Multisided Platforms (MSPs)

Multisided Platforms

10.1 Introduction

• Multisided platforms (MSPs) facilitate interactions between two or more distinct user groups, creating mutual benefits.

• Two-sided platforms are a subset of MSPs, involving just two user groups. The theory applicable to two-sided platforms is generally valid for MSPs as well.

• Definition 10.1: A multisided platform (MSP) enables direct interactions between two or more distinct user groups in which all user groups are affiliated with the MSP (Hagiu & Wright, 2015).

• MSPs are a significant innovation in the digital economy, with companies like Google, Facebook, and eBay utilizing this model.

• There is still potential for new MSPs across various business sectors and the public domain.

• Sanchez-Carlas and Leon (2018) provide a literature overview, noting that the dynamics of platforms are based on supply and demand theory and agent-based behavior theory.

• These methods offer insights into pricing, network effects, platform service coupling, user behavior, competition, regulations, and monopoly formation.

• The focus is on the temporal evolution of MSPs triggered by strong network effects rather than pricing and competition in equilibrium markets.

• Many platforms lack market saturation (e.g., social media), and some have become de facto monopolies (e.g., Facebook), rendering standard supply/demand theories inapplicable.

10.2 Characteristics of Multisided Platforms

• MSPs provide users with:

  • Uniform, simple, and secure login procedures and ease of use.

  • Built-in matchmaking mechanisms for connecting customers with matching interests.

  • Efficient transaction management simplifying search, reducing management costs, and streamlining administrative and payment processes.

  • Assistance in trust-building between users.

• The MSP concept is related to value networks where mediation services are offered either within a single group or between different groups.

• The mediation between user groups is asymmetric, meaning the platform serves groups with different motives.

• Types of MSPs:

  • Digital MSPs: Mediate the exchange of digital goods and services (e.g., Facebook and MasterCard).

  • Tangible MSPs: Mediate the exchange of physical goods and non-digital services (e.g., Uber and Airbnb), also termed online-to-offline (O2O) MSPs.

• Key characteristics of MSPs include network effects, pricing, competition, business ecosystem, and market regulation.

10.2.1 Network Effects

• MSPs are subject to complex network effects both within and between user groups.

• Network effects can lead to winner-take-all markets, where one platform becomes a de facto monopoly.

10.2.2 Pricing

• Pricing models vary:

  • Free services for one group, paid services for another (e.g., Facebook and Google Search).

  • Pay-per-interaction or service amount.

  • Fixed monthly subscription fees (e.g., eBay and Airbnb).

  • Combination of free and paid services (e.g., electronic newspaper).

• User groups often subsidize each other through differentiated charges.

• MSPs may benefit from reduced prices to increase sales and platform usage, enhancing cross-side network effects.

• In scenarios with free goods/services, supply/demand theories become less relevant.

10.2.3 Competition

• Three types of competition:

  • Direct competition between similar platforms (e.g., Facebook and Myspace).

  • Competition with different platforms for the same customers (e.g., Facebook and Google competing for advertisers).

  • Competition between customers on the same platform (e.g., Uber drivers).

• Influencers on social media platforms operate as two-sided platforms (readers and advertisers) without significant infrastructure.

10.2.4 Business Ecosystem

• MSPs have complex ecosystems, requiring analysis of seemingly unrelated businesses.

• Standard business modeling tools may not capture cross-side network effects.

• Characterizing the MSP in terms of its ecosystem is crucial.

10.2.5 Market Regulations

• The existence of multiple user groups and strong network effects complicate regulation.

• It's difficult to establish a regulatory regime that supports fair competition and avoids monopolies.

• Intricate competition and complex ecosystems further complicate regulation, making it hard to identify what needs regulating, what can be regulated, and the effects of regulation.

10.3 Network Effects and MSPs

• Network effects are vital in MSPs (positive feedbacks from the market, where markets cannot be in equilibrium unless saturated).

• Same-side network effect: Involves only one user group.

• Cross-side network effect: Impacts the other user group(s).

• Positive, negative, direct, and indirect network effects can exist within and between user groups.

• The dynamics of an MSP are complex due to dependencies and network effects.

• Equilibrium theory is inapplicable in markets with network effects.

• The Bass equation (Chap. 18) exemplifies market evolution with same-side network effects.

• Box 10.1 analyzes the impact of a simple cross-side network effect mathematically.

• A simple mathematical model for the temporal evolution of a two-sided platform with a single cross-side network effect is shown in .Fig 10.2

• There are two types of customers, A and B. Initially there are $N$ potential customers of type A and $M$ potential customers of type B. Customers of type A adopts the platform service offered to them at a fixed rate $p$, symbolized by a valve controlled by the parameter $p$. The adoption rate of customers of type B is proportional to the number of customers of type A, i.e., the adoption rate of type-B customers is $qA$.

• The flow rate of customers is equal to the number of users adopting the service per unit time. This is, by definition, equal to the time derivative of the number of customers having adopted the service at given time. Hence, the flow of customers of type $A = \frac{dA}{dt} = p(N - A)$

• and the flow of customers of type $B = \frac{dB}{dt} = qA(M - B)$, where $N − A$ and $M − B$ are potential customers who have not adopted the services yet.

  • $\frac{dA}{dt} = p(N - A)$

  • $\frac{dB}{dt} = qA(M - B)$

  • $A = N(1 - e^{-pt})$

  • $B = M(1 - e^{-\frac{qN}{p} (1 - e^{-pt})})$

  • For small $t$, $B \approx \frac{MNpqt^2}{2}$, which is much slower than linear increase for small values of $t$.

• The network effects may lead to slow service adoption, potentially causing premature abandonment by the platform provider.

• Case Study 10.1 applies the theory to study Facebook's temporal evolution.

• The model in Box 10.1 is used to study the temporal evolution of Facebook.

• Figure 10.4 shows the evolution of users and revenue of Facebook from 2008 to 2019

• The theoretical curves are calculated using the formulas of Box 10.1 with parameters

  • $N = 7.8 \times 10^9$

  • $M = 1.9 \times 10^8$

  • $p = 3.7 \times 10^{-2}$

  • $qN = 1.9 \times 10^{-2}$

• The similarity between theoretical and observed curves is striking.

• Network effects in MSPs with users and advertisers (e.g., Facebook):

  • User numbers positively impact advertiser numbers.

  • Advertisers have little effect on user numbers.

  • Strong positive network effects exist among users.

• In electronic marketplaces (e.g., eBay):

  • Sellers prefer many buyers, and vice versa.

  • Positive cross-side network effects.

  • Increased competition among sellers may create a weak negative same-side network effect.

  • User reviews may generate weak network effects among buyers.

10.4 Business Ecosystem and MSPs

• A generic MSP model includes six stakeholder types: content providers, advertisers, developers, professionals, merchants, and consumers.

• Platforms may serve all or some of these categories.

• The MSP's ecosystem can be overly complex due to the various connections.

• Stakeholders include:

  • Content providers: Stream media, offer specialized content, produce digital content, and support video games.

  • Advertisers: Use platforms for marketing and personalized advertisements.

  • Developers: Create new services or goods (e.g., apps).

  • Professionals: Receive services for their production (e.g., cloud computing).

  • Merchants: Utilize platforms for online shopping.

  • Consumers: End users accessing digital services or receiving physical goods.

10.5 Trade Process of MSPs and Resellers

• MSPs are one organizational method; resellers are another.

• Resellers purchase goods/services from a producer and resell to the buyer.

• MSPs enable direct contact between user groups is essential to being classified as such.

• Supermarkets are resellers; eBay is an MSP.

• Taxi companies are resellers; Uber is an MSP

• Amazon buys books from publishers and resells them to readers in the same way as any other bookstore.

• MSPs may range from simple apps to complex platforms (e.g., Google and Facebook).

• Most sharing economies are two-sided or multisided platforms.

• The MSP mediates contact between the seller and the buyer. The trade process for MSPs facilitates direct exchange between seller and buyer, without direct involvement from the MSP in the exchange of goods.

10.6 Conclusions

• MSPs serve multiple user/customer groups simultaneously.

• Interactions between groups provide benefits for each user group (cross-side network effects), establishing complex ecosystems.

• Analyzing MSPs is more complex than analyzing businesses with homogenous customers.

• Most digital economy businesses are MSPs.

• Understanding platform interactions is essential for analyzing price formation, revenue generation, and competition.

• Competition occurs between similar platforms and platforms in different business segments (e.g., Facebook and Google).

• MSPs often offer free services to some users, with revenues determined by cross-side network effects.

• Standard demand/supply analysis may be meaningless in such cases.

• Several MSPs are de facto monopolies in certain segments while competing in others.