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We introduce a multi-level model of the dependence of interfirm network topologies on the distribution and commonality of information in a network and the information strategies pursued by its member firms. Network topology, information properties of the network, and firm-level action within the network form dynamic, recursive, cross-level relationships – information properties in the network determine firm-level action, which in turn impacts the network topology and information properties. We derive predictions about the kinds of information strategies that firms are likely to adopt and succeed with in different information regimes, and about the kinds and short- and long-run dynamics of network topologies expected under different information regimes. Our model sheds new light on network topologies as a dependent variable that can be explained by network-level information regimes and firm-level information strategies.

This chapter focuses on business and industry networks. All six facets of knowledge networks are described. Three of the six facets have particular importance for these networks, specifically domain, relationships, and how messages are managed and controlled. The authors provide six network profiles, including health care industry networks, fashion industry networks, technology industry networks, food production industry networks, building industry networks, and transportation industry networks.

Town centre redevelopment provides an opportunity to redesign the topology of the road network. Environmental and safety considerations will usually entail some streets being reserved for pedestrians only and others for access to car parks and service bays close to the pedestrian precinct. The effect of the new topology on traffic flow can and should be an input to the planning process. One way to appraise alternative schemes is to find the extent to which traffic could be routed to reduce the amount of conflict there will be between the different streams of traffic at the junctions; conflict at junctions is a simple measure indicating the potential for both accidents and congestion with its attendant pollution.

The problem of finding an assignment of flow such that conflict is minimised is a constrained optimisation problem. The main constraints are provision of routes for a demand specified by an origin-destination (OD) matrix. The objective function which measures the amount of conflict between the different streams is simple to formulate; it depends only on the topology of the network and the OD matrix of demand. But it is a quadratic function of a type which is not amenable to existing programming methods. However, the author has developed an iterative method for obtaining good, if not necessarily optimal, solutions.

The purpose of the paper is to demonstrate the appraisal of hypothetical networks involving four external zones. The OD matrix has been chosen to model some through as well as mostly inbound traffic flow. Various alternative schemes are appraised ranging from those which merely allow one access point to a car park within a ring of streets surrounding the pedestrian precinct, to those which retain one link across the ring and up to two car parks. This is a pilot study for a larger one involving the systematic analysis of hypothetical town centre topologies. So far it has shown the advantage of two access points over one, and the greater advantage of two separate car parks each with a single access point which allows each car park to be in a separate cell of the road network. The relative positions of the access points and the link across the ring also affect the amount of conflict.

The variance targeting estimator (VTE) for generalized autoregressive conditionally heteroskedastic (GARCH) processes has been proposed as a computationally simpler and misspecification-robust alternative to the quasi-maximum likelihood estimator (QMLE). In this paper we investigate the asymptotic behavior of the VTE when the stationary distribution of the GARCH process has infinite fourth moment. Existing studies of historical asset returns indicate that this may be a case of empirical relevance. Under suitable technical conditions, we establish a stable limit theory for the VTE, with the rate of convergence determined by the tails of the stationary distribution. This rate is slower than that achieved by the QMLE. The limit distribution of the VTE is nondegenerate but singular. We investigate the use of subsampling techniques for inference, but find that finite sample performance is poor in empirically relevant scenarios.

Tourism studies have conceptualized social media as artifacts and networks of tangible objects based on neat distinctions and categorizations. These neat ontological distinctions and categorizations have been discussed within the academic field of actor-network theory. Several scholars have most significantly investigated the spatialities of messier ways of conceptualizing and approaching societal objects and the trajectories of societal phenomena. Efforts are being made to widen the ontological register that has traditionally dominated social science research, including tourism studies. The purpose of this chapter is to address and problematize the social media pertaining to tourism, focusing on a research project as analytical and methodological lens.

In this chapter, we propose a nonconventional methodology, the graph theory, which is especially relevant for the study of high-dimensional financial data. We illustrate the advantages of this method in the context of systemic risk in derivative markets, a main subject nowadays in finance. A key issue is that this methodology can be used in various areas. Numerous applications have now to face the challenge of analyzing gigantic financial data sets, which are more and more frequent. We offer a pedagogical introduction to the use of the graph theory in finance and to some tools provided by this method. As we focus on systemic risk, we first examine correlation-based graphs in order to investigate markets integration and inter/cross-market linkages. We then restrain the analysis to a subset of these graphs, the so-called “minimum spanning trees.” We study their topological and dynamic properties and discuss the relevance of these tools as well as the robustness of the empirical results relying on them.

This chapter focuses on the treatment and characterization of networks as an emerging discipline. Networks are defined. The authors call out and explain the importance of network domains, network geographies and topologies, network behaviors, network nodes, network links, relationships and flows, and network messages. While network sciences provide a strong foundation for research and analysis, the authors note the lack of knowledge networks. This chapter highlights the need to expand coverage to include knowledge networks.