Network Perspective Research Articles

Investors as members in transnational sustainable finance initiatives: Collectors, mediators and performers

The last 20 years have seen the emergence and proliferation of transnational sustainable finance initiatives (hereafter: TSFI). From associations like the Principles of Responsible Investment to pledges like the Finance for Biodiversity Pledge, investors have connected with each other and with other kinds of organisations in transnational fora dedicated to sustainable finance. Taking inspiration from political economy scholarship on global corporate networks, we apply a network perspective to the transnational governance of sustainable finance, examining the overlaps between investors’ membership in TSFI. In particular, we aim to identify those investors’ that hold a large number of TSFI membership (collectors), that connect centrally located TSFI with those at the margins (mediators), and that take on active roles within TSFI (performers). Analysing membership data for 30 TSFI, totalling 10.602 observations, at three analytical levels, we identify a group of 21 investors holding core positions in the global network. The majority of these investors are active in asset management and located in Nordic or continental European political economies. The predominance of some of the world’s largest investors in our three member categories suggests that the transnational governance of sustainable finance relies in part on the activities of actors that are associated with harmful financial practices. Nevertheless, the simultaneous presence of publicly owned enterprises on our list of most connected members also indicates the importance of public leadership in the transnational governance of sustainable finance.

Analysis of Global Core Countries from a Complex Network Perspective

This paper analyzes the importance of countries in a globalized world and explores their cooperative tendencies using a complex network approach. By extracting data from The GDELT Project, an undirected weighted global network is constructed, where each node represents a country. The network is found to be scale-free based on the degree distribution. Core countries are identified using different centrality metrics, such as degree centrality, closeness centrality, and PageRank. The occurrence of war is identified as a significant factor influencing the importance of countries like Israel and Ukraine in the network. By considering the types of events, the study examines the cooperative tendencies of countries and finds an overall trend of cooperation rather than conflict among nations, with varying levels of collaboration. Countries involved in conflicts or wars show limited cooperation with other nations during the selected period. The findings suggest that globalization may influence the cooperative tendencies of countries. The paper contributes to the understanding of the importance of countries in a globalized world and their cooperative tendencies using a complex network perspective

Is corrections officers' use of illegal force networked? Network structure, brokerage, and key players in the New York City Department of Correction

PurposeRecent research on police misconduct has adopted a network perspective, while recent work on correctional officer (CO) use of force has similarly framed it as an organizational behavior, learned through socialization and deployed with considerable discretion. This paper leverages the network paradigm in police misconduct research to study the use of force by COs. MethodsUsing data on lawsuits involving the New York City Department of Correction from 2013 to 2022, this paper forms a co-offending network of those COs who have been sued for excessive force. This paper then uses descriptive social network analysis and key player selection and community detection methods. ResultsAfter describing the basic network structure of COs who use force together, this paper identifies brokers who connect disparate parts of the CO network; it also uses a community detection algorithm to identify clusters of COs involved in force incidents. Finally, the paper compares this network to an analogous network of police use of force, finding structural similarities. ConclusionsThis analysis bridges disparate work on correctional officer use of force and police misconduct; for policymakers who seek to curtail COs' excessive use of force, this paper might provide a blueprint for identifying key players and clusters.

Spatial Analysis of Intercity Migration Patterns of China’s Rural Population: Based on the Network Perspective

Since entering the 21st century, many developing countries around the world have begun to enter a stage of rapid urbanization; large-scale “rural-urban” population migration has become a typical social phenomenon in these countries. Against this backdrop, this paper aims to elucidate the spatial migration characteristics of rural populations and to discuss future rural–urban development strategies. For this purpose, this paper takes China as a case and employs methods such as spatial autocorrelation analysis, hotspot analysis, and network analysis to construct an intercity migration network of rural migrants and analyze its spatial characteristics and internal structure. The results indicate that the migration pattern of the rural population exhibits notable spatial clustering features. Cities in the eastern and central regions are, respectively, hotspots for the inflow and outflow of rural populations, with internal migration dominating in western cities and relatively inactive rural population movements in northeastern cities. Municipalities directly under the central government, sub-provincial cities, and provincial capitals show a significant tendency to attract rural populations, while prefecture-level and county-level cities mainly radiate rural populations outward. Cities nationwide form seven major clusters in the migration network, and these clusters exhibit distinct structural characteristics. Rural population migration is influenced by various factors. In the future, considerations should focus on the county as the primary unit, attracting rural populations for local employment, and promoting rural revitalization and agriculture development. The findings of this paper are of reference significance not only to China but also to many developing countries with similar national conditions in the world.

Investigating cognitive and motivational proximal outcomes in a randomized clinical trial of writing about the future self to reduce drinking.

Drinking identity (the extent to which one links the self with drinking alcohol) is a unique risk factor for college students' hazardous drinking that is not directly targeted by existing interventions. We conducted a study that aimed to decrease drinking identity among college students with hazardous drinking. We adapted a writing task about the future self and tested whether three writing sessions could decrease drinking identity and change drinking. We also investigated whether two additional factors (writing perspective and inclusion of participants' social networks) would enhance task impact. The present study evaluated whether posited proximal cognitive and motivational outcomes (drinking identity, self-efficacy, readiness to change, and drinking intentions) changed immediately after each writing session. The study is a randomized clinical trial in which hypotheses and analyses were pre-registered. Participants were 328 college students who met hazardous drinking criteria. The study had a 2 (narrative writing topic: low-risk drinker vs. reduced smartphone use) × 2 (writing perspective: first-person vs. non-first-person) × 2 (social network instruction: instructed to include vs. not) factorial design. Proximal outcomes were drinking identity, self-efficacy, readiness to change, and drinking intentions. The clinical outcome was alcohol consumption. Participants completed three laboratory sessions at weekly intervals that included the writing task and pre- and post-task assessments. Results were largely null, except that readiness to reduce drinking was higher in the low-risk drinker condition and increased over the lab sessions. Time effects indicated that reductions in drinking identity, drinking intentions, and alcohol consumption, and increases in self-efficacy were observed but did not change above and beyond control conditions. Findings indicate the need to strengthen the writing task and select a more appropriate control task to target proposed proximal outcomes. Future studies might try personalizing the task, evaluating its efficacy with individuals motivated to change their drinking, and using a control task that does not involve imagining a future self.

Evolutionary model and risk analysis of ship collision accidents based on complex networks and DEMATEL

To manage and control ship collision risk, this paper aims to develop a quantitative risk analysis approach based on complex networks and Decision-making Trial and Evaluation Laboratory (DEMATEL), to study the evolution of ship collision accidents. Firstly, through the search, selection and analysis of accident investigation reports of ship collisions in the world, 46 Risk Influential Factors (RIFs) were identified, and a network model for the evolution of ship collision was established. Secondly, a risk analysis of the evolution model for ship collision accidents was conducted by utilizing the topology characteristics of the complex network theory. Thirdly, a robustness analysis was used to identify 10 key RIFs involved in ship collisions from a global network perspective, and the grey relation analysis technique was employed to verify the key RIFs. Finally, the DEMATEL method was utilized to identify 11 key RIFs from a perspective of causality, and corresponding risk control measures were proposed to mitigate those key RIFs. The research results provide theoretical support for identifying the key RIFs and controlling the risk transmission of ship collision, and have practical significance for preventing the occurrence of ship collision accidents and ensuring the safe navigation of ships.

Central bank swaps and foreign reserves: From the perspective of a global network

Central bank swaps have flourished since the 2008 financial crisis and the intertwining swap lines have formed a typically complex network, in which bilateral swap relationships have been deeply embedded. This paper constructs a global swap network of central banks and then utilises network indices to measure the network positions and resources of swap central banks. From the perspective of the global swap network, it employs the Spatial Durbin Model to empirically estimate both direct and indirect effects of swap positions on foreign reserves and then further explores the applicability of these effects. The findings confirm a negative impact of network positions on foreign reserves. Besides, swaps can significantly substitute for foreign reserves of relevant banks by back-up rescue and demonstration mechanisms. The fact that spatial spill-over effects are much larger than direct effects justifies the necessity to assess swap performance from a spatial perspective. Applicability tests show that the substitution effect is larger in less developed countries and those with lower foreign exchange stability and financial openness. The conclusions have important policy implications for the construction of a global financial safety net and the coordination of counter-measures to cope with crises.

Network constraint and online group innovation: a dual perspective of inter-community group network and intra-community group network

PurposeThis study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.Design/methodology/approachThe authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.FindingsThe results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.Originality/valueThe findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

An ecological input-output CGE model for unveiling CO2 emission metabolism under China's dual carbon goals

Carbon mitigation is essential for combating climate change and its impacts, safeguarding ecosystems, and protecting human health and livelihoods. This study develops an ecological input-output CGE (EIOC) model that integrates computable general equilibrium (CGE) model, input-output analysis (IOA), and ecological network analysis (ENA) to explore the evolution of the CO2 emission metabolism under long-term carbon tax policies. The EIOC model excels not only in intimately depicting economic relationships and evaluating the economic impacts of policy interventions but also in unveiling the complex internal interactions within the context of emission dynamics through multidimensional network perspectives. The EIOC model is employed to analyze CO2 emission flows under carbon tax policies aimed at fulfilling China's dual carbon goals, thereby validating its applicability. It is found that (i) the implementation of carbon tax policies (P25 and P30 scenarios) would lead to economic decline; however, there would emerge potential for recovery in investment and international trade; (ii) adopting an earlier carbon peak target (P25 scenario) would yield more pronounced emission reductions in the early to mid-term (in 2035, reductions in steel, construction, and manufacturing sectors would exceed those under the P30 scenario by 15.74%, 11.89%, and 11.59% respectively); (iii) long-term policies would significantly impact the dynamics of CO2 emission metabolism; chemical sector would display an increased reliance on the system, indicating a heightened need for inputs from the system; transactions exhibiting increased centrality (between chemical and other mining, and between chemical and manufacturing) reveal their elevated significance as transfer pathways of CO2 flows. Identifying significant changes in CO2 emission metabolism can inform incentivizing or constraining measures aimed at further adjusting emissions.

Rest to Promote Learning: A Brain Default Mode Network Perspective.

The brain often switches freely between focused attention and divergent thinking, and the Default Mode Network (DMN) is activated during brain rest. Since its discovery, the DMN, together with its function and characteristics, indicates that learning does not stop when the brain "rests". Therefore, DMN plays an important role in learning. Neural activities such as beta wave rhythm regulation, "subconscious" divergence thinking mode initiation, hippocampal function, and neural replay occur during default mode, all of which explains that "rest" promotes learning. This paper summarized the function and neural mechanism of DMN in learning and proposed that the DMN plays an essential role in learning, which is that it enables rest to promote learning.

Does ecological network affect the construction land spatial development intensity? -An empirical study based on the main urban area of Jinan, China

The ecological network as the cornerstone of urban ecological security protection, understanding the interaction between ecological network and construction land spatial development intensity (CLSDI), which is crucial for guiding the orderly utilization of territorial space and promoting regional sustainable development. However, the information on the complex spatial and temporal interactions between ecological networks and CLSDI has not yet been adequately studied. This study takes the main urban area of Jinan City as an example, and explores the spatial and temporal coupling relationship and change rule of ecological network and CLSDI during 2006–2018 through spatial multiple buffer analysis tools, and proposes the optimization path of construction land spatial development under the perspective of ecological network. The results showed that: from 2006 to 2018, there is a significant spatial effect between CLSDI and ecological network elements; within the buffer zone of 300–3000 m for ecological sources and nodes, CLSDI rises with the increase of buffer zone distance; while the ecological corridor exhibits decreased CLSDI within the 500-m buffer zone, the 500–3000-m CLSDI tends to increase. Based on the empirical analysis, the optimization path of construction land spatial development is proposed from three aspects: ecological source, corridor and node. The 300 m control range of the ecological source is designated as a “specific protection zone”, and strictly control the increase of the CLSDI within the zone; the ecological corridor is set up with differential protection and utilization zoning, and CLSDI and activity types are controlled in a hierarchical and classified manner; the CLDSI around the ecological nodes is strictly controlled in order to prevent encroachment of construction activities on the nodes. This study provides a reference value for constructing a territorial spatial pattern coordinated with ecological protection and development of construction.

A complex network perspective on spatiotemporal propagations of extreme precipitation events in China

Extreme precipitation events (EPEs) cause catastrophic losses to human lives and social economy. Focusing on the wet season from May to October, this paper formulates the complex network to characterize the spatiotemporal propagations of EPEs over 218 river basins in China. Specifically, based on the daily Multi-Source Weighted-Ensemble Precipitation version 2, the event synchronization along with significance test facilitates the complex network of EPEs from 1979 to 2020. By characterizing the topology of EPEs, the results show that synchronous EPEs generally occur over the Hetao Area of Yellow River Basin, Haihe River Basin and Northeast China. The complex network of EPEs classifies the 218 river basins into six communities. In May and June, more than 50 % of EPEs generally occur in South China. From July to September, over 60 % of EPEs tend to be observed in the Huang-Huai-Hai Plain, upper-middle reaches of Yellow River Basin, Northeast China and Southwest China. In October, about 65 % of EPEs happen in South and Southwest China. In the meantime, less than 10 % of EPEs occur in Northwest China. Among the synchronous EPEs starting in late June or early July and peaking in late July to early August, there exist propagations along the Yellow River, Haihe, Liaohe and Songhua River Basin within one to eight days. Eastward moisture transport along this pathway within four to six days drives the propagation of synchronous EPEs. The complex network analysis of this paper provides useful information for early warning and forecasting of EPEs and flood hazards.

Assessing the role of actors in river restoration: A network perspective.

The aim of this study was to identify and characterize the actors involved in river restoration in Romania by untangling the complex networks that they are part of. Actors were considered nodes in a social network, tied by a common action or project. The nodes were characterized through the centrality metrics of a network. The network of actors in river restoration in Romania has a low density and high average path length and diameter for such a spare network, which suggests that knowledge transfer and collaboration are difficult. In the context of a highly centralized water governance system in Romania, the National Authority for Water exerts power and influence in river restoration as well. It has numerous partners, both disconnected and well connected in the network, therefore, it tends to be connected to everybody, as well as gets and diffuses knowledge. Yet, other actors are willing to get involved in river restoration in Romania. NGOs and research organizations have a central position in the network and play various roles (e.g., unconcerned influencers, gate-keepers, pulse-takers). As a recommendation for governing river restoration in Romania, we urge the creation of a national programme focused on river restoration, where the call for projects would be coordinated by the National Authority for Water and open to its territorial subordinates in agreement with stakeholders from various sectors and domains.

Global Production Networks and Dynamic Cores in the World’s Main Nodes: The Technological-Productive Transition of the Automotive Industry

The global production networks (GPNs) perspective, to account for key aspects of the new global space, takes on its full dimension from a theoretical-methodological approach to capitalism in terms of historical-spatial phases of development, implying the existence of industrial cycles differentiated by their dynamic core. The global automotive industry is undergoing a profound transformation due to the transition to electric and autonomous vehicles. Under its preceding technological-productive base, it had become part of the automotive-mechanical-metal-petrochemical complex that constituted the dynamic core of the Fordist-Keynesian development phase. Underlying this transition is a process of technological-productive revolutionization in the industry by the electronic-informatics and telecommunications sector, which constitutes the dynamic core of a new industrial cycle typical of the current phase of development. This implies a changing technological-productive base and a spatial and hierarchical reconfiguration of the automotive industry, with macro-regions and new leading countries, old leading macro-regions and countries that have become second-tier players, and new competing countries; with the deployment of new GPNs involving the dynamic cores of global nodes within macro-regions. This article concludes that the actual further regionalization of GPNs between the dynamic cores is in contradiction to the necessary global sourcing of key elements of the industry.

Fast learning without synaptic plasticity in spiking neural networks

Spiking neural networks are of high current interest, both from the perspective of modelling neural networks of the brain and for porting their fast learning capability and energy efficiency into neuromorphic hardware. But so far we have not been able to reproduce fast learning capabilities of the brain in spiking neural networks. Biological data suggest that a synergy of synaptic plasticity on a slow time scale with network dynamics on a faster time scale is responsible for fast learning capabilities of the brain. We show here that a suitable orchestration of this synergy between synaptic plasticity and network dynamics does in fact reproduce fast learning capabilities of generic recurrent networks of spiking neurons. This points to the important role of recurrent connections in spiking networks, since these are necessary for enabling salient network dynamics. We show more specifically that the proposed synergy enables synaptic weights to encode more general information such as priors and task structures, since moment-to-moment processing of new information can be delegated to the network dynamics.

Deep calibration with random grids

We propose a neural network-based approach to calibrating stochastic volatility models, which combines the pioneering grid approach by Horvath et al. [Deep learning volatility: A deep neural network perspective on pricing and calibration in (rough) volatility models. Quant. Finance, 2021, 21(1), 11–27]. with the pointwise two-stage calibration of Bayer and Stemper [Deep calibration of rough stochastic volatility models. Working Paper, arXiv:1810.03399, 2018] and Liu et al. [A neural network-based framework for financial model calibration. J. Math. Ind., 2019, 9(1), 1–28]. Our methodology inherits robustness from the former while not suffering from the need for interpolation/extrapolation techniques, a clear advantage ensured by the pointwise approach. The crucial point to the entire procedure is the generation of implied volatility surfaces on random grids, which one dispenses to the network in the training phase. We support the validity of our calibration technique with several empirical and Monte Carlo experiments for the rough Bergomi and Heston models under a simple but effective parametrization of the forward variance curve. The approach paves the way for valuable applications in financial engineering—for instance, pricing under local stochastic volatility models—and extensions to the fast-growing field of path-dependent volatility models.

Investigating change in network structure of eating disorder symptoms after delivery of a smartphone app-based intervention.

Eating disorder (ED) research has embraced a network perspective of psychopathology, which proposes that psychiatric disorders can be conceptualized as a complex system of interacting symptoms. However, existing intervention studies using the network perspective have failed to find that symptom reductions coincide with reductions in strength of associations among these symptoms. We propose that this may reflect failure of alignment between network theory and study design and analysis. We offer hypotheses for specific symptom associations expected to be disrupted by an app-based intervention, and test sensitivity of a range of statistical metrics for identifying this intervention-induced disruption. Data were analyzed from individuals with recurrent binge eating who participated in a randomized controlled trial of a cognitive-behavioral smartphone application. Participants were categorized into one of three groups: waitlist (n = 155), intervention responder (n = 49), and intervention non-responder (n = 77). Several statistical tests (bivariate associations, network-derived strength statistics, network invariance tests) were compared in ability to identify change in network structure. Hypothesized disruption to specific symptom associations was observed through change in bivariate correlations from baseline to post-intervention among the responder group but were not evident from symptom and whole-of-network based network analysis statistics. Effects were masked when the intervention group was assessed together, ignoring heterogeneity in treatment responsiveness. Findings are consistent with our contention that study design and analytic approach influence the ability to test network theory predictions with fidelity. We conclude by offering key recommendations for future network theory-driven interventional studies.

The synergy effect of multi-country policy actions announced in reaction to global risk: A network structure perspective.

The policy actions of countries reflect adaptive responses of local components within the system to the dynamic global risk landscape. These responses can generate interactions and synergy effects on alleviating the evolution of global risks. Adopting a network perspective, the study proposes a theoretical framework that connects three structural characteristics of policy synergy, namely, synergy scale, alignment intensity, and timing synchronization. Focusing on the Covid-19 pandemic as a typical global risk context, the study finds that policy synergy with a larger scale, stronger alignment intensity, and more synchronized timing has a positive impact on mitigating global risks. The effect of alignment intensity is particularly pronounced when polycentric governance involves 20 countries facing severe risks, whereas the effect of timing synchronization is more significant when the multicenter group comprises more countries. Building upon the concept of an efficient scale of polycentric governance in various dimensions, this study develops a policy synergy index model. Through multiple empirical analyses, this study validates the causal relationship between policy synergy and the future evolution of global pandemic risk. Policymakers can leverage the dynamic changes in the policy synergy to predict future risk situations and implement well-rounded and appropriate policy actions, thereby enhancing the efficacy of the synergy effect of multi-country policy actions for risk governance.

Exploring the intra-platoon planning problem for heterogeneous train traffic under virtual coupling in the railway network via simulation

Study on the platoon planning of virtual coupling (VC) is indispensable for both passenger and freight railway operation in terms of capacity, scheduling, and timetabling. As an advanced technology in train operation and control systems, VC can significantly improve the performance of rail operations, with regards to capacity, flexibility and robustness. In this study, we mainly focus on the former one, i.e., to maximize the capacity gains, by employing the relative braking distance based spacing policy for heterogenous train traffic. To our knowledge, this article is the first to address the VC intra-platoon planning problem for a railway network. The main function/purpose of this study is to decide a leader train and allocate an order to the heterogeneous follower trains for the virtually coupled platoon in the off-line mode. The objective is transformed to minimize and compare the sum of minimum safe distance for platoons on the common shared route sections in the railway network from various perspectives, so as to seek the desirable orders of potential train consists within the platoons from the perspective of the whole railway network. Our contributions are mainly threefold. First, the conditions for train platooning under virtual coupling are synthesized. Second, the solution flow charts and algorithms for simulation are proposed, including general framework for simulation, classification of prioritizing the shared common route section, and flow charts and algorithms for decision of coupling order to train platoons. Finally, the proposed methodology was tested and discussed on the designed computational experiment (i.e., numerical simulations of a typical case study with two sets of test examples) via NetLogo platform. The numerical simulation results series revealed some key findings and validated the effectiveness of the proposed methodology. Results of this study can provide guidance to decision makers in timetabling and potential capacity bottleneck identification under VC. We believe that it is worth investigating and further advancing this research direction in the future.

The association between urbanization and depression in the elderly: A network analysis from the complexity science perspective

ImportanceThe global increase in urbanization has coincided with a rise in depression prevalence. However, the effect of urbanization on depression remains controversial, especially for the elderly. ObjectiveTo clarify how urbanization impacts depression in the elderly from a network perspective. Design, setting, and participantsThis sectional cohort study used data from China Health and Retirement Longitudinal Study (CHARLS). Main outcomes and measuresThe occurrence of depressive symptoms in urban and rural elderly residents. Network metrics of depressive symptoms. ResultsOf the 13,993 participants, lower incidence of depressive symptoms was observed in urban (26.3 %, 95 % CI, 24.7 %–27.8 %) than in rural (40.4 %, 95 % CI, 39.5 %–41.3 %, P < 0.0001) residents. However, higher incidence of depressive symptoms was observed in urban (26.3 %, 95 % CI, 25.2 %–28.4 %) than in rural (17.5 %, 95 % CI, 16.1 %–18.9 %, P < 0.0001) residents in a subset of 2898 pairs of participants after PSM. No difference in the network structure and metrics between urban and rural residents before (M = 0.071, p = 0.054, S = 0.037, p = 0.80) and after (M = 0.085, p = 0.133, S = 0.086, p = 0.47) PSM was detected. The networks structure revealed that negative affect was strongly connected to somatic symptoms and that the two anhedonic symptoms were also strongly connected. ConclusionsThe current study indicated the homogeneity of the ultimate nature of depression between rural and urban residents from the network perspective, supporting the viewpoint that urbanization might not impose influence on depression. Further researches delving deeper into the complexity of the issue may provide new insights into our understanding of depression in an urban environment among the elderly.