Lin Guangbin and Xiong Youcheng: How Non-productive Platforms Participate in the Distribution of Surplus Value
Introduction
The platform economy, formed by the development of Internet information technology and the revolution in Artificial Intelligence (AI), is shaping new modalities of human production and life, becoming a vital engine for economic development. Generally, a platform is considered a business model that gains profit by providing a venue to facilitate transactions, interactions, or exchanges between different user groups through the construction of network effects. Platforms themselves are not a new phenomenon; however, due to the application of Internet technology, digital platforms have broken through the constraints of geography, time, transaction scale, and information communication faced by traditional platforms, acquiring entirely new scales, connotations, efficiency, and influence.
Based on the criteria of target audiences and functional uses, Nick Srnicek's five-fold classification of platforms [1] is currently widely applied: First are advertising platforms, whose function is primarily to extract and analyze data generated by platform users and then provide digital services such as analytical results or advertising promotion. Second are product platforms, which use digital technology to transform traditional commodities into digital goods and services, charging rents or subscription fees while providing services to consumers. Third are lean platforms, which outsource a large number of services and functions, profiting by providing digital information services and data products acting as means of production. Fourth are cloud platforms, which mainly provide rental services for cloud analysis capabilities. Fifth is the Industrial Internet of Things (IIoT), where information enterprises build internet connection services capable of supporting traditional manufacturing. In addition, domestic scholars such as Qu Jiabao have classified platforms according to the methods of corporate capital accumulation; Xie Fusheng and others have also classified platforms by combining corporate charging models with categories of traded commodities.
Platform enterprises refer to firms that take digital platforms as their core assets and business models. To date, the main types of enterprises include four categories: 1) Transactional platform enterprises, which primarily facilitate the trade of goods or services, such as Alibaba (B2B/B2C), JD.com, DiDi Chuxing, Meituan, and Amazon. 2) Innovation platform enterprises, which primarily build technical foundations and ecosystems to provide basic technologies and tools, allowing third parties to develop complementary products or services upon them, thereby empowering myriad industries; these include industrial internet platforms, AI and IoT platforms, and basic software and system platforms, such as Changhong's CHiM industrial internet platform, Huawei’s AI large models, Tencent’s AI large models, Huawei’s HarmonyOS, Microsoft’s Windows, Apple’s iOS, and Google’s Android system. 3) Content/Social platform enterprises, which primarily facilitate content creation, sharing, and social interaction, such as WeChat, Douyin, Weibo, Facebook, and YouTube. 4) Hybrid platform enterprises, as many large platforms are moving toward hybrid models; for example, WeChat is both a social platform and an integrated suite for payments, mini-programs (an innovation platform), and e-commerce (a transactional platform). Similarly, the JD.com platform has evolved into a logistics delivery service plus "JD Manufacturing," and Alibaba Group integrates diverse businesses ranging from advertising platforms to cloud computing.
The platform economy refers to a new economic system and economic form centered on platform enterprises, based on digital technology, and composed of data-driven processes, platform support, and network coordination. China's "14th Five-Year Plan" defines the platform economy as an economic form in which resource allocation is coordinated and organized by Internet platforms.
Compared to the traditional economy, the platform economy exhibits several new economic characteristics. From a positive perspective: First, it enhances the efficiency of matching supply and demand and reduces costs. Algorithms greatly improve the precision and speed of matching, significantly lowering search, information, and contracting costs. Second, it stimulates the vitality of innovation and entrepreneurship. It provides low-threshold entrepreneurial and employment opportunities for a large number of micro, small, and medium-sized enterprises and individuals (such as online shop owners, food delivery riders, and content creators). In particular, open platforms (such as the App Store) have spawned a massive application development ecosystem. Third, it optimizes resource allocation, activating and efficiently utilizing idle social resources (such as vacant rooms, private cars, and personal time), thereby promoting the development of the "sharing economy." Fourth, it creates consumer welfare, providing consumers with unprecedentedly rich choices, lower prices, greater convenience, and personalized experiences. Fifth, it promotes the digital transformation of industries. Industrial internet platforms (such as Haier's COSMOPlat and Rootcloud) are reshaping the production and management models of traditional manufacturing.
From a negative or challenging perspective: First, it brings new monopolies and the concentration of market power. Strong network effects easily lead to "winner-take-all" outcomes, forming market monopolies that suppress competition and innovation—such as the predatory acquisition of small and medium enterprises by "super-platform" firms, which stifles the innovative potential of others. Second, data privacy and security issues urgently require regulation. Platform firms collect vast amounts of user data, presenting risks of data abuse, privacy leaks, and security breaches. Third, there are issues of algorithmic ethics and transparency. Algorithmic "black boxes" may lead to price discrimination ("big data price gouging" [2]), biased content recommendations, and unfair evaluations of laborers (such as delivery riders). Fourth, there are problems regarding the protection of workers' rights and interests. Under the gig economy model, issues such as labor protection and social insurance for platform workers (e.g., riders and ride-hailing drivers) are prominent. Fifth, there are tax and regulatory challenges. The cross-regional and cross-sectoral nature of platforms poses a huge challenge to traditional tax and industry regulatory systems based on geography. Furthermore, disorderly competition between different platform enterprises and a lack of social responsibility on the part of platform firms can lead to many behaviors that cross legal lines, infringe on user rights, and disrupt social order.
In short, platform enterprises are the representative economic organizations of the digital economy era, creating enormous commercial value by constructing multilateral markets and utilizing network effects. The platform economy is a new economic paradigm formed around these platforms; while it has greatly promoted economic growth and social progress, it has also brought severe challenges such as monopoly, privacy leakage, and algorithmic "black boxes." Under these circumstances, a concrete analysis of the laws of value operation and the distribution of surplus value in the platform economy is highly necessary for promoting the steady development of China's platform economy.
I. Sources of Value in the Platform Economy
Regarding the source of value in the platform economy, one can employ the basic analytical framework of Marxist political economy to investigate the respective roles played by the platform economy in production and exchange (or circulation), as well as in value creation and value transfer.
(1) Productive Platforms and Non-productive Platforms
From the perspective of their contribution to the real economy, economic platforms can theoretically be divided into "productive platforms" and "non-productive platforms." The core lies in judging whether the platform's primary economic activity creates new social value (increments), primarily optimizes and redistributes existing value (stocks), or potentially extracts excess profits through a monopoly position (decrements).
First, let us look at productive platforms. These platforms are deeply integrated into the chains of the real economy, directly enhancing production efficiency and resource allocation efficiency through digital means to create new value. They are key forces in creating new industries and promoting industrial upgrading and high-quality development. Their core characteristics include: 1) Empowering the real economy. They focus on serving the primary and secondary industries and producers, enhancing their core capabilities in R&D, production, manufacturing, and supply chain management. 2) Enhancing total factor productivity. By providing technology, data, finance, and other services, they help traditional enterprises reduce costs, increase efficiency, improve quality, and innovate. 3) Creating incremental value. Their activities directly lead to the emergence of new products, services, and processes, expanding the total economic volume. 4) Generating new technology-intensive economies, including economic entities built upon "hard" technologies such as the industrial internet, AI, big data, and the IoT. The main types of productive platforms include the aforementioned industrial internet platforms, B2B industrial e-commerce platforms, R&D and collaborative innovation platforms, and digital technology empowerment platforms. Haier Kaos COSMOPlat (which empowers enterprises to achieve mass customization), Rootcloud's Rootcloud platform (providing equipment connection and data analysis services), and Siemens MindSphere (an industrial IoT operating system) are typical industrial internet platforms; their role is to connect industrial equipment, optimize production processes, provide predictive maintenance, and facilitate supply chain coordination. Alibaba (1688.com), Guolian Shares, and Ouyeel (for the steel industry) are typical B2B industrial e-commerce platforms; their role is to link the up- and down-streams of industry, reduce the cost of raw material procurement and product sales, and enhance supply chain efficiency. GitHub in the software field and the Apollo open platform in the field of autonomous driving are typical R&D and collaborative innovation platforms; their role is to aggregate global intellectual resources, share technical tools, and accelerate technological innovation and product R&D. Cloud computing service providers like Alibaba Cloud, Huawei Cloud, and Tencent Cloud are digital technology empowerment platforms; their role is to provide enterprises with computing power, data, and AI capabilities, lowering the threshold and cost of digital transformation. Productive platforms are exemplars of the "integration of the digital and the real" [3]; they represent the direction of development for the platform economy. They are capable of making the real economy stronger and better, enhancing national competitiveness in global industrial chains, and serving as the core driving force of the digital economy and the focus of policy encouragement and support.
Second, let us look at non-productive platforms. The activities of these platforms are mainly concentrated in the fields of circulation, consumption, social interaction, and entertainment. Their core value lies in optimizing transaction matching and distribution efficiency, but they do not directly participate in the production and creation of material products. Their core characteristics include: 1) Focusing on transaction and consumption links. They primarily serve end-point consumption, optimizing the circulation and matching of goods, services, information, and content. 2) Optimizing "stock" value. They redistribute existing consumption and attention primarily by improving information symmetry and convenience, rather than creating entirely new material products. 3) Capital and data-intensive nature. Their expansion is highly dependent on capital investment and the accumulation of user data, making them prone to forming winner-take-all monopoly patterns. 4) Potential to trigger social problems. If regulation is ineffective, they can easily lead to the disorderly expansion of capital, data abuse, deterioration of the content ecosystem, and the squeezing of profits from the real economy. The main types of non-productive platforms include: traditional e-commerce and O2O platforms, social and content platforms, and gig economy platforms. Taobao, JD.com, Meituan (in-store business), and Pinduoduo are typical enterprises of traditional e-commerce and O2O platforms; their role is to efficiently match goods/services with consumers, greatly facilitating life, but what they primarily optimize is the "transaction" itself. WeChat, Douyin, and Facebook are typical representatives of social and content platforms; their role is to satisfy people's needs for social interaction, entertainment, and information acquisition, primarily allocating the "attention" and "time" of users. DiDi, Meituan Waimai (rider side), and Uber are typical representatives of gig economy platforms; their role is to efficiently match labor with short-term demand, providing employment flexibility. The value sources or income models of non-productive platforms mainly include: 1) Transaction commissions, i.e., taking a certain percentage of each successful transaction (e.g., Meituan, DiDi). 2) Advertising revenue, i.e., charging merchants fees to display advertisements more accurately to users (e.g., Google, ByteDance). 3) Subscription services, i.e., charging users or merchants periodic fees for access to premium features or services (e.g., Amazon Prime, LinkedIn Premium). 4) Value-added services, charging service fees for providing additional services such as data analysis, cloud computing, and financial loans (e.g., Alibaba Cloud, Ant Group).
From the above analysis, we can see that productive platforms primarily serve the supply side or producers. Their core value is to create incremental value and enhance production efficiency, mainly through the industrial internet, the IoT...
New quality productive forces such as AI and cloud computing perform economic functions including empowerment, innovation, and manufacturing. Non-productive platforms primarily serve the demand side or consumers; their core value lies in optimizing the distribution of existing stocks and improving transaction efficiency. They perform economic functions such as matching, circulation, and consumption mainly through recommendation algorithms, payment systems, and user interface services. However, the classification of platforms into productive and non-productive categories must be viewed dialectically. Non-productive platforms have greatly improved the consumption experience, created convenience, activated idle resources, and spawned a large number of new types of employment. Their "non-productivity" is a neutral description in the economic sense rather than a moral critique. The key lies in their development model: healthy non-productive platforms truly reduce social transaction costs through technological innovation, create win-win situations for sellers and consumers, and abide by regulations. If alienated non-productive platforms exploit their dominant market positions to extract excess profits from both producers and consumers—through methods like "choosing one of two" [4], big data-enabled price discrimination [5], or exorbitant commissions—they then become extractive or rent-seeking platforms that suppress the vitality of the overall economy. This is especially true as many large platforms develop toward hybrid models. For example, JD.com has B2C businesses facing consumers (non-productive), but also possesses powerful intelligent supply chains and logistics systems serving brand owners (productive). Meituan has "in-store" businesses connecting consumers and merchants (non-productive services), but also empowerment businesses such as unmanned delivery and catering SaaS systems that serve merchants (productive services). Therefore, one must avoid absolutizing the classification of productive and non-productive.
(2) New Changes in Labor under the Digital Economy Under the support of information technology, forms of labor in the digital economy have exhibited a series of changes. From the perspective of the laborer, the subject of labor manifests in more diverse forms under the digital economy. While digital technology has dismantled the rigid boundaries of traditional labor forms, it has also spawned new digital labor models. Be it the transportation services of ride-hailing drivers or the digital production of online content creators, these are all new changes brought about by digital technology empowering traditional labor. New digital labor enables workers to break through the constraints of time and space; they are no longer confined to fixed working hours and locations, demonstrating capital's characteristic of expanding beyond all spatial boundaries. The object of labor has also undergone multiple transformations in the digital economy, the most important of which is that user data, as a new type of labor object, has been incorporated into the production process, becoming an important raw material for platform capital accumulation. In addition, instruments of labor [6] in the digital age have gradually transformed into a combination of information technology and digital equipment; whether in traditional manufacturing or new technology industries, the updating of instruments of labor has been achieved through empowerment by digital technology.
In 2000, the Italian scholar Tiziana Terranova first proposed the concept of "Digital Labour." She categorized the construction of basic internet hardware infrastructure, the production of terminal products, network operation and maintenance, as well as behaviors such as receiving messages and creating content when users use social media, all as digital labor. Later, Christian Fuchs systematically organized relevant concepts in Digital Labour and Karl Marx. Currently, the academic community divides the concept of digital labor into narrow and broad senses. Broad digital labor includes paid digital labor under employment forms and unpaid digital labor under non-employment forms, while narrow digital labor refers only to the data information labor paradigm within the social media or internet fields where digital technology serves as the terminal.
Below, we provide an in-depth analysis of labor providing information technology, labor providing digital commodities, and labor providing digital services.
First, labor providing information technology. In the era of the digital economy, the labor involved in platform construction possesses dual historical characteristics: it is both the material basis for digital relations of production and the implicit premise of the valorization process. This part of labor is often contained within the work of software engineers required in the early stages of platform establishment and the technical labor required for maintenance during later operations; it primarily utilizes internet information technology to provide hardware and software support for the building of internet platforms. From an abstract perspective, the labor of platform construction merely provides the vehicular foundation for subsequent exchange and creates conditions for the production of new value. If a platform, after completion, is partially or wholly leased out for profit—such as a cloud computing platform—then this labor directly participates in the production process of value and surplus value. It belongs to the necessary conditions for the continuous proceeding of the production process and can be called productive labor.
Second, labor providing digital services. Digital services are economic activities that use digital means to provide customers with various forms of added value, such as convenience, comfort, efficiency improvements, or health. There are two primary services that the platform economy can provide: first, providing more efficient and convenient sales services for platform merchants, typical representatives of which are various online shopping platforms and food delivery platforms; second, providing various advertising information pushes for platform customers, such as the Baidu browser platform and the WeChat platform. This type of digital service carries typical characteristics of commercial capital, manifested specifically in the fact that it does not participate in the production of products but is extremely dependent on industrial capital. This characteristic is similar to commercial capital: the activities of commercial capital depend on the operation of productive capital, and its realization of value depends on the production of commodities. Similar to commercial capital, the role of labor participating in the provision of digital services in the platform economy lies primarily in accelerating the circulation speed of existing commodities. Circulation itself does not create new value; it only accelerates the realization of value and therefore cannot produce surplus value. The profits it obtains primarily originate from the fragmentation of industrial profits. As Marx pointed out: "Commercial capital realizes profit only because industrial capital does not realize the entire surplus value or profit in the price of the commodity." Commercial capital itself does not add even a trace of value to these commodities. Therefore, this type of labor does not produce any new value or surplus value.
Finally, labor directly providing digital commodities. Regarding labor providing digital commodities, there has been much discussion in academic circles. A segment of Western scholars adheres to the "audience commodity" theory, particularly the school of political economy of communication. The American Tim O’Reilly proposed that the current internet society has entered the Web 2.0 era, characterized by decentralization, openness, and flatness. Compared to the Web 1.0 era, the greatest feature of the 2.0 era is the shift from the traditional "one-to-many" unilateral output of traditional media to a "many-to-many" content dissemination and output mode characterized by deep user participation and user-generated content (UGC). Social media platforms are typical representatives of this change, such as Facebook and Twitter. Within this context, the political economy of communication proposed the "audience commodity" theory, arguing that media capitalists, by using various media vehicles, exploit and appropriate the "attention" of audiences to share the extra profits brought by the increased speed of capital turnover from the hands of industrial capitalists. However, this theory actually contains significant logical flaws. Marx emphasized that productive labor should possess the characteristic of "purposefulness," whereas users' spontaneous content production behaviors (such as social interaction and content posting) do not have the direct purpose of producing data factors to achieve valorization. At the same time, the precise delivery of advertisements to audiences can only push the speed of commodity flow faster, thereby accelerating the process of capital turnover and valorization. But this part of the operation still belongs to the sphere of circulation—that is, as Harvey stated, the "spatial fix" strategy of digital platforms alleviates the crisis of over-accumulation of capital by accelerating the flow of information, but it does not itself create new use-values. The act of industrial capitalists purchasing advertising services from media capitalists is essentially the accelerated accumulation of surplus value of industrial capital by shortening commodity circulation time, rather than releasing the value contained within the data itself. The above two points fully demonstrate that the labor of users spontaneously creating data cannot be called productive labor, and thus produces no surplus value for the platform. Realistic data also confirms this view. For instance, the famous social platform Meta (Facebook) saw advertising revenue account for 97.5% of its total in 2022; the core source of digital platform profits remains the transfer of surplus value from traditional industrial sectors.
To clarify this issue, it is necessary to define two basic concepts: what constitutes a digital product and what constitutes a digital commodity. Digital products refer to raw data information that has not undergone capitalization (such as user browsing traces and social interaction content); their essence is the unconscious byproduct of digital behavior. Digital commodities, on the other hand, refer to exchangeable data packages formed after the subject of labor processes and integrates digital products. The theoretical basis for this distinction remains Marx’s labor theory of value: only labor with valorization as its explicit goal can be incorporated into the value-creation system of capitalist relations of production.
Based on this, one can better distinguish the nature of labor related to digital commodities. Data spontaneously created or left behind by users (such as UGC content), i.e., digital products, are important factors in the production of data commodities. However, this content is not the result of conscious labor, but rather a kind of "accidental spillover," and therefore produces no value. Yet, once digital products are transformed into digital commodities through processing by workers employed by the platform economy, they possess surplus value. First, from the perspective of the concrete form of labor, "all labor is, on the one hand, an expenditure of human labor power in the physiological sense; and in its character of identical or abstract human labor, it creates and forms the value of commodities." The expenditure of mental and physical effort by digital laborers not only creates concrete use-values that satisfy user needs (such as data analysis and content production) but also forms the basis of the exchange value of the commodity through the objectification of socially necessary labor time. In this regard, it can be said that digital commodities satisfy the basic characteristics of commodities. Second, at the level of the relations of production, the platform achieves substantive control over the processing procedure through labor contracts. Through algorithmic monitoring, performance indicators, and data rating systems, the platform forces the living labor of digital laborers to be continuously invested in the valorization process. Digital laborers not only work under the platform’s close supervision, but their labor products are also appropriated by the platform. When the digital commodity achieves its "salto mortale" [7] through market exchange, the surplus value congealed within it is appropriated by capital without compensation. That is to say, this labor produces surplus value and is exchanged with capital, achieving valorization for capital. Therefore, it can be said that platforms producing digital commodities create new value.
Based on the above analysis, the following understanding can be reached: not all digital platforms are capable of producing new value or surplus value; only when the digital labor involved in the platform falls within the scope of productive labor, such as participating in the production of digital commodities, can the platform directly earn surplus value. Therefore, when a digital platform can directly perform surplus value production and provide valorization services and data commodities, it is called a productive platform; when a digital platform primarily participates in the subsequent realization stage of surplus value, it is called a non-productive platform. In theory, the concepts of productive and non-productive platforms are absolutely mutually exclusive, but specific platforms existing in reality often possess both productive and non-productive qualities.
II. How Non-Productive Digital Platforms Participate in the Distribution of Surplus Value
Productive platforms can create new value through the labor of hired data workers, but how do non-productive platforms obtain their surplus value? In the era of digital capitalism, although non-productive platforms do not directly participate in the production of surplus value, their value extraction mechanism has achieved a breakthrough over traditional paradigms. In the perspective of traditional political economy, commercial capital obtains a transfer of value from industrial capitalists by facilitating commodity circulation, and landowners collect differential land rent by virtue of monopolistic property rights; these two forms of value distribution have clear boundaries. However, by constructing multilateral market architectures, non-productive platforms can act both as commercial capital to accelerate commodity circulation and as monopolists of virtual space to collect digital land rent. This dual value-capture mechanism constitutes the new modality of capital accumulation for such platforms.
(1) Non-productive platforms are the development of commercial capital in the digital era The profits earned by non-productive platforms bear a strong character of commercial profit. Commercial capital refers to capital specialized in the buying and selling of commodities. It is...
"[Commercial capital is] older than the capitalist mode of production, and is in fact historically the oldest free mode of existence of capital." Commercial capital is not limited to capitalist relations of production; rather, it has existed since the emergence of commodity economy. The process of the socialization of production catalyzed by the modern Industrial Revolution propelled a morphological transformation of commercial capital. The capital functions within the circulation process acquired an independent form, and through the social division of labor, they were solidified into the specific functions of specialized capital; commodity capital thus transformed into specialized commercial operating capital. Commercial capital serves commodity circulation, representing the independence and differentiation of this function. Independent commercial capital acts back upon the sphere of production through mechanisms such as shortening circulation time and accelerating capital turnover. This division of labor in capital is directly driven by the continuous development of the productive forces, and ultimately acts back upon their further development.
In the era of the digital economy, non-productive platforms, while fully inheriting the characteristics and functions of commercial capital, have further reconstructed the operational paradigm of traditional commercial capital by virtue of network information technology. Relying on digital technologies such as big data, cloud computing, and intelligent algorithms, they continuously concentrate and integrate collected information resources to construct point-to-point precision transaction networks, greatly enhancing their ability to accelerate the speed of capital turnover. On a concrete level, the role of non-productive platforms in promoting commercial efficiency is multi-dimensional. Non-productive platforms have largely eliminated the problem of information asymmetry existing between the supply and demand sides. Based on algorithm-driven intelligent matching mechanisms, platforms transform discrete supply-side information and demand-side preferences in traditional markets into clear interactive interfaces, significantly reducing the information search costs of market subjects. At the same time, non-productive platforms have established mature credit guarantee mechanisms; by intervening in the market as third parties, they have reshaped the mode of trust production in market transactions. Taking the "Alipay" system of the Taobao platform as an example: as the leader of transactions, the platform established a delayed payment settlement and bilateral evaluation system, transforming transaction relationships that were dominated by personalized trust [8] in traditional commerce into an institutionalized governance structure based on algorithmic credit scores, effectively guaranteeing the legitimate rights and interests of both parties. Beyond this, non-productive platforms have also built dynamic pricing models based on big data algorithms, achieving flexible control over the allocation of resources across time and space, and effectively optimizing the circulation speed of platform resources. A typical representative of this is how certain e-commerce retail platforms utilize real-time interest data on relevant commodities to dynamically adjust prices.
The above mechanisms fully demonstrate that non-productive platforms effectively link commodity transactions across different times and spaces and greatly improve the efficiency of supply-demand matching. They exhibit the typical traits and functions of commercial capital and are a derivative of commercial capital in the digital era.
(2) The Sources and Characteristics of Digital Ground Rent Collected by Non-productive Platforms
Capitalist ground rent is the concrete expression of private property rights in land within the sphere of value distribution; it is the economic form through which land ownership is realized. It is rooted in the special natural monopoly of land as a means of production, representing the landowner's uncompensated appropriation of surplus value created by direct producers through their monopoly over scarce natural elements.
In the digital economy era, as virtual space becomes a new type of site for production and exchange, platform capital becomes the new rent collector. Jathan Sadowski has pointed out: "Landlords extract rent through land ownership; platforms extract data rent through data ownership and control." Non-productive platforms in the digital economy possess sufficient conditions for collecting digital ground rent. From the perspective of scarcity, although virtual space seems to be an infinitely expanding resource, with the continuous development of the platform economy, the entire industry often becomes monopolized by a few leading enterprises. The development of the platform economy itself carries a trend toward natural monopoly. As Cédric Durand said, the first reason driving monopoly is "what economists call natural monopoly conditions, that is, the market structure itself is the result of the action of three elements: network complementarity, economies of scale, and sunk investment." These characteristics make it inevitable that the platform economy, in its development process, will gradually form a few monopoly leaders occupying an absolutely dominant market position. Taking Meta and Google as examples, the two occupy 68% of the global digital advertising market; their platforms have become necessary channels for enterprises to reach consumers. This platform-level monopoly confirms Marx's thesis on ground rent: "It [ownership] is not the cause of the creation of this surplus profit, but rather the cause of its transformation into the form of ground rent." When certain production conditions are monopolized by a few and their supply cannot be increased through competition, surplus profit is transformed into ground rent. From the perspective of the organic composition of capital [9] ($c/v$), the organic composition of capital for the platform economy is generally lower than that of traditional sectors such as manufacturing, which also provides the precondition for the generation of ground rent.
The rent collected by the platform economy can also be divided into differential rent and absolute rent according to Marxist standards. First, let us analyze differential rent (also known as relative rent). The formation mechanism of differential rent is always closely related to the differences in the nature of the means of production—such as differences in land fertility or production factor conditions—which lead to differences in the actual output of land, thereby resulting in differences in the rent that can be collected from different plots. As Marx revealed in Volume III of Capital: "It arises because of the limited area of the best land... it arises because equal capitals must be invested in different classes of land which provide unequal products for equal capitals." Efficiency differences also exist between platforms. In the digital age, the sources of user data, information collection tools, and big data algorithms owned by a platform can be regarded as the intangible assets of the platform enterprise, serving as the core competitiveness for its survival and development. Cédric Durand believes that these intangible assets precisely form the differential rent obtained by the platform, noting: "Intangible assets generally have scalability, such as software or organizational experience. Once the initial investment is completed, they can be replicated at negligible marginal cost, so returns to scale tend toward infinity... the benefit of this differentiation constitutes the key to understanding the specificity of current competitive logic." Differences in the quality and quantity of intangible assets owned by different enterprises lead to differences in their efficiency. The gap in technical efficiency between digital platforms creates the basis for the generation of a new type of differential rent. Consequently, the relative returns that different platforms can obtain will also vary. Leading platforms, by virtue of the advanced nature of their data infrastructure, are able to achieve value capture capabilities far exceeding the industry average. This difference in the productivity of "virtual land" allows platforms occupying the technological high ground to continuously obtain surplus profit, much like high-quality plots of land, exhibiting a characteristic of increasing returns. Furthermore, the mechanism of digital differential rent greatly influences the results of value distribution. When a platform is in a disadvantageous position during technological generational shifts, the additional income it can bring to platform users shows a trend of diminishing marginal returns, and the rent it can collect will be relatively less; enterprises at the tail end of the industry will be unable to obtain this portion of ground rent. Even within the camp of monopoly platforms themselves, due to differences in parameters such as algorithm iteration speed and the completeness of the ecosystem, a return gradient similar to "better land providing more rent" will still form, thereby creating sufficient conditions for the collection of differential rent.
Next, let us analyze absolute rent. Marx revealed in Volume III of Capital that the basis for the existence of absolute rent lies in the fact that the organic composition of capital in a specific production sector is long-term lower than the social average. This enables the sector to create a quantity of surplus value higher than the average profit by absorbing excess living labor, thereby providing a source of rent for the landowner. The internet platform industry shares these same characteristics. Once platform construction is complete and operations begin, the platform's primary expenditure is on labor; therefore, its organic composition is generally lower than the social average organic composition of capital. Simultaneously, the organic composition of the industrial capital [10] attached to it is often lower than the social average. The digital platform economy allows industrial capital to significantly reduce its own fixed capital investment, such as site rental costs. Compared with physical merchants, online merchants on platforms use the digital space provided by the platform to achieve a relocation of their business premises and possess a lower organic composition of capital, which creates the conditions for paying rent out of surplus profits.
Compared to traditional ground rent, new digital rent also presents two entirely new characteristics. First, digital rent has achieved a transition from the finite to the infinite. Digital rent, parasitic on virtual space, breaks through the constraints of limited physical space faced by traditional rent, realizing the infinite predation of surplus value. The digital services provided by non-productive platforms are non-rivalrous and infinitely reproducible, which makes the marginal cost of their reproduction process approach zero. For example, a shopping platform may have a large number of merchants entering every day, but the platform does not need to provide any specific additional services for them, basically achieving zero investment. This provides a basis for the process by which non-productive platforms more conveniently harvest the surplus value generated by merchants. Second, the value extraction mechanism of digital rent shows an important trend toward evolving into the form of "ecosystem rent." Since platforms themselves require high user stickiness, they will inevitably strive to form their own ecosystem models during expansion to ensure user dependence. Currently, the architectural expansion of platform ecosystems mainly occurs through horizontal business expansion (such as extending from core e-commerce into fintech or cloud computing services); a typical case is JD.com [11] entering the food delivery market by leveraging its own logistics advantages. On the one hand, this mechanism improves the platform's ability to serve customers; on the other hand, it enables the platform to more effectively ensure its dominant position in the sphere of circulation.
(3) The Profits Obtained by Non-productive Platforms Possess the Nature of Both Commercial Profit and Ground Rent
Non-productive platform rent reflects the symbiotic nature of commercial profit and capitalist ground rent. From the perspective of commercial profit attributes, platform rent income essentially originates from monopolistic intervention in the commodity circulation process—through algorithmic matching, traffic distribution, and rule-making, the platform builds a virtual transaction space to aggregate supply and demand sides, facilitating the accelerated circulation of industrial capital and thereby deeply participating in the stage of value realization. The commissions and service fees it collects can be seen as an extension of commercial profit in the digital era. As for its ground rent nature, enterprises rely on technical barriers and network effects to deeply occupy the digital space elements of the platform; the rent obtained can be seen as the surplus return on the monopolistic occupation of "digital space," possessing the composite characteristics of differential rent and monopoly rent. This symbiotic logic reflects the new contradictions of digital capitalism: the platform both participates in value distribution as a circulation intermediary and forms a new type of rental exploitation through the occupation of monopolized means of production, ultimately deepening dual control over both producers and consumers under the logic of capital valorization.
Taking business commissions [12] as an example, these are an important realization form for non-productive platforms to earn income and are the most direct manifestation of platform economy revenue. Specifically, a platform's extraction of business fees is not done in a single one-off extraction; rather, based on the strategic needs of the platform's ecological development, different forms of extraction are adopted at different stages, and a transformation in the nature of the extraction occurs between them.
First, consider the case of a single platform and a single producer. In the initial stage, platforms will basically extract a certain entry fee for joining the platform. For example, when merchants enter food delivery platforms (such as Meituan and Ele.me), they all need to pay entry fees, including shop rent, operation and maintenance fees, marketing fees, and transaction fees. This is the basic form of extraction, i.e., the membership threshold fee. Since the platform has not yet begun to serve the merchant at this point—the merchant pays simply to enter the platform—this fee reflects the platform enterprise's nature as a digital virtual landlord, collecting absolute rent from other producers.
As business proceeds, the platform begins to collect commissions on every business transaction carried out. In a relatively pure case, the platform collects entry fees in advance and subsequently only charges users based on the transactions facilitated. For example, the fees Meituan charges merchants are split into technical service fees (commissions) and fulfillment service fees. Among these, the technical service fee is what the merchant pays when operating on the delivery platform and reaching a transaction, based on services provided by the platform such as information display, technical services, traffic support, and operational guarantees—this is the actual commission. This part of the technical service fee is collected entirely because the platform uses its own big data matching capabilities to facilitate transactions; it is, therefore, pure commercial profit. However, in many cases, the two are not clearly distinguished. To improve their own competitiveness, some platforms adopt a strategy of lowering their own entry fees to attract more merchants. For instance, in order to form a platform business ecosystem, some platforms often implement free entry and provide various promotional services, but they will compensate for this loss in the subsequent commissions collected during business operations.
Secondly, consider the situation where the number of merchants and platforms increases. At this point, efficiency differentials exist between different platforms, creating space for the formation of differential rent. Differential rent causes the fees merchants pay to vary when using different platforms; as previously mentioned, high-efficiency platforms charge higher commissions. A typical example is seen among China's major online shopping platforms, such as Taobao, JD.com, and Pinduoduo. For the same item, the price on JD.com is relatively higher, meaning the platform takes a larger cut. This is because JD.com provides superior delivery services compared to the other two, ensuring that the supplier's goods are delivered to the customer more perfectly and in a more timely manner. In this scenario, the supplier’s revenue per unit of time increases, and a portion of this revenue is ceded to the platform in the form of commission fees. This demonstrates that superior platforms are able to collect higher commissions.
It is worth noting that in the actual platform economy, commercial profit and differential rent always attach themselves to the existence of absolute rent. This is because commercial profit and differential rent derive from the platform's facilitation of transactions—that is, they must depend on the realization of platform functions, which necessitates entry into the virtual space of platform monopoly. Some platforms, in order to increase their attractiveness, may choose to lower this portion of rent income as much as possible, but in such cases, we can only say that absolute rent is zero, not that it does not exist.
Finally, real-world demand has birthed various forms of business commissions. Tiered rent collection is a typical method. It indicates that the platform economy has further derived a third category of rent referred to by Marx, now manifesting in the digital economy era: monopoly rent. A classic example is when a platform charges different commission percentage rates based on the size of the enterprise. Here, because the platform occupies a monopoly position in the market, it is able to collect profits exceeding the sum of the previous three forms of rent. A more advanced form of this rent is dynamic collection, where the enterprise dynamically adjusts the collection ratio for merchants based on market information and data. For instance, food delivery platforms dynamically adjust commission rates based on factors such as the merchant’s scale, product category, and level of competition. A milk tea shop might enjoy a lower commission in the platform's early stages, but as sales rise and the platform categorizes it as a "popular category," the commission rate may increase. This is the precision extraction of surplus value. The components above constitute the primary makeup of profits collected by non-productive platforms.
III. Power Sources of Value Appropriation by Non-Productive Platforms
In the era of the digital economy, the logic of value valorization for non-productive platforms exhibits characteristics starkly different from those of productive platforms. Although these platforms do not directly participate in the creation of new value within the sphere of material production, they have constructed a mechanism for the appropriation and sharing of value created by productive sectors by restructuring the power relation paths within the sphere of circulation. The reason non-productive platforms can command the power of value redistribution lies in their possession of multiple powers—including the right to use (usufruct) [13] data factors—which essentially allows them to control core functions such as information matching, credit assessment, and transaction brokering in commodity circulation, achieving a two-way monopoly control over both the producer and consumer ends.
The foundation for the platform's acquisition of this monopoly status lies in the separation of ownership and the right to use digital products. Ownership of data should rightfully belong to the data producers, but within the framework of the platform economy, this right of individual users is effectively hollowed out by the platform. From the perspective of historical materialism, the separation of ownership and the right to use is not a new phenomenon. With the deepening of the division of labor and the popularization of large-scale socialized production, the separation of property ownership from actual control has become a characteristic feature of the modern economy. The development of the platform economy is precisely the continuation and deepening of this historical trend in the digital era.
The inherent non-rivalrous and reproducible nature of data factors initially set the conditions for the separation of their power structures. In the digital economy era, the single data point of an individual does not meet the quantitative requirements to generate economic benefit, and the utilization of one's own data still faces high costs and technical thresholds. However, when massive amounts of data are aggregated by platform enterprises, they often form powerful scale effects and network effects, thereby fully stimulating the potential of data factors. This characteristic leads individuals to naturally overlook rights related to data, while platform enterprises treat them with great importance. Simultaneously, "non-exclusive characteristics such as data reproducibility and shareability are unique advantages for the development of the digital economy; exclusive data property rights would diminish the realization of data value." [14] Under these circumstances, the data ownership held by individuals must factually give way to the convenience of platform economic activities. Beyond this, the massive base of data factors required for the operation of the platform economy, and the multi-layered ownership characteristics of data factors in circulation—possessing private, public, and platform attributes—all make the protection of individual possession of data factors fraught with difficulties.
Therefore, in the digital economy era, the ownership and the right to use individual data factors have gradually separated alongside the operation and development of the digital economy. This trend of separation provided the factor-basis for the development of non-productive platforms. Platforms, in turn, further amplified this trend through a "digital enclosure movement."
In this movement, platform enterprises—cloaked in the legal veneer of user agreements—transform digital traces such as user behavior and social relationships into privatized means of production. This "digital enclosure movement" is essentially the contemporary form of what David Harvey described as "accumulation by dispossession"—platforms, under the guise of technological neutrality, use user agreements and algorithmic technology to achieve the privatized appropriation of public data resources. In the process of using the platform, users are forced to sign a series of user agreements and contracts, ceding the right to use the data factors they produce to the platform, retaining only formal ownership of the data. "The 'micro-enclosure' of platform capitalism is essentially a physical extension of data colonialism—it no longer needs to enclose land, but directly encloses user behavior and data through code and protocols." At the same time, platforms further construct high technological walls, utilizing their own exclusive power to ensure the realization of their authority. Ezrachi and Stucke pointed out in their work Virtual Competition [15] that although platforms often exhibit a state of "co-opetition," the core of their relationship remains competition—competing with each other to seize the market and exclude rivals; "the most important function lies in reaching potential competitors... to prevent the latter from gaining traction and truly growing into rivals for those super-platforms." At the level of hardware technology, platform enterprises use proprietary big data algorithms to collect and process data traces, which possess strong non-reproducibility and exclusivity, constituting difficult-to-replicate technical barriers. At the level of institutional arrangements, platforms use user agreements and intellectual property protection systems to ensure their absolute control over the flow of data within the platform. This control includes both the infinite extension of the scope of data collection and the unilateral determination of how data is used.
At this point, under the inherent trend of separation between ownership and use rights of data factors, and driven by the promotion of the platforms, platforms have achieved control over the core resource of data factors. Consequently, they have occupied a dual dominant position over both the user end and the client (merchant) end. This is a crucial condition for the platform to realize the redistribution of total social value.
In addition to the main mechanisms mentioned above, two major characteristics of the platform economy itself have also promoted the formation of a monopoly pattern. First, the development model of the platform economy is often accompanied by the emergence of "bilateral monopoly." For the individual users of the platform, the platform locks them into its own closed ecosystem through behavioral design and the reinforcement of path dependency. Research by Ezrachi and Stucke indicates that the services provided by super-platforms cause users to voluntarily give up the opportunity to independently investigate external options, thereby restricting their exposure to external choices and eventually trapping them in an "ecological cage" constructed by the super-platform. Meanwhile, because massive amounts of personal data have already been acquired and analyzed by the platform, the "virtual assistants" provided by the platform "have grown into reliable personal stewards through the process of interacting with users, which invisibly raises the switching costs for the user." This gives consumers a strong dependency on and habitual use of the platforms they utilize, making platform migration difficult. For merchants using the platform, after investing significant funds into costs such as data access fees and traffic buy-back fees, the cost of transferring platforms also gradually rises, forming a "voluntary binding" relationship with the platform. At this point, both parties are jointly parasitic on the platform, yet they in turn construct the platform ecosystem, further strengthening their own dependence on the platform and allowing the platform's monopoly status to be further consolidated.
Secondly, competition within the platform economy inherently carries "winner-take-all" and "polarization" characteristics, possessing a strong zero-sum game nature. That is, there is a powerful positive feedback loop between the development of the platform economy and its market monopoly status. To obtain a larger market share, platform enterprises will constantly improve their algorithmic capabilities and related service quality; when an enterprise gains more market share, the larger volume of data information factors it obtains and its scale-cost effects will, in turn, promote the enterprise to expand on an even larger scale, ultimately leading the enterprise to move continuously toward a monopoly position. In this process, the platform enterprises in the market will gradually polarize; relatively disadvantaged enterprises will fall into a vicious cycle of "low service quality — decreasing customer base — decreasing data factor resources — even lower service quality," and will be forced to exit. This leads the market eventually and inevitably toward an oligopolistic structure. The reduction in the number of platform providers shrinks the choice set for platform users, forcing them to accept the platform's unreasonable demands, which further reinforces the platform's monopoly status.
The value appropriation system of non-productive platforms also endogenously produces multiple structural contradictions. Viewed from within the platform economy, in order to expand market power and preserve their monopoly status, non-productive platforms engage in massive disorderly competition with rivals, thereby disrupting the normal market resource allocation system and ultimately causing a massive waste of resources. A typical case was the customer-snatching war between Meituan and Ctrip. Regulatory authorities in Sanya once held talks with platforms like Meituan and Ctrip, pointing out that they disrupted market order and harmed consumer rights by using non-compliant vehicles to solicit customers at low prices and through false advertising. Such disorderly competition does not bring significant benefits to platform enterprises but leads to a waste of social resources. Viewed externally, this value appropriation system also inevitably increases the burden on other social production sectors. From the perspective of producers, the platform's appropriation of more surplus value forces production sectors to surrender a portion of their earnings as platform rent, which creates a greater cost burden for production sectors, squeezing their profit margins and making their operations more difficult. Meanwhile, the monopoly status of the platform places other enterprises at a disadvantage in cooperation negotiations with the platform, forcing them to accept more unreasonable terms—for example, procurement and sales contracts for Tmall Supermarket clearly assign more responsibilities and obligations to the suppliers. From the perspective of laborers, the burden caused by the platform’s excessive seizure of surplus value eventually falls on the workers. Meituan’s system algorithms once caused a massive public outcry: they compressed each rider’s (delivery driver’s) time to the extreme, forcing riders to risk their lives, health, and legal violations to complete delivery tasks. The existence of this appropriation mechanism severely damages the interests of ordinary laborers.
Furthermore, examined from a long-term perspective, as structural intermediary organizations in the sphere of circulation, the survival of non-productive platforms is highly dependent on the continuous expansion of the circuit of commodity capital. Currently, the platform economy is in its early stages of development; this emerging model has achieved market expansion by activating potential consumer demand, and this consumption increment has, in turn, fed back into the platforms, providing support for their maintenance and development. When the marginal propensity to consume decreases as the stock of demand is exhausted, the platform economy will also enter a period of maturity.
IV. Conclusion
At present, global trends and policy directions for the platform economy are shifting from encouraging platform enterprises to engage in "model innovation" in "non-productive" fields toward "technological innovation" in "productive" fields, so as to better serve the high-quality development of the real economy. Future healthy development requires finding a balance between encouraging innovation and standardizing regulation, guiding platform enterprises away from "barbaric growth" [16] that pursues traffic and scale, and toward high-quality development that pursues technological innovation, value creation, and social responsibility.
First, regulate the existing basis of data privatization and monopoly. The capitalized appropriation of data factors is an inevitable phenomenon brought about by the development of non-productive platforms, as well as a necessary condition for their expansion. However, if the current...
If the "digital enclosure movement" [17] is allowed to develop unchecked, it will inevitably lead to a series of problems such as market monopolies and disordered competition. Whether the scale and scope of the appropriation of data factors [18] can be restricted within reasonable limits is a critical proposition for guiding the development of the platform economy. On the one hand, it is necessary to re-establish and improve the attribute of users' raw data as a public information resource and realize the communication and sharing of information resources. This could include, for instance, mandating that leading platforms open non-core data interfaces to small and medium-sized enterprises to prevent single firms from leveraging data to establish monopoly positions. On the other hand, the definition of the data resources possessed by platforms must be strengthened to distinguish between a platform's core data assets and general information resources. While ensuring the returns on a firm's technological innovation are protected, the scope of exclusive data property rights must be strictly limited to prevent regulatory policies from weakening the vitality of market competition.
Second, a transparent platform disclosure system and regulatory matrix must be established and improved. From the perspective of profit acquisition, because non-productive platforms occupy vertical control over both the production and consumption ends as well as a horizontal dominant market position, they can utilize this monopoly status to levy composite rents [19] on other social production sectors that exceed reasonable limits. For example, many current platforms suffer from "black box" [20] commission structures and a lack of standards regarding commission ratios. This is, in effect, an excessive appropriation of the value created by other production sectors of society, which will ultimately suppress social production efficiency and reduce the people's sense of gain [21] and happiness. In response, legal and administrative means should be used to compel platforms to disclose the proportions of their commission structures—such as technical service costs versus ground-rent [22] returns—and to establish a sound and transparent public disclosure system for platform commissions. Simultaneously, a multi-stakeholder collaborative regulatory matrix should be built, integrating the triple forces of platform self-discipline, peer-industry checks and balances, and user supervision to form a process-wide monitoring system for rent extraction.
Finally, platform enterprises should be made to shoulder more social responsibility through secondary distribution [23]. From the perspective of social value distribution, secondary distribution should be used to correct distributive distortions caused by the excess value [24] already captured by platform capital. By establishing special adjustment funds, capital can be extracted proportionally from audited and confirmed rent-based returns to improve social insurance and labor protection systems for platform practitioners, thereby reducing the overall social loss caused by imbalances in value distribution.
Author Profiles: Lin Guangbin is a Professor at the School of Economics, Central University of Finance and Economics. Xiong Youcheng is a Master's student at the School of Economics, Central University of Finance and Economics.
Source: Teaching and Research (Jiaoxue yu Yanjiu), Issue 11, 2025. Editor: Hui Hui.