Summary by James R. Martin, Ph.D., CMA
Professor Emeritus, University of South Florida
Organization Structure Main
Page | Platforms
Bibliography
The purpose of this paper is to describe five fundamental properties of networks that determine why some platform firms thrive while others struggle. These properties include network effects, clustering, risk of disintermediation, vulnerability to multi-homing, and bridging to multiple networks.
Strength of Network Effects
Network effects include same-side or direct effects (e.g., the more Facebook friends you have, the more likely you are to attract additional friends), and cross-side or indirect effects where different groups of participants attract each other (e.g., users and app developers). As the number of participants increases, the value of a platform increases. Since the strength of network effects can change over time, firms should design platforms with features to strengthen the effects. For example, Amazon's review system generates same-side effects as users come back to read the reviews. Amazon also allows third parties to sell products to its users creating cross-side network effects where third party sellers and buyers attract each other. Learning effects can increase barriers to entry. Amazon's recommendation system adds value as the firm learns about consumers' preferences.
Network Clustering
The structure of a network influences a platform's ability to sustain its scale. When a network is fragmented into isolated local clusters it becomes more vulnerable to challenges. For example, Uber has clusters of drivers and riders in cities that are isolated from similar clusters in other cities. In contrast, Airbnb's visitors regularly connect with hosts around the world. Airbnb's network is essentially one large global cluster. This means that a competitor's attempt to enter Airbnb's global market would be more difficult and costly than a similar threat to Uber's fragmented ride-share platform business.
Risk of Disintermediation
Disintermediation refers to situations where network participants bypass the hub and connect directly. For example, a user might hire a house cleaner from a platform like Homejoy, but continue to use the cleaner without going back to Homejoy to hire the same cleaner again. There are various ways a platform can deter disintermediation including terms of service that prohibit transactions off the platform, and blocking participants from exchanging contact information. Another approach is to enhance the value of transactions on the platform. For example, some firms provide insurance, communication tools, and resolve disputes between participants.
Vulnerability to Multi-Homing
Multi-homing occurs when users or service providers form ties with multiple platforms at the same time. Examples include where drivers and riders use both Lyft and Uber, or where app developers create products for both iOS and Android systems. Multi-homing makes it difficult for a platform business to become profitable. To minimize multi-homing, Amazon provides fulfillment services to third-party sellers, and charges them higher fees when their orders are not from Amazon's marketplace.
Network Bridging
Network bridging refers to where a platform connects different networks to one another while diversifying into different lines of business. For example, Alibaba bridged its payment platform (Alipay) with its e-commerce platforms (Taobao and Tmail) to provide a service to both buyers and sellers. Amazon moved beyond retail into entertainment and consumer electronics. These networks reinforce each other's ability to sustain its scale.
Conclusion
Successful platforms find ways to strengthen network effects, build global network structures to limit isolated clusters, minimize multi-homing, mitigate the risk of disintermediation, and use network bridging to increase scale. These five fundamental properties of networks determine whether a platform will thrive or fail. Van Alstyne, Parker and Choudary told us that scale trumps differentiation (See Summary). According to Zhu and Iansiti, network properties trump platform scale.
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