The establishment, use, and replacement of resources in enterprises is significantly affected by network structures.
Although this topic is highly relevant to business administration, there is still need for clarification. What characterizes the structure of social networks and how do they affect the use of resources in strategic enterprises and in the economy overall?
Social network communities & structures
It is important for firms to uncover like-minded people in online platforms with the goal of accruing financial value. Within networks, these individuals form communities must be found. We have evaluated the performance of state-to-art community detection algorithms and provided recommendations on when to apply which method. Another important macro scale architecture of networks is “nestedness”. This concept refers to the fact that, given any pair of agents in the network, if one has a larger number of connections than the other, then the set of neighbors of the former contains that of the latter. In one study, we have performed real world data analysis and developed new methodological tools to numerically evaluate this network arrangement.
Abel Camacho, Alex Grimm, Carlo G. Ferrari, Claudio J. Tessone, Jian-Hong Lin, Manuel S. Mariani, Radu Tanase, René Algesheimer, Zhao Yang
Social influence is the change in behavior that one person causes in another, intentionally or unintentionally, as a result of the way the changed person perceives themselves in relationship to the influencer, other people and society in general. Identifying individuals who are influential in diffusing information, ideas or products in a population is an important problem. We contribute to this research stream by employing the wisdom of crowd. In our study, we propose a method to aggregate the behavioural reactions of the members of the social group into a collective judgment that considers the temporal variation of influence processes. The aggregation method addresses different sources of heterogeneity encountered in social systems and leads to results that are easily interpretable and comparable within and across systems.
Claudio J. Tessone, Jian-Hong Lin, Manuel S. Mariani, René Algesheimer, Zhao Yang
The nature of R&D networks
Different types of networks pervade the activity of firms. Firms engage in collaborations, exchange knowledge, and innovate; thus, new products are developed and introduced to the market. Firms are connected by commercial and ownership relations that affect the way they behave, and ultimately how they face their customers. Inter-organizational Research and Development (R&D) alliances have grown rapidly, especially in some industrial sectors (pharmaceuticals, high-tech). These alliances allow firms to gain access to different assets more quickly than they could do in-house; also, they can share the costs and risks of a project, especially when this is expensive or uncertain. In this way, an efficient inter-organizational alliance network has a direct impact on the company valuation.
Claudio J. Tessone, Hui Liu, Zhao Yang
The value of Blockchain ecosystems
The Blockchain ecosystems is a new type of ecosystem based on Blockchain technologies: By design, it can create secure and trustworthy peer-to-peer interactions on this type of ecosystems mainly due to their decentralised control and governance mechanisms. In one study, we try to understand the role of social interactions in the creation of price bubbles. Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. By using Bitcoin data, we identify two positive feedback loops that lead to price bubbles in the absence of exogenous stimuli: one driven by word of mouth, and the other by new Bitcoin adopters.
Claudio J. Tessone