Friday, October 28, 2016

Reverse Network Effects

Network effects exist when the value per user rises as the number of users for a particular product or service increase.  Classic examples of firms with network effects include eBay, Uber, Google, and Netflix.  Sangeet Paul Choudary has written extensively about network effects in the past few years.  His recent post examines the concept of reverse network effects.  Is there some point where adding more users decreases value per user?     He explains in this excerpt:  

Reverse Network Effects may sometimes set in with scale i.e. online networks may become less useful as they scale. I do not imply that all online platforms lose value as they grow. However, in the absence of robust curation, online platforms may lose value as they grow.  Under what conditions do online platforms lose value as they scale?  Since the participants on an online platform create value, an online platform loses value with scale when the participants it allows in OR the information/value that they create are not curated appropriately. Poor curation leads to greater noise which makes the platform less useful.

He goes on to give some examples of the ways in which increased noise can become a problem.  For example, he points out that less sophisticated participants may began to use the platform, and that might reduce value per user.   He cites Quora as one platform in which this danger may arise.  Quora worked very well in the beginning as experts answered interesting and challenging questions.   As people with less expertise use the system, however, may create a problem.  As their answers offer less value, some experts may leave the platform.  As experts leave, that can create a downward spiral of value loss and further expert attrition.   His work in this area is interesting, because it stresses the fact that more is not always better in the realm of network effects.  A reverse mechanism can begin to take hold on certain platforms.  

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