Tackling information asymmetry in networks: a new entropy-based ranking index

Information is a valuable asset for agents in socio-economic systems, a significant part of the information being entailed into the very network of connections between agents. The different interlinkages patterns that agents establish may, in fact, lead to asymmetries in the knowledge of the network structure; since this entails a different ability of quantifying relevant systemic properties (e.g. the risk of financial contagion in a network of liabilities), agents capable of providing a better estimate of (otherwise) unaccessible network properties, ultimately have a competitive advantage. In this paper, we address for the first time the issue of quantifying the information asymmetry arising from the network topology. To this aim, we define a novel index - InfoRank - intended to measure the quality of the information possessed by each node, computing the Shannon entropy of the ensemble conditioned on the node-specific information. Further, we test the performance of our novel ranking procedure in terms of the reconstruction accuracy of the (unaccessible) network structure and show that it outperforms other popular centrality measures in identifying the "most informative" nodes. Finally, we discuss the socio-economic implications of network information asymmetry.Comment: 12 pages, 8 figure

University Spin-off Fundraising: The Impact of Entrepreneurial Capabilities and Social Networks Of Founding Teams during Start-ups

University spin-offs have increasingly received attention from academia, governments, and policymakers in studying the financing policies, venture capital investment decision making, the roles of venture capitalist in the development of new ventures, and the contributions of entrepreneur’s social capital to the fundraising activities. However, the limited number of studies in understanding of the contribution made by the entrepreneurial capabilities and social networks of a founding team to its fundraising ability still remains, especially within university spin-off context. Employing resource-based view theory and social networks approach, this paper enriches the knowledge by exploring university spin-offs in Spain. The results of this study empirically demonstrate that by exploiting social networks a founding team can improve its entrepreneurial capabilities, which in turn enhance its fundraising ability

Explorative and exploitative learning strategies in technology-based alliance networks

alliance, networks

The impact of partially missing communities~on the reliability of centrality measures

Network data is usually not error-free, and the absence of some nodes is a very common type of measurement error. Studies have shown that the reliability of centrality measures is severely affected by missing nodes. This paper investigates the reliability of centrality measures when missing nodes are likely to belong to the same community. We study the behavior of five commonly used centrality measures in uniform and scale-free networks in various error scenarios. We find that centrality measures are generally more reliable when missing nodes are likely to belong to the same community than in cases in which nodes are missing uniformly at random. In scale-free networks, the betweenness centrality becomes, however, less reliable when missing nodes are more likely to belong to the same community. Moreover, centrality measures in scale-free networks are more reliable in networks with stronger community structure. In contrast, we do not observe this effect for uniform networks. Our observations suggest that the impact of missing nodes on the reliability of centrality measures might not be as severe as the literature suggests

A survey on Human Mobility and its applications

Human Mobility has attracted attentions from different fields of studies such as epidemic modeling, traffic engineering, traffic prediction and urban planning. In this survey we review major characteristics of human mobility studies including from trajectory-based studies to studies using graph and network theory. In trajectory-based studies statistical measures such as jump length distribution and radius of gyration are analyzed in order to investigate how people move in their daily life, and if it is possible to model this individual movements and make prediction based on them. Using graph in mobility studies, helps to investigate the dynamic behavior of the system, such as diffusion and flow in the network and makes it easier to estimate how much one part of the network influences another by using metrics like centrality measures. We aim to study population flow in transportation networks using mobility data to derive models and patterns, and to develop new applications in predicting phenomena such as congestion. Human Mobility studies with the new generation of mobility data provided by cellular phone networks, arise new challenges such as data storing, data representation, data analysis and computation complexity. A comparative review of different data types used in current tools and applications of Human Mobility studies leads us to new approaches for dealing with mentioned challenges

The Cooperative Participatory Evaluation of Renewable Technologies on Ecosystem Services (CORPORATES)

Publisher PD

The role of structural embeddedness in an IT outsourcing network

The design of governance to safeguard against a vendor's opportunistic behaviour is one of the critical issues in information technology outsourcing (ITO) since this behaviour causes cost escalation and service debasement. The roles of structural embeddedness underlying network governance have been gaining its importance as complementary or substitutable governance in ITO. Our research attempts to reveal how structural embeddedness can affect the decision-makings of clients and vendors and their resulting outcomes in an ITO network and how these effects are moderated by various ITO network structures according to outsourced IT services. An agent-based simulation and game-theoretic approach are adopted to build a simulation model to describe ITO networks with various structures and ITO transactions between clients and vendors. Finally, the future research directions are discussed

Network Formation and Strategic Firm Behaviour to Explore and Exploit

The aim of this paper is to investigate the effect of technological opportunities and knowledge tacitness on inter-firm network formation, under two different industry regimes. In the first regime environment is stable and the aim of firms is to exploit knowledge. In this case, they attribute more value to repeated interactions with geographically close firms. In the second regime, there is environmental turbulence, which increases the value of access to novelties from distant partners for the purpose of exploration. The question addressed is, under these regimes how do technological opportunities and knowledge tacitness influence structure of networks? A simulation model is carried out where firms select partners and learn from them, which further shapes their selection process. How the macro structure of the network is shaped from the individual partner selection decisions of firms is analysed. The results reveal that in both regimes richer technological opportunities and higher tacitness generates local and global star firms depending on the parameter range.Networks, Knowledge, Innovation, Exploitation, Exploration