Digital Firm Lecture Summaries (1) PDF
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These lecture summaries cover the topic of network effects, analyzing information technology industries and the concept of "winner-take-all" in the context of long-distance telephony, software, microprocessors, telecommunications, e-commerce, and electronic marketplaces. The lecture notes discuss different types of network effects, and their economic consequences.
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Lecture 2: Winner takes all? Pipelines, Platforms, and Beyond. Sundarajan (2006): Network Effects When analyzing information technology industries, one often hears terms like winner-take-all, positive feedback and ‘tippy markets’. There is a general impression that success breeds more success, and...
Lecture 2: Winner takes all? Pipelines, Platforms, and Beyond. Sundarajan (2006): Network Effects When analyzing information technology industries, one often hears terms like winner-take-all, positive feedback and ‘tippy markets’. There is a general impression that success breeds more success, and that early success is critical. The most important underlying economic concept here is of network effects: where higher usage of certain products makes them more valuable. What are Network Effects? A product displays positive network effects when more usage of a product by any user increases the product’s value for other users (and sometimes all users). Furthermore, it is formally different from the more general concept than network externalities, however, much of the theory underlying network effects was developed to study network externalities, and the two terms are still used interchangeably. How Common are Network Effects? Network effects were first studied in the context of long-distance telephony in the early 1970s (Rohlfs, 1974). Today, they are widely recognized as a critical aspect of the industrial organization of IT industries, and are prevalent in a wide variety of sectors, including software, microprocessors, telecommunications, e-commerce, and electronic marketplaces. Furthermore, empirical evidence of network effects can be found in product categories such as: spreadsheets, databases, networking equipment and DVD players. Types of Network Effects: 1. Direct The simplest network effects are direct: increases in usage lead to direct increase in value. The original example of telephone service is a good illustration of a product that displays direct network effects. 2. Indirect When increase in usage of the product spawns production of increasingly valuable complementary goods, and this results in an increase in the value of the original product. E.g. For Windows, the indirect network effects arise from the increased quality and availability of complementary applications. 3. Two-sided Increases in usage by one set of users increases the value of a complementary product to another distinct set of users, and vice versa. E.g. Hardware/software platforms, reader/writer software pairs, and marketplaces/matching services display this kind of network effects. In many cases, one may think of indirect network effects as a version of two-sided network effects. eBay is an example, the more sellers in it, the more buyers would want to join. 4. Local The microstructure of an underlying network of connections influences how much network effects matter. For example, a good displays local network effects when rather than being influenced by an increase in size of a product’s user base, each consumer is influenced directly by the decisions of only a small subset of other consumers. E.g. People/ users are “connected” via an underlying social or business network (instant messaging is a great example of a product that displays local network effects). The extent of clustering in the network as well as the extent of information each customer possesses become relevant in this context. For instance, a neighbourhood social network like Nextdoor connects people within a specific neighborhood and as more people in the neighbourhood join the value of the network increases for everyone. 5. Compatibility and Standards For IT products to derive benefits of network effects from each other, they need to be compatible. This often poses strategic trade-offs for firms, between performance and backward-compatibility of evolving product lines, and between openness and control of core technologies. Moreover, ensuring the evolution of shared technology standards is critical in network industries, which can be difficult when competing technology firms each want their R&D to be well-represented. Economic Consequences of Network Effects When increases in usage cause an increase in value across all users, this creates a form of increasing returns, which changes the nature of competition substantially. Theories of competition in network industries emphasize the path dependence of outcomes and suggest that early leads are important. It highlights how intrinsically inferior products can dominate superior products, as influencing customer expectations plays a crucial role in ‘winning’ in a network market (e.g. the QWERTY Keyboard). These increasing returns often lead to an equilibrium in which a single firm or product dominates an industry segment. For example, Microsoft’s near-total control over the office productivity and US desktop operating systems market, and the substantial profits they are able to generate from these product lines. Feng Zhu & Iansiti, M. (2019). Why some platforms thrive…and others don’t: what Alibaba, Tencent, and Uber teach us about networks that flourish. The five characteristics that make the difference. The factors affecting the growth and sustainability of platform firms (and digital operating models generally) differ from those of traditional firms. Let's start with the fact that on many digital networks the cost of serving an additional user is negligible, which makes a business inherently easier to scale up. And because much of a network-based firm's operational complexity is outsourced to the service providers on the platform or handled by software, bottlenecks to value creation and growth usually are not tied to human or organizational factors - another important departure from traditional models. Ultimately, in a digital network business, the employees do not deliver the product or service - they just design and oversee an automated, algorithm-driven operation. Lasting competitive advantage hinges more on the interplay between the platform and the network it orchestrates and less on internal, firm-level factors. In other words, in the digitally connected economy, the long-term success of a product or service depends heavily on the health, defensibility, and dominance of the ecosystem in which it operates. The reason that some platforms thrive while others struggle really lies in their ability to manage five fundamental properties of networks: network effects, clustering, risk of disintermediation, vulnerability to multi-homing, and bridging to multiple networks. Strength of Network Effects The strength of network effects can vary dramatically and can shape both value creation and capture. When network effects are strong, the value provided by a platform continues to rise sharply with the number of participants. For example, as the number of users on Facebook increases, so does the amount and variety of interesting and relevant content. Video game consoles, however, exhibit only weak network effects, as we discovered in a research study. This is because video games are a hit-driven business, and a platform needs relatively few hits to be successful. Even more critically, the strength of network effects can change over time. Windows is a classic example. During the heyday of personal computers in the 1990s, most PC applications were 'client based', meaning they actually lived on the computers. Back then, the software's network effects were strong. However, as internet-based apps, which worked across different operating systems, took off, the network effects of Windows diminished and barriers to entry fell, allowing Android, Chrome, and iOS operating systems to gain strength on PCs and tablets. It is possible for firms to design features that strengthen network effects. Amazon, for example, has built multiple types of effects into its business model over the years. In the beginning, Amazon's review systems generated same-side effects. Later, Amazon's marketplace generated cross-side network effects, in which buyers and third-party sellers attracted each other. Meanwhile, Amazon's recommendation system, which suggests products on the basis of past purchase behavior, amplified the impact of the company's scale by continually learning about consumers' preferences. The more consumers used the site, the more accurate the recommendations Amazon could provide them. While not usually recognized as a network effect per se, learning effects operate a lot like same-side effects and can increase barriers to entry. Network Clustering The structure of a network influences a platform business's ability to sustain its scale. The more a network is fragmented into local clusters - and the more isolated those clusters are from one another - the more vulnerable a business is to challenges. It is possible to strengthen a network by building global clusters on top of local clusters. Some digital networks are fragmented into local clusters of users. In Uber's network, riders and drivers interact with network members outside their home cities only occasionally. But other digital networks are global; on Airbnb, visitors regularly connect with hosts around the world. Platforms on global networks are much less vulnerable to challenges, because it is difficult for new rivals to enter a market on a global scale. Risk of Disintermediation Disintermediation, wherein network members bypass a hub and connect directly, can be a big problem for any platform that captures value directly from matching or by facilitating transactions. Platforms have used various mechanisms to deter disintermediation, such as creating terms of service that prohibit users from conducting transactions off the platform and blocking users from exchanging contact information. Such strategies are not always effective, though. Anything that makes a platform more cumbersome to use can make it vulnerable to a competitor offering a streamlined experience. Some platforms try to avoid disintermediation by enhancing the value of conducting business on them. They may facilitate transactions by providing insurance, payment escrow, or communication tools; resolve disputes; or monitor activities. But those services become less valuable once trust develops among platform users - and the strategies can backfire as the need for the platform decreases. Vulnerability to Multi-Homing Multi-homing happens when users or service providers (network 'nodes') form ties with multiple platforms (or 'hubs') at the same time. This generally occurs when the cost of adopting an additional platform is low. When multi-homing is pervasive on each side of a platform, as it is in ride hailing, it becomes very difficult for a platform to generate a profit from its core business. Incumbent platform owners can reduce multi-homing by locking in one side of the market (or even both sides). Other approaches seem to work better. Let's look at the video game industry: console makers often sign exclusive contracts with game publishers. On the platform’s user side, the high prices of consoles and subscription services, such as Xbox Live and PlayStation Plus, reduce players’ incentive to multi-home. Lowering multi-homing on both sides of the market decreased competitive intensity and allowed the console makers to be profitable. Network Bridging In many situations, the best growth strategy for a platform may be to connect different networks to one another. In any platform business, success hinges on acquiring a high number of users and amassing data on their interactions. Such assets can almost invariably be valuable in multiple scenarios and markets. By leveraging them, firms that have succeeded in one industry vertical often diversify into different lines of business and improve their economics. This is a fundamental reason why Amazon and Alibaba have moved into so many markets. When platform owners connect with multiple networks, they can build important synergies. As the most successful platforms connect across more and more markets, they are becoming increasingly effective at tying together industries. Platforms are thus becoming crucial hubs in the global economy. When evaluating an opportunity involving a platform, entrepreneurs (and investors) should analyze the basic properties of the networks it will use and consider ways to strengthen network effects. It is also critical to evaluate the feasibility of minimizing multi-homing, building global network structures, and using network bridging to increase scale while mitigating the risk of disintermediation. That exercise will illuminate the key challenges of growing and sustaining the platform and help business people develop more realistic assessments of the platform's potential to capture value. Marco Iansiti, & Karim R Lakhani. (2017). Managing Our Hub Economy The global economy is coalescing around a few digital superpowers. We see unmistakable evidence that a winner-takes-all world is emerging in which a small number of 'hub firms'. Beyond dominating individual markets, hub firms create and control essential connections in the networks that pervade our economy. The more users who join these networks, the more attractive (and even necessary) it becomes for enterprises to offer their products and services through them. By driving, increasing returns to scale, and controlling crucial competitive bottlenecks, these digital superpowers can become even mightier, extract disproportionate value, and tip the global competitive balance. Hub firms do not compete in a traditional fashion - vying with existing products or services, perhaps with improved features or lower cost. Rather, they take the network-based assets that have already reached scale in one setting and then use them to enter another industry and 're-architect' its competitive structure - transforming it from product-driven to network-driven. If current trends continue, the hub economy will spread across more industries, further concentrating data, value, and power in the hands of a small number of firms employing a tiny fraction of the workforce. Thoughtful hub strategies will create effective ways to share economic value, manage collective risks, and sustain the networks and communities we all ultimately depend on. A real opportunity exists for hub firms to truly lead our economy. This will require hubs to fully consider the long-term societal impact of their decisions and to prioritize their ethical responsibilities to the large economic ecosystems that increasingly revolve around them. The Digital Domino Effect The emergence of economic hubs is rooted in three principles of digitization and network theory. The first is Moore's law, which states that computer processing power will double approximately every two years. The second principle involves connectivity. Most computing devices today have built-in network connectivity that allows them to communicate with one another. Modern digital technology enables the sharing of information at near-zero marginal cost, and digital networks are spreading rapidly. Metcalfe's law states that a network's value increases with the number of nodes (connection points) or users - the dynamic we think of as network effects. But while value is being created for everyone, value capture is getting more skewed and concentrated. This is because in networks, traffic begets more traffic, and as certain nodes become more heavily used, they attract additional attachments, which further increases their importance. This brings us to the third principle, a lesser-known dynamic: the notion that digital-network formation naturally leads to the emergence of positive feedback loops that create increasingly important, highly connected hubs. As digital networks carry more and more economic transactions, the economic power of network hubs, which connect consumers, firms, and even industries to one another, expands. Re-Architecting the Automotive Sector As with many other products and services, cars are now connected to digital networks, essentially becoming rolling information and transaction nodes. This connectivity is reshaping the structure of the automotive industry. When cars were merely products, car sales were the main prize. But a new source of value is emerging: the connection to consumers in transit. In a future where people are no longer behind the wheel, cars will become less about the driving experience and more about the apps and services offered by automobiles as they ferry passengers around. Apart from a minority of cars actually driven for fun, differentiation will lessen, and the vehicle itself might as well become commoditized. That will threaten manufacturers' core business: the car features that buyers will care most about - software and networks - will be largely outside the automakers' control, and their price premiums will go down. The transformation will also upend a range of connected sectors - including insurance, automotive repairs and maintenance, road construction, law enforcement, and infrastructure - as the digital dominos continue to fall. Increasing Return to Scale are Hard to Beat Competitive advantage in many industries is moderated by decreasing returns to scale. In traditional product and service businesses, the value creation curve typically flattens out as the number of consumers increases, as we see in the exhibit "Profiting from a Growing Customer Base". A firm gains no particular advantage as its user base continues to increase beyond already efficient levels, which enables multiple competitors to coexist. Some digital technologies, however, exhibit increasing returns to scale. A local advertising platform gets better and better as more and more users attract more and more ads. And as the number of ads increases, so does the ability to target the ads to the users, making individual ads more valuable. These considerations are important to the nature of hub competition. The economics of traditional decreasing returns make it possible for several competitors to coexist and provide differentiated value to attract users. In contrast with traditional product and service businesses, network-based markets exhibiting increasing returns to scale will, over time, tip toward a narrow set of players. With increasing returns to scale, a digital technology can provide a bottleneck to an entire industrial sector. Pushing Back With enough foresight and investment, traditional firms can resist by becoming hubs themselves, as we are seeing especially in the Internet of Things (loT) space. Firms can also shape competition by investing to ensure that there are multiple hubs in each sector - and even influencing which one's win. They can organize to support less-established platforms, thus making a particular hub more viable and an industry sector. more competitive in the long term. Most importantly, the value generated by networks will change as firms compete, innovate, and respond to community and regulatory pressure. Multihoming - a practice enabling participants on one hub's ecosystem to easily join another - can significantly mitigate the rise of hub power. Open source has grown beyond all expectations to create an increasingly essential legacy of common intellectual property, capabilities, and methodologies. Now, collective action is going well beyond code sharing to include coordination on data aggregation, the use of common infrastructure, and the standardization of practices to further equilibrate the power of hubs. The public is also raising concerns about privacy, online tracking, cybersecurity, and data aggregation. The Ethics of Network Leadership The responsibility for sustaining our (digital) economy rests partly with the same leaders who are poised to control it. By developing such central positions of power and influence, hub firms have become de facto stewards of the long-term health of our economy. Building and maintaining a healthy ecosystem is in the best interests of hub companies. If hubs do not promote the health and sustainability of the many firms and individuals in their networks, other forces will undoubtedly step in. Governments and regulators will increasingly act to encourage competition, protect consumer welfare, and foster economic stability. Ozalp, H., P., Dinckol, D., Zachariadis, M., &Gawer, A. (2022). “Digital Colonization” of Highly Regulated Industries: An Analysis of Big Tech Platforms’ Entry into Health Care and Education. Digital platforms have disrupted many sectors, including retail, entertainment, hospitality, transportation, gaming, and music, but have not yet visibly transformed highly regulated industries. Platform firms are dominating the markets and are often referred to as "Big Tech" players. This paper describes a four-stage process model of platform entry, termed as "digital colonization". This involves provision of data infrastructure services to regulated incumbents; data capture in the highly regulated industry; provision of data-driven insights; and design and commercialization of new products and services. The Platform Business Model and the Role of Data A platform creates value in connecting different users through enhanced matchmaking and facilitating transactions among them. It can achieve rapid growth through highly scalable technological intermediation and reduction of various costs for transacting, matching and innovating. Growth is further increased by data network effects, which refers to increasing value users obtain from the platform in parallel with the amount of data the platform accumulates (e.g, better recommendations on Netflix). Due to their digital nature, platforms can connect various platform sides via digital interfaces, and, in the process, accumulate external resources (i.e., data) develop relevant capabilities (i.e., algorithm-driven data analysis) to improve and expand offering. Big Tech firms started out as platforms with a single and focused intermediation activity, and then grew significantly in scope and entered new markets. First, they expanded to markets of their own complementary competitors with their platform ecosystems. After this they have entered related or other sectors (e.g., Facebook acquisition of Instagram) or what may at first seem to be unrelated markets (e.g., Google acquisition of Waymo). The main aims of platforms’ entries to the various market segments are: Maximize data collection. Enhance data network effects that they have already built across industries to create more value. Apply their data analysis capabilities. Take precedence over existing firms while improving products for consumers. This approach to platform growth and industry entry raises problems and questions on: Fair Competition Data Privacy Balance of value creation and value capture These issues became even more critical in highly regulated industries where value creation becomes extremely salient and concerns about data privacy and fair competition are even more important. Platforms in Highly Regulated Industries Even though digital platforms became dominant in many industries, that isn't the case in highly regulated sectors such as energy, finance, education, and healthcare due to high regulatory control creating barriers to entry for platforms. Highly regulated industries typically have high entry barriers and high operational and compliance costs. These industries are characterized by the heavy involvement of state and government actors, mainly because these industries play crucial strategic role in ensuring social welfare and boosting the economic growth and development, and also because of the associated social ramifications in terms of access, privacy and data sensitivity, as these factors are tied directly to human and constitutional rights. Those interested in entering the digital platform business need data to develop their own products and services. This calls for different strategies in highly regulated industries due to the need to capture and process sensitive personal data. Whenever this type of data is leaked or misused, it can result in harm for individuals-for example, biometric information, genetic information, health-related data, race, ethnicity, religious beliefs (typically expressed in educational contexts and recorded in essays, online educational platform discussions, and so on), and student education records. However, this started to change, as Big Tech firms have been expanding into some of these highly regulated industries. This was accelerated by COVID-19 pandemic as firms like Google, Apple, and Amazon started offering services and systems for contact tracing, remote education, and solutions for hospitals and research institutes. This paper focuses on healthcare and education industries, and identifies an four-phase entry pattern for these digital platforms, named 'digital colonization': 1. Provision of data infrastructure services to incumbents - as incumbent service providers such as hospitals and schools typically lack capabilities in data management, they contract out Big Tech firms to reduce costs and improve services. 2. Direct and Indirect data capture in industry - Big Techs leverage their existing relationships as well as their data analysis capabilities to get access to the data already held by incumbent service providers. 3. Provision of data-driven insights - as Big Tech firms combine the data they captured directly and indirectly they can provide superior data-driven insights which can add significant value to incumbent service providers. 4. Design and commercialization of new products and services - In this phase digital platforms may end up competing with their former clients over time. While Big Tech firms rarely end up directly offering the "primary service" (e.g., providing school education) in highly regulated industries, they change the power dynamics in these industries over time by commoditizing incumbent service providers, turning them into mere complementary competitors while Big Tech firms control the data and become unique providers of critical, data-driven value. Big Tech in Healthcare After the research was done on the Big Techs, several findings on Google, Microsoft, and other Big techs were described. Over the 2008-2020 period, Google's role evolved from that of peripheral IT service provider to healthcare incumbents to that of an increasingly present and central actor in the industry. This led to Google becoming an essential partner to infrastructural projects, dominating the industry for diagnostics, electronic health records, and development of new treatments in healthcare. Compared to Google, Microsoft had a limited approach to collaboration with healthcare organizations rather than starting new ventures. Apple, on the other hand, has more limited data analysis capabilities than Google, and it has more focus on functionalities directly supported by Apple hardware The entry activities of Big Techs into UK healthcare industry are shown in the graphs below. Big Tech in Education This research showed that Google has a broad influence and reach in education. Google has entered the education industry as an IT and hardware provider and then moved into more central roles such as content provider and potential educator, preparing for a "skills" based future in which degree institutions are not the only primary service providers in the industry. Microsoft has more diverse activities in education than other Big Techs, as it offers more industry-specific services in education than other platforms, building on its role as an operating system, infrastructure, and technology provider. Apple was a first mover in disrupting education. Starting with providing hardware and software, and moving to offering courses in coding and software programming. Despite the early entry, Apple lost its market position to Google. The entry activities of Big Techs in U.S. education is shown in figure on the next page: Synthesis of Findings Figure below shows a process model of Big Tech entry into highly regulated industries: A clear pattern that emerges from our research is that Big Tech firms haven’t so far been involved in offering primary services (e.g., providing healthcare, banking, or schooling). Rather, they have focused on capturing data as a way to other value-adding activities. Capturing data from the highly regulated industry, combining it with data from various other industries, and analyzing it through co-specialized Al technologies give Big Tech firms a competitive advantage in the newly entered highly regulated industry. It allows them to generate data-driven insights and to design and commercialize new products and services for the industry, generating value above and beyond what incumbents can offer. Big Tech Firms’ Data-Driven Competitive Advantage over Incumbents Beyond capturing data both directly and indirectly, Big Tech firms engage in two types of activities that add and capture value in highly regulated industries: 1. Data-Driven Insights - insights that rely on the data analysis capabilities of the platforms leveraging Al/ML, and are the 'powerhouse' driving Big Tech entry into highly regulated industries. Al-based diagnostics, which is early diagnosis of diseases or responses to treatment, is particularly noteworthy, as it can cut costs and improve results for healthcare and educational service providers. These data-driven insights show many benefits for these platforms: Initiating or advancing indirect data capture by offering these insights to primary service providers - entering a positive feedback loop. Designing and commercializing new products and services that are superior to incumbents’ alternatives. Utilizing the insights in their existing platforms - strengthening their dominant position. 2. New Products and Services - Once they collect data, Big Tech firms also start to add value to the value chain in healthcare and education by leveraging their data-driven insights to participate in the innovation process for new products and services that complement primary services. They can cut costs, speed up the R&D process and target lucrative areas where their own ventures can develop more tailored products and services. These new products and services that are based on cloud and/or Al capabilities contribute to a change in the core products or services in the industry, moving Big Tech platforms toward the core of value creation in the industry. The value that is captured by Big Tech firms in new product and service design is threefold: In the case of a partnership with another party (e.g., pharma), value capture focuses on charging for providing data for R&D purposes and/or capturing the newly created data in the partnership for fueling Al inside and outside the industry. Various kinds of new data (e.g., from transaction or hardware) are captured and can be monetized through data analysis inside and outside the industry. In the case of a direct investment into a new venture, the platform receives direct profits from sales of the products and services. Overall, in highly regulated industries where access to primary service data (e.g., individual-level clinical data or educational records) is a bottleneck due to the sensitivity of this data, those firms that overcome this bottleneck, generally through indirect data capture combined with data-driven insights, gain a unique competitive advantage in the design of new products and services where incumbents (e.g., medical device manufacturers, textbook publishers) have historically operated without such data capture or analysis capabilities. This allows Big Tech firms to "digitally colonize" a highly regulated industry without providing the primary services (e.g., education, healthcare) that are highly unprofitable by providing unique added value through data-driven products and services that other industry players increasingly rely on, which in turn commoditizes these players over time. Contributions to Theory and Practice A critical point to consider in the digital colonization of highly regulated industries is the balance between the increase in value creation, which will serve the whole industry, and the rise in value capture by Big Tech firms. This study illustrates the two opposing forces quite vividly: Big Tech firms that can add more value to existing products and services through better data capture, data analysis (and therefore data-driven insights), and data infrastructure services are more likely to get access to data collected by incumbents. Big Tech firms, once they get access to data, can develop a unique competitive advantage over incumbents and become increasingly powerful within the highly regulated industry as well as in other industries (e.g., advertising, retail) where the obtained data can be leveraged. Managerial Implications Platform managers need to negotiate access to primary service data, and they also need to make efforts to capture novel data through proprietary hardware and software user interfaces. In this context, platform firms may find that subsidizing hardware and access to services can work effectively to "buy their way" into data access. After this initial stage, they can focus on capturing value through a variety of data-related industry activities, such as selling data-driven insights or designing new products and services. This study also holds managerial implications for incumbent firms who need to respond to Big Tech firms' uniquely powerful form of competition: It shows that entry of established platforms is not impossible but takes a different form in highly regulated industries. It clarifies the possible pathways of entry and explains how these depend on Big Tech firms' data-related capabilities. It suggests that incumbent firm managers need to formulate their own data capture and analysis strategies and decide quickly whether they will compete or partner with entering platforms. The findings also provide implications for new, non-platform entrants into highly regulated industries: They highlight the role of data access in gaining competitive advantage in the newly entered industry. For many new entrants (e.g., biotech or education startups), partnerships with large incumbents and/or Big Tech platforms will be essential in gaining this access. Findings indicate that the locus of competition shifting toward data-driven products and services in these industries will mean a change in entrepreneurial activity in these industries, most likely organized within ecosystems around Big Tech platforms. Understanding this new competitive landscape will be important for the entrepreneurs of tomorrow to develop their growth strategies. Finally, understanding platform entry patterns into regulated markets is crucial for policymakers and regulators, who want to make sure that digital markets remain competitive while protecting the privacy of consumers. Conclusion This paper expands the traditional focus of platform research beyond low-regulation industries such as retail or entertainment to highly regulated industries, enhancing our understanding of firm strategy and platform growth. Several actors in highly regulated industries express a desperate need for insight and the efficiencies offered by data analytics. But the logic of efficiency brought about by digital platform firms can clash with the logic of public service and the necessity of protecting user data and privacy as a fundamental right. It will become increasingly important to find ways to combine the benefits of digital platforms with respect for personal data in the future. Rahman, K. S., & Thelen, K. (2019). The rise of the platform business model and the transformation of twenty-first-century capitalism. Introduction This article emphasizes the political forces that have driven the transformation of the 20th century consolidated firm through the firm as a "network of contracts" and toward the platform firm. The traditional (industrial) model of a firm broke down in the late 20th century. This old model has been described as a "nexus of reciprocal relationships" between the firm and its internal and external stakeholders. This model supported large workforces on permanent employment contracts and concentrated power in the hands of managers whose goal was stable long-term growth. The shareholder revolution shifted power from consolidated firms and powerful managers to investors and securities analysts, transforming the classic mid-century firm into a "network of contracts" (NOC). In the world of shareholder value, stock price was the core metric of success, and share value rested heavily on hitting profit projections. Firms engaged in aggressive outsourcing, asset stripping, and labor-reducing strategies because of the intense investors' pressure to focus on "core competencies". The new vanguard firms of the 21 century represent a new type of platform-based business model that builds on the developments of the 1980s and 1990s but combines them with new features. Whereas the previous NOC model centered largely on "price-based competition among producers of relatively similar products", today's platform firms represent a new way to create and capture value. They do so, above all, through their capacity to extract and harness immense amounts of data in ways that allow them to operate as critical intermediaries and market makers. Some of these platforms now exercise a level of market dominance that inspires comparison to classic monopolies of the 19th and 20th centuries. But what is distinctive about them is the way they achieve market dominance: the goal for these firms is not so much direct ownership as control. Indeed, compared to the monopolists of yesteryear, today's platform firms in many ways exercise deeper control because of the way the platform's data and algorithms "structure the rules and parameters of action" that are available to participants on the platform. In short, today's platform firms combine features of previous models with new elements. Moreover, and most important for purpose of this paper, their distinctive features rest on three political-economic enabling factors that set them apart from previous models: Platform firms have benefited from a more "patient" form of capital. The most dynamic new platform firms are backed by a different type of investor with different motives. Network effects are the essential and crucial factor that drive the platform firm. The central goal is to secure a level of market dominance and concentration that will ultimately vindicate investor patience. Once achieved, this "winner takes all" market dominance offers many avenues for generating returns. This networked dominance is what makes platform firms both a revival and a reinvention of classical monopoly concerns. Platform firms enjoy a much more direct and unmediated link to their users, most of whom connect to these firms through devices they carry in their pockets every day. Beyond Financialization and Fissurization Whereas the mid-century firm was characterized by authority concentrated in the top executives and ownership dispersed among a large number of passive investors, the "shareholder revolution" starting in the 1970s and accelerating in the 1980s led to the dominance of investor interests in corporate governance. Those changes were seen as a way to promote efficiency and growth by disciplining firms to investor demands. In practice, the result was that organized and moneyed investor groups exerted intense and coordinated pressure on managers, which punished public firms for engaging in longer term investments at the expense of short-term returns. CEO pay also boomed during that period, as managers increasingly operated in coalition with investor interests. Those pressures resulted in a radically different organizational structure: a shift from large capital-intensive facilities to a model of aggressive outsourcing, franchising, and streamlining. Weil calls this "fissuring" (also called "Nikefication") of the workplace. That organizational form crucially signaled a retreat from "standard employment" — full-time, open-ended employment contracts attached to a package of benefits-as peripheral support functions from janitorial services to back-end functions were outsourced, and precarious forms of work with fewer (if any) benefits increased. The fissuring of the workplace has dramatically altered the corporate landscape. Widespread fissurization has broken up what had been robust internal labor markets in large firms, which allowed for upward mobility with a range of different income levels and jobs within the firm. From a model of strong managers, backed by passive investors, in coalition with labor, to a model of powerful investors, deputizing managers to extract returns primarily through an attack on wages, benefits, and labor costs. Platformization as Re Centralization and Consolidation The shift to the platform firm is made possible by new technologies. As Weil pointed out, the fissuring of the firm was enabled by technologies that lowered the cost of monitoring outsourced or franchised operations. Technology thus allowed lead firms to get the "best of both worlds" - slashing labor costs and escaping regulatory oversight while at the same time exercising enormous control throughout their networks of outsourced, franchised, or contracted labor, production, and manufacture. Investors are still important, but the financial interests behind the new platform firms represent a different type of investor. This change marks a first distinctive feature of the platform firm. The types of institutional investors behind today's most dynamic firms are not in the business of demanding positive quarterly profit reports; they are instead committed to the longer-term project of consolidating market domination. Promising platforms can now draw financing from a variety of sources: venture capital, private equity firms, and even international sovereign wealth funds now often play a critical role in financing promising platforms to scale up. Such sources of investment share similarities with long-term patient capital. Moreover, as platform firms become more dominant, they become stable, reliable investments for other sources of capital such as pension funds. The most successful platform firms today: Have been able to consolidate and concentrate power in ways that signal durability, not fragility. Demonstrate enormous capacity to anticipate and absorb potential competitors, sometimes to extend their own reach and sometimes just to quash a potential threat. The power of platform firms is thus not just anchored in the investors behind them; it derives as well from the way network effects allow the firms to secure concentrated "infrastructural power" that enables other forms of rent and revenue generation. In contrast to the classic model of the vertically or horizontally integrated monopolistic firm that achieves and maintains its power through mechanisms of ownership or acquisition, the platform firms - although often built through mergers and acquisitions as well - exercise market power by controlling other participants on either side of the platform. Exercising enormous control both upstream and downstream, these firms enjoy tremendous power over producers, workers, and other partners who all depend on the platform for access to consumer dollars. Another distinguishing feature of platform firms is their relationship to consumers. The concentration of power in platform firms is often rationalized and defended under the banner of serving consumer interests. This alliance with consumers - whether explicit or tacit - further distinguishes today's platforms from other types of monopolies, past and present. Like other monopolies, the efficiency gains of today's platforms are a function of their scale and scope. But unlike past monopolies, consumers often do not experience the power of the platform as an unwelcome constraint. The Changing Politics of the Firm The new platform model rests on a novel political coalition. Two broad models can be identified regarding coalition alignments among owners, managers, and workers: A diffuse shareholder model, often underpinned by a coalition of owners and managers, A concentrated block-holder model supported by managers and labor. Although a full analysis lies well beyond the bounds of this article, the authors of the article begin to draw out the political dynamics, at least for the platform business model, by contrasting developments in the US to other more coordinated market economies in Europe. Their contention here is that platform firms rest on a new investor-consumer alliance, one brokered by powerful managers and representing a fusion of the financial powers of their investors and the political clout of their carefully cultivated user base. The combination is distinctive in being simultaneously patient and hostile to labor: both investors and consumers are served by reducing labor costs to lower prices and to slim down the firm. It is important that both are also served by the platform firms' focus on achieving market dominance, which secures winner-takes-all returns for investors while maximizing consumer ease and welfare, although often at the direct expense of labor. The combination of investor and consumer interests around a business model that seeks market dominance and cuts labor out of the modern social contract is politically and rhetorically powerful. It allows platform firms to portray themselves as defending consumers against "stifling" regulation in the interest of efficiency, innovation, and consumer choice. Facilitating the Rise of Platform Capitalism: The US Comparative Perspective The pioneering role played by US firms in the advance of the platform firm is often attributed to an entrepreneurial culture or the innovation-promoting features of a liberal market economy. Platform firms in the US clearly benefited from the technological lead resulting from US military spending on R&D. It is hard to imagine the emergence of this new corporate form without considering the role played by the US government in the development of the core technologies on which these firms are built. Moreover, other features of US political economy also tend to support "radical" innovation over the more incremental technological change characteristic of Europe's coordinated market economies. Beyond the initial innovations, however, those technologies had to be adapted and brought to broad markets, and for that task, different factors come into play. Three structural features of the political landscape in the US that have provided an especially congenial context for platform firms are specified: The fragmentation of state regulatory capacity and the weakness of countervailing pressures, particularly from organized labor and rival business interests, provide the permissive context that "disruptive" market players require to gain a foothold. Features of the American legal regime, particularly the prevailing pro-consumer orientation of antitrust law, actively promote the new platform model and sustain the political coalition on which it rests. The heavily financialized tilt of the American political economy and the availability of plentiful sources of patient capital - underemphasized in mainstream literature on comparative political economy - provide the resources that have fueled the growth of the new platform business model. A Permissive Political-Economic Landscape A core challenge posed by the rise of new corporate forms is that many of the strategies that they pursue are not well covered by a regulatory apparatus inherited from the industrial era. Indeed, today's most dynamic platforms often grew precisely by moving aggressively into legal gray zones - pushing the bounds of existing rules and creating wholly new markets beyond the reach of existing policies. These gray zones arise not only from the strategic exploitation at the edges of labor, financial, and other economic regulations but also from new technologies not yet regulated by government agencies. The US is not uniquely open to such strategies, but the country's distinctive political-economic landscape provides uncommonly fertile terrain for platform firms: The highly fragmented nature of the regulatory infrastructure inhibits a swift and coordinated response to the power-concentrating effects of the new corporate forms. ○ The strategic capacity of today's mega-companies dwarfs that of fragmented US jurisdictions and creates a power mismatch. ○ Variation in regulations at the state and even the municipal level provokes a deregulatory race to the bottom as firms pursue changes in their favor. The vertical fragmentation of authority in the American political system is mirrored horizontally within the federal government. ○ Wide gaps exist between the jurisdictions, energies, and attentions of the several regulatory agencies that oversee the economy. ○ In the less professionalized American bureaucracy, agency personnel often share a cultural and social background with business leaders that makes them more favorable to business interests. ○ Weak (and in some cases openly permissive) securities enforcement by financial regulators is well documented and played a role in the financialization of the modern economy. The US political economy offers few societal backstops to the advance of powerful new concentrations of economic power. Although European political economies are not immune to such strategies, they tend to be less congenial to them. In European countries, organized labor has also been more successful in pioneering new forms of platform agreements to establish minimum pay and benefits or (where they cannot negotiate directly) to provide services that help freelancers gain access to prevailing pay and benefits. More generally, strong unions (and associated higher wages and more generous social benefits) mean that platform firms compete for workers in a very different labor-market environment, one in which it is more difficult to recruit labor to work under sub contractual conditions. The trend in the US is, if anything, in the opposite direction. The playing field is tilted decisively toward employers: lawyers are reluctant to take on small suits that promise small payouts, and workers reasonably hesitate to bring complaints with prospects so heavily outweighed by the potential costs, including retaliation. But organized labor is not the only possible societal backstop and source of countervailing pressure. In Europe, disruptive market entrants with winner-take-all ambitions are also more likely to encounter strong headwinds from organized business interests. In Europe's coordinated market economies, strong and well-organized trade groups and employer associations are often among the keenest to inhibit the advance of would-be monopolists, particularly those perceived to achieve competitive advantage via illegitimate (or illegal) market strategies. In sum, structural features of the American political-economic landscape constitute an unusually permissive political context, with ample openings for aggressive, highly resourced firms to engage in the types of regulatory entrepreneurship. To many of today's mega-companies, "move fast and break things" means exploiting legal gray areas aggressively and in some cases flagrantly breaking the law as a matter of course. Firms backed by investors with deep pockets can often outlast their opponents - for example by tying up labor advocates in protracted and expensive court battles. They can buy the time to entrench themselves in the market and then mobilize and weaponize their user base to pressure politicians to sanction their actions after the fact. By the time regulators and judges have caught up, these companies present themselves as too important, too popular, and too big to be undone. A Supportive Legal Regime Beyond the political-economic landscape of organized interest groups, central features of the American legal regime - in particular the pro-consumer orientation of antitrust theory and practice - make the US singularly fertile terrain in which platform capitalism can thrive. The "Chicago school" of law and economics was the center of gravity of the movement, which began in the late 1960s as part of a broader pushback against what was seen as excessive government intervention in the area of antitrust. Robert Bork argued that firm size and concentrated industry structures are often reflections of efficiency gains and thus serve consumer interests. Over the next decade, Bork's views worked their way into the courts and antitrust bureaucracy before they were formally embraced in the new merger guidelines issued by the Reagan administration in 1982. Since that time, consumer welfare has represented the primary metric on which American anti-trust enforcement depends. Europe has so far declined to embrace the US' consequentialist approach to antitrust fully; it continues instead to view market concentration per se as a threat to competition and efficiency. The European Union, which has a more overtly deregulatory bias than many of the member states, has generally been more open to the US approach. The Commission's Directorate-General for Competition in fact specifically advocated moving in that direction. However, those initiatives have typically been watered down in the face of fierce resistance from legal intellectuals and antitrust professionals. In a sustained analysis of the evolution of competition law in the US and the European Union, there is a continued divergence between the two jurisdictions when it comes to antitrust. Although EU competition law embraces the same goals of the American antitrust regime, there are continued "substantial differences in practice". The influence of the Chicago school is emphasized and "the approach that now dominates the academy and the courts [in the US] is utterly different from that prevailing prior to 1974". It is in the years since then that a "huge gap" has opened up between EU and US jurisprudence. Gifford and Kudrie acknowledge more recent pressures for convergence and even some signs of movement in European antitrust practice, but they insist that the process is slow and halting. They note that European countries tend to give more weight to social justice concerns than to the efficiency concerns that figure so prominently in the US. All these differences are reflected in contrasting approaches to competition law, despite similarities in the texts. EU law, for example, is especially attentive to the possibility that dominant firms may abuse their market power, and "abuse of a dominant position" is more likely to be met with official intervention in Europe than in the US. In sum, and in contrast to Europe, US antitrust law not only supports but explicitly reinforces and entrenches the pervasive ideology of consumerism in the US. Companies such as Amazon and Uber know how to take full advantage; they never cease to emphasize the benefits offered to consumers in the form of better service and, at least for Amazon, lower prices. The appeal to consumers does more than insulate these firms against potential antitrust enforcement; it also creates a broader sense of social legitimacy and even active political support for these companies against government regulation. A Financial Business Sector Finally, the business strategies of platform firms depend heavily on a particular type of investor, one willing to underwrite massive losses in the short and medium term in pursuit of winner-take-all gains. Finance is a critical ingredient, and the US political economy is again particularly well suited to provide it. By almost any measure, the level of financialization is far higher in the US than in Europe. The financialization of the American political economy profoundly altered the business landscape and culture. Europe's coordinated market economies, by contrast, generally continue to exhibit a stronger continued commitment to industry. Although Europe was not immune to the shareholder value revolution, stronger traditions of family ownership, more robust unions, and more resilient social partnerships have also kept many companies more committed than their American counterparts to the traditional long-term time horizons characteristic of the mid-century firm. The strategic relationship between managers and investors is not new to platform capitalism, but it takes a distinctive form. Long having played a pivotal role in assembling funds to finance promising new startups, Venture Capitalist (VC) firms were the major seed investors in many tech giants. Some VC firms actively participate in cultivating a new startup's business model, suggesting personnel or business plan modifications. Alongside funding from individual "angel investors", VC funding carries with it a mark of prestige in Silicon Valley, with VC firms playing "king-maker" among competing tech startups. Although VC and angel investors certainly demand high returns, they can also operate as patient forms of capital, shielding firms from short-term market imperatives and allowing them to focus on long-term value creation rather than short-term profits. The model of the patient investor seeking the rare, extremely high-return investment leads to unusual business strategies that arise from the joint interests of VC investors and startup leaders. The explosive success of aggressive winner-takes-all strategies has had a broader transformative effect. Among other things, this new business model has inspired a search for additional new arrangements that can accommodate longer time horizons. One such arrangement is the idea of a long-term stock exchange (LTSE). The core concept is to "create an exchange that is focused on the needs of companies with a long-term vision and investors who are similarly aligned". Venture capitalism has evolved beyond incubation funding into the kind of large and stable source of patient capital that has been so important in underwriting the platform business model. At the same time, there has been a shift in the mode of financing. Not "core competencies" but network effects, potential for market dominance, and explosive and perpetual returns now justify a much longer time horizon of patience from investors and forge a strategic unity between investors and firm managers in pursuing winner-takes-all strategies - and in absorbing the legal costs of regulatory arbitrage or boundary pushing along the way. Countervailing Power, Regulation, and Restraint on the Platform Firm The rise of the platform firm thus owes much to the political power and influence of business and financial interests in evoking the support of consumerist ideals and exploiting the weaknesses of the American political landscape. This new model built on several important changes that earlier gave rise to the NOC firm; It accelerated some - such as the continued assault on organized labor - and shifted others - such as the move from impatient to patient investor influence. The article suggests that, from a political economy perspective, responses to the inequalities and instabilities created by the shift to the platform model of the firm must address the institutional and political features that created such imbalances of power and influence in the first place. More vigorous enforcement of existing labor laws would bolster worker protections, but current developments clearly call for further changes, such as closing the loophole of employee misclassification by updating definitions of "employee" and "independent contractor".However, even those reforms would not address the underlying structural power disparity between employers and workers, particularly as employers would still retain the flexibility to define occupations strategically to exploit legal gaps and boundaries. More meaningful and durable change would thus require major reform of labor laws to make organizing workers more effective in the context of a fissured and platformized economy. Given the transformations of the modern workplace, as several organizers and labor lawyers have suggested, a more radical reimagining of worker power is necessary. In practice, the proliferation of new models of labor activism represents attempts to overcome the problems we have identified. Worker centers, for example, organize workers not around any particular employer or workplace but rather as members of a shared minority group, or residents of a local community, or employed across a broadly similar industry, such as restaurant workers, domestic workers, or guest workers. More effective modes of worker organizing that build on these innovations, however, require far-reaching structural legal change. Furthermore, labor law would need to shift its focus from workplace-based organizing centered on the immediate demands of a particular group toward sector-based organizing with social demands that extend well beyond wages and worker standards. The labor-empowering measures are essential to overcome the challenges posed by both the NOC firm of the fissured workplace and the platform firm, as both models rest on a shift in power from workers to firms and investors. Indeed, one of the most important ways to counter the problematic trends we have identified is to create new forms of 21st century worker power capable of advocating in opposition to modern business and finance lobbies. Thus a revamped labor movement would need to pay attention not only to labor law and worker rights but to the full range of legal regimes that structure corporate power. The unique characteristics of platform business models may necessitate further alternative strategies. Countervailing power in a platform economy must become more adept at advocating for changes in the securities laws that facilitate patient but unaccountable venture capital financing, for example. Lax antitrust enforcement has enabled both monopsony power in local labor markets and the predatory pricing schemes central to such firms as Amazon or Uber. Greater antitrust enforcement could, for example, limit the platform firms' ability to achieve market dominance, while closer regulation of platform firms could ensure that they treat all businesses and counterparts fairly. Financial regulation, similarly, might address some patterns of investor power and spur more investment in startups and "real economy" firms. Conclusion There is an extensive literature on the political power of the modern corporation and on the influence exercised by business interests within the formal political process. There is also long-standing concern about the decline of labor and the rise of corporate power in the modern economy. This article adds to these discussions by highlighting how the nature of the modern firm itself has changed in critical ways over the past few decades and by illuminating the broader legal and organizational conditions that have facilitated that change. The ideal type of the 20th century consolidated firm as a large employer well regulated by government and in dialogue with organized labor has given way first to the fissured (or Nikefied) firm that operates as a nexus of contracts, through extensive networks of franchising, outsourcing, and labor-cost shedding. The rise of the NOC firm has facilitated the emergence of a new vanguard firm: the 215t century ideal type of the platform firm. In the platform model, the lead firm or brand is slimmed even further, offloading much of its labor force to contracted out partners, legally distinct entities that can provide labor more cheaply and flexibly. The platform firm is also marked by concentrated ownership and influence among investors, increasingly operating in alliance with consumers. The rise of the platform firm thus represents a new development in: The changing nature of work The growth of inequality The eroding social contract This transformation is not simply a product of natural or technological change; rather it is crucially tied to the political-economic landscape, particularly in the US. The rise of the platform firm, in part through interaction with the political-institutional structure and the landscape of regulatory policy, introduces a further mechanism through which political and economic inequality interact. This diagnosis of the nature and origins of the platform firm suggests that responding to 21st century inequality will require - beyond redistributive tax and wage policies - a change in political-economic dynamics that can address the concentrations of power and shifts of influence the platform firm represents. The Network Effects Bible (2024). Part 1. Why Network Effects are Important Network effects occur when each new user increases the value of a product or service for others. They are crucial for creating defensibility and driving value in the digital economy, surpassing other defenses like brand, embedding, and scale. Many successful tech companies have leveraged network effects to dominate their markets. There are 16 different identified kinds of network effects. Listed in order based on their strength: Physical (landline telephones) Protocol (Ethernet) Personal utility (iMessage, Whatsapp) Personal (Facebook) Market Network (Honeybook, AngelList) Marketplace (eBay, Craigslist) Platform (Windows, iOS, Android) Asymptotic Marketplace (Uber, Lyft) Data (Waze, Yelp!) Tech Performance (Bittorrent, Skype) Language (Google, Xerox) Belief (currencies, religions) Bandwagon (Slack, Apple) Expertise (Figma, Microsoft Excel) Tribal (Apple, Harvard, NY Yankees…) Hub-and-Spoke (Tiktok, Medium, Craigslist) Part 2. How Networks Work Networks are present in nearly every complex system. Although there are many types of networks, they share some characteristics. Nodes and Links Nodes are the participants in a network (e.g., consumers, devices, or sellers), and each node can have varying levels of influence and value. Central nodes have more value, while marginal nodes have fewer connections. Links are connections between nodes. The strength of a link depends on factors like durability and activity. Network size can be measured by the total number of nodes in a network, however, this does not determine the value, for which the amount of activity needs to be accounted for. Network Density The density of a network is the ratio of links to nodes. Higher density networks often have stronger network effects, as links reinforce connections. It's beneficial to focus on the densest parts of a network to encourage growth. The "white-hot center" of a network refers to the most active and densely connected group within that network. To harness this powerful aspect, the strategy involves focusing on this group by tailoring product features and messaging to activate other users to emulate their behaviors. Directionality Links can be directed (unidirectional) or undirected (bidirectional). Directed links are seen in platforms like Twitter, where central nodes (celebrities) broadcast to many followers, while undirected links are seen in platforms like Facebook Messenger, where interactions are mutual. One-to-One vs One-to-Many One-to-many connections (e.g. celebrities with followers on Instagram) are directed and asymmetric, while one-to-one connections are typically reciprocal (e.g. on Facebook). Central nodes in one-to-many networks broadcast to marginal nodes, which typically don't interact in return. Clustering Nodes in networks often form tightly-knit subgroups or clusters. These clusters can be connected by bridges (isolated links between groups). High clustering leads to stronger network effects, making the network more valuable. Critical Mass Critical mass is the point when a network becomes more valuable than the product itself. For example, a telephone network gains value once more users are connected. Platform networks like Windows or iOS need a large user base and developer ecosystem to reach critical mass. The Network “Laws” ○ Sarnoff’s Law suggests network value increases in proportion to the number of users (N). For many types of networks, it underestimates the network value. ○ Metcalfe’s Law states network value grows as the square of the number of users (N^2), applicable to networks like Ethernet, phone networks, social media and marketplaces. ○ Reed’s Law argues that group-forming networks, where subgroups can form (e.g., social media), grow in value exponentially at a rate of 2^N. This is faster than Metcalfe's Law due to the large number of possible groups within a network. Part3. Network Properties 1. Irregularity Networks are irregular with clusters, hot spots, and dead zones, reflecting real-world complexities like geography, relationships, and organizational size. To build strong network effects, begin by targeting the most active and valuable segments ("white-hot center") before expanding to the broader network. 2. Real Identity vs Pseudo Identity vs Anonymity Real-identity networks (LinkedIn, Facebook) tend to create stronger network effects due to trust and accountability, especially in marketplaces or platforms requiring reputation (e.g., Airbnb). On the other hand, anonymity is essential in some cases (crypto, espionage). Anonymous networks are often fragile due to trust issues, low-quality contributions, or regulatory interventions. 3. Asymmetry Demand-side marketplaces focus on attracting buyers (e.g., Fiverr), while supply-side marketplaces prioritize acquiring suppliers (e.g., Uber). Node Value Variability: Certain nodes are significantly more valuable than others, so businesses should prioritize these high-impact nodes to maximize network value. 4. Homogeneous vs. Heterogeneous Networks In homogeneous networks, all nodes perform the same function, as seen in traditional telephone systems. In heterogeneous networks, nodes have distinct roles and utilities, such as buyers and sellers on eBay or planners and florists on Honeybook. 5. Asymptotic Network Effects Some networks, like Uber, see value growth plateau after a certain size when additional supply no longer benefits users - diminishing returns. Platforms like Waze avoid this issue by relying on constant updates of real-time data to remain useful. 6. Same-Side Network Effects Same-side network effects are direct network effects that occur on the same side of a multi-sided (2-sided or N-sided network). Additional users can enhance network value, as seen with Windows users who benefit from file compatibility. I can also have a negative effect and lead to congestion or competition. For example, Uber drivers competing for the same riders and vice versa. 7. Cross side Network Effects Growth on one side of the network directly benefits the other, such as additional Uber drivers improving the experience for passengers. 8. Indirect network Effects Growth on one side indirectly benefits others. For instance, more sellers on eBay attract buyers, which in turn benefits all sellers by increasing demand. Another example, increasing the number of developers on a platform such as Microsoft Windows will attract more users. 9. Negative Network Effects In some cases, a greater network size may decrease the network value. One category is congestion, a perfect example of which is rush-hour traffic on roads. On the other hand, there is network pollution, which is more common for on online networks. In this case, larger networks may dilute its quality, such as irrelevant posts on Facebook feeds. Part 4. Building And Maintaining Network Effects 1. Multiplayer vs. Single-Player mode Single-player products provide value to users independently, without requiring the presence of other users: For example, buying a product on Amazon or filing taxes using TurboTax are single-player experiences. In contrast, multiplayer products rely on user interactions to create value collectively. Platforms like YouTube, where users interact through views and comments, exemplify this model. Some products blend both modes, starting with single-player functionality and transitioning to multiplayer. For example, Amazon evolved by adding reviews and a marketplace, transforming its value proposition and enabling exponential growth. 2. Switching costs Switching costs refer to the effort, time, or money required to change from one product to another. High switching costs create customer lock-in. For instance, Apple's ecosystem, including MacBooks, AirPods, and iTunes, discourages users from switching due to its tightly integrated compatibility. Network effects amplify these costs. In two-sided marketplaces like Craigslist, users are further locked in because both sides (e.g., renters and landlords) must move simultaneously, making a switch impractical. 3. Chicken or Egg Problem (Cold start Problem) The "chicken or egg" problem describes the difficulty of achieving critical mass in networks, especially in two-sided marketplaces where one side (e.g., buyers) depends on the other (e.g., sellers). Overcoming this challenge often involves creating initial value for one side, such as offering single-player functionality or incentivizing early adoption with benefits like cash or leads. 4. Multi-Tenanting Multi-tenanting occurs when users participate in multiple competing networks simultaneously. For example, people may use both Uber and Lyft, or share photos on Instagram and Snapchat. While this can weaken network effects, larger networks usually prevail because they offer more options and visibility. However, multi-tenanting can occasionally reinforce usage across networks by increasing overall engagement in the category. 5. Disintermediation Disintermediation happens when users bypass a marketplace after making an initial connection and conduct future transactions directly. This is a significant threat to marketplaces since repeat purchases are critical for success. Preventing disintermediation involves offering tools, reputation systems, insurance, compliance, and other incentives to keep users loyal. 6. Retention Retention measures how often users return to a product, which is crucial for sustaining network effects. High retention ensures that networks continue to provide value as they grow. For example, Facebook's early success was driven by its ability to retain users, ensuring that the network remained valuable over time. Strong retention underpins network effects, as usage is more critical to success than the network's size alone. Part 5. Related Concepts Geometric (Exponential/Non-Linear) Growth vs. Linear Growth Linear growth refers to steady, incremental progress typical of businesses without viral or network effects. While this can sustain a business, it lacks the transformative impact of geometric growth. Exponential growth occurs when viral or network effects drive a rapid, nonlinear increase in users or revenue, often after reaching a tipping point. Founders should aim for this type of growth and monitor metrics to transition from linear to geometric growth. Viral Effects vs. Network Effects Viral effects and network effects are distinct but interconnected. Viral effects focus on growth but don't guarantee long-term value or defensibility. Network Effects enhance the value of a product as more people use it, strengthening retention and defensibility. While viral effects bring users, network effects ensure users stay and generate enduring value. Platform Business Model The term "platform business model" broadly refers to companies that scale by facilitating external networks. While this is an essential concept, the term often conflates distinct attributes of network effects. It's more precise to analyze individual network effects and how they operate within the platform. Reinforcement Network effects create a foundation for building additional defensibilities. Each added defensibility strengthens others, resulting in a "reinforcement effect." For example, combining network effects with scale or embedding amplifies overall defensibility. However, founders must balance this with operational focus to avoid overextension. Scale Effects Scale effects refer to cost advantages gained as a company grows larger. With increased volume, companies achieve lower per-unit costs, enabling competitive pricing and better ad performance. These economies of scale create a mathematical edge that is difficult for competitors to overcome. Amazon exemplifies scale effects, which it now combines with network effects for added defensibility. Brand A strong brand provides a psychological edge by creating familiarity and reducing users' willingness to switch to competitors. Brand defensibility correlates with usage and growth but operates differently from network effects. A recognized brand introduces switching costs and leverages trust, even in highly competitive markets. Embedding Embedding integrates a product deeply into a customer's operations, making it challenging and costly to replace. This creates significant switching costs. While common in B2B settings with tools like Oracle or SAP, embedding is also present in consumer products like Google Drive. Embedding can complement network effects but is a separate strategy. Van Alstyne, M. W., Parker, G. G., & Choudary, S. P. (2016). Pipelines, platforms, and the new rules of strategy. The Rise of Platforms and Strategic Shift The article explores the transformative shift in business models, highlighting the dominance of platforms over traditional pipeline businesses. While pipeline businesses rely on a linear value chain, platforms focus on creating value by connecting producers and consumers in high-value exchanges. Platforms leverage network effects to achieve exponential growth and competitive advantage, a strategy that has reshaped entire industries. The rapid success of Apple's iPhone illustrates this shift. Despite being a relatively weak player in the mobile industry in 2007, Apple's combination of innovative product design and a robust platform strategy allowed it to dominate global profits. By 2015, Apple's iPhone accounted for 92% of the industry's profits, while traditional incumbents like Nokia and Motorola struggled, despite having strong brands, superior logistics, and vast R&D budgets. What are Platforms? Platforms are business models that facilitate value-creating interactions between external producers and consumers. Unlike pipeline businesses, which create value through a sequential chain of activities (e.g., sourcing, production, and distribution), platforms enable decentralized interactions. They rely on four core players: Owners: Control the platform's intellectual property and set governance rules. Providers: Act as interfaces for users (e.g., devices or applications). Producers:Create offerings for the platform (e.g., app developers). Consumers: Use the platform’s offerings This ecosystem-based approach allows platforms to scale rapidly by leveraging advances in information technology. Platforms such as Uber, Airbnb, and Alibaba demonstrate how reduced physical infrastructure requirements and increased data analytics capabilities enhance scalability and efficiency. The Transition from Pipeline to Platform The transition from pipeline to platform involves a fundamental rethinking of value creation and competition. The article identifies three major strategic shifts: 1. From Resource Control to Resource Orchestration Traditional pipeline businesses gained competitive advantage by controlling tangible and intangible assets, such as factories or intellectual property. Platforms, in contrast, orchestrate resources owned by their community members. For instance, Airbb facilitates the rental of privately owned rooms, while Uber mobilizes independently owned vehicles. The primary asset is the network of producers and consumers. 2. From Internal Optimization to External Interaction Pipeline businesses optimize internal processes to improve efficiency and reduce costs across the value chain. Platforms create value by enabling interactions between external participants. This shift requires platforms to govern their ecosystems effectively, encouraging collaboration while minimizing conflicts. 3. From Customer Value to Ecosystem Value Pipeline businesses focus on maximizing the lifetime value of individual customers. Platforms aim to maximize the value of their entire ecosystem. This often involves subsidizing one side of the market (e.g., providing free tools for app developers) to attract the other side (e.g., users). Success is measured by the strength and growth of the ecosystem rather than individual transactions. Network Effects: The Engine of Platforms Network effects are the driving force behind platform success. They occur when the value of a platform increases as more participants join. For example: Alibaba: Dominates Chinese e-commerce by facilitating efficient matches between buyers and sellers. Facebook: Benefits from a growing user base that enhances the richness of social interactions. Uber: Improves service quality and availability as more drivers and riders join the platform. Unlike supply-side economies of scale, where efficiency improves with volume, demand-side economies of scale amplify value through network effects. Platforms like Google and Facebook have become monopolistic due to these dynamics. How Platforms Change Competition Platforms fundamentally alter the nature of competition. Traditional businesses face new challenges as platforms redefine competitive boundaries. Key dynamics include: 1. Ecosystem Dynamics Participants in a platform ecosystem can switch roles, enhancing or threatening the platform's value. For instance, Uber users can become drivers, adding value to the ecosystem. However, producers or providers may defect and create competing platforms, as seen with Netflix leveraging telecommunication infrastructure to challenge its providers. 2. Cross-Industry Competition Platforms often expand into unrelated industries, creating unexpected competition. Google's expansion from web search into mobile operating systems, home automation, and driverless cars disrupted traditional players like Siemens and Honeywell. 3. Emergent Competitors Platforms that collect similar types of data can challenge incumbents. For example, wearables like Fitbit and retail pharmacies like Walgreens are launching health data platforms, competing with traditional healthcare providers. Metrics for Platform Success Pipeline businesses traditionally rely on metrics like inventory turnover and profit margins. Platforms, however, require new performance indicators: 1. Interaction Failure Rates - A platform must efficiently match supply and demand. For instance, a lack of available drivers on Lyft can deter users and disrupt network effects. 2. Engagement - Platforms track activities that strengthen network effects, such as content sharing or repeat visits. 3. Match Quality - Poor matches between users and producers weaken network effects. Platforms like Google continuously refine their algorithms to improve match quality. 4. Negative Network Effects - Congestion, misbehavior, or poor governance can reduce platform value. Chatroulette's failure to manage inappropriate behavior led to its decline. Government and Access Management Effective governance is critical for platform success. Platform owners must balance openness and control: Open Architecture: Encourages innovation by allowing external participants to create value (e.g., Apple's App Store) Controlled Access: Prevents low-quality content and misbehavior, as seen with Airbnb's rating system for hosts and guests. Platforms often start with closed governance and gradually open as they mature. For example, Google's Android platform fosters innovation by being more open than Apple's iOS, allowing app developers to contribute freely. The Leadership Challenge Platform leadership requires a shift in mindset. Traditional management focuses on controlling resources and optimizing processes. In contrast, platform leaders must nurture ecosystems, foster collaboration, and govern complex interactions. The failure to adapt explains the decline of businesses like MySpace, which was mismanaged under a traditional pipeline model. Conclusion: The Future of Platforms The platform economy is reshaping industries and redefining competition. Businesses that fail to embrace platform strategies risk obsolescence. The article underscores the urgency for traditional firms to adapt, innovate, and learn the new rules of strategy in a platform-driven world. The rise of platforms like Uber and Airbnb demonstrates that the future belongs to those who can orchestrate ecosystems, leverage network effects, and redefine value creation. Zhu, F. (2019). Friends or foes? Examining platform owners' entry into complementors' spaces. Introduction As platforms become increasingly important in our economy, concerns are growing about platform owners' misuse of their market power with respect to their value creation partners. In particular, many platform owners imitate complementors and enter their product spaces with similar offerings. These moves position the platform owners as direct competitors to their complementors. The textbook explanation for why a platform owner should provide some of the complementors itself is that these complementary applications help solve a chicken-and-egg problem. Without an existing base of platform users, no complementors would be interested in supporting that platform, and without complementary applications, no consumers would be interested in adopting the platform. What is not clear, however, is whether a platform owner should still offer complementary products by itself after the platform has taken off. Motivations for Platform-Owner Entry Studies have identified motivations for platform-owner entry beyond value capture. Gawer and Cusumano (2002) point out that Intel enters certain product spaces because it is not satisfied with complementors' products and wants to motivate them to innovate by introducing competition. Wen and Zhu (2018) examined Google's introduction of its own mobile apps for its Android system. Similar to Wang, Li, and Vir Singh (2018), they find that in each of the three entry events they studied there are a large number of third-party apps offering similar features. Because Google's entry makes these markets less attractive for app developers, its entry pushes these app developers to innovate in other product spaces, which may reduce wasted efforts in developing these duplicate apps. They also point out that platform owners may use direct entry to exercise better quality control. Zhu and Sun (2018), in their case study on JD, one of the largest e-commerce companies in China, find that JD wants to offer products in certain categories by itself to minimize counterfeiting. Impact of Platform Owner Entry Most empirical papers in the literature focus on the impact of platform-owner entry on platform users and complementors. While these studies have documented positive effects on platform users, the effect on complementors is mixed. The mixed findings suggest that the impact on complementors may be moderated by other factors. Li and Agarwal (2017) show that the effects depend on the size of the complementors. One would also expect the effect to depend on how tightly platform owners bundle their own offerings with their platforms, the degree of differentiation between platform owners' own offerings and third-party complements (Belleflamme & Peitz, this issue), and the extent to which platform owners preferentially promote their own offerings (e.g., Wu & Zhu, 2018). Future research could seek to explore these moderating factors to reconcile these mixed findings. All empirical studies thus far have examined the short-term effects of platform-owner entry. The long-term effects could be different. Defense Strategies of Complementors In cases where platform-owner entry has negative effects on complementors, one would expect complementors to design strategies to mitigate the negative effects. The literature has identified several strategies that complementors adopt. First, complementors can strategically form ties with platforms. Summary The extant research has documented the multifaceted nature of platform entry in terms of both its motivations and its impact. Different from the theoretical literature, these studies suggest that the motivations for platform entry can go well beyond value capture and may vary across various industries. While none of the studies has documented harmful effects on platform users, there is mixed evidence on whether platform-owner entry is harmful for complementors. We also lack evidence on the long-term effects of platform-owner entry. Hence, there does not seem to be a single prescription that policymakers can follow in regulating platform-owner entry. It is also important to recognize that in addition to direct entry, platform owners can use other means to appropriate more value.