Core-periphery Structure Research Articles (Page 4)

The Delta variant of COVID-19 has been found to be extremely difficult to contain worldwide. The complex dynamics of human mobility and the variable intensity of local outbreaks make measuring the factors of COVID-19 transmission a challenge. The inter-suburb road connection details provide a reliable proxy of the moving options for people between suburbs for a given region. By using such data from Greater Sydney, Australia, this study explored the impact of suburban road networks on two COVID-19-related outcomes measures. The first measure is COVID-19 vulnerability, which gives a low score to a more vulnerable suburb. A suburb is more vulnerable if it has the first COVID-19 case earlier and vice versa. The second measure is COVID-19 severity, which is proportionate to the number of COVID-19-positive cases for a suburb. To analyze the suburban road network, we considered four centrality measures (degree, closeness, betweenness and eigenvector) and core–periphery structure. We found that the degree centrality measure of the suburban road network was a strong and statistically significant predictor for both COVID-19 vulnerability and severity. Closeness centrality and eigenvector centrality were also statistically significant predictors for COVID-19 vulnerability and severity, respectively. The findings of this study could provide practical insights to stakeholders and policymakers to develop timely strategies and policies to prevent and contain any highly infectious pandemics, including the Delta variant of COVID-19.

Abstract We build a theory of financial intermediation based on the premise that some investors are better able to figure out the trade motives of their counterparties in bilateral meetings—screening experts. We solve for the equilibrium market structure and study how information asymmetries stemming from heterogeneity in screening expertise shape up the core–periphery trade structure. In particular, the core of the market is populated by screening experts: they have the largest share of trade volume, they are actively engaged in middleman activity, and trade with the most counterparties. Using transaction-level micro-data and information disclosure requirements, we provide extensive evidence consistent only with our theory of financial intermediation.

Linking corporate social responsibility (CSR) practices and organizational performance in the construction industry: A resource collaboration network

The global financial crisis was characterized by heightened financial risk in the USA, which spread to the rest of the world, including emerging economies. This paper constructs a core–periphery model with a global banking network and financial frictions. Due to a common-lender effect, when global banks lend to an emerging economy, heightened financial risk in the center depresses cross-border lending to the emerging economy, reducing real activities and exacerbating monetary policy trade-offs. As financial markets become more integrated, exchange rate flexibility becomes less welfare enhancing and active capital account policy becomes more welfare enhancing.

Research on multilayer network structure characteristics from a higher-order model: The case of a Chinese high-speed railway system

Modelling and analysis of big data platform group adoption behaviour based on social network analysis

The article deals with word stress adaptation in French loanwords in Polish. The presented data demonstrate that the borrowings in question can be divided into two categories in terms of stress placement. On the one hand, there are items with penultimate stress, which conform to native Polish stress rules. On the other hand, there are those which retain the original final stress in violation of these rules. The proposed formal analysis of this phenomenon within Optimality Theory is based on the assumption derived from Itô and Mester (1995, 1999, 2001) that phonological systems of natural languages have a core-periphery structure. The gallicisms with penultimate stress have thus been assigned to the core, while those with final stress to the periphery. It is argued that each stratum has a different constraint ranking, which results in the divergent adaptation of word stress.

Air transportation plays an essential role in the global economy. Therefore, there is a great deal of work to understand better the complex network formed by the links between the origins and destinations of flights. Some investigations show that the world air transportation network exhibits a community and a core-periphery structure. Although precious, these representations do not distinguish the inter-regional (global) web of connections from the regional (local) one. Therefore, we propose a new mesoscopic model called the component structure that decomposes the network into local and global components. Local components are the dense areas of the network, and global components are the nodes and links bridging the local components. As a case study, we consider the unweighted and undirected world air transportation network. Experiments show that it contains seven large local components and multiple small ones spatially well-defined. Moreover, it has a main global component covering the world. We perform an extensive comparative analysis of the structure of the components. Results demonstrate the non-homogeneous nature of the world air transportation network. The local components structure highlights regional differences, and the global component organization captures the efficiency of inter-regional travel. Centrality analysis of the components allows distinguishing airports centered on regional destinations from those focused on inter-regional exchanges. Core analysis is more accurate in the components than in the whole network where Europe dominates, blurring the rest of the world. Besides the world air transportation network, this paper demonstrates the potential of the component decomposition for modeling and analyzing the mesoscale structure of networks.

The pandemic indicates that the use of digital technologies is going to become more important hereafter. In such a world where countries need to take action to shape their future in accordance with this ‘new normal’, the policies followed by countries in high technological sectors will be determinative on their positions within global value chains in the future. Based on this, international trade of industrial robots among the Belt and Road Initiative members is analyzed via complex network tools in the present study. The empirical results indicated that the international trade network of industrial robots has complex system properties such as power-law distribution, disassortativity, core-periphery structure etc. The results also revealed that developing members of the Initiative may exploit export hubs of the network, namely South Korea, Singapore, Austria and Italy in order to digitalize their economies in the short-term.

Yu, J., 2020. Disentangling the core–periphery structure in marine reserve networks based on a genetic algorithm. In: Yang, D.F. and Wang, H. (eds.), Recent Advances in Marine Geology and Environmental Oceanography. Journal of Coastal Research, Special Issue No. 108, pp. 250–253. Coconut Creek (Florida), ISSN 0749-0208.Various methods have been proposed in the literature to detect an optimal partitioning of marine reserve networks into core and periphery subsets. However, these methods has been approached using approximate procedures, such as genetic algorithms, that do not guarantee an optimal bipartition. In this paper, a genetic algorithm is presented to detect the core–periphery structure in marine reserve networks, and the effect of the algorithm is analyzed. First, it presents mathematically the optimization of the error score for the core–periphery model, which is an improved expression of optimization function. Moreover, the genetic algorithm was selected to afford a guarantee of an optimal bipartition, because the genetic algorithm as a significative method is beneficial in jumping from local optimizations.

Purpose This study aims to analyze a trade network between countries on agricultural products exports and imports from a social network perspective, and specifically identify the core and peripheral countries of agricultural product trade network. Design/Methodology/Approach We calculate coreness score and core-peripheral matrix values using core-periphery structure analysis of social network analysis techniques and recommend core countries and periphery countries. Findings We identified countries belonging to each block of the core-periphery structure, namely core block, peripheral block, core-peripheral block, and peripheral-core block, to discover the path and impact of crisis movement. Research Implications This study made it possible to predict how to respond to a crisis in the trade network from a macroscopic point of view to managers of a country or a company. The research implications of this study increased the understanding of core-peripheral structure analysis through network visualization as well as mathematical calculations.

The objective of this study is to examine the properties of actor collaboration networks and to analyze how they influence the coordination of hazard mitigation in resilience planning in Harris County, Texas. Effective resilience planning can only be achieved through the collective actions of various actors and the network structures unfold the collaboration among the actors. Understanding the structural properties of actor collaboration networks for hazard mitigation may hold the key to understanding and improving the resilience planning process. To this end, after Hurricane Harvey, we administered a stakeholder survey to actors in various urban sectors involved in hazard mitigation (e.g., flood control, transportation, and emergency response). The survey aimed to capture actor collaboration networks for hazard mitigation in Harris County, Texas prior to Harvey. The collaboration represents that the survey respondents worked with the actors in the survey roster for hazard mitigation. We asked the respondents the frequency of the collaboration in the survey (e.g., yearly, monthly, weekly and daily). We examined three network structural properties to study actor positions in the network: degree centrality, boundary spanners, and core-periphery structure, because degree centrality could indicate what actors had more collaborations; boundary spanners could reveal what actors were in strategic positions to connect otherwise separate actors; and core-periphery structure could identify what actors formed the core of actor collaboration network for hazard mitigation and whether the core was composed of actors from diverse sectors. The results showed: (1) governmental actors from different sectors had high degree centrality and betweenness centrality, which indicated that governmental actors had a more influential role in coordination and information dissemination in hazard mitigation planning and implementation; and (2) fewer flood control and non-governmental actors were at the core of the actor collaboration networks, which reduced the extent of hazard mitigation coordination. The results identify potential influential actors (such as City of Houston, Harris County, and Houston–Galveston Area Council) in coordination of hazard mitigation and yield recommendations for increased actor network cohesion for better coordination of hazard mitigation across diverse sectors in resilience planning.

One of the key features which promote growth of industrial clusters is collaboration among firms within such clusters. Collaboration among firms leads to the formation of networks. Stability of these networks is vital to the sustainability of the particular firms. In this paper, we model a supply chain network where a set of downstream firms (players) source inputs from upstream firms (players) who manufacture goods, add value to the products and resell them. The upstream firms produce identical goods and compete on quantities to sell these goods to the downstream firms. The upstream firms procure goods from the downstream firms and sell them. Additionally, upstream firms network among themselves so as to reduce their costs. We model this setting as a two-stage [Formula: see text]-player strategic network formation game. Firms decide their links before competing on quantities in the second stage of the game. Using the defined model, we derive equilibrium quantities and profits as a function of the network structure and number of firms. Following which we analyze the conditions under which different stable network emerge. Our analysis brings forth several interesting insights such as higher connections among downstream players lead to increased profits for upstream manufacturers. From the network stability perspective, we obtain the conditions under which regular, star, etc. network structures are pairwise and bilaterally stable. Furthermore, we also find the conditions under which core–periphery network structures emerge and are stable.

ABSTRACT Iran has implemented financial and legal support policies for new technology-based firms (NTBFs) since 2009. An assessment of these policies shows an unintended effect of perpetuating core–periphery development gaps, but also a limited understanding of the conditions for NTBF creation. This paper proposes a policy model for NTBF creation in less developed regions that adopts the broader perspective of the entrepreneurial discovery process associated with the Smart Specialisation concept. The policy model considers the entrepreneurs’ level, the firms’ level and the regional entrepreneurial environment to ensure adequate representation of all actors in the process.

Stakeholder participation has become an important driving force in policy decision-making and implementation, particularly in the nature conservation sector, where complex interactions and conflict of interest between stakeholders are common. A stakeholder analysis, which was complemented with a social network analysis, was used to examine the cooperation and conflict network between stakeholders, their institutions, and sectors in the case of the formulation of the Natura 2000 Management programme in Slovenia for the period 2015–2020 (PUN). Using data from a web survey (n = 167), cooperation and conflict networks were analysed while using degree centrality, indegree centrality, betweenness centrality, and blockmodeling. The results of the stakeholder analysis showed that the highest number of stakeholders that are involved in the participatory process of PUN was from the forestry and hunting sector, followed by the agriculture and nature conservation sector. The results of the cooperation network showed that the network is highly centralized, with only few institutions taking a central position in the PUN process (Institute for Nature Conservation, Ministry of Environment and Spatial Planning, Chamber of Agriculture and Forestry, Ministry of Agriculture, Forestry and Food, and the Slovenian Forest Service). Moreover, the nature conservation sector was, on average, a sector with the highest concentration of power. In addition, in the cooperation network, which was fragmented across sectors, there were institutions that belonged to the same sector, which tended to cooperate with each other. The analysis of the conflict network showed that institutions with a central position in the cooperation network also had a central role in the conflict network. In addition, conflicts between institutions more frequently appeared among institutions from different sectors. The exceptions were institutions from the fishery and water sector, as this sector seemed to have many conflicts within it. Based on a blockmodeling, four groups of institutions were identified according to their cooperation network (core institutions, semi-core institutions, semi-periphery institutions, and periphery institutions). Our finding suggested that the participatory process of formulating PUN needs to be improved in such a way that in the future various stakeholders, especially excluded local ones, are more actively involved and a balance of the power between the stakeholders involved achieved.

Asymmetric anthracene derivatives as multifunctional electronic materials for constructing simplified and efficient non-doped homogeneous deep blue fluorescent OLEDs

In many real-world networks, the ability to withstand targeted or global attacks; extinctions; or shocks is vital to the survival of the network itself, and of dependent structures such as economies (for financial networks) or even the planet (for ecosystems). Previous attempts to characterise robustness include nestedness of mutualistic networks or exploration of degree distribution. In this work we present a new approach for characterising the stability and robustness of networks with all-positive interactions by studying the distribution of the k-shell of the underlying network. We find that high occupancy of nodes in the inner and outer k-shells and low occupancy in the middle shells of financial and ecological networks (yielding a “U-shape” in a histogram of k-shell occupancy) provide resilience against both local targeted and global attacks. Investigation of this highly-populated core gives insights into the nature of a network (such as sharp transitions in the core composition of the stock market from a mix of industries to domination by one or two in the mid-1990s) and allow predictions of future network stability, e.g., by monitoring populations of “core” species in an ecosystem or noting when stocks in the core-dominant sector begin to move in lock-step, presaging a dramatic move in the market. Moreover, this “U-shape” recalls core-periphery structure, seen in a wide range of networks including opinion and internet networks, suggesting that the “U-shaped” occupancy histogram and its implications for network health may indeed be universal.

The natural circulation flow characteristic of the core in floating nuclear power plant in rolling motion

The Bitcoin Lightning Network (BLN), a so-called "second layer" payment protocol, was launched in 2018 to scale up the number of transactions between Bitcoin owners. In this paper, we analyse the structure of the BLN over a period of 18 months, ranging from 12th January 2018 to 17th July 2019. Here, we consider three representations of the BLN: the daily snapshot one, the weekly snapshot one and the daily-block snapshot one. By studying the topological properties of the three representations above, we find that the total volume of transacted bitcoins approximately grows as the square of the network size; however, despite the huge activity characterising the BLN, the bitcoins distribution is very unequal: the average Gini coefficient of the node strengths (computed across the entire history of the Bitcoin Lightning Network) is, in fact, ~0.88 causing the 10% (50%) of the nodes to hold the 80% (99%) of the bitcoins at stake in the BLN (on average, across the entire period). This concentration brings up the question of which minimalist network model allows us to explain the network topological structure. Like for other economic systems, we hypothesise that local properties of nodes, like the degree, ultimately determine part of its characteristics. Therefore, we have tested the goodness of the Undirected Binary Configuration Model (UBCM) in reproducing the structural features of the BLN: the UBCM recovers the disassortative and the hierarchical character of the BLN but underestimates the centrality of nodes; this suggests that the BLN is becoming an increasingly centralised network, more and more compatible with a core-periphery structure. Further inspection of the resilience of the BLN shows that removing hubs leads to the collapse of the network into many components, an evidence suggesting that this network may be a target for the so-called split attacks.

An approach for calculating ex-core detector response using Monte Carlo code MCNP was developed. As a first step towards ex-core detector response prediction a detailed MCNP model of the reactor core was made. A script called McCord was developed as a link between deterministic program package CORD-2 and Monte Carlo code MCNP. It automatically generates an MCNP input from the CORD-2 data. A detailed MCNP core model was used to calculate 3D power distributions inside the core. Calculated power distributions were verified by comparison to the CORD-2 calculations, which is currently used for core design calculation verification of the Krško nuclea power plant. For the hot zero power configuration, the deviations are within 3 % for majority of fuel assemblies and slightly higher for fuel assemblies located at the core periphery. The computational model was further verified by comparing the calculated control rod worth to the CORD-2 results. The deviations were within 50 pcm and considered acceptable. The research will in future be supplemented with the in-core and ex-core detector signal calculations and neutron transport outside the reactor core.