Research on Private Label Introduction and Sales Mode Decision-Making for E-Commerce Platforms Considering Coupon Promotion Strategies

Abstract

With the rapid development of the digital economy and the evolving shopping preferences of consumers, e-commerce platforms have been enhancing their competitiveness by launching private label brands and optimizing their sales channel strategies. This study focuses on an online sales system comprising a strong brand and an e-commerce platform. Four game modes were constructed: agency selling only (NN), agency selling combined with reselling (NS), agency selling combined with private labels (IN), and reselling combined with agency selling under the introduction of private labels (IS). Under the coupon promotion strategy, this study focused on the introduction strategy for private labels (PLs) and the selection strategy for platform sales modes. Our research produced the following findings: (1) Regardless of whether the platform introduces its own brand, adopting a reselling mode can significantly enhance the profits of both the brand owner and platform. (2) Irrespective of whether the reselling mode is implemented, the platform’s profits are always increased when introducing its own brand. (3) When the coupon redemption rate is higher, the brand owner achieves greater profitability in the absence of PL introduction. Conversely, when the coupon redemption rate is low, an increase in the commission rate leads to reduced profit margins for the brand owner due to competition from a private label. (4) When the coupon redemption and commission rate are both high, the coupon face value without a PL is larger. Otherwise, when these rates are both low, the coupon face value is higher under the introduction of a PL. This study offers a theoretical foundation and decision-making support for e-commerce platforms to optimize sales mode selection, introduce private-label brands, and develop coupon strategies.

1. Introduction

In the past two decades, a significant number of retail platforms have emerged and experienced rapid growth, reaching a substantial economic scale. China’s online retail market—the world’s largest for 11 consecutive years—was projected to reach CNY 15.42 trillion in 2023, constituting an 11% increase [1]. With the rapid development of information technology, e-commerce platforms have diversified their interactions with consumers through various touchpoints, including point-of-sale systems, online stores, social media, and search advertising [2,3]. To address the rapid evolution of e-commerce and information technology (IT), the reselling and agency selling modes have been extensively adopted by suppliers and platforms due to their ability to effectively integrate resources and enhance operational efficiency [4]. For instance, Tmall primarily operates under an agency selling mode, whereas Amazon and JD.com are renowned for their reselling mode. In the reselling mode, manufacturers sell products to the platform at wholesale prices to secure wholesale profits, after which the platform determines the retail price and sells the product to consumers. In contrast, in the agency selling mode, manufacturers directly sell products to consumers via the platform to earn revenue and subsequently pay a predetermined percentage to the platform as agency fees. For example, Tmall charges merchants a commission rate ranging from 2% to 5%, JD.com charges between 5% and 8%, and Pinduoduo levies a service fee of 0.6%. Apple and Google charge a fixed fee per unit of the sales volume as the entry fee for electronic retail platforms [5,6].

As the online market has evolved, some platforms have sought to enhance their bargaining power in transactions and capture greater market share by entering the market with their own brands, offering competing products alongside those of suppliers. For instance, JD.com has introduced its own brands such as Jingxuan, Jiabai, and Zhixing and Amazon has launched Lark & Ro, Rivet, and Amazon Essentials, as shown in Figure 1. To enhance their market competitiveness and capture greater market share, e-commerce platforms have employed coupon strategies as a pivotal marketing instrument to shape consumer perceptions and promote private labels. For instance, following the introduction of the reselling mode, JD.com integrated the promotion of its own brands with various coupon campaigns, including “full reduction coupons”, “time-limited discount coupons”, and exclusive coupons for specific brands. This adaptable coupon strategy not only enables e-commerce platforms to maintain a competitive edge in the market, but also offers consumers more cost-effective options.

Therefore, the primary objective of this study was to investigate the following research questions:

(1)

Is it advisable for platforms to adopt a reselling mode? How does the implementation of the reselling mode affect the overall profitability of the supply chain?

(2)

Should platforms launch their own private brands? In what ways does the introduction of private labels modify the profit distribution mechanism within the supply chain?

(3)

Under varying sales modes and private brand strategies, how can e-commerce platforms strategically design coupon strategies to balance the interests of brand owners and their own objectives, thereby promoting collaborative development across the supply chain?

Based on this, this study focused on the introduction strategy for the platform’s brand and the selection strategy for the platform sales mode under a coupon promotion strategy. It constructed an online sales system comprising a strong brand owner and e-commerce platform, and analyzed the interaction effects of each decision-making entity’s behavior under the influence of consumer preferences, coupon redemption rates, and commission rates. Through an in-depth analysis of the decision-making behavior of each entity in various scenarios, it provides a scientific foundation for decision-making by e-commerce platforms and enterprises, thereby facilitating the collaborative development of the supply chain. We obtained some interesting results by determining the optimal mode: (1) The introduction of a reselling mode can consistently lead to substantial profit improvements for both the brand and platform. (2) Regardless of whether the platform adopts the reselling mode, introducing its own private-label brand can invariably enhance profitability. (3) When coupon redemption rates and commission rates are high, the face value of coupons is larger in the absence of private label offerings. Conversely, when these rates are low, the face value of coupons tends to be higher with the introduction of private label products.

Our research contributes to the literature in the following aspects. First, this study presents a systematic selection of sales modes for e-commerce platforms. Unlike the existing literature [7,8], this study explores the market equilibrium when multiple sales modes coexist. It further clarifies the interactions among different sales modes and their implications for the profits of both platforms and brand owners. Second, compared to prior research on brand introduction [9,10,11], this study adopts a distinct perspective. Specifically, it investigates whether and when platforms should introduce private brands along with platform coupons, as well as the impact of private brand introduction on the decision-making behaviors of e-commerce platforms and brand owners. Thus, this research offers a more comprehensive decision-making foundation for both platforms and brand owners.

The rest of the paper is organized as follows: Section 2 reviews the related literature, and Section 3 describes the problem. In Section 4, the analysis of the four modes NN, NS, IN, and IS is presented. The mode strategy, whether the platform should introduce a PL, and the reselling mode were analyzed. Finally, Section 5 concludes the paper, provides managerial insights, and outlines future recommendations. All proofs are presented in Appendix A.

2. Literature Review

The current paper is relevant to three streams of research: sales mode choice, PL introduction, and coupon strategies.

2.1. Sales Mode Choice

The rise in e-tailers has spurred extensive research into sales modes, particularly focusing on agency selling and reselling. The existing literature on sales modes choice can be categorized into two main streams. The first stream investigates the choice between operating modes (agency selling vs. reselling) and the critical factors influencing this decision, such as quality differentiation [12], cross-channel effects [13], and pricing strategies [14]. The second stream delves into the supplier’s decision-making process when determining its operational strategy. There are numerous papers investigating suppliers’ choice of selling channel based on various aspects, including carbon constraints [15], different pricing power structures and pricing strategies [16], and vertical differentiation [17].

Furthermore, Tan et al. examined the impact of three sales cooperation models (direct sales, wholesale, and hybrid) on manufacturers and e-commerce platforms under environmental regulations on supply chain profits and social welfare, and found that the optimal model depends on the environmental costs and benefits of the products [18]. Yuan et al. found that, regardless of whether manufacturers choose third-party logistics services or e-commerce platform logistics services, manufacturers should adopt a dual-channel sales model combining direct sales channels and agency channels to sell products [19]. Most of the existing literature has focused solely on analyses from a single-factor perspective. This study investigated how different sales modes interact with one another following the introduction of private labels on e-commerce platforms.

2.2. Private Label Introduction

The existing literature has primarily examined the multifaceted impact of private brand introduction on retailers and manufacturers. This includes enhancing profit margins [9], potentially increasing manufacturers’ profits in various competitive environments [10], and refining sales modes [20]. Additionally, Chu et al. investigated the interactive relationship between the introduction of private brands on online retail platforms and manufacturers’ channel selection strategies [21]. As market competition intensifies, the academic community has increasingly focused on brand competition. Abhishek et al. revealed that e-retailers should adopt the agency selling approach when channel competition yields adverse effects [7]. Building upon this foundational research, subsequent studies explored brand competition from various perspectives, including brand value [22,23], supplier competition intensity [24], e-tailer competition intensity [25,26], inventory levels and commission rates [27], and channel spillover effects [28,29]. However, these studies primarily focused on brand competition under two sales modes. In contrast, this study provides an in-depth analysis of brand competition between brand owners and e-commerce platforms in the context of private brand introduction.

2.3. Coupon Strategies

The research on coupons has primarily centered on two aspects: the impact of coupons on consumer choice and their influence on supply chain pricing and revenue. Christoph Bauner et al. investigated the coupon strategies of manufacturers and retailers, revealing that the quality and characteristic differences between private brands significantly affect the coupon value [30]. Hu et al. demonstrated that when platforms bear the cost of coupons, a “sufficient supply” strategy can lead to a win–win outcome for both platforms and merchants [31]. Li, Z. et al. examined coupon promotion strategies and their cross-channel effects in omnichannel retailing and found that retailers’ incentives to issue online or offline coupons depend on the retail price [32]. Li, H. et al. explored the procurement strategy for e-retailers’ private labels (PLs), constructing a mode to analyze the optimal approach for selecting PL products from national brand (NB) manufacturers, third-party suppliers, or internal production [33]. Niu et al. concentrated on brand resale decisions on e-commerce platforms, developing an approach for analyzing operational strategies in response to competition from platform private brands and PDT services [34]. While most existing studies have focused solely on the impact of coupons on consumer choice or supply chain returns, this research integrated coupon promotion strategies with sales mode selection and brand competition.

2.4. Research Gap Analysis and Contributions

Regarding the operation strategies of e-commerce platforms, most existing studies independently investigated the impact of sales channel selection, the introduction of private brands, and coupon promotions. However, few studies comprehensively examined the interplay among these three factors within the context of e-commerce platforms. This study aimed to analyze how e-commerce platforms integrate sales channel selection and private label introduction under coupon promotion strategies, as well as how the synergistic effects of these strategies influence the decision-making processes and market equilibrium among the various participants in the supply chain. A closely related study is that of Chu et al. [21], which explored the interaction between private brand introduction in online retail platforms and manufacturers’ channel choices. Table 1 highlights the primary distinctions between this study and the existing literature.

In summary, the innovations of this study are as follows: First, this study provides an in-depth analysis of the impact of private brand introduction on e-commerce platforms and the decision-making behaviors of brand owners. In contrast to prior studies [35], this study also extends the research by integrating a sales mode with a coupon promotion strategy to comprehensively evaluate its overall impact. Second, this study systematically investigated the selection of sales modes following the introduction of reselling and PLs within e-commerce platforms. In contrast to prior studies [11,36], this study delved into the market equilibrium when multiple sales modes coexist, elucidating the interactions between different sales modes and their implications for the profits of both platforms and brand owners.

Table 1. Summary of the literature.

Study	Decisions
	Agency Selling	Reselling	PL Introduction	Coupon Strategies
Alan et al. [9]			√
Shopova. [20]			√
Choi and Turut [10]			√
Hu et al. [31]				√
Abhishek et al. [7]	√	√
Li et al. [8]	√	√
Tan et al. [18]	√	√
Bauner et al. [30]			√	√
Yuan et al. [19]	√	√	√
Hemmati et al. [36]	√	√	√
Chu et al. [21]	√	√	√
Shen et al. [6]	√	√	√
Li et al. [32]	√			√
Niu et al. [34]		√		√
Wan et al. [11]	√	√
This paper	√	√	√	√

Table 1. Summary of the literature.

Study	Decisions
	Agency Selling	Reselling	PL Introduction	Coupon Strategies
Alan et al. [9]			√
Shopova. [20]			√
Choi and Turut [10]			√
Hu et al. [31]				√
Abhishek et al. [7]	√	√
Li et al. [8]	√	√
Tan et al. [18]	√	√
Bauner et al. [30]			√	√
Yuan et al. [19]	√	√	√
Hemmati et al. [36]	√	√	√
Chu et al. [21]	√	√	√
Shen et al. [6]	√	√	√
Li et al. [32]	√			√
Niu et al. [34]		√		√
Wan et al. [11]	√	√
This paper	√	√	√	√

3. Selling Mode

3.1. Problem Definition

Consider an online sales system comprising a strong brand owner M and an e-commerce platform P. Based on this framework, the platform may evaluate whether to introduce a reselling mode as well as its own brand PL. This study primarily examined the following four scenarios, as shown in Figure 2:

Scenario NN: The e-commerce platform adopts the agency selling mode to facilitate transactions. Under this mode, the brand owner establishes flagship or specialty stores on the platform, retaining direct pricing authority over their products $p_A$. They sell directly to consumers and remit a commission rate $\lambda \left(0<\lambda <1\right)$, which varies depending on the product category, to the e-commerce platform.

Scenario NS: The e-commerce platform incorporates a reselling mode alongside the existing agency selling mode. The brand owner can now choose to either sell their products through the platform under the agency selling arrangement or transfer goods to the e-commerce platform at wholesale prices. In this scenario, the e-commerce platform independently establishes the retail pricing strategy $p_o$ and oversees the entire sales process.

Scenario IN: The e-commerce platform launches its own private label while continuing to operate under the agency selling mode. The pricing for these private-label products is determined independently by the e-commerce platform $p_B$, and they are marketed alongside the products under agency selling from the brand owner on the same platform.

Scenario IS: The e-commerce platform utilizes both the agency selling and reselling modes while introducing its PL for sale. Within this framework, intricate competitive and cooperative dynamics exist among the brand owner, the e-commerce platform, and the platform’s private label.

Figure 2. Supply chain structures.

Figure 2. Supply chain structures.

Without loss of generality, we assume that the production cost for both brands is zero. For the sake of clarity, NB is employed to denote the brand owner in this paper, while PL is utilized to represent the private label of the e-commerce platform. In order to enhance brand competitiveness, the e-commerce platform offers store-wide coupons with a face value of $f$ for products under the reselling mode, agency selling mode, and the platform’s own PL. The coupon redemption rate is set at $\alpha ,\alpha \in (0,1)$. The impact coefficient of the coupon on goods within a single store is denoted as $k\in [0,1]$, and $kf$ represents the actual amount deducted by the coupon in that store. In the market, private label (PL) products are frequently perceived as inferior substitutes compared to well-known national brand (NB) products [37]. Consequently, consumers tend to prefer purchasing NB goods over PL goods. The consumer preference for NB goods in the reselling mode is normalized to 1. The consumer preference for NB goods in the agency selling mode is denoted by ${\theta }_A$. This hypothesis has been widely adopted in the literature [38,39]. In practice, e-commerce platforms typically provide superior services for goods sold in the reselling mode, leading to a higher consumer preference for NB goods in the reselling mode compared to the agency selling mode. Let ${\theta }_B$ denote the consumer’s preference for PL goods. Thus, $1>{\theta }_A>{\theta }_B>0$, signifying that the consumer exhibits a stronger preference for the NB goods in the reselling mode compared to the NB goods in the agency selling mode, while the preference for the PL goods is the weakest.

According to Yan et al. [39], the demand function is derived from the consumer utility function, assuming that the total market demand consists of a group of heterogeneous consumers. The reservation price for the product, denoted as $v$, is uniformly distributed within the interval $\left[0,1\right]$. Each consumer purchases at most one unit of the commodity and makes purchasing decisions by maximizing their utility. According to reference [40], service can enhance the utility obtained by consumers when purchasing goods. Consequently, e-commerce platforms allocate service investments indifferently across the reselling mode, agency selling mode, and their own brand PL. Here, $r$ represents the sensitivity of consumers to service quality. Assuming that the service cost is a quadratic function of the service level, let the service cost function be denoted as $C(s)={\displaystyle \frac{\eta s^2}{2}}$, and let $\eta$ represent the coefficient of the service investment cost. The notations used in the models are outlined in

Table 2. Notations and descriptions.

Variable	Description
$v$	Consumer valuation of goods
$U_i^r$	The utility of purchasing the good from channel i for the type r consumer in
$\lambda$	Commission rates, $0<\lambda <1$
$f$	Face value of coupons placed on e-commerce platform $(0<f<p)$
$\alpha$	Coupon redemption rate, $\alpha \in (0,1)$
$k$	Coupon coefficients on individual store items, $k\in [0,1]$
${\theta }_i$	Consumer preference for different channels, $0<\theta <1$
$w$	Wholesale prices of goods
$p_i$	Prices of goods in channel $i$
$r$	Consumer sensitivity to services
$s$	Level of service provided by e-commerce platform
$\eta$	Service investment cost factor $(0<\eta <1)$
${\mathsf{\Pi }}_k$	The profit of $k$ ($k=M,P$, where $M$ denotes the brand owner and $P$ denotes the platform)
Subscript $i$	$i=o,A,B$, where $o$ indicates the reselling mode, $A$ indicates the agency selling mode, and $B$ indicates the PL

.

3.2. Mode Setup

This section primarily examines consumers’ purchasing decisions under four scenarios: NN, NS, IN, and IS. The market segments of the four schemes in this paper are identified below.

Scenario NN: Given that only the agency mode exists in the e-commerce platform, the utility for consumers purchasing NB products under the agency mode is $U_A={\theta }_{A}v-p_A+kf+rs$. Consumers will purchase the product only if $U_A\ge 0$, leading to an indifference point $x_1$, which can be expressed as $x_1={\displaystyle \frac{p_A-kf-rs}{{\theta }_A}}$. From this, we can derive $Q_A^{NN}=1-{\displaystyle \frac{p_A-kf-rs}{{\theta }_A}}$.

Scenario NS: If the platform introduces the reselling mode under Scenario NN, consumers can only purchase NB products, but there are two purchase channels. The utility obtained by consumers purchasing through the reselling mode is $U_o=v-p_o+kf+rs$. A customer’s utility is $U_A={\theta }_{A}v-p_A+kf+rs$ under the agency selling mode. When $U_o\ge \max \left\{U_A,0\right\}$, consumers purchase through the reselling mode. Similarly, consumers purchase through the agency selling mode only when $U_A\ge \max \left\{U_o,0\right\}$. From this, we can derive $Q_o^{NS}=1-{\displaystyle \frac{p_o-p_A}{1-{\theta }_A}},$ $Q_A^{NS}={\displaystyle \frac{p_o-p_A}{1-{\theta }_A}}-{\displaystyle \frac{p_A-kf-rs}{{\theta }_A}}$.

Scenario IN: If the platform introduces a PL under Scenario NN, consumers have two purchasing options. A customer’s utility is $U_A={\theta }_{A}v-p_A+kf+rs$ under the agency selling mode. The utility obtained by consumers purchasing from the PL is $U_B={\theta }_{B}v-p_B+kf+rs$. When $U_A\ge \max \left\{U_B,0\right\}$, consumers purchase through the agency selling mode. Similarly, consumers purchase from the PL only when $U_B\ge \max \left\{U_A,0\right\}$. From this, we can derive $Q_A^{IN}=1-{\displaystyle \frac{p_A-p_B}{{\theta }_A-{\theta }_B}},$ $Q_B^{IN}={\displaystyle \frac{p_A-p_B}{{\theta }_A-{\theta }_B}}-{\displaystyle \frac{p_B-kf-rs}{{\theta }_B}}$.

Scenario IS: If the platform introduces a PL and the reselling mode under Scenario IS, consumers have three purchasing options. The utility obtained by consumers purchasing through the reselling mode is $U_o=v-p_o+kf+rs$. A customer’s utility is $U_A={\theta }_{A}v-p_A+kf+rs$ under the agency selling mode. The utility obtained by consumers purchasing from the PL is $U_B={\theta }_B*v-p_B+kf+rs$. When $U_o>U_A,U_o>U_B$ and $U_o>0$, consumers purchase through the reselling mode. Consumers purchase through the agency selling mode only when $U_A>U_o,U_A>U_B$ and $U_A>0$. Similarly, consumers only purchase from the PL when $U_B>U_A,U_B>U_o$ and $U_B>0$. From this, we can derive $Q_o^{IS}=1-{\displaystyle \frac{p_o-p_A}{1-{\theta }_A}},Q_A^{IS}={\displaystyle \frac{p_o-p_A}{1-{\theta }_A}}-{\displaystyle \frac{p_A-p_B}{{\theta }_A-{\theta }_B}},Q_B^{IS}={\displaystyle \frac{p_A-p_B}{{\theta }_A-{\theta }_B}}-{\displaystyle \frac{p_B-kf-rs}{{\theta }_B}}$.

Based on the market segments, the profit functions of the platform and brand are as follows:

Scenario NN:

$$\left\{\begin{array}{l}{\mathsf{\Pi }}_P^{NN}=\lambda p_A{Q}_A-\alpha kf{Q}_A-{\displaystyle \frac{\eta s^2}{2}}\\ {\mathsf{\Pi }}_M^{NN}=\left(1-\lambda \right)p_A{Q}_A\end{array}\right.$$

(1)

Scenario NS:

$$\left\{\begin{array}{l}{\mathsf{\Pi }}_P^{NS}=\left(p_o-w\right)Q_o+\lambda p_A{Q}_A-\alpha kf\left(Q_o+Q_A\right)-{\displaystyle \frac{\eta s^2}{2}}\\ {\mathsf{\Pi }}_M^{NS}=w{Q}_o+\left(1-\lambda \right)p_A{Q}_A\end{array}\right.$$

(2)

Scenario IN:

$$\left\{\begin{array}{l}{\mathsf{\Pi }}_P^{IN}=p_B{Q}_B+\lambda p_A{Q}_A-\alpha kf\left(Q_A+Q_B\right)-{\displaystyle \frac{\eta s^2}{2}}\\ {\mathsf{\Pi }}_M^{IN}=\left(1-\lambda \right)p_A{Q}_A\end{array}\right.$$

(3)

Scenario IS:

$$\left\{\begin{array}{l}{\mathsf{\Pi }}_P^{IS}=\left(p_o-w\right)Q_o+\lambda p_A{Q}_A+p_B{Q}_B-\alpha kf\left(Q_o+Q_A+Q_B\right)-{\displaystyle \frac{\eta s^2}{2}}\\ {\mathsf{\Pi }}_M^{IS}=w{Q}_o+\left(1-\lambda \right)p_A{Q}_B\end{array}\right.$$

(4)

This study determined the optimal strategy and optimal solution, as shown in Proposition 1.

 Proposition 1. 

There exist optimal coupon values, prices, and wholesale prices across all four scenarios, which maximize the profits of both the brand and platform. The optimal solutions in Scenarios NN, NS, IN, and IS are shown in

Table 3. Equilibrium price, coupon face value, wholesale price, and yield across different scenarios.

Variable	Scenario NN	Scenario NS	Scenario IN	Scenario IS
$p_o$	—	${\displaystyle \frac{\left(\begin{array}{l}3\alpha +2rs\alpha -3\lambda \\ -\alpha {\theta }_A+3\lambda {\theta }_A\end{array}\right)}{4\alpha -4\lambda }}$	—	${\displaystyle \frac{2\left(1+\alpha \right){\theta }_B^2+{\mathsf{\Omega }}_7}{4{\mu }_1}}$
$p_A$	${\displaystyle \frac{\alpha \left(rs+{\theta }_A\right)}{2\left(\alpha -\lambda \right)}}$	${\displaystyle \frac{\alpha \left(rs+{\theta }_A\right)}{2\left(\alpha -\lambda \right)}}$	${\displaystyle \frac{\left[\begin{array}{l}\left({\theta }_A-{\theta }_B\right)\left(\alpha -1\right)rs\alpha +\\ {\left(\alpha -1\right)}^2{\theta }_A-\left(1+\alpha \right){\theta }_B\end{array}\right]}{2{\mu }_1}}$	${\displaystyle \frac{\left[\begin{array}{l}\left({\theta }_A-{\theta }_B\right)\left(\alpha -1\right)rs\alpha +\\ {\left(\alpha -1\right)}^2{\theta }_A-\left(1+\alpha \right){\theta }_B\end{array}\right]}{2{\mu }_1}}$
$p_B$	—	—	${\displaystyle \frac{{\theta }_B\alpha \left({\theta }_A-{\theta }_B\right)+{\mathsf{\Omega }}_2}{{\mu }_1{\mu }_2}}$	${\displaystyle \frac{\alpha \left({\theta }_A-{\theta }_B\right){\theta }_B+{\mathsf{\Omega }}_2}{{\mu }_1{\mu }_2}}$
$f$	${\displaystyle \frac{\left(\alpha -3\lambda \right)\left(rs+{\theta }_A\right)}{4k\left(\lambda -\alpha \right)}}$	${\displaystyle \frac{\left(\alpha -3\lambda \right)\left(rs+{\theta }_A\right)}{4k\left(\lambda -\alpha \right)}}$	${\displaystyle \frac{{\mathsf{\Omega }}_3}{2k{\mu }_1{\mu }_2}}$	${\displaystyle \frac{{\mathsf{\Omega }}_3}{2k{\mu }_1{\mu }_2}}$
$w$	—	${\displaystyle \frac{\left(\begin{array}{l}\alpha -\lambda +r\alpha s-r\alpha s\lambda \\ +\lambda {\theta }_A-\alpha \lambda {\theta }_A\end{array}\right)}{2\left(\alpha -\lambda \right)}}$	—	${\displaystyle \frac{{\mathsf{\Omega }}_8-{\left(\alpha -1\right)}^2\lambda {\theta }_A^2}{2{\mu }_1}}$
${\mathsf{\Pi }}_P$	${\displaystyle \frac{\left[\begin{array}{l}2s\left(r\alpha -4s\eta \right)\\ +r^2{s}^2\alpha +\alpha {\theta }_A\end{array}\right]}{16{\theta }_A}}$	${\displaystyle \frac{\left(\begin{array}{l}{r}^2{s}^2\alpha +{\theta }_A+2{\theta }_{A}rs\alpha \\ -8{\theta }_A{s}^2\eta +\alpha {{\theta }_A}^2-{{\theta }_A}^2\end{array}\right)}{16{\theta }_A}}$	${\displaystyle \frac{{\mathsf{\Omega }}_4}{-4{{\mu }_1}^2{{\mu }_2}^2}}$	${\displaystyle \frac{{\mathsf{\Omega }}_9}{16{\mu }_2{{\mu }_1}^2}}$
${\mathsf{\Pi }}_M$	${\displaystyle \frac{\alpha \left(1-\lambda \right){\left(rs+{\theta }_A\right)}^2}{8\left(\alpha -\lambda \right){\theta }_A}}$	${\displaystyle \frac{{\mathsf{\Omega }}_1}{8\left(\alpha -\lambda \right){\theta }_A}}$	${\displaystyle \frac{\left(1-\lambda \right)\left({\theta }_A-{\theta }_B\right){\mathsf{\Omega }}_5}{4{\mathsf{\Omega }}_6}}$	${\displaystyle \frac{\left[{\theta }_A^3{\left(\alpha -1\right)}^4\left(2\lambda -1\right)+{\mathsf{\Omega }}_{10}\right]}{8{\mu }_1{\mu }_2}}$

See Appendix A for detailed information.

.

4. Mode Analysis

4.1. Parameter Sensitivity Analysis

Using the equilibrium decisions presented in Section 3, Corollary 1 examines how important parameters (i.e., $\alpha ,\lambda ,k$) impact the equilibrium decisions under Scenarios NN, NS, IN, and IS. The corresponding proofs are provided in Appendix A.

 Corollary 1. 

Impact of Parameters (i.e., $\alpha ,\lambda ,k$) on coupon values and product prices in Scenarios NN, NS, IN, and IS.

(i) 

Scenario NN

$${\displaystyle \frac{d{p}_A^{NN}}{d\lambda }}>0,{\displaystyle \frac{d{f}^{NN}}{d\lambda }}>0;{\displaystyle \frac{d{p}_A^{NN}}{d\alpha }}<0,{\displaystyle \frac{d{f}^{NN}}{d\alpha }}<0;{\displaystyle \frac{d{f}^{NN}}{dk}}<0.$$

(ii) 

Scenario NS

$${\displaystyle \frac{d{w}^{NS}}{d\lambda }}>0,{\displaystyle \frac{d{p}_A^{NS}}{d\lambda }}>0,{\displaystyle \frac{d{p}_o^{NS}}{d\lambda }}>0,{\displaystyle \frac{d{f}^{NS}}{d\lambda }}>0;$$

$${\displaystyle \frac{d{w}^{NS}}{d\alpha }}<0,{\displaystyle \frac{d{p}_A^{NS}}{d\alpha }}<0,{\displaystyle \frac{d{p}_o^{NS}}{d\alpha }}<0,{\displaystyle \frac{d{f}^{NS}}{d\alpha }}<0;{\displaystyle \frac{d{f}^{NS}}{dk}}<0.$$

(iii) 

Scenario IN

If  $\widetilde{{\theta }_A}<{\theta }_A<1$, then  ${\displaystyle \frac{d{p}_A^{IN}}{d\lambda }}<0,{\displaystyle \frac{d{p}_B^{IN}}{d\lambda }}<0,{\displaystyle \frac{d{f}^{IN}}{d\lambda }}<0$;

If ${\theta }_{B1}<{\theta }_B<{\theta }_{B2}$, ${\displaystyle \frac{d{p}_A^{IN}}{d\alpha }}>0$; ${\displaystyle \frac{d{f}^{IN}}{dk}}<0$.

(iv) 

Scenario IS

If  $\widetilde{{\theta }_A}<{\theta }_A<1$, then  ${\displaystyle \frac{d{w}^{IS}}{d\lambda }}<0,{\displaystyle \frac{d{p_A}^{IS}}{d\lambda }}<0,{\displaystyle \frac{d{p_o}^{IS}}{d\lambda }}<0,{\displaystyle \frac{d{p_B}^{IS}}{d\lambda }}<0,{\displaystyle \frac{d{f}^{IS}}{d\lambda }}<0$;

If ${\theta }_{B1}<{\theta }_B<{\theta }_{B2}$, then ${\displaystyle \frac{d{w}^{IS}}{d\alpha }}<0,{\displaystyle \frac{d{p_A}^{IS}}{d\alpha }}>0,{\displaystyle \frac{d{p_o}^{IS}}{d\alpha }}>0$; ${\displaystyle \frac{d{f}^{IS}}{dk}}<0$.

Corollary 1(i) and (ii) shows that in Scenarios NN and NS, the coupon face value, agency selling price, reselling price, and wholesale price are positively correlated with the commission rate and negatively correlated with the coupon redemption rate. The underlying reason is that in Scenarios NN and NS, when the commission rate rises, the brand owner will increase the product price under agency selling to protect their profits, and at the same time, they will increase the wholesale price under reselling to make up for the loss of profit due to the increase in commission. To maintain its own revenue, the e-commerce platform will also support the price increase behavior of the brand owner, which in turn leads to an increase in the price of goods under reselling. Meanwhile, the platform will increase the face value of coupons to stimulate consumer purchases. When the coupon redemption rate increases, to safeguard profits, the brand owner tends to reduce the prices of goods under agency selling. At the same time, the platform will also lower the reselling prices and encourage the brand owner to decrease the wholesale prices to maintain market share and revenue. Additionally, to control costs, the platform will reduce the face value of coupons.

Surprisingly, Corollary 1(iii) and (iv) reveals that in Scenarios IN and IS, when consumers have a greater preference for goods under the agency selling mode, the coupon face value, price under agency selling, price under reselling, price of the PL brand, and wholesale price are negatively related to the commission rate. The reason for this is that when consumers have a greater preference for agency selling in Scenarios IN and IS, the brand owner will reduce their support to the e-commerce platform as the commission rate rises, thus lowering the price under agency selling. As a result, the platform will reduce the coupon values to control costs. Additionally, due to the dominance of products under agency selling, the platform will also reduce reselling and PL prices to maintain market stability and consumer satisfaction. Furthermore, when the consumer’s preference for the private label is within a certain range, the price under the agency selling and reselling modes are positively related to the coupon redemption rate, and the wholesale price is negatively related to the coupon redemption rate. This is because as the coupon redemption rate increases, the brand owner will appropriately increase the price under agency selling to gain more profit. To achieve a balanced overall profit structure, the platform will appropriately increase the resale price. Simultaneously, the brand will reduce the wholesale price, thereby providing the platform with greater flexibility to adjust the resale price and boost sales.

Corollary 1 also shows that the coupon face value is negatively correlated with the coefficient of the coupons’ effect on individual store items in all four scenarios. When the coefficient of effect $k$ increases, it implies that the actual discounting power of coupons in individual stores is enhanced. At this juncture, to avoid the increased costs for the e-commerce platform without a significant increase in consumer purchase volumes, the e-commerce platform will correspondingly reduce the face value of the coupons. Based on the analysis above, the platform should dynamically adjust the par value in accordance with the commission rate and par redemption rate to prevent excessive discounts from adversely impacting profitability. For the brand owner, it is essential to closely monitor platform commission rates and coupon strategies, optimize supply chain management to minimize costs, and reinforce the brand image to enhance competitive differentiation.

4.2. Analysis of Introduction of Reselling Mode

This section compares the optimal solutions across the different sales mode scenarios (i.e., NN vs. NS and IN vs. IS). First, this section identifies the inherent relationships between prices, coupon values, and demand in each scenario.

 Corollary 2. 

Difference in coupon face value and price in different scenarios.

(i) 

Scenario NN vs. Scenario NS

$$p_A^{N{N}^{*}}=p_A^{N{S}^{*}},f^{N{N}^{*}}=f^{N{S}^{*}}$$

(ii) 

Scenario IN vs. Scenario IS

$$p_A^{I{N}^{*}}=p_A^{I{S}^{*}},p_B^{I{N}^{*}}=p_B^{I{S}^{*}},f^{I{N}^{*}}=f^{I{S}^{*}}$$

Corollary 2 indicates that the price of goods under the agency selling mode remains unchanged $\left(p_A^{N{N}^{*}}=p_A^{N{S}^{*}},p_A^{I{N}^{*}}=p_A^{I{S}^{*}}\right)$ as the brand owner and platform maintain consistency in their pricing strategies to avoid market uncertainty caused by price fluctuations. Moreover, the face value of coupons remains unchanged when the platform introduces the reselling mode $\left(f^{N{N}^{*}}=f^{N{S}^{*}},f^{I{N}^{*}}=f^{I{S}^{*}}\right)$. In order to maintain the consistency of the overall marketing strategy, the platform retains the stable coupon strategy. For example, when Tmall introduces a new reselling merchant, its previously issued cross-store coupons, such as the “300 minus 50” coupon, have already formed certain consumer expectations and usage habits in the market, so the coupon’s face value remains unchanged for a period of time. Notably, the prices for the private label remain relatively stable $\left(p_B^{I{N}^{*}}=p_B^{I{S}^{*}}\right)$. The intuition is that private brands typically exhibit a clear market positioning and target specific consumer groups. These brands are strategically designed to cater to particular needs and preferences of consumers, with the pricing strategies remaining relatively consistent to uphold the brand image and maintain market positioning.

 Corollary 3. 

Difference in market demand in different scenarios.

(i) 

Scenario NN vs. Scenario NS

$$Q_A^{N{N}^{*}}>Q_A^{N{S}^{*}}$$

(ii) 

Scenario IN vs. Scenario IS

$$Q_A^{I{N}^{*}}>Q_A^{I{S}^{*}},Q_B^{I{N}^{*}}=Q_B^{I{S}^{*}}$$

Corollary 3 shows that the introduction of the reselling mode leads to a decrease in the demand for goods under the reselling mode regardless of the introduction of a PL $\left(Q_A^{N{N}^{*}}>Q_A^{N{S}^{*}},Q_A^{I{N}^{*}}>Q_A^{I{S}^{*}}\right)$. The reason for this is that after the introduction of the reselling mode, consumers have more choices for purchasing channels, and some of the consumers who originally purchased through the agency selling mode turn to the reselling mode, which leads to a decrease in the demand for goods under the reselling mode. Furthermore, the demand for the private label remains relatively stable $\left(Q_B^{I{N}^{*}}=Q_B^{I{S}^{*}}\right)$. The rationale for this lies in the fact that certain platforms adopt market segmentation strategies to distinguish their own brands from competitors. This approach enables the private label demand to remain relatively independent, thereby mitigating significant fluctuations even as the platform introduces new sales modes. For instance, Amazon differentiates its “Amazon Basics” brand by employing a dedicated page and recommendation system, effectively emphasizing its unique brand characteristics.

Next, this study compared the profit between Scenario NN vs. NS and IN vs. IS, as shown in Figure 3, Figure 4, Figure 5 and Figure 6 and Corollaries 4 and 5.

 Corollary 4. 

Difference in platform’s profit in different scenarios.

(i) 

Scenario NN vs. Scenario NS

$${\mathsf{\Pi }}_P^{N{S}^{*}}>{\mathsf{\Pi }}_P^{N{N}^{*}}$$

(ii) 

Scenario IN vs. Scenario IS

$${\mathsf{\Pi }}_P^{I{S}^{*}}>{\mathsf{\Pi }}_P^{I{N}^{*}}$$

The proof of Corollary 4 is provided in Appendix A. To more intuitively display the results, based on the existing research and real-world scenarios, the basic parameters were set as follows: $r=0.6,s=0.7,\eta =1.2$. In addition, we conducted multiple simulations to observe the trend in profit changes within the range of the parameter values.

Corollary 4 implies that the introduction of the reselling mode will always increase the profits of the platform $\left({\mathsf{\Pi }}_P^{N{S}^{*}}>{\mathsf{\Pi }}_P^{N{N}^{*}},{\mathsf{\Pi }}_P^{I{S}^{*}}>{\mathsf{\Pi }}_P^{I{N}^{*}}\right)$, regardless of whether the platform introduces a PL, as shown in Figure 3 and Figure 4. This is because the reselling mode offers an additional revenue stream for the platform. Within the reselling mode, the platform exercises greater control over pricing and sales of goods, enabling it to generate profits directly from the sale of goods rather than solely relying on commissions from brand owners. Furthermore, it is interesting to note from Figure 3 and Figure 4 that, with the increase in ${\theta }_A,{\theta }_B$, the impact of the commission rate on the platform’s profit diminishes, while the profit of the platform significantly rises with an increase in the coupon redemption rate. This is attributable to the diversification of the platform’s profit streams, which mitigates the impact of the commission rate on its overall profitability. Consequently, the platform can enhance sales, particularly for its own brand products, by increasing the use of coupons, effectively leveraging the coupon redemption rate to augment its profits. Therefore, platforms should actively consider introducing a reselling mode to expand business channels and integrate supply chain resources.

 Corollary 5. 

Difference in brand owner’s profits in different scenarios.

(i) 

Scenario NN vs. Scenario NS

$${\mathsf{\Pi }}_M^{N{S}^{*}}>{\mathsf{\Pi }}_M^{N{N}^{*}}$$

(ii) 

Scenario IN vs. Scenario IS

$${\mathsf{\Pi }}_M^{I{S}^{*}}>{\mathsf{\Pi }}_M^{I{N}^{*}}$$

The proof of Corollary 5 is provided in Appendix A.

Corollary 5 shows that the introduction of the reselling mode always increases the profits of the brand owner $\left({\mathsf{\Pi }}_M^{N{S}^{*}}>{\mathsf{\Pi }}_M^{N{N}^{*}},{\mathsf{\Pi }}_M^{I{S}^{*}}>{\mathsf{\Pi }}_M^{I{N}^{*}}\right)$, regardless of whether the platform introduces a PL, which is illustrated in Figure 5 and Figure 6. Under the reselling mode, the brand owner no longer relies on commission income from the e-commerce platform, and the brand owner can sell goods to the e-commerce platform through wholesale. In addition, the reselling mode enables the brand owner’s products to reach more consumers through the extensive channels of the e-commerce platform, bringing more sales opportunities and profit growth. In the case of Apple, its products are sold on the Tmall platform not only through its official flagship store, but also through the offline stores and online channels of numerous authorized dealers (reselling mode), which significantly increase the sales of its products.

Furthermore, as can be observed from Figure 5 and Figure 6, when the e-commerce platform has not introduced its own brand, there is a positive correlation between the profit of the brand owner and the commission rate. However, once the platform introduces its own brand, the situation changes: there is a negative correlation between the profit of the brand owner and the coupon redemption rate, and the impact of the commission rate on the profit of the brand owner becomes less significant. This is mainly because the platform tends to use promotional means such as coupons to attract consumers to purchase its own brand products, which may disperse the consumer base of the brand owner. Therefore, brand owners must enhance their market competitiveness to address the competitive pressure from the platform’s brands, mitigate their reliance on fluctuations in commission rates, and simultaneously fully capitalize on the channel advantages provided by the reselling mode to further expand their market share and profit margins.

4.3. Analysis of the Introduction of PLs

This section compares the optimal solutions across the different sales mode scenarios (i.e., NN vs. IN and NS vs. IS). First, this section identifies the inherent relationships between prices, coupon values, and demand in each scenario.

 Corollary 6. 

Difference in coupon face value and price in different scenarios.

(i) 

Scenario NN vs. Scenario IN

$p_A^{NN}>p_A^{IN}$ if ${\theta }_A<{\theta }_{A1}$ and $0<s<s_1$; $f^{NN}>f^{IN}$ if $\alpha ,\lambda$ are large.

(ii) 

Scenario NS vs. Scenario IS

$p_A^{NS}>p_A^{IS}$ if ${\theta }_A<{\theta }_{A1}$ and $0<s<s_1$; $p_o^{NS}>p_o^{IS}$ if ${\theta }_A<{\theta }_{A1}$; $f^{NS}>f^{IS}$ if $\alpha ,\lambda$ are large.

Figure 7 provides proof of the difference in coupon face value.

Corollary 6 indicates that within the specified threshold, when the platform introduces its own private-label brand, the product pricing of the brand owner is likely to decrease $\left(p_A^{NN}>p_A^{IN},p_A^{NS}>p_A^{IS}\right)$. This indicates that the introduction of private labels intensifies market competition and diverts a portion of the market share from brand owners. Consequently, brand owners may need to adjust their product pricing strategies to sustain market competitiveness. Corollary 6 also shows that when consumers’ preferences for products under agency selling is relatively low, the price of products under the reselling mode in Scenario NS is higher than that in Scenario IS ($p_o^{NS}>p_o^{IS}$), potentially due to the brand owner’s increased dependence on reselling and their strategy of setting higher prices to secure profits in Scenario NS.

A graphic illustration of the coupon face value in the different scenarios is shown in Figure 7. It can be seen that the coupon face value tends to be larger in the absence of a private brand introduction if $\alpha ,\lambda$ are large. When both the coupon redemption rate and commission rate are at a high level, coupons with a larger face value can effectively reduce consumers’ purchasing costs, thereby enhancing the appeal of products. In Scenarios NN and NS, since the platform does not introduce its own brand, it tends to increase the face value of coupons to attract consumers, stimulate demand, and boost sales. In contrast, in Scenarios IN and IS, given the introduction of a private label, the platform tends to exercise greater caution in formulating coupon strategies and appropriately decrease the face value of coupons. This approach aims to avoid over-reliance on coupon promotions, which could potentially affect the market positioning and profit margins of private brands.

 Corollary 7. 

Difference in market demand in different scenarios.

(i) 

Scenario NN vs. Scenario IN

If ${\alpha }_1<\alpha <{\alpha }_2$, $Q_A^{NN}>Q_A^{IN}$.

(ii) 

Scenario NS vs. Scenario IS

If $0<{\theta }_B<\widetilde{{\theta }_B}$ and $r>\tilde{r}$, $Q_A^{NS}>Q_A^{IS}$; $Q_o^{NS}=Q_o^{IS}$.

Corollary 7 indicates that when the platform launches private-label brands, it may lead to a reduction in demand for goods from the brand owner operating under the agency selling mode $\left(Q_A^{NN}>Q_A^{IN},Q_A^{NS}>Q_A^{IS}\right)$. By comparing Corollary 6, it is evident that the introduction of a private label on the platform not only leads to a reduction in product pricing by the brand owner but also results in the reallocation of market share from the brand owner, as certain consumers may opt to purchase the private-label products available on the platform. After the platform introduces its own brand, the demand for products under the reselling mode in Scenario IS remains unchanged ($Q_o^{NS}=Q_o^{IS}$). In order to prevent potential disruption to the existing consumer base, maintaining the continuity of this strategy ensures a stable demand for goods within the reselling framework.

Next, this study compared the profit between Scenario NN vs. IN and NS vs. IS, as shown in Figure 8, Figure 9 and Figure 10 and Observations 1 and 2.

 Observation 1. 

Difference in platform’s profit in different scenarios.

(i) 

Scenario NN vs. Scenario IN

$${\mathsf{\Pi }}_P^{I{N}^{*}}>{\mathsf{\Pi }}_P^{N{N}^{*}}$$

(ii) 

Scenario NS vs. Scenario IS

$${\mathsf{\Pi }}_P^{I{S}^{*}}>{\mathsf{\Pi }}_P^{N{S}^{*}}$$

Observation 1 shows that the introduction of a PL can enhance the platform’s profitability, as shown in Figure 8 and Figure 9. In Scenarios IN and IS, by introducing a private label, the platform can directly control product pricing and marketing strategies, thereby more effectively catering to the diverse needs of consumers while diversifying their sources of profit. Owning a private label can be more lucrative for a platform compared to relying solely on the agency selling and reselling modes that generate revenue primarily through commissions. According to the analysis above, the platform should proactively expand its sales mode by introducing private labels and establishing a diversified business ecosystem to address the diverse demands of consumers while effectively enhancing its market competitiveness.

 Observation 2. 

Difference in brand owner’s profits in different scenarios.

(i) 

Scenario NN vs. Scenario IN

${\mathsf{\Pi }}_M^{NN}>{\mathsf{\Pi }}_M^{IN}$   if   $\alpha$   is large;   ${\mathsf{\Pi }}_M^{NN}>{\mathsf{\Pi }}_M^{IN}$   if   $\alpha$   is low and   $\lambda$   increases.

(ii) 

Scenario NS vs. Scenario IS

${\mathsf{\Pi }}_M^{NS}>{\mathsf{\Pi }}_M^{IS}$   if   $\alpha$   is large;   ${\mathsf{\Pi }}_M^{NS}>{\mathsf{\Pi }}_M^{IS}$   if   $\alpha$   is low and   $\lambda$   increases.

Combined with the practice of coupon promotion, Observation 2 shows that the brand owner achieves higher profits when the platform does not introduce private labels, as illustrated in Figure 10. When the coupon redemption rate is high in Scenarios IN and IS, the introduction of a private label intensifies the market competition. This leads to a diversion of the brand owner’s market share towards the private label, thereby reducing their profits. In contrast, under Scenarios NN and NS, the absence of private label competition fosters a relatively simple and stable cooperative relationship between the brand owner and platform, ensuring sustained sales and profitability. Based on the analysis above, brand owners should closely monitor the dynamic changes in coupon redemption rates and commission rates, strive to maintain a stable partnership with platforms, and secure greater resource allocation from platforms to enable flexible adjustments in business strategies.

5. Conclusions

The growing prevalence of multi-channel sales modes on e-commerce platforms, driven by the introduction of private labels and coupon promotions, has greatly impacted supply chain operations and marketing strategies. Yet, prior studies have mostly focused on single factors such as private label introduction, sales channel choices, or coupon promotions, with insufficient research on their interplay in the e-commerce platform context. This study constructed an online sales system with a strong brand owner and e-commerce platform. It deeply analyzed the synergies among private label introduction, sales mode choice, and coupon promotions, as well as their impacts on the profits of supply chain members.

5.1. Main Findings

Regarding the introduction of the reselling mode, the main findings were as follows: (1) The implementation of the reselling mode consistently leads to a significant enhancement in the profits of both brand owners and platforms. This was also the conclusion of Ke et al. [11] who found that, by achieving supply chain coordination through channel diversification and optimized consumer engagement, this mode introduces new profit growth opportunities for brands and platforms. Specifically, the reselling mode allows platforms to directly control the pricing and sales of goods, thereby generating profits from the sale of goods rather than solely relying on commissions from brand owners. (2) Upon integrating the reselling mode into the platform, consumers gain access to additional purchasing channels, which correspondingly reduces the demand for the products sold under the agency selling mode. To maintain short-term market stability and avoid uncertainty caused by price fluctuations, brand owners and platforms should ensure the consistency of their pricing strategies. Consequently, product prices and coupon values were similar when comparing the NN vs. NS and IN vs. IS scenarios. This strategy is crucial for maintaining market stability and consumer expectations, as demonstrated by the practices of major platforms like Tmall and JD.com.

Regarding the introduction of PLs, the main findings were as follows: (1) The incorporation of private labels enhances the flexibility of platform pricing strategies and better aligns with the diverse needs of consumers, thereby consistently increasing platform profitability. This is the same conclusion as Chu et al. [21], who found that the introduction of private brands provides platforms with more pricing flexibility, thereby alleviating the double marginal effect in the supply chain to a certain extent. (2) When the coupon redemption rate is at a high level, brand owners have greater profitability in the absence of PL introduction. Conversely, when the coupon redemption rate is at a low level, an increase in the commission rate leads to reduced profit margins for brand owners due to competition from private labels. This is consistent with Shen et al. [6] who concluded that the introduction of private labels increase market competition, thereby reducing the profits of manufacturers.

Regarding the optimal coupon strategy, the main findings were as follows: (1) When both the coupon redemption rate and commission rate are at a high level, the coupon face value tends to be larger in the absence of a private brand introduction. Since a high conversion rate may reduce platforms’ actual revenue and a high commission rate increases brands’ costs, platforms must control costs and maintain profitability by reducing the coupon face value. (2) Conversely, when the coupon redemption rate and commission rate are low at a low level, introducing private labels allows for larger coupon face values. Given that a low redemption rate indicates weaker consumer sensitivity to price discounts, platforms can attract more consumers by increasing the coupon face value, thereby enhancing their sales volume and overall profitability.

5.2. Managerial Insights

This study provides the following guidelines and insights for brand owners and e-commerce platforms:

(1)

For e-commerce platforms: It is essential to proactively explore the introduction of a reselling mode to broaden business channels and effectively integrate supply chain resources. Furthermore, platforms should actively expand their sales modes by introducing private labels and establishing a diversified business ecosystem that incorporates agency selling, reselling, and PLs. This approach will better address the diverse needs of consumers while enhancing market competitiveness. Lastly, platforms must flexibly adjust coupon face values in response to changes in redemption rates, commission rates, and consumer sensitivity, thereby avoiding an over-reliance on coupon promotions. Taking industrial practice as an example, JD.com dynamically adjusts the face value and usage conditions of coupons based on users’ purchasing behaviors, consumption frequencies, and other relevant factors. For instance, to attract new or high-value users, JD.com may provide coupons with higher denominations, thereby encouraging first-time purchases or increasing purchase frequencies.

(2)

For brand owners: It is crucial to actively participate in the reselling mode of e-commerce platforms. By capitalizing on the channel advantages of these platforms, brands can broaden their market reach and target a wider consumer base—particularly price-sensitive consumers—thereby enhancing both their sales volume and revenue. Although the reselling mode may introduce price competition, brands can address this challenge by optimizing supply chain management, improving operational efficiency and service quality, and driving profit growth. Additionally, brand owners must focus on strengthening brand equity, elevating the brand image and consumer awareness, and cultivating brand loyalty to effectively compete with private-label offerings from e-commerce platforms. Furthermore, brands should closely monitor changes in coupon redemption rates and commission structures, maintain transparent communication with e-commerce platforms, and collaboratively develop strategic promotional plans.

5.3. Limitations and Future Research

This study has achieved certain outcomes in exploring the synergistic effects of e-commerce platforms’ multi-channel sales modes, private label introduction, and coupon promotion strategies on supply chain profits. However, several limitations remain. First, in order to simplify the model, we made the assumption that the production cost is negligible. Future research could incorporate production cost factors to enhance the model’s applicability to real-world scenarios. Second, the analysis primarily focused on interactions between a single e-commerce platform and a dominant brand, without fully considering the complex dynamics in multi-platform competition. Subsequent studies could extend to competitive multi-platform environments to examine inter-platform strategic interactions and their impacts on supply chain decisions and profitability. Finally, the potential impacts of digital marketing tools on supply chain decisions warrant deeper investigation. Future research could leverage big data analytics and artificial intelligence technologies to explore how digital marketing optimizes supply chain decision-making mechanisms.