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Let H be a connected subgraph of a connected graph G. The H-structure connectivity of the graph G, denoted by κ(G;H), is the minimum cardinality of a minimal set of subgraphs F={H1′,H2′,…,Hm′} in G, such that every H′i∈F is isomorphic to H and removal of F from G will disconnect G. The H-substructure connectivity of the graph G, denoted by κs(G;H), is the minimum cardinality of a minimal set of subgraphs F={J1′,J2′,…,Jm′} in G, such that every Ji′∈F is a connected subgraph of H and removal of F from G will disconnect G. In this paper, we provide the H-structure and the H-substructure connectivity of the circulant graph Cir(n,Ω) where Ω={1,…,k,n−k,…,n−1},1≤k≤⌊n2⌋ and the hypercube Qn for some connected subgraphs H.

Computerized layout (or “topology”) optimization was pioneered almost four decades back. However, despite dramatic increases in available computer power and the application of increasingly efficient optimization algorithms, even now only relatively modest sized problems can be tackled using the traditional “ground structure” approach. This is because of the need, in general, for the latter to contain every conceivable member connecting together the nodes in a problem. A simple, but effective solution method capable of tackling problems with large numbers of potential members (e.g. >100,000,000) is presented. Though the method draws on the linear programming technique of “column generation”, since layout optimization specific heuristics are employed it is presented as an iterative “member adding” method. The method requires a ground structure with minimal connectivity to be used in the first iteration; members are then added as required in subsequent iterations until the (provably) optimal solution is found.

The study described in this article aimed to gather insights into what people think when they search the Internet for information. The premise is that people relate to information services and systems metaphorically. In other words, they identify the system or service as analogous to something perhaps more mundane or commonplace. These are known as wild metaphors. They help to explain the unknown or unfamiliar and help us to learn new things. They arise from our individual beliefs and backgrounds but they are also inevitably influenced by our collective experience of contemporary media characterisations of the Internet. This study relates the analogies that academics in Australia report for the Internet with the satisfaction that they derive from information seeking on the network. It provides some insight into how academics in Australia perceive the Internet when they use it to search for information.

For this discussion, assume there are n sample observations of the dependent variable y at unique locations. In spatial samples, often each observation is uniquely associated with a particular location or region, so that observations and regions are equivalent. Spatial dependence arises when an observation at one location, say y i is dependent on “neighboring” observations y j, y j∈ϒi. We use ϒi to denote the set of observations that are “neighboring” to observation i, where some metric is used to define the set of observations that are spatially connected to observation i. For general definitions of the sets ϒi,i=1,…,n, typically at least one observation exhibits simultaneous dependence, so that an observation y j, also depends on y i. That is, the set ϒj contains the observation y i, creating simultaneous dependence among observations. This situation constitutes a difference between time series analysis and spatial analysis. In time series, temporal dependence relations could be such that a “one-period-behind relation” exists, ruling out simultaneous dependence among observations. The time series one-observation-behind relation could arise if spatial observations were located along a line and the dependence of each observation were strictly on the observation located to the left. However, this is not in general true of spatial samples, requiring construction of estimation and inference methods that accommodate the more plausible case of simultaneous dependence among observations.

This paper aims to propose an empirically grounded governance framework based on complex adaptive systems (CAS) principles to facilitate formation of well-connected regional supply chains that foster economic development, adaptability and resilience of mining regions.

This study is an exploratory case study of the South Australian (SA) mining industry that includes 38 semi-structured interviews with the key stakeholders and structural analysis of the regional supply network (RSN).

Findings demonstrate the applicability of the CAS framework as a structured approach to the governance of the mining industry regional supply chains. In particular, the findings exemplify the relationship between RSN governance, its structure and interconnectivity and their combined impact on the adaptability and resilience of mining regions.

The data set analysed in the current study is static. Longitudinal data would permit a deeper insight into the evolution of the RSN structure and connectivity. The validity of the proposed framework could be further strengthened by being applied to other industrial domains and geographical contexts.

The proposed framework offers a novel insight for regional policy-makers striving to create an environment that facilitates the formation of well-integrated regional supply chains in mining regions through more focussed policy and strategies.

The proposed framework is one of the first attempts to offer a holistic structured approach to governance of the regional supply chains based on CAS principles. With the current transformative changes in the global mining industry, policy-makers and supply chain practitioners have an urgent need to embrace CAS and network paradigms to remain competitive in the twenty-first century.

This paper aims to develop a more nuanced view of subnational location choice with a particular focus on global cities. It is argued that multinational firms may use global cities to establish bridgeheads-subsidiaries at intermediate levels of the ownership chain that enable further international as well as subnational expansion.

Beyond those host country subsidiaries that are directly owned by a foreign multinational, the authors go deeper and focus specifically on the multi-tiered – “subsidiaries of subsidiaries” to examine how the geographic origins and destinations of these investments are associated with micro-location choices in a host country.

The authors find that there are substantial differences between the types, roles, activities and geographic origins of the firms locating in different areas, and in the ownership structures spanning them. The authors propose that this has managerial and theoretical implications which may be understood based on an organizing framework describing a tradeoff between the pursuit of global connectivity and local density on the one hand and cost control on the other.

Empirical work on foreign location choices should take into account ownership structures and take a more fine-grained view of subnational variation.

Managers need to consider the trade-offs between connectivity, density and costs when making foreign location decisions.

Policy makers should think about the unique contributions that various subnational regions such as global and ordinary cities can make to global value chains.

The authors bridge the hitherto separate literatures pertaining to subsidiary mandates and subnational dimensions of foreign location choice by investigating the fine-grained roles and ownership structures from a supranational as well as subnational perspective.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.

The aim of this article is to obtain a stable tensegrity structure by using the minimum knowledge of the structure.

Three methods have been formulated based on the eigen value decomposition (EVD) and singular value decomposition theorems. These two theorems are being implemented on the matrices, which are computed from the minimal data of the structure. The required minimum data for the structure is the dimension of the structure, the connectivity matrix of the structure and the initial force density matrix computed from the type of elements. The stability of the structure is analyzed based on the rank deficiency of the force density matrix and equilibrium matrix.

The main purpose of this article is to use the defined methods to find (1) the nodal coordinates of the structure, (2) the final force density values of the structure, (3) single self-stress from multiple self-stresses and (4) the stable structure.

By using the defined approaches, one can understand the difference of each method, which includes, (1) the selection of eigenvalues, (2) the selection of nodal coordinates from the first decomposition theorem, (3) the selection of mechanism mode and force density values further and (4) the solution of single feasible self-stress from multiple self-stresses.