Network Linkages Research Articles

Research on the Characteristics and Influencing Factors of Provincial Urban Network from the Perspective of Local Governance—Based on the Data of the Top 100 Enterprises in Four Categories in Fujian Province

With the development of the division of labor in product value chains and the specialization of urban functions, the network link structure model among cities is being reshaped. Studying the structure of urban networks and its related theories in the context of scale, place and policy is still an open area. This study constructs a research framework to study the urban network formed by the synergy of scale, place and policy. It mainly takes enterprises in different industries in different provinces as the empirical scale and object, and uses methods such as a social network and Geo Detector to analyze the characteristics and influencing factors of the provincial network relationship mode of enterprises among cities. The main findings are as follows. (1) Firstly, the urban network linkage in general shows strong coastal centrality and small-world network characteristics. The urban network linkages reflected by different types of enterprises all have obvious spatial directionality and polarization effects. (2) Coastal cities have strong centrality, and the specialized division of urban functions emerges, with large cities becoming a concentration area for different types of corporate headquarters, while small- and medium-sized cities carry a large number of processing and assembly enterprises. (3) The networks of different types of enterprises have different sensitivity to each influencing factor. For example, emerging industries have the strongest correlation with the economic scale and social services; manufacturing industries are most influenced by the public services, administrative level and development zone level; and service industries are most influenced by science and technology expenditure and the same metropolitan area. In conclusion, this study contributes to the understanding of network heterogeneity at the provincial scale and provides policy support for the local governance scale, as well as promotes the expansion of the urban network theory to network governance applications in the “flow space”.

Analysis on the structure and economic resilience capacity of China’s regional economic network

ABSTRACT This paper analyzes the heterogeneous influence of economic networks on urban economic resilience capacity from different network characteristics, providing an innovative research perspective and theoretical framework for the economic resilience capacity of urban clusters. The urban economic elasticity is measured by multiple indicators and constructed economic network using night light data, the complex network approach was combined with spatial econometrics to analyse the contribution of economic network linkages and economic network locations to regional economic resilience capacity. The results show that: urban economic network linkage has a significant positive impact on urban economic resilience capacity, and the polycentric pattern of urban clusters has a driving effect on this impact; in contrast, the influence of urban network location on economic resilience capacity has an inverted u-shaped curve. Compared with non-smart cities, regions in smart cities are better able to promote urban economic resilience capacity through economic networks, and the impact of economic networks on regional economic resilience capacity has network external spillover effects beyond geographical distance, The results of the study infer that cities in urban agglomeration should rationalize network locations, and build a coordinated urban agglomeration network structure to enhance economic resilience capacity of the regional economy.

Predicting the Blockchain Technology Acceptance in Supply Chains with Inter-Firm Perspective: An Integrated DEMATEL and PLS-SEM Approach

Predicting the Blockchain Technology Acceptance in Supply Chains with Inter-Firm Perspective: An Integrated DEMATEL and PLS-SEM Approach

Are associations of leisure-time physical activity with mortality attenuated by high levels of chronic ambient fine particulate matter (PM2.5) in older adults? A prospective cohort study

Background and purposeAlthough leisure-time physical activity (PA) has established health benefits in older adults, it is equivocal if exercising in environments with high levels of PM2.5 concentrations is equally beneficial for them. To explore the independent and joint associations of ambient PM2.5 and PA with all-cause mortality among adults aged 60 or older and to assess the modifying effect of age (60–74 years vs. 75+ years) on the joint associations. MethodsA prospective cohort study based on the MJ Cohort repeat examinations (2005–2016) and the Taiwan Air Quality Monitoring Network and death registry linkages (2005–2022). We included MJ Cohort participants aged 60 or more at baseline who attended the health check-ups at least twice (n = 21,760). Metabolic equivalent hours per week (MET-h/week) of leisure-time PA were computed. Multivariable adjusted associations were examined using time-varying Cox proportional hazard models. ResultsThere were 3539 all-cause deaths over a mean follow-up of 12.81 (SD = 3.67) years. Ambient PM2.5 and physical inactivity are both independently associated with all-cause mortality. The joint associations of PA and PM2.5 concentrations with all-cause mortality differed in the young-old (60–74 years) and the older-old (75+ years) (P for interaction = 0.01); Higher levels of long-term PM2.5 exposures (≥25 μg/m3) had little influence on the associations between PA and mortality in the young-old (HR = 0.68 (0.56–0.83) and HR = 0.72 (0.59–0.88) for participants with 7.5–<15 and 15+ MET-h/week respectively) but eliminated associations between exposure and outcome in the older-old (HR = 0.91 (0.69–01.21) and HR = 1.02 (0.76–1.38) for participants with 7.5–<15 and 15+ MET-h/week). ConclusionLong-term exposures to higher PM2.5 concentrations may eliminate the beneficial associations of PA with all-cause mortality among adults aged 75 and over.

Learning Financial Networks with High-frequency Trade Data.

Financial networks are typically estimated by applying standard time series analyses to price-based economic variables collected at low-frequency (e.g., daily or monthly stock returns or realized volatility). These networks are used for risk monitoring and for studying information flows in financial markets. High-frequency intraday trade data sets may provide additional insights into network linkages by leveraging high-resolution information. However, such data sets pose significant modeling challenges due to their asynchronous nature, complex dynamics, and nonstationarity. To tackle these challenges, we estimate financial networks using random forests, a state-of-the-art machine learning algorithm which offers excellent prediction accuracy without expensive hyperparameter optimization. The edges in our network are determined by using microstructure measures of one firm to forecast the sign of the change in a market measure such as the realized volatility of another firm. We first investigate the evolution of network connectivity in the period leading up to the U.S. financial crisis of 2007-09. We find that the networks have the highest density in 2007, with high degree connectivity associated with Lehman Brothers in 2006. A second analysis into the nature of linkages among firms suggests that larger firms tend to offer better predictive power than smaller firms, a finding qualitatively consistent with prior works in the market microstructure literature.

Evaluating the impact of different spatial linkages on forum outcome interdependencies in polycentric systems

AbstractIn complex polycentric systems, decisions regarding the governance of certain subsystems (e.g., watersheds) are often determined by networks of diverse actors who participate across a range of forums tackling interconnected collective actions issues (e.g., water quality, biodiversity, flood management). Compounding this structural complexity are the multifaceted interdependencies that exist between forums across a system. Drawing on the Ecology of Games Theory (EGT), this article investigates the impact of different types of network linkages on outcome interdependence between forums. Using a series of spatial autoregressive models on data collected in a Tampa Bay water governance system, I find evidence that co‐membership and organizational networks serve as pathways for outcome spillovers between forums. Building theory that helps elucidate how different types of network relationships may influence outcomes across a system is critical for the continued development of EGT and the governance of polycentric systems.

Measuring network linkages of housing prices: Evidence from the Guangdong-Hong Kong-Macao Greater Bay Area

In this paper, we examine the pattern of network linkages of housing prices across a group of neighboring cities in the Greater Bay Area (the GBA). Using monthly data of housing prices across 11 cities in the GBA from June 2013 to December 2020, we explore the contemporaneous causal relationships as well as cross-city housing market connectedness within the GBA. Our findings provide evidence for contemporaneous causality in housing prices across cities in the GBA. There is a core-periphery hierarchical structure of transmission mechanism for housing price shocks that are transmitted from core cities to key node cities within the GBA in contemporaneous time. Moreover, the spillover index indicates that cross-city connectedness is an important source of volatility in the housing markets in the GBA. However, the patterns of housing price connectedness behave differently across categories of cities in the GBA. In addition, using the Quadratic Assignment Procedure (QAP) analysis, we find that similarities in economic openness and urbanization contribute to the strong linkages of regional housing markets in the GBA.

A Zigzag-Based Thickness-Accommodating Foldable Prismatic Structure With a Single-Degree-of-Freedom

Abstract Origami inspires various designs of foldable prismatic structures with zero-thickness facets. However, there is a difficulty in directly applying them to thick materials. This paper presents a novel design of the foldable prismatic structure inspired by the zigzag pattern, which can accommodate the thickness of materials easily by placing hinges on the top or bottom surfaces of panels. The foldable prismatic structures are constructed by connecting multiple zigzag strips, in which each strip is made up of uniform-thickness hexagonal panels. By identifying the relationship between the foldable structure and spatial linkages, we analyze the mobility of the assembly based on the matrix method with DH notations. The result reveals that the foldable prismatic structure is equivalent to a network of spherical 4R linkages and Bennett linkages, and its motion has a single-degree-of-freedom. Based on the proposed foldable prismatic structure, a foldable manipulator is developed to demonstrate its potential engineering applications. The actuation strategy is designed by employing a motor-cable-driven system and torsional spring hinges. The physical prototype of the foldable manipulator is fabricated, and experimental results prove that our designs are feasible and effective.

Research initiatives and network linkages in COVID-19: Neo-dynamics of R&amp;D in the Ayush sector

Research initiatives and network linkages in COVID-19: Neo-dynamics of R&amp;D in the Ayush sector

Greenery and water structure before and after political system transformation. A Poznań city case study

The greenery and water structure, in the form of wedges cutting into the city, is a characteristic and unique element of Poznań’s urban model. Already before the Second World War, it became the matrix setting the framework for spatial and natural connections within and around the city. These areas were originally clearly demarcated and formed an organic network that permeated the built-up areas. It was this local network of linkages that was to have the greatest impact on the quality of urban living, climate improvement, biodiversity and the functional and spatial structure of the city.&#x0D; In the idea of the socialist city, ensuring access to green spaces for the masses, was one of the essential policy elements of the time. However, over time, in the various models of the city proposed by successive planners, these interconnections began to disappear and the individual bands were narrowed and sometimes discontinued altogether.&#x0D; This study aims to verify the urban planning models of the city of Poznań against the original idea of a wedge-ring system of greenery and water areas, before and after the political transformation in 1989.&#x0D; How does this original structure function today and how have the socio-economic changes that followed the fall of communism affect the greenery and water solutions proposed in the new city model?&#x0D; A comparative analysis of changes in green and water structure in the different spatial models of the city of Poznań, before and after the political transformation, makes it possible to observe the pace and directions of these changes. The analysis was based on the findings of the then-current master plans and on the studies of spatial development conditions and directions, which are an expression of the city’s spatial policy. It can be used to verify the assumptions made or even to change the current model of the city.

The impact of network connectivity on factor exposures, asset pricing, and portfolio diversification

This paper extends the classic factor-based asset pricing model by including network linkages, leading to a network-augmented linear factor model. This extension of the model allows a better understanding of the determinants of systematic risk and shows that cross-sectional risk premia can be estimated more precisely. Moreover, we demonstrate that in the presence of network links a misspecified traditional linear factor model presents residuals that are correlated and heteroskedastic. We support our claims with an extensive simulation experiment and real data.

Poverty, social networks, and clientelism

Why are the poor susceptible to clientelism, and what factors shield them from the influence of vote buying? We explore the role of both formal and informal social networks in shaping the likelihood of being targeted with private inducements. We argue that when the poor lack access to formal social networks, they become increasingly reliant on vote buying channelled through informal networks. To test our theory, we build the informal, family-based network linkages between voters and local politicians spanning a city in the Philippines. We then collect survey data on formal network connections, electoral handouts, and voting behaviour of 900 voters randomly drawn from these family networks. We show first that campaigns disproportionately target poorer voters. We then show that familial ties further influence targeting among poor voters. Finally, we show that access to formal networks such as workers’ associations mitigate voter fears of punishment for failing to reciprocate.

Targeting Diverse Bridging Motifs within Actinide Borosulfates and Establishing an Unconventional Structural Hierarchy.

The first actinide borosulfates, (UO2)[B(SO4)2(SO3OH)] (TSUBOS-1) and (UO2)2[B2O(SO4)3(SO3OH)2] (TSUBOB-1), were synthesized solvothermally in oleum using UO3. The classical borosulfate crystal structure of TSUBOS-1 is partially consistent with an established conventional hierarchy. Uranyl pentagonal bipyramids limit the anionic network linkages and isolate sulfate tetrahedra within the anionic network. Therefore, the classical one-dimensional chain established in the hierarchy does not fully describe the structure. The structure of TSUBOB-1 is the first actinide borosulfate that contains an unconventional borate-to-borate bridging mode (denoted B-O-B) and a zero-dimensional oxoanionic unit consisting of one sulfate tetrahedron that shares vertices with two B-O-B bridged borate tetrahedra that each share a vertex with two sulfate tetrahedra. As this structure departs from the existing structural hierarchy, a modified approach for understanding the unconventional borosulfate substructure and dimensionality is proposed, together with a new graphical notation. In the course of our synthesis experiments, a novel uranyl disulfate compound (UO2)2[(S2O7)(SO3OH)2] (TSUDS) was isolated and characterized. The structure of TSUDS is a framework consisting of uranyl pentagonal bipyramids and sulfate tetrahedra. Each uranyl pentagonal bipyramid is surrounded by five sulfate tetrahedra, two of which share a vertex creating a disulfate with a S-O-S bridging mode. The uranyl bipyramids are linked to one another via the singular sulfate or disulfate groups.

Effects of Covid-19 on the BIST 100 network structure

ABSTRACT This article investigates the effects of Covid-19 on the network structure of BIST 100 firms. Analysis are carried out with filtered daily volatilities. Even after filtering out common factors, correlation and autocorrelation heat maps of the filtered volatilities indicate that there are still some patterns. Granger and contemporaneous type volatility networks are estimated and visualized for both the pre-Covid-19 and Covid-19 periods to determine the network structure differences. The article shows that there are centrality-type structures in the Granger network and chain-type linkages in the contemporaneous network for the pre-Covid-19 periods. The degree of interconnectedness is multiplied three times in the Granger network and eight times in the contemporaneous network with Covid-19.

Global Container Port Network Linkages and Topology in 2021.

The maritime transport of containers between ports accounts for the bulk of global trade by weight and value. Transport impedance among ports through transit times and port infrastructures can, however, impact accessibility, trade performance, and the attractiveness of ports. Assessments of the transit routes between ports based on performance and attractiveness criteria can provide a topological liner shipping network that quantifies the performance profile of ports. Here, we constructed a directed global liner shipping network (GLSN) of the top six liner shipping companies between the ports of Africa, Asia, North/South America, Europe, and Oceania. Network linkages and community groupings were quantified through a container port accessibility evaluation model, which quantified the performance of the port using betweenness centrality, the transport impedance among ports with the transit time, and the performance of ports using the Port Liner Shipping Connectivity Index. The in-degree and out-degree of the GLSN conformed to the power-law distribution, respectively, and their R-square fitting accuracy was greater than 0.96. The community partition illustrated an obvious consistence with the actual trading flow. The accessibility evaluation result showed that the ports in Asia and Europe had a higher accessibility than those of other regions. Most of the top 30 ports with the highest accessibility are Asian (17) and European (10) ports. Singapore, Port Klang, and Rotterdam have the highest accessibility. Our research may be helpful for further studies such as species invasion and the planning of ports.

Optical, luminescence, and energy transfer studies of Gd3+/Dy3+ doped potassium gadolinium borophosphate glasses

The K2O–Gd2O3–B2O3–P2O5 glass doped with Dy2O3 (Dy:KGPB) were synthesized by the melt-quenching technique. These glasses were subjected to characterize the physical, structure, optical and luminescence properties. It was observed that the density, molar volume and refractive index of glass increased with increasing Dy2O3 concentration. The FTIR result confirmed the main glass network of BOB and POP linkages those were degraded by adding Dy2O3 modifier. Glasses absorbed photons in ultraviolet, visible light and near-infrared region. The photoluminescence under direct Dy3+ excitation performed the strong emissions at 574 and 482 nm corresponding to 4F9/2 → 6H13/2 and 4F9/2 → 6H15/2 transition, respectively. The Gd3+ excitation also caused strong emission of Dy3+ by the Gd3+-Dy3+energy transfer. Glass doped with 1.00 mol% of Dy2O3 owned the highest emission intensity due to the concentration quenching. The lifetime of 4F9/2 level was found to decrease with addition of Dy2O3 content via dipole-diploe interaction between Dy3+ ion. Judd-Ofelt (J-O) intensity parameters were initially calculated and applied to evaluate the radiative parameters such as branching ratios, radiative transition probabilities, and stimulated emission cross-sections. The radioluminescence of glass was also investigated and found the scintillation efficiency around 15.6%, compared to BGO scintillator. The Dy:KGPB glass has an interesting potential for solid-state laser, LED and X-ray detection applications.

Counterparty Risk: Implications for Network Linkages and Asset Prices

AbstractWe study the relation between trade credit, asset prices, and production-network linkages. Empirically, firms extending more trade credit earn 7.6$\%$ p.a. lower risk premiums and maintain longer relationships with customers. Using a production-based model, we quantitatively explain these novel facts. Trade credit reduces the departure probability of high-quality customers, thereby reducing firms’ exposures to systematic costs incurred in finding new customers. The mechanism predicts that the aggregate amount of trade credit proxies for customer-search costs and that suppliers with shorter-duration links to customers command higher expected returns. We confirm these and other novel predictions in the data.

Identification of Metropolitan Area Boundaries Based on Comprehensive Spatial Linkages of Cities: A Case Study of the Beijing–Tianjin–Hebei Region

As a regional management unit to solve "urban diseases,” metropolitan areas are gradually attracting widespread attention. How to objectively and accurately delineate the boundaries of a metropolitan area is the primary prerequisite for carrying out targeted studies and precisely formulating regional planning measures. However, the existing methods for delineating metropolitan area boundaries have problems, such as high data acquisition costs, subjectivity, and a single perspective of urban linkage. To address the above problems, we propose a “bottom-up” approach to metropolitan area boundary delineation based on urban comprehensive spatial linkages. We used only publicly available data to construct a directionally weighted network of urban spatial linkages, and applied community detection algorithms to delineate metropolitan area boundaries. Taking the Beijing–Tianjin–Hebei region as a case study area, the method’s validity was confirmed. The results showed the following: (1) Eight metropolitan areas were delineated within the region, with two types of metropolitan areas: “Inter-municipal” and “single-city”. (2) The overall accuracy of the delineation results reached 83.41%, which is highly consistent with their corresponding isochrone maps. (3) Most metropolitan areas were observed to have an obvious “central–peripheral” structure, with only the JingJinLang metropolitan area being a polycentric mature metropolitan area, whereas the other metropolitan areas remained in the initial stage of development, with Zhangjiakou and Chengde not yet having formed metropolitan areas. This study’s methodology highlights the basic criteria of “inter-city spatial linkage” as the foundation for boundary delineation, avoiding the inaccuracy caused by the subjective selection of boundary thresholds, and can also accurately determine the developmental stage and internal spatial structure of metropolitan areas. Our method can provide new perspectives for regional boundary delineation and spatial planning policy formulation.

Influence of Centrifugation Cycles of Natural Rubber Latex on Final Properties of Uncrosslinked Deproteinized Natural Rubber.

Natural rubber latex (NRL) is a polymer (blend) extracted from the milky sap of para rubber trees. Due to being a natural biopolymer, NRL contains various proteins that may be allergenic to humans when in skin contact. Attempts have been made to use deproteinized natural rubber (DPNR) instead of impure NRL, and the final properties of these two types of rubber tend to differ. Thus, the correlations between their chemistry and properties are of focal interest in this work. DPNR was prepared by incubating NRL with urea, followed by aqueous washing/centrifugation. The physical, mechanical, and dynamic properties of incubated NRL before and after washing/centrifugation were examined to distinguish its influences from those of incubation with urea. According to the findings, the proteins, phospholipids, and chain entanglements were responsible for natural polymer networks formed in the NR. Although the proteins were largely removed from the latex by incubation, the properties of high ammonia natural rubber (HANR) were still maintained in its DPNR form, showing that other network linkages dominated over those contributed by the proteins. In the incubated latex, the naturally occurring linkages were consistently reduced with the number of wash cycles.

CFLP: A new cost based feature for link prediction in dynamic networks

Dynamic networks are social networks in which node-to-node links contain a temporal component, i.e., node-to-node interactions over a specific time interval. As a result, the dynamic network’s structure changes over time, and previously connected nodes may or may not have an edge connecting them at any one time. The link prediction issue in dynamic networks aims to identify future network linkages based on the relative behavior of previous network updates. We present a feature-based solution that considers both individual snapshots and the overall network throughout the full-time span to answer the link prediction problem. We present a novel feature called Cost-based feature for link prediction (CFLP) for estimating edge behavior throughout the entire network, which uses a reward and penalty structure to summarize node activity across the entire network. We use similarity indices, classified into four major categories: local similarity, global similarity, quasi-local similarity, and clustering coefficient-based similarity, to measure edge activity in individual snapshots. We have also selected fourteen different snapshot-based features to find the most excellent combination of minimum features for link prediction. We used regression and mutual information-based scoring for feature selection to correctly quantify the relative effect of features among themselves and the overall link prediction problem. In order to give the best feasible solution to the link prediction problem, these individual features and their combinations were examined with five machine learning models. We employed five performance matrices – AUC, AUPR, Average Precision, F1, and Balance Accuracy Score – to compare the performance of our method to those of state-of-the-art approaches, and found that our method outperformed all.