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.
Sharing can morph into copying as nodes imitate each other’s benign behavior. This can have adverse system wide effects.
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Notes
- 1.
The fifth largest Wall Street investment bank, Bear Stearns was on life support over the March 15–16, 2008 weekend and remained solvent on Monday, March 17 only after a $30 billion cash infusion from the Federal Reserve via the regulated commercial bank, JP Morgan Chase [90].
- 2.
The desire for anonymity, safety and insurance will remain the bedrock for a significant demographic, which will use and keep a cash reserve. The worldwide circulation of the most popular $100 billion increased 348 % over the past twenty years; the next most popular $20 billion increased 103.4 % over the same time period [92].
- 3.
Following convention, bitcoin, the currency has a lower case b, and Bitcoin, the technology platform has an upper case B.
- 4.
Bubbles in speculative markets are founded on the imitation phenomenon. Blinder concludes that “the herding behavior that produces them may well be programmed into our DNA” [90].
- 5.
The theoretical explanation of information cascades is Bayes’ Rule. If P(A) is the prior probability of event A and P(B/A) is the conditional probability of event B given A, then Bayes’ Rule says that \(p\left( {A/B} \right) = \left\{ {P\left( A \right)/P\left( B \right)} \right\}* P\left( {B/A} \right). \ P\left( {A/B} \right)\) can be interpreted as the posterior probability of A, now that B has occurred.
- 6.
This discussion of diffusion of ideas is based on Easley and Kleinberg [12a]. More formally, the threshold for switching to a new product, p, depends upon the relative payoffs. Let p and (1-p) be the fraction of an individual’s neighbors adopting the new product A and the old product B, respectively. Suppose the person has x neighbors and that the payoff from adopting the new product is a, while the old product has payoff b. Then switching to the new product is the best choice if:
$$\begin{array}{*{20}{l}}{pxa \ge \left( {1 - p} \right)xb}\\{{\rm{or}}\,p \ge \frac{b}{{a + b}}}\end{array}$$ - 7.
In the marketing world, disseminating new product information can be structured after this threshold model. Production introduction can be diffused more widely if the threshold is lowered (payoffs raised by raising quality) or if key nodes are infected with the product, either with lower prices or some promotion. Chapter 5 discusses the role of gatekeepers in infecting key nodes for advertising purposes.
- 8.
It has been found in [96] that this fraction follows a Power Law
$$f(k) = a{k^{ - c\ }}{\rm{ or\ log }}\ f\left( k \right) = \log a - c\log k.$$The unique feature of the Power Law distribution is that there is no characteristic node or average number of links for nodes, nor a well-defined standard deviation, as is common in the bell curve or normal distribution.
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Bhatt, S. (2017). The Sharing Economy: Information Cascades, Network Effects and Power Laws. In: How Digital Communication Technology Shapes Markets. Palgrave Advances in the Economics of Innovation and Technology. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-47250-8_6
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