{1}{2}}bcr$, ${\displaystyle \frac{\partial p^{NE\ast }}{\partial \rho }}<0$, and when $\beta <{\displaystyle \frac{1}{2}}bcr$, ${\displaystyle \frac{\partial p^{NE\ast }}{\partial \rho }}>0$. (4) Whatever the channel power structure, ${\displaystyle \frac{\partial e^{H\ast }}{\partial \rho }}<0$, ${\displaystyle \frac{\partial q^{H\ast }}{\partial \rho }}<0$, ${\displaystyle \frac{\partial {\pi }_M^{H\ast }}{\partial \rho }}<0$, ${\displaystyle \frac{\partial {\pi }_R^{H\ast }}{\partial \rho }}<0$, and ${\displaystyle \frac{\partial {\pi }_S^{H\ast }}{\partial \rho }}<0$.

Proposition 9 shows that, no matter what the channel power structure, the green design level, market demand, and either the profitability of the supply chain members or the overall supply chain are decreasing. However, counterintuitively, the wholesale and retail prices may not necessarily rise accordingly. In fact, when the green investment coefficient rises, the manufacturer directly lowers the green design level, which in turn indirectly restrains market demand. The profits of the manufacturer and the retailer are more dependent on market demand, which is subject to product price and green design level. Therefore, the manufacturer and retailer will counter the loss of market demand caused by the decline in green design level through price reduction strategies when CEA is stronger. On the contrary, when CEA is relatively weak, the reduction in market demand caused by the decline in green design level is limited. This time, the manufacturer and retailer benefit themselves by increasing prices appropriately.

Proposition 9 reveals that increased investment in green design by the manufacturer will lead to a reduction in green design level, thereby reducing product demand and the overall profits of the supply chain. Therefore, the government, as regulator of the market, should create a better environment for manufacturers to innovate green design, so as to encourage manufacturers to improve green design level and thus better enhance the overall performance of supply chain.

6. Numerical Simulation Analysis

This section mainly analyzes and verifies relevant conclusions through numerical examples. First, it analyzes the impact of CEA ($\beta$) on products’ retail price, green design level, supply chain operation performance, and environmental impact. Secondly, the effect of $\lambda$ (reduction degree of environmental impact of unit product caused by green design level) on reducing the total environment impact of products is examined. Referring to the parameter settings of Raz et al. [5], etc., we assume $a=100$, $b=6$, $c=12$, $r=0.2$, $k=50$, and $\theta =1$.

6.1. Impact of CEA on Supply Chain Pricing, Performance, and Environmental Impact

Figure 4, Figure 5, Figure 6 and Figure 7 show that, whatever the channel power structure, CEA’s enhancement will help encourage the manufacturer to elevate green design levels to boost product demand and raise overall supply chain profits. When the channel power structure is dominated by the manufacturer, the retail pricing of products is always at a high level, while the market demand, the level of green design, and the overall profitability of the supply chain are at a low level. However, the advantages and limitations of the two channel power structures depend on the relationship between CEA and green design investment parameters. When CEA is higher (${\displaystyle \frac{{(bcr+\beta )}^2}{2b}}>\rho$), the retailer-led channel power structure is better. On the contrary (${\displaystyle \frac{{(bcr+\beta )}^2}{2b}}<\rho$), the Nash game structure is better.

Figure 4, Figure 5, Figure 6 and Figure 7 also show that CEA is crucial to encouraging manufacturers to improve their green design and supply chain performance. Consequently, the government, in its capacity as the market regulator, has the authority to promote standards and certifications for green products and strengthen the publicity of green consumption by combining relevant enterprises, third-party public welfare certification agencies, and other social forces, so as to improve CEA and cultivate green consumption habits. For manufacturers, they should actively carry out green manufacturing through green design, strengthen the certification of green, energy-saving products, and strive to establish a good, green brand image for enterprises in the minds of consumers, so as to improve the competitiveness of enterprises. In practice, appliance manufacturers GREE (with inverter air conditioners), HAIER (with fluoride-free refrigerators), and other companies have actively developed green design research and development, with their energy-efficient, eco-friendly products gaining consumer recognition and support.

Figure 8 shows that, whatever the channel power structure, the enhancement of CEA is not always conducive to reducing the total environment impact of products. To be specific, the different colors represent two different values of the environmental impact reduction parameter $\lambda$ (e.g., $\lambda =0.1$ and $\lambda =0.9$). The solid lines correspond to the case of $\lambda =0.1$ while the colorful dotted lines correspond to $\lambda =0.9$. By comparing these two sets of curves, it can be seen that a larger $\lambda$, meaning a stronger effect of green design in reducing the environmental impact of the unit product, makes it more likely for an increase in CEA to reduce the total environmental impact. Conversely, when $\lambda$ is small, the increase in CEA tends to exacerbate the total environmental impact. In fact, as CEA increases, it inevitably encourages consumers to purchase more products. Therefore, only when green design significantly reduces the environmental impact per unit product can the increase in consumer purchases driven by higher CEA avoid leading to negative environmental outcomes.

Figure 8 reveals that the excessive enhancement of CEA may lead consumers to fall into the “green consumption trap”, which will lead to excessive purchasing behavior and have adverse effects on the environment. The “green consumption trap” refers to a paradox in which increasing CEA leads to higher demand for green products, yet the overall environmental outcome worsens due to insufficient per-unit environmental benefits. This occurs when green design fails to significantly reduce the environmental impact of individual products, while the demand surge driven by eco-conscious consumers results in a net increase in total pollution through expanded production. For example, because of the energy-saving nature of new energy vehicles, people increase their frequency of use or purchase more energy-consumption-related accessories more frequently, which makes them fall into the green consumption trap. Specifically, our results show that under such conditions, rising environmental awareness can paradoxically lead to greater total pollution rather than environmental improvement. This counterintuitive outcome—the “green consumption trap”—emerges when consumers’ pursuit of greener products inflates market demand, but each product’s environmental performance remains marginal.

To mitigate this risk, regulatory and policy interventions are essential. Authorities should implement minimum green design thresholds to ensure that green-labeled products achieve genuine per-unit environmental improvement. Simultaneously, mandatory transparency mechanisms should be introduced, requiring disclosure of quantifiable emission reduction metrics at the product level to help consumers distinguish between substantial and superficial green efforts. Furthermore, government subsidies and incentives should be strategically redirected toward supporting green technologies and practices that deliver verifiable ecological effectiveness, rather than simply rewarding increased demand or symbolic green claims.

6.2. Effect of Unit Green Design Level on Per-Unit Environmental Impact Reduction

This section mainly analyzes the effect of $\lambda$ on reducing the total environmental impact. The parameters mentioned in Section 6.1 are still applied, and $\beta =12$ is set.

Figure 9 shows that, whatever the channel power structure, the total environmental impact diminishes as the per-unit product impact reduction from green design rises (with an increase in $\lambda$). And the channel power structure that contributes most to the total environment impact will gradually change from the manufacturer-led to the Nash game structure, while the retailer-led structure is never the best.

Figure 9 reveals that manufacturing enterprises should focus on how to lower the adverse unit environmental impact through green design, thereby lowering overall environmental impact. For example, HUAWEI has reached the target of cutting CO₂ emissions by 11% and energy consumption by 8% by incorporating green design into its manufacturing system.

7. Conclusions, Management Insights, and Future Research

7.1. Conclusions

With the increasingly stringent environmental laws and regulations and the enhancement of CEA, more and more manufacturing enterprises reduce their resource consumption in the production process through green design to fulfill the environmental responsibility of green and low-carbon development and realize the transformation from traditional manufacturing to green manufacturing.

From the perspective of environmental responsibility, this study examines three types of channel power structures—manufacturer-led, retailer-led, and Nash game—and develops six supply chain decision-making models under scenarios with and without green design implementation. We investigate whether the manufacturer has incentives to engage in green design under different power structures and analyze the resulting impacts on supply chain decisions and environmental outcomes. The main conclusions are as follows: (1) Regardless of the channel power structure, the manufacturer always has the incentive to implement green design to increase both the profits of supply chain members and the supply chain as a whole. (2) Compared with the manufacturer-led structure, the retailer-led and Nash game structures are more conducive to improving the green design level, market demand, and the overall profits of the supply chain. (3) When the investment cost coefficient of green design is large, the Nash game channel power structure is more conducive to improving the green design level and the overall performance of the supply chain. When the opposite is the case, the channel power structure dominated by the retailer is better. (4) Although a large green design investment cost coefficient may not lead to higher product prices, it will reduce the enthusiasm of the manufacturer to engage in green design and thus reduce the overall profits of the supply chain. The enhancement of CEA is conducive to encouraging the manufacturer to improve her green design level, expand market demand, and increase the overall profits of the supply chain, but it may not always be conducive to reducing the total environmental impact of products. (5) Only when green design can significantly reduce the environmental impact of unit products can the manufacturer reduce the total environmental impact through implementing green design. (6) When green design can only reduce the environmental impact of unit products to a small extent, the manufacturer-led structure is more conducive to reducing the total environmental impact of products. When the opposite is the case, the Nash game channel power structure is better.

7.2. Management Insights

Based on the above theoretical insights and numerical results, we derive several practical implications for governments, enterprises, and consumers to jointly promote the efficiency and sustainability of green supply chains:

Governments play a pivotal role in shaping green supply chain practices. On one hand, they should reduce the cost of green innovation for manufacturers through targeted policy tools such as green subsidies, low-interest green credits, and tax incentives. For example, China’s Green Credit Guidelines have already facilitated financing for eco-friendly manufacturing upgrades in the home appliance and electronics sectors. On the other hand, regulatory authorities must ensure environmental effectiveness by setting minimum thresholds for green design performance and enforcing stricter eco-labeling standards. To avoid superficial green labeling, policies should encourage or mandate the disclosure of unit-level emission reduction data. This will enhance transparency and enable consumers to distinguish between genuinely sustainable products and those driven merely by green marketing.

At the firm level, manufacturers—regardless of their position in the channel power structure—should proactively fulfill environmental responsibilities by investing in authentic green design innovations. Real-world examples such as Huawei and BYD demonstrate the tangible benefits of such strategies: Huawei’s eco-design efforts reduced CO₂ emissions by over 30,000 tons while boosting market share, while BYD lowered NEV production costs by 30% and improved energy efficiency. Through sustained innovation, firms can build a strong green brand image, improve supply chain performance, and enhance their competitive position in environmentally conscious markets.

However, increasing green demand also brings risk. Our analysis reveals the potential for a “green consumption trap”, in which rising CEA stimulates demand, but if per-unit environmental impact is not significantly reduced, the total environmental burden may actually increase. For instance, the Autohome New Energy Vehicle Consumption Insight Blue Book finds that NEV users drive more frequently and longer daily distances than traditional vehicle users. Similarly, consumers using energy-efficient appliances often extend usage time, offsetting energy savings. To address this issue, governments should direct subsidies toward technologies that deliver real emission reductions, while consumers must be educated to avoid overconsumption of green products and make informed, rational purchasing decisions based on verified environmental data.

7.3. Future Research

While this study offers valuable theoretical insights, it has several limitations that suggest promising avenues for future research. First, the model adopts a simplified dyadic supply chain structure involving a single manufacturer and a single retailer. Although this captures key strategic interactions in many durable goods industries, real-world supply chains often involve more-complex, multi-tiered networks comprising suppliers, distributors, and logistics providers. Extending the analysis to multi-echelon or networked supply chains would enhance the generalizability of the findings. Second, the model is based on a static game framework, which limits its ability to capture dynamic strategic decisions over time—particularly relevant in the context of green design, where investment and regulatory responses evolve gradually. Future work could explore dynamic Stackelberg or differential game formulations to account for time-dependent decision-making and long-term environmental impacts. Third, the assumption of a linear demand function may oversimplify consumer behavior, which is often nonlinear and subject to uncertainty due to trends, media influence, and market volatility. Incorporating stochastic demand models or nonlinear functional forms, such as those based on random utility theory or robust optimization, could yield more-nuanced results. Lastly, while this study is grounded in analytical modeling, it lacks empirical validation. Future research should seek to calibrate the model using firm-level or industry-level data—such as from Huawei, BYD, or HP—or employ simulation-based case studies to assess the robustness of the theoretical conclusions and their relevance in real-world green supply chain practices.