Diffusion and Social Influence


The first article of the week is about strategies for two-sided markets. A two-sided market is a market where you have two sides that connect through a platform. For example video game consuls like the PlayStation or Xbox. On one side you have the players and on the other side the game developers. With in the middle, for example PlayStation, as a platform provider. The article discusses the challenges a platform provider faces. Roughly they talk about three main challenges, the first one is the pricing challenge. Because there are two sides in this market you have to come up with two different prices. The prices has to be chosen carefully so that both sides stay satisfied. The next challenge is about winner-take-all dynamics. Try to keep both sides of the platform depend on your platform. So when one of the sides decides to switch to another platform they will incur high switching costs. The last challenge is about the threat of envelopment. Nowadays technology changes very quick therefore a platform provider needs to make sure to keep up with these changes. This can be done by upgrading your technology or changing the business model. (Eisenmann et al, 2006)

The second article is about social influence. As specially how firm can create word-of-mouth peer influence and social contagion by designing viral features into their products and marketing campaigns (Aral and Walker, 2011). In this article they discuss a field experiment involving the 1.4 million friends of 9,687 experimental users on Facebook. The researchers made three test groups: baseline group, passive-broadcast group and active-personalized group. Experimental users had to use an application that is free to download and provides users the opportunity to share information and opinions about movies, actors, directors and the film industry in general. In the end the saw how the different groups where using notifications and invites to convince their peers to use the application as well. They concluded that understanding optimal viral product design strategies could enable firms to optimally create and manage social contagion (Aral and Walker, 2011).

The third article explores whether Twitter messages proxy present or even future stock performance and whether they can be used to make better investment decisions in stock market (Sprengers, 2013). The experiment analysis tweets based on the words and hash tacks used in the tweet and evaluate the potential influence on stock market behavior. The sample consists of all companies listed at the S&P100, during the period March 12 and August 5, 2011. Three different computers collecting tweets over 20 minute intervals. In all, 560,783 tweets have been collected for the mentioned sample period. The conclusion of the experiment is that buying, holding, and selling stocks based on past sentiment leads to several profitable outcomes. The problem with this trading strategie is that the money will flow into this strategie in an attempt to exploit the anomaly, in turn causing the anomaly to disappear.

Next I found a case that gives some arguments which says that using big data like Google searches, Wikipedia searches and the service Amazon Mechanical Turk is better to predict stock markets than using Twitter. By using Twitter you create tunnel vision because you will miss the information of people who are not using Twitter. Almost everybody uses Google therefor these findings will be beter to predict stock market.

Another case I talk about is Crowdtap. It is a company specialized in helping brands to inspire a crowd of consumers to create quality content, drive unmatched social activity and provide real-time insights. How does Crowdtap work? Crowdtap runs an online marketing service that helps brands interact with social media followers via online games, surveys and contests. Users receive prizes, like gift card and products, in exchange for promotion and interaction. This is related to the second article on how to use peer influence for companies.

References

Eisenmann, T., Parker, G., and Van Alstyne, M.W. 2006. Strategies for Two-Sided Markets. Harvard Business Review 84(10) 92-101

Aral, S. and Walker, D. 2011. Creating social contagion through viral product design: A randomized trial of peer influence in networks. Management Science 57(9) 1623-1639.

Li, T., Sprengers, D., and van Dalen, J. 2013. Leveraging public sentiment to beat the market

Websites

http://www.forbes.com/sites/timworstall/2014/08/04/big-data-using-google-searches-to-predict-stock-market-falls/

www.crowdtap.com

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