The Sharing Economy: Information Cascades, Network Effects and Power Laws
Sharing can morph into copying as nodes imitate each other’s benign behavior. This can have adverse system wide effects.
Abstract Connectivity generates familiarity and induces collaboration, and also the phenomenon of copying, known also as FOMO (fear of missing out). Imitating others’ behavior derives from the social influence of networks which is different from homophily or joining groups with similar characteristics. While financial markets have manifested granularity in the unbundling of functions of financial intermediation, such as payments, risk management, savings and investment, there has also been the formation of OB due to copying. Connectivity has fostered imitation to economize on search costs and to benefit from shared networks. Copying can have adverse consequences, as when all economic agents congregate at the same hub, and, by adopting the same behavior, precipitate disastrous consequences as we saw in the 2008 financial crisis.
Keywords Information cascades • Network effects • Financial markets • Spontaneous feedback effects
The social and psychological forces that propel group formation in societies, such as homophily or the tendency to gravitate toward people with similar characteristics, can work in reverse, as with social influence or the
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desire to remake oneself in the image of others. The Internet has spawned connections, some by deliberate choice but some created by the structure and behavior of the network. In any given connection, similarities between individuals will be understood but differences will be puzzling, at first. Repeated interaction will then move these individuals to erase these differences, as one or both copy characteristics and behaviors of each other. This phenomenon ofimitation will then be replicated across the entire network in various strengths leading to systemic changes in the entire network. Connectivity not only brings information from node to node but it also makes their economic and social identities gravitate toward each other.
This phenomenon of copying is prevalent in all industries, but in the financial industry it can have massive consequences. “Finance is more like the circulatory system of the economic body” writes Alan Blinder . Because finance is an important factor in all businesses, events in the financial industry will have ripple effects across the economy, enabling financial institutions to acquire the behemoth status. Too big to fail institutions are more than OB - these institutions are not simply large, their very survival is practically guaranteed. Congress offers these institutions a safety net so that they face limited probability of being dissolved. Dissolving an institution in this industry has far reaching consequences. In 2008, “Bear Stearns was deemed to be too interconnected to fail” .1
Paradoxically, both granularity and behemoths co-exist in the financial industry. The simple reason is that DCT has generated a cobweb of connections. In this chapter I examine, first, how increasing embeddedness, in the context of financial markets, dismantles traditional organizational structures, leading to granularity. When the decision makers are not the ones with the requisite information and resources, value maximizing choices may not be made. Granularity narrows the gap between these two groups, mitigating the agency problem. Second, increasing embeddedness connects seemingly isolated transactions across OB. When economic agents imitate choices made by others, the overall outcome is likely to be value decreasing, and quite possibly disastrous. As digital connectivity increases, the effects can sweep across the entire economy, well beyond financial markets themselves.