Motivated by the difficulty of effecting fundamental change in the architecture of the Internet, in this paper, we study from a theoretical perspective the question of how individuals can join forces toward collective ventures. To that end, we draw on an elementary concept in Internet systems engineering, namely, that of incremental deployability, which we study mathematically and computationally. For example, we show that incremental deployability is at least as general a concept as the Nash equilibrium (in that the latter can be derived from the former). We then draw on this foundation to design and analyze institutional mechanisms that are not only promising to bootstrap emerging Internet architectures but they also have broader applications in social organization beyond its predominant market (and finance)-based character.
The problem of diffusing innovation in social systems has been the subject of extensive scrutiny primarily by social scientists. The study of diffusion of technology falls squarely in the ballpark of social science: Quoting @cite_7 , The people who have thought hardest about the general questions of technology have mostly been social scientists and philosophers, and understandably they have tended to view technology from the outside as stand-alone objects. 0.2 mm Seeing technology this way, from the outside, works well enough if we want to know how technologies enter the economy and spread within it.'' But computer scientists have also been involved with the diffusion of innovation from an algorithmic perspective. The term innovation assumes various interpretations in the literature from agricultural practices, social norms (such as which hand to extent in a handshake), medical drugs, commercial products (such as fax machines and cellphones), to networking technologies such as secure versions of BGP and quality-of-service capabilities in IP networks.
@cite_7
2155796078
Social norms and institutions are mechanisms that facilitate coordination between individuals. A social innovation is a novel mechanism that increases the welfare of the individuals who adopt it compared with the status quo. We model the dynamics of social innovation as a coordination game played on a network. Individuals experiment with a novel strategy that would increase their payoffs provided that it is also adopted by their neighbors. The rate at which a social innovation spreads depends on three factors: the topology of the network and in particular the extent to which agents interact in small local clusters, the payoff gain of the innovation relative to the status quo, and the amount of noise in the best response process. The analysis shows that local clustering greatly enhances the speed with which social innovations spread. It also suggests that the welfare gains from innovation are more likely to occur in large jumps than in a series of small incremental improvements.