Channel membership mechanisms in UGC platforms: content creation, revenue structure, and platform incentives

1 Introduction

With the development of Internet technologies and mobile devices, user-generated content (UGC) platforms have become one of the most important platform forms in the digital economy. Users are not only consumers of content, but also producers of content. Representative UGC platforms such as TikTok, Bilibili, Rednote, and Dianping have become deeply embedded in people’s daily lives: users watch short videos for entertainment on TikTok, learn knowledge-oriented content on Bilibili, obtain travel and consumption experiences on Rednote, and search for local service information on Dianping. The monthly active user base of these platforms generally reaches hundreds of millions or even billions [1].

Unlike traditional content platforms such as Netflix and Disney+, which rely on purchasing copyrights or producing professionally generated content (PGC), UGC platforms rely more heavily on third-party content creators to continuously produce content and form network effects through user interactions [2]. Because the entry barriers for users to create content are extremely low and fixed entry costs are almost negligible [3], platforms are able to rapidly attract a large number of creators and consumers, thereby forming rich content ecosystems. However, this open content-supply structure also means that platforms must continuously bear substantial operational costs related to content distribution, traffic recommendation, server maintenance, and creator incentives. Therefore, how to establish a sustainable monetization mechanism has become a core issue in the development of UGC platforms.

In the early stages, most UGC platforms primarily relied on advertising revenue to sustain operations. On the one hand, platforms generated revenue through embedded advertisements. For example, YouTube inserts pre-roll and mid-roll advertisements when ordinary users watch videos and earns revenue based on advertising impressions [3]. On the other hand, platforms also act as intermediaries connecting advertisers and content creators. For example, Bilibili allows creators to publish sponsored advertising content and extracts a certain proportion of commission revenue from advertising activities [4]. However, as competition among UGC platforms has intensified, the limitations of relying solely on advertising revenue have gradually emerged. On the one hand, advertising revenue is vulnerable to fluctuations in advertising markets, platform policy adjustments, and user advertising aversion [5, 6]. On the other hand, high-quality content creation usually requires substantial investments in time, equipment, and production effort, while the uncertainty of advertising revenue makes it difficult to continuously support content production [7]. Against this background, channel membership mechanisms have rapidly emerged and gradually become an important business model for UGC platforms.

Channel membership refers to a commercial mechanism under which users pay membership fees to specific content creators (channels) in exchange for exclusive content, early-access viewing privileges, or other special benefits. Unlike platform-level subscription services, such as Bilibili Premium Membership or YouTube Premium, where users pay the platform for site-wide privileges, channel membership emphasizes direct payment relationships between users and individual creators.

In recent years, channel membership mechanisms have become widely adopted across UGC platforms. For example, Bilibili allows creators to designate certain videos as paid-exclusive content, requiring users to purchase creator-specific premium videos or courses before accessing them. YouTube has introduced the “Channel Membership (Join)” function, through which members can watch videos several days earlier and obtain exclusive badges and livestream interaction privileges. Similar mechanisms are also widely adopted on overseas content platforms such as Patreon and Twitch. The popularity of channel membership essentially reflects the evolution of UGC platforms from single advertising-based monetization models toward hybrid “advertising + subscription” revenue structures. On the one hand, platforms hope to alleviate the instability of advertising revenue through membership income. On the other hand, creators also seek to strengthen income stability and user stickiness by establishing paid communities.

However, the introduction of channel membership mechanisms may also generate new impacts on the UGC platform ecosystem. First, from the perspective of content creators and content consumers, channel membership may change creators’ allocation of effort between free content and paid content. Since paid content can directly generate subscription revenue, creators may have incentives to shift more high-quality content toward membership-exclusive areas, thereby changing the platform’s original free-content ecosystem. This raises an important question: whether channel membership mechanisms affect the supply of free content and further influence consumer welfare and user subscription behavior.

Second, from the platform perspective, although channel membership provides platforms with an additional revenue source beyond advertising, it may also crowd out existing advertising revenue. On the one hand, as more content is transferred into membership-exclusive areas, traffic to free content may decline, thereby weakening advertising revenue. On the other hand, platforms need to balance advertising commissions and membership commissions in order to maintain creator incentives and platform profitability. Therefore, whether channel membership mechanisms can genuinely improve platform profitability, and how platforms should design optimal commission strategies, are also important research questions.

In addition, different channel membership mechanisms may generate different economic consequences. Specifically, content-partition membership refers to a mechanism in which certain content remains permanently exclusive to paying members, whereas time-partition membership allows members to obtain temporary early access before the content is released to all users. For example, the content-partition model represented by Bilibili emphasizes exclusive paid content, whereas the time-partition model represented by YouTube emphasizes early-access privileges for members. These two mechanisms may differ significantly in their effects on creator incentives, consumer welfare, and platform profitability. Therefore, under different market conditions, how platforms should choose the optimal channel membership mechanism also deserves further study.

Although existing studies have examined advertising mechanisms, platform subscription services, and creator incentives on UGC platforms, research on creator-level subscription mechanisms such as channel membership remains relatively limited. Existing literature focuses more on the choice of platform-wide subscription models, while paying less attention to how channel membership reshapes content supply structures and revenue allocation relationships within UGC platforms. Therefore, there is still a lack of systematic theoretical analysis regarding how channel membership mechanisms influence platform profitability, creator content production, and consumer welfare.

To address this gap, this paper develops a three-stage game-theoretic framework based on the Salop circular model, incorporating platforms, content creators, and content consumers into a unified analytical system. We examine how different channel membership mechanisms reshape creators’ allocation of effort between free and paid content, and how such changes further affect platform profitability and commission strategies.

This study contributes to the literature in three aspects. First, it extends the literature on UGC monetization by incorporating creator-level channel membership into a unified analytical framework. Second, it reveals how different membership mechanisms reshape creators’ allocation of effort between free and paid content through the strategic interactions among platforms, creators, and consumers. Third, it identifies the conditions under which different channel membership mechanisms are preferable and provides theoretical implications for platform mechanism design and commission strategies.

The remainder of this paper is structured as follows. Section 2 reviews the relevant literature. Section 3 presents the theoretical model and describes the strategic interactions among platforms, creators, and consumers. Section 4 derives the equilibrium outcomes under the baseline, content-partition, and time-partition membership models. Section 5 conducts numerical simulations and examines the effects of key parameters. Section 6 discusses the theoretical and managerial implications of the findings. Section 7 concludes the paper and discusses its limitations and directions for future research.

2 Literature review

Existing studies on UGC platforms primarily examine how platform incentive mechanisms influence creators’ content supply decisions and content quality.

2.1 Content supply and creator incentive mechanisms on UGC platforms

Existing studies on UGC platforms generally believe that platform competitiveness largely depends on the ability of content creators to continuously provide high-quality content, while platform incentive mechanisms are important factors affecting content supply behavior. Around this issue, the related literature has developed along two dimensions, namely, economic incentives and non-economic incentives.

In terms of economic incentives, a large number of studies focus on the impact of advertising revenue-sharing mechanisms on content creators’ supply decisions. Sun and Zhu analyze how advertising revenue sharing affects content quality on UGC platforms and point out that reasonable revenue-sharing mechanisms can improve creators’ content effort levels [8]. Subsequently, Jain and Qian and Bhargava further characterize the design problem of optimal platform advertising revenue-sharing ratios under creator competition and user heterogeneity through game-theoretic models [9, 10]. Ren, from the perspective of the interaction between platform advertising policies and creator production strategies, reveals that adjustments in advertising strategies may trigger changes in content supply structures [11]. However, some studies also point out that monetary incentives are not always positively effective. Liu and Feng show that excessively strong monetary incentives may instead suppress creators’ willingness to supply content [12].

In addition to direct monetary incentives, platforms may also influence content supply decisions through various non-monetary incentive mechanisms. Ghosh and McAfee show that rating mechanisms can effectively encourage the generation of high-quality content under certain conditions [13]. Chen and Xu find that moderate review mechanisms not only do not inhibit content supply, but also help improve overall content quality [14]. Baek and Shore point out that UGC supply often relies heavily on a small number of highly active creators, and the effects of platform incentive mechanisms on different types of creators exhibit significant heterogeneity [15]. From the perspective of peer rewards, Burtch et al. find that social incentives can increase the quantity of content supply, but may reduce content diversity [16]. Amaldoss and Shin, from the perspective of content configuration strategies on UGC platforms, systematically analyze the interaction between user-generated content and platform-owned content [3]. In addition, some scholars extend the discussion to paid knowledge and community environments [17], factors affecting creators’ participation in continuous content creation [18, 19], and mechanisms for achieving sustainable content ecosystems [20].

Overall, existing studies have systematically revealed the influence of platform incentive mechanisms on content supply behavior. However, most of the literature still mainly focuses on general incentive issues related to user-generated content, while paying relatively limited attention to the multi-sided interactions among UGC platforms, content creators, and content consumers. At the same time, existing studies usually treat content as a homogeneous whole, with relatively limited distinction between the supply structures of free content and paid content, and less discussion of how platform monetization mechanisms change creators’ allocation of effort across different content types. By contrast, based on the channel membership mechanism, this paper further analyzes the trade-offs faced by content creators between free content and paid content, as well as the impact of platform commission mechanisms on content supply structures, thereby extending the existing research on content supply in UGC platforms.

2.2 Monetization mechanisms and revenue allocation on UGC platforms

Existing research on content monetization in UGC platforms mainly takes advertising and subscription as basic revenue mechanisms and analyzes how platforms achieve profit maximization through pricing and incentive strategies in bilateral or multi-sided markets.

In terms of advertising monetization, related studies mainly focus on the effects of advertising allocation, advertising aversion, and advertising revenue distribution on platforms and content supply. Ahn et al. show that advertising is not only an important source of platform revenue, but also affects UGC supply and platform content structures by changing content-space allocation [21]. In the context of advertising monetization, Li and Tan, considering users’ emotional utility and content uncertainty, analyze the optimal decisions regarding video pricing under paid models and advertising intensity under free models [22]. Subsequently, Chi et al., from the perspectives of advertising aversion costs and cross-side network effect intensity, compare the conditions under which short-video platforms choose pure advertising models or hybrid pricing models [23]. Li et al. further incorporate word-of-mouth diffusion and differences in user experience into the analytical framework, revealing that platforms may endogenously switch between advertising-dominant and fee-dominant strategies [24]. Regarding differences in advertising participants, Zhu et al. compare three models: platform advertising, creator advertising, and joint advertising by platforms and creators. They point out that different forms of advertising intervention significantly affect content supply incentives, platform revenue, and creator effort levels [25].

However, with increasing user advertising aversion and rising content production costs, relying solely on advertising monetization has gradually become constrained, prompting platforms to expand revenue sources through subscription and membership systems. In terms of subscription and membership monetization, related studies mainly focus on the trade-offs among content provision models, membership pricing, and advertising allocation. Amaldoss et al. systematically characterize the endogenous selection mechanisms among free-with-advertising, paid-with-advertising, and paid-without-advertising strategies within a multi-sided market framework [26]. Jiang et al. compare subscription fees and advertising decisions under digital content provision models such as exclusive subscription, exclusive free access, and co-distribution competition [27]. Li et al. examine the optimal choices among content provision models such as member-free, symmetric pricing, and member discounts in premiere-release settings, revealing the nonlinear effects of membership subscription fees and membership privileges on platform profits [28].

Overall, existing studies have systematically characterized the content monetization mechanisms of UGC platforms from the two dimensions of advertising and subscription, and have gradually paid attention to the interaction between platform revenue structures and content supply behavior. However, most studies still mainly focus on platform-level unified monetization models, while relatively limited attention has been paid to the “channel membership” mechanism under which users pay for individual content creators. At the same time, existing studies usually regard membership mechanisms as simple pricing tools, while paying relatively limited attention to how different membership organization mechanisms affect the dynamic trade-offs among free content supply, platform advertising revenue, and creators’ effort allocation. Based on this, this paper starts from the channel membership mechanism and compares platform commission strategies, content supply structures, and platform revenue differences under content-partition and time-partition membership models, thereby supplementing the existing research on content monetization in UGC platforms.

3 Problem description and model setup

As illustrated in Figure 1, this study develops a three-stage Salop circular-city model involving a UGC platform, content creators, and consumers. There exist n symmetric content creators on the platform whose content differs only horizontally in style, theme, or presentation. The platform acts as the first mover and determines its commission rates on advertising and subscription revenues. Content creators subsequently choose their content supply strategies, and finally consumers decide whether to subscribe to channel memberships after observing the content offerings and subscription prices.

3.1 The problem of content consumers

Consumers on the platform must not only choose among different content creators but also decide whether to purchase a creator’s channel membership. To represent consumers’ horizontally differentiated preferences over creators, we adopt the Salop circular-city framework [29]. Let consumers’ preference intensity for content quality be denoted by θ ∈ 0 , 1, uniformly distributed. Consumers are uniformly located on a unit circle 0 , 1, with each consumer indexed by location x ∈ [ 0 , 1. On the circle, there are n symmetric content creators indexed by i ∈ 1 , 2 , . . . , n, evenly spaced with location x i = i − 1 / n, i = 1 , 2 , . . . , n. To capture taste mismatch across creators, we introduce a matching cost. When a consumer at location x consumes creator i’s content, she incurs a cost t d x , i, where t > 0 reflects the degree of horizontal differentiation—larger t implies stronger sensitivity to stylistic differences and higher switching costs. Distance is defined as the shorter of the two arc lengths on the circle: d x , i = min ⁡ { x − x i , 1 − x − x i.

Consumers may choose to purchase a channel membership from creator i. Let s i denote the proportion of consumers subscribing to creator i. Subscribers obtain access to both free and paid content, whereas non-subscribers can only view free content. Creator i supplies two types of content: free content with intensity q f , i, and paid content with intensity q p , i. For analytical tractability, we assume symmetric creators in equilibrium and normalize consumers’ total attention to 1 per period.

Under the content-partition model (e.g., the paid-video system on Bilibili), consumers can subscribe to creator i’s channel by paying a fee p i to gain access to paid content, while non-members may only view free content. To capture the positive relationship between content quality and subscription pricing, we assume p i = m q p , i 2, m > 0, where m reflects users’ willingness to pay per unit of paid-content quality. This specification is intuitive: higher-quality paid content increases users’ perceived value at an accelerating rate, as it enhances viewing experience, loyalty, and perceived differentiation. Prior empirical studies also document a positive link between subscription pricing and content quality or service level [30, 31]. The quadratic mapping additionally yields analytical tractability and avoids degeneracy in platform commission solutions under a purely proportional rule. Thus, the utility of a non-subscriber and a subscriber to creator i is given respectively by

U 0 , i c θ , x = θ q f , i − t d x , i

U 1 , i c θ , x = θ q f , i + q p , i − p i − t d x , i

3.2 The problem of content creators

In each period, content creators i ∈ 1 , 2 , . . . , n choose the allocation of effort between free and paid content in order to maximize total profit. Let the effective supply intensities of free and paid content be denoted by q f , i > 0 and q p , i > 0, respectively. Following Gu et al. (2024) [3], and to avoid intractability arising from multi-dimensional effort choice, we assume that content quality is equivalent to creators’ effort provision. Accordingly, the cost function is specified as C i q f , i , q p , i = k 2 q f , i 2 + q p , i 2, where k > 0 represents the marginal effort cost associated with increasing content supply intensity.

Creators earn revenue from two sources: advertising income and channel membership subscriptions. Advertising revenue is generated solely from exposure to free content. The platform charges commission rates τ a , τ p ∈ 0 , 1 on advertising and subscription revenue, respectively, with the residual allocated to creators. Consistent with the literature, expansion in advertising supply reduces unit advertising returns due to congestion and attention scarcity [32, 33]. To capture this relationship, we assume that the platform’s unit advertising revenue is a linearly decreasing function of free-content supply: r q f , i = w j R − ϕ q f , i, R , ϕ > 0, where R represents advertiser valuation, and ϕ captures the rate at which marginal advertising value declines. The parameter w j ∈ ( 0 , 1, with j ∈ c , t, reflects the effective size of the advertising market under the two membership mechanisms. Because channel membership diverts part of users’ viewing activity from the free-content area to the paid-content area, the total advertising inventory decreases. Under content-partition membership, paid content remains permanently exclusive, resulting in persistent and substantial shrinkage of the advertising market. In contrast, under time-partition membership, the reduction is temporary and thus more moderate. Therefore, we assume 0 < w c ≤ w t ≤ 1.

Under content-partition, a consumer subscribes to creator i only if U 1 , i c θ , x ≥ U 0 , i c θ , x. This implies a subscription threshold: θ ^ i c = p i q p , i = m q p , i, with 0 < m q p , i < 1. Therefore, the share of creator i’s subscribers is s c , i = Pr θ ≥ θ ^ i c = 1 − θ ^ i c = 1 − m q p , i. Advertising and subscription revenues for creator i are thus given by

A c , i = D 0 , i c r q f , i q f , i = D 0 , i c w c R − ϕ q f , i q f , i

S c , i = D 1 , i c p i s c , i = D 1 , i c m q p , i 2 1 − m q p , i

Hence the profit of creator i under content-partition is

π c , i c = 1 − τ a A c , i + 1 − τ p S c , i − k 2 q f , i 2 + q p , i 2

Under the time-partition mechanism, paid content is first released exclusively to members. Non-members cannot access it during the window period, during which no advertising is shown because user attention is concentrated on early-access content. After the window period, a fraction η ∈ 0 , 1 of the paid content becomes free, but advertising inventory remains determined solely by the level of free content q f , i. Early access yields an immediacy premium ψ > 1, while advertising value after the window suffers depreciation, captured by a discount factor δ ∈ 0 , 1. Accordingly, creator i’s advertising revenue is A t , i = D 0 , i t δ r q f , i q f , i = D 0 , i t δ w t R − ϕ q f , i q f , i. Consumers subscribe when U 1 , i t θ , x ≥ U 0 , i t θ , x, which yields a subscription threshold θ ^ i t = m q p , i ψ − δ u η. When ψ > δ u η and 0 < m q p , i < ψ − δ u η, the share of subscribers is s t , i = Pr θ ≥ θ ^ i t = 1 − θ ^ i t = 1 − m q p , i ψ − δ u η. Thus subscription revenue is S t , i = D 1 , i t p i s t , i = D 1 , i t m q p , i 2 1 − m q p , i ψ − δ u η. Creator i’s profit under time-partition is therefore:

π c , i t = 1 − τ a A t , i + 1 − τ p S t , i − k 2 q f , i 2 + q p , i 2

3.3 The problem of the UGC platform

As the sole intermediary for content distribution and monetization, the UGC platform earns revenue from both advertising and channel membership subscriptions. Observing creators’ content supply decisions and consumers’ subscription behaviors, the platform acts as the first mover in the game and determines the commission rates on advertising and subscription revenues in Stage 1 to guide subsequent strategic decisions by creators and consumers.

Under a given mechanism j ∈ c , t, the platform’s total profit equals the sum of commissions collected from all creators’ advertising and subscription revenues. Formally, the platform’s profit function is expressed aswhere A j , i and S j , i denote creator i’s advertising and subscription revenues, respectively, under mechanism j. Within the Salop circular-city framework, symmetric equilibrium implies that the n creators are evenly distributed on the circle and consumers allocate themselves symmetrically across creators. Therefore, each creator receives the same market share under any mechanism and membership state: D z , i j = 1 / n, ∀ i. Since this market share enters only as a scale factor when aggregating revenues across creators, it does not affect the qualitative structure of the platform’s optimal commission policy. Hence, under symmetry, the platform’s profit function can be equivalently written as

π p j = ∑ i = 1 n τ a A j , i + τ p S j , i

π p j = n τ a A j , i + τ p S j , i

In Stage 1 of the game, the platform chooses commission rates τ a and τ p to maximize its total profit:where q f , i * , q p , i * represent creators’ optimal content supply decisions in Stage 2, and s i * denotes consumers’ optimal subscription choices in Stage 3. Thus, the platform’s decision problem fundamentally reflects its strategic trade-off between advertising monetization and subscription revenue extraction. By setting commission rates appropriately, the platform influences creators’ allocation of effort between free and paid content, which in turn shapes consumer subscription behavior and determines overall monetization outcomes.

max π p j τ a , τ p , q f , i * , q p , i * , s i *

4 Model solution

4.1 Baseline model

In the baseline setting without channel membership, the UGC platform monetizes solely through advertising; creators produce only free content, and consumers have unrestricted access to all content. The interaction between the platform and creators thus forms a standard two-stage Stackelberg game. In Stage 1, the platform determines the advertising commission rate, and in Stage 2, creators choose their free-content supply intensity. Consumers do not make explicit strategic decisions because all content is freely available; their viewing behavior is implicitly captured in the advertising revenue function.

Since our subsequent analysis focuses on symmetric equilibrium and all n creators are uniformly distributed along the Salop circle with identical cost structures and payoff functions, we examine the optimal decision of a representative creator i. In symmetric equilibrium, each creator’s market share equals D i 0 = 1 / n. Hence, creator i’s profit function in the baseline model is given by:

π c , i 0 = 1 n 1 − τ a R − ϕ q f , i q f , i − k 2 q f , i 2

Taking the first-order condition with respect to q f , i, ∂ π c , i 0 ∂ q f , i = 0, we obtain the creator’s best-response function:

q f , i 0 * = 1 − τ a R 2 1 − τ a ϕ + k n

Clearly, content supply decreases as the commission rate τ a increases, reflecting the fact that higher platform extraction reduces creators’ marginal returns and discourages effort provision. Given the creators’ optimal responses, the platform chooses τ a to maximize its advertising profit. In symmetric equilibrium, the platform’s total advertising revenue equals ∑ i = 1 n 1 n τ a r q f , i 0 * q f , i 0 *, Substituting the best-response expression yields:

π p 0 τ a = τ a R − ϕ 1 − τ a R 2 1 − τ a ϕ + k n 1 − τ a R 2 1 − τ a ϕ + k n

From this expression, we derive the following proposition. A detailed proof is provided in the Supplementary Appendix.where Δ 1 = 27 k 4 n 4 k n + 2 ϕ 2 + k 6 n 6 1728 ϕ 6. At this optimal commission rate, the platform’s maximum profit isand the representative creator’s equilibrium supply and profit are

τ a 0 * = 1 − k 2 n 2 2 ϕ + k n 8 ϕ 3 + Δ 1 3 − k 2 n 2 2 ϕ + k n 8 ϕ 3 − Δ 1 3 + k n 2 ϕ

π p 0 * = τ a 0 * R − ϕ q f , i 0 * q f , i 0 *

q f , i 0 * = 1 − τ a 0 * R 2 1 − τ a 0 * ϕ + k n

π c , i 0 * = 1 n 1 − τ a 0 * R − ϕ q f , i 0 * q f , i 0 * − k 2 q f , i 0 * 2

Proposition 1 In the baseline case without channel membership, suppose parameters satisfy R > 0, ϕ > 0, and k > 0. Under symmetric equilibrium, each creator faces market share D i 0 = 1 n. The platform’s profit function admits a unique interior optimal advertising commission rate:

4.2 Content-partition channel membership

Under the content-partition membership model, the platform, creators, and consumers interact in a three-stage Stackelberg game. In Stage 1, the platform chooses the commission rates on advertising and subscription revenue, τ a , τ p. In Stage 2, each creator i ∈ 1 , 2 , . . . , n observes the commission scheme and selects free- and paid-content intensities q f , i c , q p , i c. In Stage 3, consumers decide whether to subscribe to channel membership after observing content supply and membership pricing. We solve for the subgame-perfect equilibrium (SPE) using backward induction. From the analysis in Section 3, creator i’s profit function under content-partition is

π c , i c = 1 − τ a A c , i + 1 − τ p S c , i − k 2 q f , i 2 + q p , i 2

In symmetric equilibrium, all creators face the same market share on the Salop circle, i.e., D i c = 1 n, so both advertising and subscription revenues are proportionally distributed across creators. Solving the first-order conditions yields each creator’s optimal supply response:

q f , i c * = 1 − τ a w c R k n + 2 1 − τ a ϕ

q p , i c * = 2 1 − τ p m − k n 3 1 − τ p m 2

These expressions show a clear functional specialization of content types: free content supports the advertising market, whereas paid content determines subscription revenue. Given symmetric strategies, total platform profit equals the sum of advertising and subscription commissions across all creators:

π p c = τ a ⁢ w c 2 R 2 1 − τ a k n + ϕ 1 − τ a k n + 2 1 − τ a ϕ 2 + τ p ⁢ 2 1 − τ p m − k n 2 1 − τ p m + k n 27 1 − τ p 3 m 4

Maximizing this profit expression yields the following result. A formal proof is provided in the Supplementary Appendix. where Δ 2 = 27 k 4 n 4 2 ϕ + k n 2 + k 6 n 6 1728 ϕ 6, Δ 3 = k 4 n 4 17 k n + 162 m 2 + 1331 k 2 n 2 46656 m 6

τ a c * = 1 − k 2 n 2 2 ϕ + k n 8 ϕ 3 + △ 2 3 − k 2 n 2 2 ϕ + k n 8 ϕ 3 − △ 2 3 + k n 2 ϕ

τ p c * = 1 − k 2 n 2 17 k n + 162 m 216 m 3 + Δ 3 3 − k 2 n 2 17 k n + 162 m 216 m 3 − Δ 3 3 + k n 6 m

Proposition 2 Suppose parameters satisfy R > 0, ϕ > 0, k > 0, m > 0, τ a, τ p ∈ 0 , 1, and 0 < m q p , i < 1. Then, under the content-partition channel membership mechanism, there exists a unique symmetric equilibrium. The platform’s optimal advertising- and subscription-commission rates are given respectively by:

At this equilibrium, the representative creator’s free- and paid-content intensities are:

q f , i c * = 1 − τ a c * w c R k n + 2 1 − τ a c * ϕ

q p , i c * = 2 1 − τ p c * m − k n 3 1 − τ p c * m 2

The equilibrium subscription share is

s c , i = 1 − 2 1 − τ p c * m − k n 3 1 − τ p c * m

The platform’s maximal profit isand creator i’s equilibrium profit is:

π p c * = τ a c * w c R − ϕ q f c * q f c * + τ p c * m q p c * 2 1 − m q p c *

π c , i c * = 1 n 1 − τ a c * ⁢ w c ⁢ R − ϕ q f , i c * ⁢ q f , i c * + 1 n 1 − τ p c * ⁢ m q p , i c * 2 ⁢ 1 − m q p , i c * − k 2 [ q f , i c * 2 + q p , i c * 2

Proposition 2 characterizes the subgame-perfect equilibrium structure under content-partition membership. Creators must allocate limited effort between free and paid content. Free content primarily generates advertising exposure, and its optimal level depends jointly on the effective advertising market size w c R, congestion intensity ϕ, and the platform’s advertising commission rate. Paid content, meanwhile, directly determines subscription revenue and is shaped by both the valuation parameter m and the platform’s subscription commission. Thus, free and paid content play distinct economic roles in equilibrium.

The platform’s optimal commission rates on both revenue streams are determined endogenously by cubic equations, reflecting the need to balance incentives across the two-sided market rather than apply fixed or linear rules. Advertising commissions trade off revenue extraction against creators’ incentives to supply free content, whereas subscription commissions balance membership revenue against incentives to produce paid content. Relative to the baseline advertising-only model, the content-partition mechanism introduces a dual-pillar revenue structure, advertising plus subscriptions, giving rise to richer feedback effects between platform pricing and creator content supply decisions.

4.3 Time-partition channel membership

Under the time-partition membership model, the UGC platform first determines the commission rates on advertising and subscription revenues in Stage 1. In Stage 2, content creators choose the intensities of free and paid content. In Stage 3, consumers observe content availability and prices and then decide whether to subscribe to channel membership. Based on the utility structure in Section 3, the representative creator i’s profit function under time-partition is:

π c , i t = 1 − τ a A t , i + 1 − τ p S t , i − k 2 q f , i 2 + q p , i 2

Because all creators face the same effective market share of 1 / n in symmetric equilibrium on the Salop circle, the above expression represents the average profit of creator i. Taking the first-order conditions with respect to q f , i and q p , i, we obtain the creator’s optimal supply responses:

q f , i t * = 1 − τ a δ w t R k n + 2 1 − τ a δ ϕ

q p , i t * = ψ − δ u η 2 m 1 − τ p − k n 3 1 − τ p m 2

Thus, as in the content-partition case, free content continues to support the advertising market, but its marginal value is now discounted by δ. Meanwhile, paid content drives membership demand, and its value depends jointly on the immediacy premium ψ and the post-window discount factor δ u. Given symmetric strategies, platform profit equals the aggregate commission income from all creators:

π p t = τ a δ w t R − ϕ q f , i t * q f , i t * + τ p m q p , i t * 2 − m 2 q p , i t * 3 ψ − δ u η

Maximizing this expression yields the following equilibrium result. A formal proof follows the same structure as Proposition 2 and is omitted for brevity. where Δ 4 = 27 k 4 n 4 2 δ ϕ + k n 2 + k 6 n 6 1728 δ ϕ 6, Δ 5 = k 4 n 4 17 k n + 162 m 2 + 1331 k 2 n 2 46656 m 6. At the resulting equilibrium, the representative creator’s free- and paid-content intensities are: and the equilibrium subscription share is:

τ a t * = 1 − k 2 n 2 2 δ ϕ + k n 8 δ ϕ 3 + Δ 4 3 − k 2 n 2 2 δ ϕ + k n 8 δ ϕ 3 − Δ 4 3 + k n 2 δ ϕ

τ p t * = 1 − k 2 n 2 17 k n + 162 m 216 m 3 + Δ 5 3 − k 2 n 2 17 k n + 162 m 216 m 3 − Δ 5 3 + k n 6 m

q f , i t * = 1 − τ a δ w t R k n + 2 1 − τ a t * δ ϕ

q p , i t * = ψ − δ u η 2 m 1 − τ p t * − k n 3 1 − τ p t * m 2

s t , i = 1 − 2 m 1 − τ p t * − k n 3 1 − τ p t * m

Proposition 3 Suppose that R > 0, ϕ > 0, k > 0, m > 0, ψ > δ u η, τ a , τ p ∈ 0 , 1, and 0 < m q p , i < ψ − δ u η. Then the time-partition channel membership mechanism admits a unique symmetric equilibrium. The platform’s optimal advertising and subscription commission rates are:

The platform’s maximal profit is:and the creator’s equilibrium profit is:

π p t * = τ a t * δ w t R − ϕ q f , i t * q f , i t * + τ p t * m q p , i t * 2 − m 2 q p , i t * 3 ψ − δ u η

π c , i t * = 1 n 1 − τ a t * ⁢ δ ⁡ w t ⁢ R − ϕ q f , i t * q f , i t * + 1 n 1 − τ p t * ⁢ m ( q p , i t * 2 − m 2 q p , i t * 3 ψ − δ u η − k 2 ( q f , i t * 2 + ( q p , i t * 2

Proposition 3 characterizes the subgame-perfect equilibrium under the time-partition membership model. Unlike content-partition, time-partition allows paid content to become partially available to non-members after the window period. As a result, free content is partly an endogenous by-product of previously exclusive paid content. This structure discounts advertising returns during the window period, implying that both the effective advertising market size and advertising visibility jointly determine the value of free content and, in turn, creators’ supply incentives.

Creators’ incentives are therefore more strongly shaped by window-period parameters. Free-content supply depends not only on creators’ voluntary effort, but also on the share of paid content later released to the public. Consequently, advertising returns become more sensitive to both platform commissions and the advertising discount factor. Meanwhile, the marginal payoff from paid content depends simultaneously on content value, early-access benefits, and the proportion of content released post-window.

Hence, the platform must jointly optimize commissions on both revenue streams to rebalance advertising value erosion against the amplification of subscription value. This process gives rise to an equilibrium characterized by a layered monetization structure driven by the window period.

5 Numerical simulation and analysis

To facilitate interpretation of the analytical equilibrium results, we conduct numerical simulations based on parameter sensitivity analysis. Specifically, we compare the equilibrium outcomes of UGC platforms under different channel membership mechanisms with respect to key performance indicators such as free-content quality and platform profit.

To ensure computational tractability and economic plausibility, we select a benchmark set of parameter values that satisfy all model constraints and reflect realistic market conditions. The baseline parameter configuration is summarized in Table 1. Under this baseline setting, we perform both univariate and bivariate perturbations of key structural parameters in the neighborhood of their reference values. This approach allows us to systematically investigate how the two channel membership mechanisms affect equilibrium outcomes—particularly free-content quality and platform profit—under varying market and incentive environments. The results provide insight into the relative performance and strategic implications of content-partition versus time-partition membership models.

TABLE 1. Baseline parameter settings.

5.1 Comparison of free-content quality

In the left panel of Figure 2, the difference q f c * − q f 0 * is consistently negative across all combinations of advertising market size R and advertising demand slope ϕ, and the magnitude of this gap increases with either parameter. This indicates that the content-partition model reduces free-content quality in all parameter regions, and the crowding-out effect becomes stronger as the advertising market expands or advertising demand becomes more sensitive to free-content supply. The underlying mechanism is that creators in the content-partition model can directly monetize high-quality paid content through subscription income. Since the advertising value of free content cannot be fully internalized by creators, their effort is systematically reallocated toward paid content, leading to a persistent decline in free-content quality relative to the baseline.

By contrast, the right panel of Figure 2 shows that although q f t * − q f 0 * is also negative under the time-partition model, the magnitude of reduction is substantially smaller and converges rapidly toward zero when R and ϕ are sufficiently large. This suggests that time-partition leads to a milder impact on free-content quality. The key reason is that a proportion of paid content eventually becomes freely accessible after the window period. As a result, creators not only earn short-term subscription revenue but also continue to benefit from advertising returns in the longer run, which preserves some incentives to maintain free-content quality. As the advertising market expands or user quality preferences strengthen, creators’ effort allocation under time-partition increasingly resembles that in the baseline scenario, thereby mitigating the marginalization of free content.

5.2 Comparison of platform profits

The left and middle panels of Figure 3 compare the profit effects of the two channel membership mechanisms relative to the baseline model. The left panel shows that when the advertising market is small and advertising demand slope is low, the content-partition model significantly increases platform profit. In this case, the subscription market provides a stable second revenue source that effectively compensates for limited advertising income; the subscription commission sufficiently offsets the advertising losses caused by reduced free content. However, as the advertising market grows or advertising becomes more sensitive to content supply, the loss of advertising potential due to restricted free content expands, gradually eroding and eventually overturning the profit advantage of content-partition.

In contrast, the middle panel shows that the time-partition model yields positive profit gains across a wider parameter region, particularly when the advertising market is weak. The model allows the platform to generate subscription income from early-access privileges while preserving much of the advertising value of free content after the window period. Only when both advertising market size and sensitivity are simultaneously high does the relative advantage of time-partition diminish and approach that of the baseline.

The right panel of Figure 3 further evaluates the three models as the willingness-to-pay parameter m varies. When m is low, neither membership mechanism generates sufficient subscription revenue to offset the decline in advertising income caused by creators’ reallocation of effort toward paid content, resulting in profits below the baseline. In this region, content-partition performs slightly better than time-partition because fully exclusive paid content concentrates subscription revenue more strongly. As m increases, the marginal value of paid content rises sharply, subscription income first compensates and then surpasses the loss of advertising returns, and profits under both membership models exceed the baseline. Time-partition then gradually becomes superior, as it combines early-access subscription income with sustained advertising monetization after content release, thereby accumulating revenue from both streams more effectively.

5.3 Optimal platform commission rates

Figure 4 illustrates the relationship between platform profit and commission rates on advertising and subscription revenues under both membership mechanisms. In both cases, platform profit displays an inverted U-shaped pattern, indicating that excessively low or high commission rates reduce platform profit, and the optimum lies within an interior interval. However, the two mechanisms differ substantially in the location of their respective profit peaks. Under content-partition, high-profit regions cluster around moderate advertising commissions and relatively high subscription commissions, whereas under time-partition, platform profit is maximized at higher advertising commissions combined with moderately high subscription commissions.

This divergence reflects the distinct monetization logics of the two mechanisms. Content-partition relies heavily on the exclusivity of paid content, making subscription revenue the primary driver of platform income. Profit is therefore more sensitive to subscription commissions, while excessively high advertising commissions suppress free-content supply and ultimately reduce total revenue. In contrast, under time-partition, exclusivity exists only during the window period and long-term monetization comes primarily from advertising revenue generated after content returns to the free-content area. Hence, platform profit becomes more responsive to advertising commissions, while the marginal contribution of subscription commissions diminishes beyond the moderate range. The peak structures observed in Figure 4 visually capture the subscription-dominant nature of content-partition and the advertising-dominant nature of time-partition.

5.4 Comparison between channel membership mechanisms

Figure 5 directly compares the relative performance of the two channel membership mechanisms. The left panel shows that when the immediacy premium ψ and the release ratio η are low, the profit under time-partition is slightly lower than under content-partition. However, as both parameters increase, the profit difference turns positive and grows steadily, indicating that time-partition becomes more profitable when the temporal value of paid content is high and a substantial proportion of content returns to the free-content area after the window period. The intuition is that content-partition relies mainly on exclusive subscription revenue, but the associated reduction in free content amplifies the loss of advertising returns. Time-partition, in contrast, extracts subscription value through early access while retaining long-term advertising monetization, thereby allowing the platform to simultaneously benefit from subscription and advertising revenues.

The right panel of Figure 5 further examines creators’ profits. When the advertising discount factor δ is low and post-window advertising value decays quickly, creator profit under time-partition is lower than under content-partition. As δ increases, however, advertising returns become more stable, allowing creators under time-partition to benefit simultaneously from subscription income and advertising revenue after the release window. Their relative payoff gradually surpasses that under content-partition. Overall, time-partition exhibits the greatest advantage when temporal value is high, content return is substantial, and advertising value remains stable. Conversely, when immediacy value is limited or advertising erosion is severe, the performance gap between the two mechanisms narrows, implying that the incremental benefit of channel membership to both platforms and creators is modest in such environments.

6 Discussion and implication

6.1 Discussion

Our findings provide new perspectives on several issues that have received growing attention in the UGC platform literature. In particular, they contribute to ongoing discussions of creator incentives, platform monetization, and ecosystem sustainability, while also offering implications for platform management.

Our first contribution is to extend the literature on UGC content supply and creator incentives. Prior research has primarily examined how advertising revenue sharing influences creative effort and content quality [8–11], highlighting the critical role of platform-level incentives. However, most studies treat UGC as a homogeneous category and do not distinguish between free and paid content. In contrast, our model explicitly characterizes creators’ allocation of limited effort between the two content types and identifies a structural substitution effect in creative effort that has received limited prior attention. Unlike existing studies that primarily focus on creator-side incentive problems, our framework further incorporates the strategic interactions among platforms, content creators, and consumers within a unified analytical system. Moreover, while some studies suggest that monetary incentives may reduce content contribution under certain conditions [12], our results show that such effects depend fundamentally on the institutional structure of monetization. Permanent exclusivity, as in content-partition membership, tends to crowd out free content, whereas temporary exclusivity, as in time-partition membership, allows creators to continue obtaining advertising revenue after the release window, thereby maintaining the continuity of free-content supply. This finding suggests that the way monetization mechanisms are organized plays an important role in shaping the sustainability of UGC content ecosystems.

Another contribution lies in advancing the understanding of monetization design on UGC platforms. Existing research has examined pricing and revenue structures under advertising, subscription, and hybrid models [21–33], but the focus largely remains at the platform-wide subscription level. We instead shift attention to creator-level channel subscriptions, where users subscribe to individual creators rather than the platform as a whole. This institutional difference fundamentally reshapes the interaction between advertising and subscription revenues and alters creators’ allocation of effort. Furthermore, by comparing content-partition and time-partition designs, we demonstrate that the two mechanisms generate structurally distinct equilibrium outcomes. Our results suggest that platform outcomes depend not only on whether monetization mechanisms exist, but also on how such mechanisms are organized. In particular, content-partition membership relies more heavily on subscription-driven monetization, whereas time-partition membership preserves a stronger interaction between subscription revenue and long-term advertising revenue.

Beyond monetization design, our findings also contribute to the broader discussion of UGC ecosystem sustainability [13, 15, 16]. Public discourse has long expressed concern that commercialization may erode the quality of free content. Our results challenge this generalized perception by showing that membership programs do not inherently harm the free-content ecosystem; rather, their impact depends on the market environment and institutional design. Content partitioning is more suitable for high-value, specialized, and niche content, whereas time partitioning is better aligned with high-frequency, advertising-dependent content communities. These findings help explain the coexistence of multiple monetization regimes in practice.

6.2 Managerial implications

From a managerial perspective, our findings yield several implications for UGC platforms undergoing commercialization transitions.

An important managerial implication is that neither channel membership mechanism is universally superior. Both channel membership mechanisms can improve platform profitability under appropriate conditions, but their performance advantages arise in different environments. Thus, there is no universally optimal membership design, and platforms should align monetization mechanisms with the characteristics of their content ecosystems. Platforms centered on knowledge-oriented or professional content are more likely to cultivate stable user loyalty and exclusive value, making content partitioning advantageous for subscription monetization. In contrast, entertainment- and short-video-based platforms rely more heavily on advertising and traffic scale; for them, time-partition membership helps preserve audience reach while maintaining advertising monetization capacity. Therefore, channel membership mechanisms should be viewed not merely as pricing tools, but also as institutional arrangements closely related to platform positioning and ecosystem structure.

The results also highlight the importance of commission design in balancing platform profitability and creator incentives. We find that the platform’s optimal commission rates on both advertising and subscription revenues lie within interior ranges. This result has practical implications for platforms seeking to raise commission rates. While higher commissions may boost platform revenue in the short term, excessive extraction weakens creator incentives, depresses content quality, and ultimately harms long-term platform value. Commission design should therefore emphasize creator surplus sustainability, especially under time partitioning where advertising and subscription income interact dynamically over time. Over-monetization risks undermining the incentive foundation of long-term content creation.

The findings further indicate that channel membership mechanisms are likely to evolve toward more content-specific institutional designs rather than uniform platform-wide policies. Platforms may assign different membership formats to different content categories depending on value characteristics, update frequency, and audience loyalty—for example, applying content partitioning to knowledge-based content while adopting time partitioning for entertainment or news content, or differentiating policies between top creators and mid-tier creators. Such refined institutional design helps balance monetization efficiency with ecosystem stability and avoids systemic risk arising from uniform policy shocks.

Overall, channel membership programs are likely to reshape the revenue structure and creative ecosystem of UGC platforms in the long term. Successful institutional design requires viewing creators as strategic partners rather than short-term revenue sources. Sustainable growth depends on achieving a workable balance between monetization efficiency, creator incentives, and ecosystem resilience.

7 Conclusion

This study develops a three-stage game-theoretic framework to investigate how creator-level channel membership mechanisms influence content supply, revenue structures, and platform profitability in UGC platforms. By comparing no membership, content-partition membership, and time-partition membership, we show that different membership designs generate distinct incentive structures for creators and platforms, leading to different equilibrium outcomes in content allocation and monetization. Overall, our results indicate that the effects of channel membership depend on institutional design and market conditions rather than the adoption of membership itself, providing theoretical support for the design of sustainable monetization strategies on UGC platforms.

Although this study provides a theoretical framework for understanding channel membership mechanisms on UGC platforms, several issues remain open for future research. First, to highlight the strategic effects of channel membership mechanisms, we consider a single-platform environment and assume homogeneous creators and content types. In practice, creators differ substantially in content quality, production capability, audience size, and monetization objectives, while different categories of content may exhibit heterogeneous demand and revenue characteristics. Incorporating creator and content heterogeneity would provide a richer understanding of membership mechanism design and further extend the applicability of the proposed framework.

Another limitation concerns the simplified representation of consumer behavior. Consumer behavior is modeled using the Salop framework to capture horizontal differentiation, which inevitably abstracts from several important behavioral factors observed on real UGC platforms. Social influence, word-of-mouth diffusion, user loyalty, platform stickiness, and recommendation algorithms may all affect users’ subscription decisions and content consumption patterns. Future research could incorporate these behavioral mechanisms to better reflect the complexity of platform ecosystems and further enrich the analysis of channel membership strategies.

Finally, this study primarily develops a theoretical framework to explain the economic mechanisms underlying channel membership. While the proposed model provides clear analytical insights into the strategic interactions among platforms, creators, and consumers, future research could further examine these mechanisms using empirical evidence from different platform environments. Combining theoretical modeling with empirical analysis or natural experiments would further strengthen the practical relevance of the proposed framework.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fphy.2026.1937180/full#supplementary-material

Supplementary material Supplementary material at the source

Footnotes

Edited by: Kaipeng Hu, Yunnan University of Finance and Economics, China

Reviewed by: Genhao Li, Yunnan University of Finance and Economics, China

Wenhua Li, Beijing Normal University, China