The Power of the Science of Networks
Imagine 100,000 independent traders who operate on a platform that enables them to monitor everybody else's performance, portfolios, and levels of risk at any point in time. Imagine also that a trader might decide to copy the choices of another, in the sense of authorizing the entity managing the platform to automatically duplicate the investment operations made by another trader. Imagine there is a huge table filled with the names of the one hundred thousand traders on its rows and columns. Now think that the match between trader 23476 and trader 57634 yields a 1, indicating that the former has decided to imitate the latter, so that every investment or divestment decision made by the latter is automatically replicated in the former's portfolio.
Why is 23476 copying 57634? Rational thinking would lead us to believe that trader 57634 has obtained satisfactory performance across time or displays superior risk-to-return ratios (all this information is publicly available). Nothing of the sort. By studying this large community of individual investors with the tools of network analysis, we would discover that the fact that a trader copies another one doesn't have anything to do with investment performance or risk.
Among the 9 billion potential connections in an investment community of 100,000 people, you decide to imitate the trader who has a picture and a real profile on the platform, detailing his/her personal description and qualities, and promptly answers the messages posted by the community of traders. Even in such an individualistic environment, people are guided by social interaction and visibility more than rationality. A similar, but negative example, is provided by the LIBOR scandal. The manipulation of interbank interest rates was the product of the biased decisions made by a tight personal network of bankers, traders, and other financial actors.
Thus, relations and networks of relations count more, and often have more explanatory power, than ideas and capabilities. Insofar as they are mechanisms for social influence, they amplify pressures toward conformism. Research on social networks has shown how relations impact on health, happiness, attitudes at work, and consumer behavior. For instance, the likelihood of becoming obese doubles if you are friend with an obese person. In other words, the probability of obesity is lower the higher the social distance from obese people (and vice versa).
These phenomena are increasingly relevant given the exponential growth of the interconnectedness of systems, economies, societies. Complexity and interdependence of markets go hand in hand. This makes forecasts on market dynamics increasingly hard to make. In fact, social and competitive processes are increasingly affected by a small-world effect, where degrees of separation among actors are decreasing, and ideas are spreading at speeds and magnitudes hitherto unthinkable. An example of the small-world effect is the average number of persons (4.7) that you need to be a friend of on Facebook to reach any of the 1.26 billion people registered on the social network. 92% of all the Facebook population has a social distance equal to 4 people. In 2008, the same variable had a value of 5.3. Let's try to imagine how little it takes for a piece of news, an idea, an opinion to spread across this network and influence the people that are part of it.
From the point of view of firms, which are called to observe this new reality and take effective economic decisions, it is all too evident they must equip themselves with new tools and advanced forms knowledge to reinvent the existing foundations of management. The new science of networks, born at the intersection of social sciences, physics, biology, and medicine, puts forward new analytical and conceptual tools that open new venues for the comprehension of complex systems such as firms, markets, economies.